THE REDISTRIBUTION OF EARNINGS IN THE IVORY COAST:
THE ROLE OF HIGHER EDUCATION FINANCE
A DISSERTATION
SUBMITTED TO THE SCHOOL OF EDUCATION
AND THE COMMITTEE ON GRADUATE STUDIES
OF STANFORD UNIVERSITY
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
Joseph Yao Yao
July 19B3

---

To the merror\\' of our father ,Joseah Balley Yao who believed
even in the early inoe8endence struggles that only an
equitable educational system will save the Ivory Coast from
future injustices.
iii

---

EFFETS REDISTRIBUTIFS DU FINANCEME}.~ DE
L'UNIVERSITE NATJONALE
rCO;~5~;.L
Par Joseph YAO YAO
",:;acr,.l1';-;'i NlALGACHE II
pQUn L;r:I\\1SE~Gi\\E~r-.'\\E:\\!·r ~UP~RjEUR J
. C. A. M. E. S. -
OUAGADOUGOU '
. Arrivee .22- J-lHN .1995..; ..... :
: Enregistre sous n' .#.0.0. (.8.3. I
I
_ .,=--.~..:;:.....-=- ~_...;. __ .
1
\\
R E~ U M E DE lHESE DE PH.D
Intitule
THE REDISTRIBUTION OF EARNINGS IN lHE
IVORY CQ~T : THE ROLE OF HIGHER EDUC~TIQN
FINANCE.
Soutenue a l'lJnivcrsit~
de STANFORD, CALIFOR.NIE
USA, en Juillet 1983.

---

2.
Au cours des deux premieres decennies de son independance, le
succes economique de la C6te d'lvoire l'a entraine dans une politique
d'investissement intensif dans l'education en general et dans l'enseigne-
ment superieur en particulier. En depit de cet effort, plus de 50 %des
emplois de cadre superieur etaient tenl~ en 1980, par des expatries. Ce-
pendant, des contraintes scolaires et lmiversitaires empechent des eleves
de fin de cycle secondaire d'acceder au systeme gratuit d'enseignement
superieur. L'acces a ce niveau d'enseignement est conditionne avant tout
par la reussite au baccalaureat. Parmi les 51 %qui satisfont en general
a cette condition, l'admission dans une grande ecole est soumise a un
examen special et l'entree a l'Universite, aux cri teres precis de selec-
tion d'une Commission Nationale. De ceux qui entrent a l'Universite, 62 %
redoublent une anneeluniversitaire et 18 %sont renvoyes avant qu'ils
ot-
achevent leurs cycles de formation. Dans la mesure ou l'acces a l'Universite
est reserve a une categorie d'etudiants et que son financement repose ex-
clusivement sur l'effort de tOl~ les contribuables nationaux, il y a la
un probleme d 'equite qui pourrait etre pose en ces termes : qui finance
l'Universite ? Qui benHicie de cette Universite ?
Pour examiner ces questions, nous avons mene une enquete aupres
de tous les etudiants qui s'inscrivaient 3 l'Universite Nationale a la
rentree universitaire 1980-81. 67 %des etudiants avaient rempli not re
questionnaire. Ce pourcentage se repartit de fa con irreguliere entre les
sous echantillons constitues par les cinq facultes. Nous avons alors proce-
de aux ponderations appropriees des sous echantillons aleatoires tires, de
facon a obtenir un echantillon global de 1274 cas, representant 20 %des
reponses obtenues. L'enquete nous a permis de recueillir non seulement des
donnees sur l'origine socio-economique des etudiants mais egalement, sur
les orientations en faculte, les resultats universitaires et la vie sociale
des etudiants. Ces donnees ont ete completees par des sratistiques finan-
cieres recueillies aupres des services de 1'Universite, des Ministeres dp
1 'Education Nationale et de 1'Economie er cles Finances. L"Ul"lysl~ cle tuutes
ces informations penner cle tirer trois grandes conclllslOns.
1°) S'agissaJlt de J'oriental iOIl, ell'
L, n'\\!<..;sil(' cl
d·:-' l'ori~~iIll'
soclo-economique des etuJiants, il a ete relevc; que jLLSqU'c, la rentree 'Ul'-
vcrsitaire 1980-~1, prcs de ia Ill(llt l(~ de:- i~llh;l,::'
: .::'

---

3.
en fonction du premler choix de faculte qu' ils avaient exprime et que 1 'on
avait plus de chance d'obtenir cC' ['n:mier choix s'i] etait ell accord avec
le type de bac obtenu. Bien qu'une mention au-dessus de passable obtenue
au bac accroisse les chances de voir cc choix accorde, en revanche, l'ori-
gine socio-economlque de l'etudiant
semble ne pas influencer le travail
de la Commission. Une fois l'etudiant oriente, les facteurs qui favorisent
sa reussite sont par ordre d'importance, le nombre total d'etudiants inscrits
dans la faculte, la nature de la faculte, la mention obtenue au bac et le
niveau d'education du pere. Ainsi l'etudiant type qui acheve sa formation
universitaire avec le moins de redoubleIllent est inscrit en Sciences [cono-
miques, appartient a une classe dite moyenne et a des parents travaillant
a la terre. L'acces ij')'Universite Nationale n'est pas privi1egie pour 1es
enfants d'une region donnee de la C6te d'Tvoire. Bien que la plus forte
proportion des etudiants (33,3 %) soient nes dans un villa2(e, ceu:~-ci ont
mains de chance d'avoir acces a l'Universite que ceux qui sont nes dans les
prefectures, a Bouake, Cl Abidjall ou dans Lme sous-prefecture, p'JJ' urdn'
de facili ter d' acces. L' etudiant de pcre possedant LID m veau cl' educat ion
eleve et occupant une fonction de cadre est quatre fois plus reprc'sent.} iJ
l'Unive!"site que l'etudiant dont il~ pere travailk c, la terre,
2°) L'analyse du financement de 1 'Universite revele que la capa-
cite d'autofinancement de cette institution reste tres faible malgrc le
net progres constate dans la diversification des sources de financement.
La contribution intemationale a ce i'lnancernent, qui autrefois se 1 imitait
" 1 'aide franpise n'a pas beaucoup c\\'oluc. La repartition du budget de
I 'IJniversite entre les differentes facultcs et instituts, ne rcpond pa, tou-
jours aux propres criteres d 'allocatiun
de ressources de j' lnstitutioC1
nombre d'etudiants inscrits, dcpenses courantes de fonctionnement, type
de: faculte. Depuis 1977, on constate egalement WlC tendance " la hais5C' du
r3pport budgC'l LUliversi te - nombre d',;tudiant5 irbcrits. Au niV";lll du cOllt
dc's etudes unj vcr~ i Ll i res, I' 6tl1(J l:lnt de Lett res supportC' 1(' lTI31H_luC' :-\\ ::::tgnC'~­
le plus clevc bj(~n quIll con1c le liloins chcr :1] ll:.t:lt. C'(~ST l'~;tlldiant en
Sciences Econollliqllcs Cllll
r,"t J1"\\-
le pllJ~ de' profiT
I('s 6tudl'~ univC'rslT3irc:-::
ct
l"!)1l1 J"lhUt'
1):11' lOIl:;C;lilll'llt
ic' pjll~ :11.1\\ rirl~llln;s r'luhllquC's dl' l'Et;tl
rnr
l'illlp01
Stir
le l"i.'V\\!llll.

---

••
4.
3°) NOllS avons ega)ement essayc d~ Lerner l'aspeLt equite du
finaneel1K'nt de l'Universite. POUT ce fairc, nou, :ll'on5 regroupc lcs etudiants
~n trois oTlgines socio-economiques (ilas, moyen, ('level selon le Teven\\! des
parents, selon 1cs biens possetles dans les menages et selon la categorie so-
Cio-pTofessionnelle du pere. Quelle que soit la methode utilisee pour eva-
luer cette or igine,
le groupc llrcvcnu 61 c:ve" <-lbso 1'1)(' 1d p1 U~ irnpo rtantc port i on
des depenses publiques de l'Etat pOUT 1 'Universite. En evaluant la contri-
bution f iscale future des etudiants, on constate que la categori (' "originE'
JIloyenne" payera le plus d'impat a l'Etat durant sa vie professionnelle. La
categorie de "revenu eleve" rece"Ta la part la plus important" des transferts
de fonds publiques pour l'educatlOn. Par categoric sOLio-professionnelle, CE
sont les etudiants dont le pere appartient au groupe dit "col bleu" qui
transfert le plus de ",res sources aux aut res groupes et le benefic iairE' le plus
important, est le groupe des "sans travail ou retraite". En general, l'Etat
retire un benefice net de sa politique ,qctlle!lc de financemcnt de 1 'Universite
malS le coOt de cc financement est JIlal reparti panni les ell ff,'rentes catego-
Ties de revenus. !lien yu'en 1981, le groupe de n:vcnu bas ait fInance la part
la plus impoTtante (28 %i ::Ill budget de 1 I UnivcL.;irc, cc group2 ;1 egalcment
retire le plus de cc financemcllt, cn rapport avcc sa contribution fiscJ.le.
Le rati6 coOt-beneficE' de l'Universite s'elevanl "vec le ni,e:ll: dc rcvenu,
on en conclut que la politique actue]]c de finance'ment est verticalement
equitable, mais qu'horizontalement, elle ne I 'est pas paree ql1C 18 mobilite
socialc est mains ouverte pour les enfants d' ongine rurale.
,
11
!1
I
11

---

· . ~ \\
ABSTRACT
The early
economic success
of the
Ivory Coast has
led to a major
public
investment
in
education
in
general
and
particularly
in
higher
education.
However,
the
country
still
relies
on
foreign
expertise to
fill
nearly
half
of
the
demand
for
management
level
and
technical
manpower.
In
addition,
many
students
completing
secondary
schools
cannot
get
access
to
the
free
higher
education
institutions
of
the
country.
When
students
are
admitted
to
the
University
at
least
62
percent
of
them wi 11
repeat
one academi c year and
18 percent wi 11
be
expelled.
The financing of the National University and other higher education
institutions
imposes
a
heavy
financial
burden
on
Ivorian
taxpayers.
Because
the
education
system
is
selective,
the
children
ofQ certain
category
of
taxpayers· benefit
proportionally
more
from
higher
education.
The
dissertation
seeks
to
determine
the
socio-economic
background
of
the
students
enrolled
in
the
National
University.
Furthermore,
it
examines
the
equity
issues
that
are
raised
by
the
financing scheme of the National University.
Not all
secondary
school
graduates enter the National
University.
The select group of 51% of students who succeed at the Baccalaureat exam
must
also
be subjected to a national
policy
of admissions analyzed in
this dissertation.
It is found that admission in university departments
of
the
already
selected
group
of
young
Ivorians
is
not
determined
by
socio-economic
background
variables
of the
student,
but
rather
by
the

---

type of Baccalaureat degree obtained and by the academic performance of
the student in high school.
Even though students are not denied access
to the University because of their birth region, they are more likely to
be
found
at
the
University
if
they
belong
to
an
ethnic
group
geographically
close
to the capital
city,
if they
are
not
born
in a
village, and if their father holds a management position job.
In
the
second
part
of
thi s dissertation 'we assess eqL<i ty in the
financing
of
the
University.
We
find
that
the
tremendous
financial
effort made by the Ivory Coast towards the University during the first
two decades of its Independence has been declining in the eighties.
We
also
find
that
university
graduates
benefit
more
from
the
financing
scheme,
than they
contri bute in
tax
resources to the
government.
However, during their lifetime these graduates will more than reimburse
the state in the form of heavy tax on wages.
We conclude that if the
current
policy
of
education
finance
is
pursued,
earnings
will
be
redistributed in favor of higher income groups.
v

---

PREFACE AND ACKNOWLEDGEMENTS
This dissertation topic emerged from a confrontation with memorable
experiences during my schooling process in the Ivory Coast.
The first
phase
of
this
confrontation
began
when
was
an
elementary
school
student
in Assinie,
a vi llage
setting,
continued whi le attending the
College Moderne of Grand Bassam, a competitive public junior secondary
schoo 1, and ended when
graduated from the famous Lycee Cl ass i que of
Abidjan.
During
this
first
phase
only
two
other
friends
from
the
vi llage elementary school could reach the university.
Among the bright
and unfortunate students who dropped out or were expe 11 ed from school,
many left us for motives ranging from insufficient grade point average
to
feeling
of a moral
obligation
to abandon
school
and assist their
aging parents.
I then became aware of the various social forces which
enter in the making of a school graduate.
The second phase of my schooling experiences started in the early
seventies with my undergraduate studies at the University of Abidjan.
was
exposed to
student
protests
on
issues
ranging
from
the
teaching
conditions, the curriculum of the University, to the general process of
social
formation of the future
Ivory Coast.
In all these discussions,
education was perceived as a prime factor capable of solving most of the
issues
raised.
Upon
graduation
from
the
university,
when
I
was
presented
the
opportunity
to
further
learn
about
the
relationship
between education and economic development in graduate school,
I could
not
but
be overwhelmed.
My
investigation
of who
pays
for,
and who
benefits
from
education
really
began
with
all
these
previous
experiences.
vi·

---

In
my
training
at
Stanford,
many
professors
and
friends
contributed to making this experience a wonderful
one.
First, I
benefitted from the vast experiences and expertise of Professors Henry
Levin,
~
academic
advisor,
and
Martin
Carnoy,
~
thesis
advisor.
Second, Professor David Rogosa, of the School of Education, Charles Ncho
and Andre Komenan, my friends from the Ivory Coast, have provided useful
comments and
suggestions on this dissertation.
In my
first years at
Stanford
I
received
academic
support
from Professors Steve Klees and
Emi 1e McAnany.
Finally,
my
wife
Colette
deserves
more
than
the
customary
acknowledgements for moral support.
She helped in searching through the
numerous
budgetary
and
other
Ivory
Coast
governmental
documents
to
gather
the
appropriate
data
needed
for
this
work.
Her
abi lity and
patience in computing the same tables many times and re-verifying my own
computations have greatly reduced the number of errors the reader may
still encounter in this work.
Financial
support
throughout
my
education
has
been
provided
by
Ivorian
taxpayers.
I
have
also
received
research
grants
from
many
institutions
and
agencies
at
several
stages
of
this
work:
the
Ford
Foundation and
the Canadian
International
Development Research Center
(IDRC)
through
a
contract
with
the
Centre
Ivorien
de
Recherches
Economiques et Sociales (CIRES), Stanford University and the Center for
Research and International Studies (CRIS).
In the Ivory Coast, the former Director of the CIRES, Dr. Jacques
Pegatienan, the current Director, Dr. Achi Atsain, the former "recteur"
of the University,
Dr.
Diarrassouba,
all
have helped
during my
field
work in cutting through numerous administrations of the country.
Dr.
vii

---

Atsain in particular h~s
been very supportive of my dissertation work.
I have received valuable clerical assistance in the preparation of
the manuscript from Ms. Evelyn Morris, Sharon Carter and Carol Wilson.
June
1983·
Vlll

---

TABLE OF CONTENTS
ABSTRACT •••••.••••••••••••••••••••••••••••••••••••••••••••••••••
PREFACE AND ACKNOWLEDGEMENT. •••••••••••••••••••••••••••••••••••• vi i
LIST OF TABLES..................................................
x'l
LIST OF FIGURES
xi)(.
Chapter
I NTRODUCTI ON. • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •
1
A.
The Issue....
..•.••..••. .••.......
1
B.
The Economi c Context...............................
3
I I
THE POLITICAL ECONOMY OF FINANCING HIGHER EDUCATION:
HOW FAR HAVE WE COME?
.
5
A.
Some Background ••••••••••••••••••••"................
5
B.
Understanding the Conceptual Framework.............
7
.--- --,-----..
1.
.
d
ff"
-<", -' '/ I •. "
Equlty an
E
lclen<;yc.· ••••.••._••.••••••.....•••.
7
:.:,~/' ",,,,--- -
',-'"
~
2.
Equa 1 Opportunit i/~s'/n Access ,\\i:qua 1 Life
T.
B
f . t
'~("'I. ,i r· -
'\\
lme
ene 1 •.•. •t ......... • '., .....f••••• •~I •••••••••••••
9
Il'" --~-_____ n"I'
, :.- '
J
'
3.
.
\\, r
\\
, . .
E
.
Inter-generatlDn and .lntra-gener.atlDn
qulty •••
\\.
. _/ijl
11
4.
Selecting an Equity'>'Yar,dstriCk":: ••••••••••••••••
11
............
.&-'
5.
Income Versus Earni ng
.
15
C.
A Review of Theoretical
Issues.......
16
1.
Education and Economic Growth....
17
2.
Education and Income Distribution..............
19
3.
Financing of Education and Distribution of
Income.. . . . . . . . . . • . . . . . . . . . . . . . . . . • . . . . . . . . . . . .
22
D.
A Synopsis Review of Some Empirical Studies........
27
E.
The State of Knowledge in the Political Economy of
Educational Finance in the Ivory Coast....
29
III
MODEL DESIGN AND DATA TREATMENT ••••••••••••••••••••••••
35

---

TABLE OF CONTENTS (Cont'd)
Chapter
A.-The Nilt-ional University Sy"slem •••••••••••• ·•• :.:: ...·•
36
1.
A Brief Historical Review •••....•••••••.•.•••••
36
2.
Organization of the University System ...................
38
B.
The Model Designs ••••••••••••••••••••••••••••••••••
41
1.
Model 1: Access to Types of HE Schools ••••••• ~.
41
2.
Model 2:
Scholastic Achievem~nt•••••••••••••••
45
C.
The Data Ba 5 e............................................................................
48
1.
Data Collection .•••••••••••••••••••••••••••••••
48
2.
Missing Values ......................................
49
IV
THE NEW FORTUNATE FEW ....................................................................
58
A.
Equa 1ity of Admission to the University ••••••••••••
58
1.
The Official Po 1icy of Admission .................
58
2.
Who Enters Which Schoo 1................................................
63
B.
Equa 1ity in Academic Achievement •••••••••••••••••••
73
1.
The Uni versity Pol i cy of Repet it i on and
Expulsion.
..•.
..••..
73
2.
Promotion Rates at the University
77
3.
The Determinants of Academic Achievements ••••••
81
·C.
The Socio-Economic Background of the University
Students ...••.•..•'........... .•...
..•.•.
91
1.
Methodology ••••••••••••••••••••••••••••••••••••
91
2.
The Results
93
D.
Comparison with Charlick's Study
111
V
THE FINANCING OF THE NATIONAL UNIVERSITy
116
A.
The Institutional Context of the University Finance 116
1.
The Financial Organs of the University
117
x

---

TABLE OF CONTENTS (Cont'd)
Chapter
~
2.
Budget Procedure and Resource -Allocation.-.;; ••• 119
B.
The Sources of Financing the National University ••• 122
1.
The Internal Sources of Revenues of the
University •••••••••••.••••••••••••••••••••••••• 122
2.
The National Sources of Subsidy to the
University .......•.................•........... 126
3.
The Foreign Sources of Funding of the
National University •••••••••••••••••••••••••••• 128
C.
Evolution of Some Economic Aggregates Clnt{the
University BudgetS ••••••••••••••••••••••••••••••••• 132
1.
University Budgets and National Economic
Aggregates ••.....•.....••••.••.••..•.•......... 133
2.
The Determinants of Budgets Allocation
to
The University .••.•.•...•.••.••.•••••••••• 139
3.
Evolution in Resources Allocation by Schools ... 14:1;.
VI
A COST ANALYSIS OF THE NATIONAL UNIVERSITy ••••••••••••• 151
A.
Cost Methodology ••••••••••••••••••••••••••••••••••• 152
B.
The Public Cost of Instruction at the National
University
154
1.
Salaries
155
2.
Housing Costs
159
3.
Administrative Costs ••••••••••••••••••••••••••• 160
4.
Amortization Costs
160
5.
The Results •••••••••••••••••••••••••••••.•••••• 163
C.
The Total Public Cost of Training One Ivorian
Student by School Attended
164
1.
The Student's Scholarship •••••••••••••••••••••• 164
2.
The Cost of Operating the CNOU ••••••••••••••••• 167
xi

---

TABLE OF CONTENTS (Cont'd)
Chapter
3.
The Total Cost of Training- One Ivor-ian
Student
by SchooL •••••••••••••••••••••••••••• 169
D.
The Private Cost of Attending the University ••••••• 173
1.
Methodology
173
2.
Empirical Estimates •••••••••••••••••••••••••••• 174
VII
THE BENEFITS FROM THE NATIONAL UNIVERSITy ••••••••••••• 183
A.
The Methodological Approach
185
B.
Empirical Estimates
188
1.
The Private Benefits from Attending the
University
189
2.
The Public Benefit from University
I nves tment ••••••••••••••••••••••••••••••••• , • •• 192
VIII
THE REDISTRIBUTIVE EFFECT OF UNIVERSITY FINANCE •••••••• 195
A.
Issues in Redistribution and their
Bearing in the Ivory Coast
195
B.
Methodological Approach •••••••••••••••••••••••••••• 199
1.
Intra-generational Equity •••••••••••••••••••••• 199
2.
Inter-generational Equity •••••••••••••••••••••• 203
C.
Empi rical Estimates
, 204
1.
Distribution of Government Expenditure-
Subs i dy.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .... 204
2.
Distribution of Tax Paid Versus Subsidy
Received ••••••••••••••••••••••••••••••••••••••• 210
IX
SUMMARY, RECOMMENDATIONS AND LIMITATIONS ••••••••••••••• 229-
A.
Summary
230
B. Policy Recommendations
238
0
c.
Limitations
0
239
Footnotes··· .........................................•........... 24'1.
xii

---

TABLE OF CONTENTS (Cont'd)
APPENDIX A:
QUESTIONNAIRE ••••••••..•.•..•••.•••.•..••••••••••••• 245
APPENDIX B:
A METHOD FOR GROUPING STUDENTS AT THE NATIONAL
UNIVERSITY BY SOCIO-ECONOMIC BACKGROUND ••••••••••••
257
1.
The Household Items Grouping •••••••••••••••••••
258
2.
The Household Income Grouping
263
APPENDIX C:
ALPHABETICAL LIST OF VARIABLES
7..57
APPENDIX D:
EMBLEM OF THE NATIONAL UNIVERSITy .•••••••••••••••••
APPENDIX E:
A NOTE ON PUBLIC FINANCE IN THE IVORY COAST. ....... 272
A.
Budgets and Taxes in the Ivory Coast
272
1.
The Budgets
.?7?
2.
The Sources of Revenues of the Budgets ••••••••• 273
3.
Taxes on Wages • .................................. 277
B.
The 1981 Budgets
783
APPENDIX F:
THE MAP OF THE IVORY COAST ••••.•••••••••••••••••••• 287
BIBLIOGRAPHY AND REFERENCES ••.•••••.•.••••••••••••••.••••••••••• 2?R
. d
X1H

---

LIST OF TABLES
2.1
Equity Criteria, An Hypothetical Example
14
2.2
Urban Colombia; Allocation of Taxes and Public
Subsidies for Education Among Income Groups..............
24
2.3
Incidence of Taxes and Distribution by Income of
Student's Parents, Kenya, 1971 •.......••.•..•...•...•....
26
2.4
Rural Botswana: Incidence and Distribution of Taxes
and Public Expenditures in Education by Deciles 1974/75..
28
2.5
A Synopsis Review of 4 Empirical Studies on Equity in
Education Finance
o..o. .. o . . o . . o . . o .
..
2.6
Average Family Incomes, Average Higher Education
Subsidies Received and Average State and Local Taxes
Paid by Type of Institution Children Attended in
California, 1964 .•....•.......•.......................•..
32
2.7
Estimated Distribution of Tax Payments by Income
Class 1960: Gillespie (in Millions of $) ........•......••
33
3.1
Population Size, Returned Rate, and Weighted Sample
Size by School for Ivorian Students at the National
University . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . • . . . . . . . . . . o.
50
3.2
Selectivity Indices on Five Variables for the Student
Group Which had Missing Values on Variables Related to
Income of Their Parents
54
3.3
Distribution of Students in Original Population and
Sample Population
56
4.1
Distribution of Uni versity Students by Type of
Distinction Obtained for BAC, Specialization of BAC,
and Att ri but i on of SchooL...............................
65
4.2
Regression of the "Fulfillment of the Preference
for School Expressed by the Student" over 6
Independent Variables
67
4.3
Discriminant Analysis of Students Who Obtained their
First Choice of University School and Those Who Did Not
by Household Items Grouping...............
70
4.4
Probability Table for Graduating N Numbers of
Students at Year T •••••••••••••••••.••.•••••••••••••••••
76
.xW

---

LIST OF TABLES (Cont'd)
4.5
Evolution of Promotion Rates Over 5 Years by Form,
for Each School..........................................
80
4.6
Percentage of Students Who Have repe?ted a FORM
in the Sample Population •••••••••••••••••••••••••••••••••
82
4.7
Regression of Average Promotion Rate Over 4
Independent Variables ••••••••••••.•••••.••.••••••••••••••
84
4.8
A Regression Analysis of a Measure of Scholastic
Achievement on Nine Independent Variables ••••••••••••.•••
87
4.9
A Discriminant Analysis of Having Repeated or Not
Repeated a "Form" at the Un' versty by Income
Level of Parents
89
4.10
Distribution of Ivorian Students at the National
University by the Ethnic Group of Their Father,
Mother, Kinsman.................................
96
4.11
Indices of Selectivity of University Students by the
Ethnic Groups of Their Father, Mother and Kinsman ••••••••
98
4.12
Distribution of Ivorian Students by Area of Bi rth and
Index of Selectivity at the National University .......... 101
4.13
Distribution of University Students by Size of City
Where They Attended Primary School
103
4.14
Distribution of Students by Region of Residence
Unti 1 12 and their indices selectivity
106
4.15
Father and Mother Level of Education and their
Selectivity Indices
108
4.16
Socio-profession of Student's Father ••••••••••••••••••••• 110
4.17
Comparison of Charlick and Yao Studies from
5 Variables
113
5.1
University Subsidy It
Schools and University
Expenditure on Students in 1980-81 (Francs CFA 1,000) .... 120
5.2
Evolution of University's Own Resources and
Their Origins .....••.....•.......••••••.•...•.•.....•.••. 123
5.3
University Institutes and Services and the Sources
of Their Finance in 1980-81 .••••......•..•••.•...•.•..... 125
5.4
National [nstitutions and Their Participation in the
Finance of the Cost of the National University
127
xv·

---

LIST OF TABLES (Cont'd)
5.5
Evolution of the Contribution of France to the
Operating
Budget of the National University ••••••••••• 129
5.6
External Funding of the University and its
Beneficiaries in 1980-81 •...••••.....••.••••••.••.•.•.••• 131
5.7
Absolute and Relative Increase in National and School
Economic Aggregates from 1971 to 1981 in CFA
Francs (current) .............................•.•.•.•.•... 136
5.~
Regression Analysis of the Effo'rt Made for University
Operating Budget on 3 Independent Variables •••••••••••••• 14~
5.9
Some Indicators of Resource Allocations by School
(Years 1975-76 to 1980-81)
14-5
6.1
The Cost of Instruction at the National University
by School in 198(}-81 (in CFA Francs, 1000)
157
6.2
Total
Annualized Cost of the SUbsidy by Student Until
Graduation by School
(in CFA Francs, 1000)
166
6.3
Annualized Cost of CNOU in 1981 (in CFA Francs Million) .. 168
6.4
Annualized Cost of Instruction for Graduating a
Student, Who Enters a School
in 1980-81
(in CFA Francs, 1000)
170
6.5
Total Annualized Public Cost of Training One
Subsidized Student Until
Graduation, by School
(in CFA Francs 1000)
.
6.6
Annualized Net Income
175
6. 7
Total Annual i zed Pri vate Cos tlncurrpn by one student
until Gradu'ation by School
(in CFA F.rancs,1000) .. 179
6.8
Monthly Utilization Rate of CNOU Restaurants by
Ivorian Students Who Have Spent at Least one Academic
Y'ear at the National
University (in percentage)
181
7.1
Expected Additional Life-time Benefit from Attending
the National University, by School
(in CFA Francs,
1,000) .....•..•.••••....•.......•.....•....•••..•.•...... 191
xv i .

---

LIST OF TABLES (Cont'd)
7.2
Additional Income Tax Revenue to the State from
Graduates. by School
(in CFA Francs. 1.000) •••••••••••••• 194
8.1
J:>resent Value of Average. Government Subsidy and
Net Trnnsfert
by Social Groupings
(in CF~ .
Francs, 1, ooof .-.. ;
;
, 205
8.2
Present Value of Averaqe Government subsidy to
Socio-ProfessiQnal Groups of. Students'Fathers
(CFA Francs,
1 UOO) • • • • • • • • • • • • • • • • • • • • • • • • • • • • • ,
209
8.3
Distribution of Future Average Net Tax Revenues.Collected
on Future Graduates by Social Group and Distribution
of Average Net Transfer of Future Tax Revenues
Among Social Levels (in CFA Francs, 1.000) ••••••••••••••• 214
8.4
Distribution of Future Life-time Tax on Wages Paid and
Net Transfer of Future Tax Resources. by Father's
Occupation Grouping •••••••...•...........•••......•..•••• 218
8.5
A Summarized Percentage Distribution of the Sources
of Revenues of the 1981 Budget ••••••••.•••••••••••••••••• 221
8.6
Percentage Distribution of 1981 Tax
Burden on
Income Groups
223
8.7
Distribution
of subsidy Received, Tax Paid
and
Private Cost-Benefit Ratios of University Finance ••••••••
220
B.1
Guttman Scaling
.
259
B.2
Items and Weights Used in Constructing Socio-economic
Backgrou:
for Stu.dents Enrolled at the National
University
262
B.3
Scores. Absolute and Relative Frequencies for Three
Variables Constructed from Household Items
26~
B.4
Distribution of Three Variables II<ed tn Measure th<e Socio-
Economic Background of Ivorian Students of the National
University, 1980-81
266
E.1
Sources of Taxes and Their Allocation to the National
Budget
27:1
E.2
Determination of Deductions .••••••••••••••••••••••••••••.
?8r
E.3
Annual Amount and Average Rate of Three Direct
Taxes on Wages in the I vary Coast ............................ 281
E.4
Sou rces of Revenue of 1981 BG F...................................................... lAd
E.5
Sou rces of Revenue of BSIE (executed) in 1981 •••••••••••• 28r:
xV 1 1

---

LIST OF FIGURES
3.1
The Management System of the University ••••••••••••••••••
39
- - - -
----
3.2
A Proposed Recursive Model Explaining
Access to Types of Higher Education in the Ivory Caost...
42
4.1
Evolution of Number of Students by SchooL.......
60
4.2
Evolution of Number of Fi rst Year Students.......
64
4.3
Evolution of Average Promotion Rate by SchooL...........
78
5.1
University Organs and Their Role in the Budget
Preparation
118
5.2
Evolution of GNP, National, Education, University
Budgets
137
5.3
Evolution of Annual Increase in GDP, National
University Budgets and Student Population •••••••••••••••• l~O
5.4
Evolution of Ratios of University Budget/Number
,
of Students ••.•.•.••••.••••••.••••••••••••••••••••••••••• 1~ r
5.5
Expenditure/Student Ratio by SchooL
'I tl7
5.6
Evolution of Teacher Student Ratios By SCh:;ol.
i ,0
" .
xillil

---

CHAPTER I
INTRODUCTION
A.
The Issue
The
formidable economic success of the sixties and seventies in
the
Ivory
Coast
led to a continuous
rise of public investment in edu-
cation v/hiGh reached 33:~j O-f -th·c nat.ional budget in 1978.
Any observer,
however,
would
also
agree
that
the
financial
effort
has
not met the
objectives
outlined
when
investment
decisions
were
being
made.
The
country still relies heavily
(40.6% in 1979) on expatriates to fill the
demand
for management
level
and technical
manpower.
A higher number
(40%)
of
Ivorians
(citizens
of
the
Ivory
Coast)
students
completing
secondary school cycles are not accepted at the National University (NU)
nor in other higher education (HE) institutions.
Of those who enter the
university, 62% will
repeat at least one year and 18% will be expelled
before graduating.
The high cost of education per student threatens the
present policy of free higher education.
When considering the heavy tax burden Ivorians carry to finance the
National
University
and
other
educational
institutions,
and
the
selective character of that system,
it is
necessary to question which
socio-economic groups
benefit
most
from the current financing
scheme.
More precisely we intend to examine the following issues:
(I)
Who
are
the
"fortunate
few"
I vori ans
who
reach
the
Nat i ona 1
University today?
(2)
What are the equity issues raised by the financing scheme of the
National University?
-
1 -

---

Initially, we
proposed
to investigate these questions for the
entire higher education system of the country.
However, a lack of data
confined the research to the parameters of the National University.
In the first question we examine the socio-economic factors which
we believe influence access to schools of the National
University.
We
also examine repetition in the schools and success rate in obtaining the
diploma which determines a student's future salary level.
These socio-
economic
factors
and
their inter-relations are analyzed
in
Chapter
3.
Regional
origin,
ethnic group, education level, and parent's occupation
are important determining factors.
We therefore examined enrollment in
faculties (schools) according to each of these factors.
Since admission
to a school
is subject to a government decision making process, we test
beforehand
for
any
discrepancies
between
the
official
policy
of
admission
and
its
actual
implementation
in the schools.
Furthermore,
students
accepted
in
schools
are
faced
with
a
high
probability
of
repetition and their chance of obtaining a diploma is as hypothetical as
entrance
into
the
faculty
itself.
We
therefore
examine
factors
determining success in the schools.
The
second question
raised
in the dissertation concerns equity in
the
National
University's
financing
scheme.
Here the concern
is over
the
effect
that
revenues
rai sed
from
today's
taxpayers
for
fi nanci ng
higher education may have on current income distribution, and on that of
future generations.
,ie want to insure that different
income groups of
taxpayers
contri bute
proport i ana lly
to
thei r
income,
to the
fi nanci ng
scheme.
At the same time,
we are concerned that similar income groups
share similar financial
burden in financing the eductional system.
The
dissertation
is
organized
in
the
following
manner:
Equity
- 2 -

---

concepts
and
other
related
theoretical
issues
in
the
literature
are
revi ewed
and
di scussed
in
Chapter
2.
In
Chapter
3,
we
explain
the
structure of the National
University where we gathered most of the data
for our analyses.
We also discuss the design and data treatment of the
survey
we
conducted
at
that
Uni versity
in
the
academic year
1980-81,
which serves as our data base. \\'iith Chapter 4 'we close the first
part of the dissertation with -the results of our survev
. .
In the second part, we examine the effect of the financing scheme
of the
University
on the distribution
of income.
First,
we assess
in
Chapter 5 the financial
effort
made
by
the
Ivory Coast towards
higher
education
relative to the overall
economic performance of the country.
In Chapter 6 we study the private cost to individual and social cost to
the
nation
as
a
whole,
by
faculty.
In
Chapter
7.
we
estimate
the
economic benefits
real ized by graduates of each faculty and we compute
the
addi t i ona 1
tax
revenues
co 11 ected
by
the
state
from
those
benefits.
Finally, in Chapter 8, we estimate the distributional effects
of
the
actual
manner
of
financing
Uni versity
education,
based
on
the
cost
and
benefi ts
calculated
in
previous
chapters.
Policy
recommendations
dealing
with
estimated
inequities
are
presented
in
Chapter g.
Before examining
al1
these
issues
a brief
review of the
economic
sett i ng in the I vory Coast is necessary.
B.
The Economic Context
Since its
Independence from France on August
7, 1960, the Ivory
Coast has experienced a tremendous economic growth.
In real terms, thi s
growth has been over 7% for the past 18 years.
In the 1980's a collapse
-
3 -

---

in prices of coffee and cocoa slowed growth to 3 or 4%.
The per capita
income
as
estimated
by the World Bank
has
risen
from
$145
in
1960 to
$2,000
in
1980.
Traditionally,
the country's major
sources
of
income
have
been
coffee,
cocoa,
and
timber.
A recent
policy of agricultural
diversification
resulted
in
the
introduction
of
cotton,
pineapple,
bananas, and a light industry of substitution in the balance of trade of
the country.
In
1960,
approximately
two
million
people
were
living
on
the
154,000
square mile
of
the
Ivory Coast.
In
1981,
the
population was
estimated
at
ten
million,
of
which
one-fifth
are
foreigners.
The
population growth rate is 3% per year.
Life expectancy in the country
is still
very low (47 years).
Literacy has progressed from a rate of 3%
in 1960 to 34% in 1980.
Educational
statistics
have
also
been
impressive
since
Independence.
The number of primary school
students has increased four
times
(200,046
to_ 863,246),
secondary
school
students
have
increased
twenty
times,
(8,326
to
172,409),
and
the
student
population
at
the
National University has increased 225 times
(48 to. 10,772).
Resources
apportioned
for
education
in
1965
were
20%
of
the
na t i ona 1
budget.
Today
(1982)
the res SOurce s devoted
exc 1us i ve ly
to
education account for 37% of the national
budget.
If we add resources
allocated
to
17
other
Ministries
responsible
for
specific
technical
training,
education
in
general
takes
up more than
50% of the National
Budget.
In
the
next
chapter
we
provide
a
discussion
of
theoretical
and
empirical studies on equity in educational
finance.
-
4 -

---

CHAPTER 11
THE POLITICAL ECONOMY OF FINANCING HIGHER EDUCATION:
HOW FAR HAVE WE COME?
This dissertation analyzes the financing strategy of the National
University of the Ivory Coast.
With regard to a set of equity criteria,
it
examines
whether
or
not
the
financing
scheme
is
"favoring"
some
social
groups
in
the
country
at
the
expense
of
others.
The
study,
therefore,
is
part of
the
general
framework
of equity
in
educational
finance.
In this chapter, we define the conceptual
framework
in which
our
analyses
will
evolve.
We
then
review
some empirical
studies
on
equity
in
educational
finance
conducted
both
in
Thi rd
World
and
developed countries.
A.
Some Background
Since the mid-fifties when economists began exploring Third World
development issues, only the growth of aggregate outputs has been at the
center of their concerns.
This is because the leading economic paradigm
(neo-classical
economics), assumes that the production process embodies
distribution.
Hence labor, capital, and other factors of production are
efficiently rewarded according to their contribution to production.
It
was not until
the early seventies when countries such as China, Cuba,
and Tanzania, where the distribution of the modest economic growth is an
important
objective
as
well
as
increasing
the
growth
of
aggregate
output,
that
economists
rediscovered
the
virtues
of
distributional
aspects of economic development in the Third World.
-
5 -

---

Since that period, the econo:"ics of education field has also ~Jde
strides to examine distributional
issues.
Previously, the concern VlilS
over aggregate' outputs:
what
number
of
students the education
system
could produce
in the most efficient
manner
(in an economic sense) to
attain a fixed target of graduate population.
Equity in the distribution of educational
outpu~ts has not been a
significant
policy
issue
in
the
Third
World,
either.
Even
in
economically advanced countries,
the concern over this
issue has been
expressed only recently
(see Hansen and ~ieisbrod,
(1969 i\\~B), and the
debate
th2t
fo110vled)1.
Further,
underdeveloped
countries
have
been
preoccupied to the present time as to ho,..1 to finance their educational
systecn no "alter '-Iho is paying for it.
Indeed, Vlhen a country relies on
foreign aid to fin2nce its educational
program, the concern over v/hi ch
socio-ecor.oGic
groups
are
bearing
the
heaviest
portion
of
the
cost
bu rden
appears
trivial
and
selfish,
and
ignores
the
broader national
perspective on education.
Declining belief that education ,·d 11 reduce income inequities has
led
to
a
critical
revie'd
of
the
"lay
public
money,
Vlhether
or
not
Hdontlted
freely,!1
is
utilized.
Inquiries as to "ha is financing the
educational
system for ,..:hose ber.efit have therefore cOr:lmenced in a fe'd
Third World countries.
In
many
of
these
studies
confusion
over
concepts
has
caused
disagree~ents
over
the
best
approach
to
changing
the
inequities
encountered.
\\':e shal12'IDid this pitfall by defining the major concepts
of this study.
-
6 -

---

B.
Understanding the Conceptual
Framework
1.
Eguity and Efficiency
The discussion over equity in educational
finance has often been
clouded by the confusion (or distinction) between eguity and efficiency.
The root of the debate between equity and efficiency,
however,
seems to
rest
on
more
fundamental
grounds
of
phi 1 osophi ca 1
and
economi c
disagreement
over
the
perception
of
social
realities.
Further
discussion
of
the
controversy wad,; take
us
beyond
the
scope
of
this
2
work.
Equity and efficiency
issues are often
so interwoven that some
arbitrary
1 ine
needs
to
be
drawn.
In
education
for
instance,
most
people
agree
that
no
one
should
be
excluded
from
a
given
level
of
education
if
the
ability
to
succeed
is
demonstrated
(and
certified).
Not
acting
accordingly
raises
an
issue
of
"fairness"
or
"equity."
However,
in
an
underdeveloped
country
1 ike
the
Ivory
Coast,
the
allocation
of
the
scarce
resources
becomes
as
important
as
the
accumulation
of
the
resources
themselves.
Hence,
most
people
also
recogni ze
the
fact
that
soci ety
has
not
the
means
to
provi de
hi gher
education to every individual.
On precisely what grounds,
and through
what mechanisms should the limited places available in higher education
be opened to some students and exclude others?
This is the efficiency
aspect
of
the
ongoing
debate
over
allocation
of
public
goods.
The
objective
is
to
find
a
financing
scheme
which
satisfies
efficiency
concerns and is also acceptable on equity grounds.
In welfare economics
and public finance, Samuel son
(1950), Arrow (1957), Friedman
(1963) and
others have suggested some theoretical
solutions.
In the economics of education the issue is complicated even more by
the
necessity
to distinguish the consumption
aspect
of education
from
-
7 -

---

investment purpose.
Are lvorlan students from higher socio-eco-
nomic background taking (consuming) higher education only to form
future relations, eujoy art,sports classes?
On the other hand, are
lower socio-economic background students repeatint their classes
over and over for the sole purpose of securing a diploma which
mayor may not open the door to a good paying job?
If one answers
these two questions affirmatively, should public monies be used
without discrimination to satisfy the needs of the~two CLasses of
ITorian ,students?
We ~pall postpone our answ~ to this quest~on
until we approach the policy recommendations.
Theoretically, the
traditional neo-classical approach to solvlng this problem starts
off by recognizlng that though private benefits are reaped by SOme
individuais consuming higher education, substantial (externaL) be-
nefits also go to society as a whoLe.
Individuals ma;! take "just"
the amount of education they need, without reaching the "optimal"
quantity they can "bUY", if the free market were to allocate the
tjUaA ti ty
of education .11.0, k.; education wilL be providea, and, sO-
ciety as a' Whole may not benefit from this seLfish restriction uut
may instead suffer.
The purpose of subsidies to individuals,is
not only to compensate for their foregone income but also to paY
for the consumption by the pUblic 0 f r\\.e~e ~,'.e.e a,oo~s. ';ubs id;~s cII':io "'(v~ '1~
incentive for individuals to buy the optimal quantity of education
they would otherwise not have bought.
(See any standard economic
te~ook for a more formal treatment of consumer behavior.)
Economists outside the neo-classical perspective (especially
Marxists, but also "Liberals") have another view on llIhy society Should
.al~6oate_~blic re~o~TCe&-for education, especially tor disadvantaged
s.tuden.ts'. -These econom:i.sts abandon the "market place" e:plana ti~o..n 0 f
- 8 -

---

the
non optimal
consumption of education to consider the pre-existing
socio-economic order in the country.
In the Ivory Coast entrance into a
ghen
le~el
of
education
is
determined
by
an
exam,
not
by
choice.
However,
unequal
distribution
of
education
is
not
due
solely
to the
entrance exams, but to other factors that still
need to be researched.
crom that perspecti~e, the current inequities should be sought in social
relations
to
the
production
process,
where
other
inequalities
rest.
Thus,
an
equally
important
objective
of
public
policy,
should
be
to
restore equity even at the expense of some inefficiencies in allocating
resources.
2.
Equal Opportunities in Access, Equal Life Time Benefit
Returning
to
the
basic
question
of
what
mechanisms
a
"fair"
allocation of public monies should be made towards education, we shall
retain
two
aspects
of
the
complex
equity
issues
in~olved: (1) equal
opportunity
of
access
to
higher
education
and
(2)
equal
life
time
benefit from higher education.
It
is
presently
a well
accepted
practice
in
democracies,
that
students of di fferent economi c backgrounds are gi ven an equal chance to
enter a particular school
level.
Any barrier which is not based on the
abi 1ity of the student himself should be removed.
Hence no tuition fee
or
other
form
of
economic
discrimination
should
be
imposed
on
the
students when he or she has shown through tests the capacity to succeed
in higher education.
Equality in opportunity to enter higher education
is
often
analyzed
through
the
social
class
composition
of
the
students.
The standard approach to define socio-economic status (SES),
that
limits
it to the
nuclear
family,
can
be
very misleading
in the
-
9 -

---

Ivory Coast if one does not have a clear understanding of other social
factors
which
affect
income
determination.
In
Fig.
3-2 we develop a
recursive
model
which
may
be
used
to
ascertain
in
a
formal
way
the
determinants of access to HE schools and higher earnings.
It depicts a
set
of
inter-relations
that
may
affect
access
to
HE,
and
therefore
higher earnings.
Following the directions of the arrows one can notice
for
instance,
that
some
variables
influence the
process more
directly
than others.
In particular the figure
shows that factors like type of
baccalaureat (SAC), parents' wealth and political
power as having direct
influence
in
access
to a
school.
Variables
such as
sex and
parents'
literacy level are mediated by other factors.
Entering
the
university
does
not
assure
success
at the mandatory
yearly
exams
nor
guarantee
the
diploma
on
which
job
offers
and
salaries
are
based.
We
may
therefore
better
understand
the
equity
aspects of a school's financing scheme by evaluating its effect on life
time benefit.
. RICA/~(~
/ ' f-·t
l'Jr '
l<$"~"~'"
The
substantial
economic
benefit
provided/.t!y{higher edut.?tion
in
H,v
CA
\\v,
the Ivory Coast coupled with selectivity through::,e,xa~s~r.ofises~ah issue
\\'%. \\
7 ,,'f
over
the
soci o-economi c
backg round
of
students~,whO~~J/;pi
t",Vfrom
the
')05'<",
•
'0'
-Ipn~ _nt~v.~
program.
We cannot draw a definite conclusion on the~i,s,sue
of equity
based only on the SES analysis because HE is financed by taxpayers.
Not
only that, but taxation and other fiscal mechanisms used to secure funds
for
HE
may
be
di sproport i ona lly
coil ected
from
di fferent
1eve 1s
of
income or socio professional
groups of the country.
The issue should,
therefore,
be broadened to assess whose funds are bei ng used today, to
provide money for tomorrow.
We, therefore need to be more precise about
the
equity
issues we seek
to analyze.
We need
be certain
that while
-
10 -

---

resolving today's inequities we don't simply create a different set of
inequities for tomorrow.
The literature distinguishes between two types
of
inequities
when
dealing
with
life
time
equity:
intragenerational
distribution equity, and equity in intergenerational distribution.
3.
Inter-generation and Intra-generation Equity
In
analyzing
the
distribution
of
income
across
generations
(intergenerational
distribution)
one
evaluates
the
extent
to
which
individuals starting in the same socio-economic groups do not end their
life-cycle
in
different
income
brackets:
a
horizontal
equity
issue.
There
is
also
a
vertical
equity
issue
involved
whereby
one
seeks
assurance
that
individuals
from
different
income
groups
contribute
proportionally the same proportion of income to the financing of higher
education.
Within
the
same
generation
(intra-generation)
the
same
distinction
in
equity
in
finance
need
to
be
made.
In
view
of this
complexity,
many
approaches
are
suggested
in
the
literature.
The
enlightening
debate
that
followed
the
Hansen
and
Weisbrod's
(1969A)
monograph attests to these difficulties.
3
4.
Selectin9 an Equity Yardstick
In evaluating the effect
on
income redistribution of government
spending
and
finance
of
higher
education
in
Kenya,
Fields
(1975)
set
three
criteria:
(1)
the
equal
opportunity
criterion,
(2)
the
cost-
benefit criterion and (3) the ability to pay criterion.
By
the
first
criterion,
i.e.,
equal
opportunity,
a
program
is
equitable if different
groups have access to it in the same proportion
they are found in the total
population of the country.
Thus, if 60% of
-
11
-

---

the
Ivori ans
are
farmers,
60'%
of
the
students
in
HE
shoul d be
from
farming
origin
before the
financing
of
higher education
in
the
Ivory
Coast can be made equitable.
It should be noted here that no account is
made of the costs of and benefit from HE.
By this criterion, we only
look at a cross-section of the student population and express an opinion
on what we find at the precise point in time the survey is conducted.
Clearly
no
historical
changes
can
be
captured
in
such
a cross-
section
survey.
In
this
type
of
analysis
we
can
compare
the
distribution of sChooling within a generation
(of HE students) to that
of an older generation (of parents) and possibly that of a much younger
one (of non-HE students).
The equal opportunity criterion is therefore
used to assess the intergenerational effect of financing HE.
The equal
opportunity
criterion
also
shed
some
light
on
the
horizontal
equity
issue, i.e., the distribution of earning between individuals of the same
income
groups.
The
cri teri on
captu res
the
long-term effect
that
an
educational
program
has
on
children
who
are
born
to the
same
socio-
economic level even though their adult lives may be in different income
brackets.
The
second
criterion
suggested
by
Fields
is
the
cost-benefit
criterion.
A program
for
financing
education
1S
equitable
by
this
criterion if "the costs paid by different groups 1n the population are
proportional
to the
benefits they each
receive,
irrespective of their
access
to
the
program"
(Fields,
op.
cit.,
p.
246).
Like
the
equal
opportunity criterion,
the cost-benefit criterion applies to horizontal
equity in the distribution of income, as well
as to comparisons between
different
income classes,
the vertical
effect of the program.
Unlike
the equal opportunity criterion, this second criterion applies primarily
-
12
-

---

to income distribution within a generation, and cannot indicate what the
the long term effect of the program wi 11
be.
For the program to be
considered equitable, the rural group must support 20% of the costs, and
receive
20% of
the
benefits
if
these
populations are of equal
size.
Likewise, the urban group must also bear 80% of the costs and enjoy 80%
of the benefits.
This criterion also fails to capture the nonmonetary
effect of having access to the program which cannot be translated into a
simple cost and benefits terms.
It relies heavily on the cost structure
considered and the ability to evaluate all the benefits accruing from,
for
example,
higher
education.
The
different
elements
of
costs
and
benefits
introduced
by
the
analysts
and
also
the
choice
of
the
appropriate discount
rate
clearly affects a judgement based
upon
the
cost-benefit criterion.
The
last criterion
is
the
"abi 1ity to pay" whereby a program is
equitable "if the cost-benefit ratio of the program
rises as a function
of income."
This
is true because a higher income bracket must bear a
heavier part of the tax burden due to the diminishing marginal utility
of income.
If,
for instance, a low income group having a cost benefit
ratio of 0.7 and a high income group participates in the financing of HE
in
the
same
proportion
of
0.7
cost-benefit
ratio,
the
scheme
is
inequitable.
This is because given their latitude to spend more money,
the
cost
benefit
of
higher
income
brackets should be
over and above
0.7.
Here a vertical equity issue is at stake.
The three critera for assessing the equity of a fiscal
program in
HE,
may yield different opinions,
depending on which one is used.
We
shall
illustrate this difference
in the following hypothetical
example
adapted from Fields
(op.
cit.)
and applied to financing of HE in the
-
13
-

---

Ivory Coas t.
TABLE 2.1
EQUITY CRITERIA, AN HYPOTHETICAL EXAMPLE
%0 f Cos t
Benefits = % of
Income Group
% of Population
supported by
Beneficiaries
High income group
25%
10%
10%
Low income group
75%
90%
90%
Toal population
100%
100%
100%
By
the
equal
opportunity
criterion,
the
above
example
of
fiscal
program for financing HE is not equitable because the low income group
which
comprises
75%
of
the
whole
population,
receives
90%
of
the
program's subsidies.
The high income group is discriminated against in
this scheme.
According to the cost-benefit criterion, where equity is measured
by the percentage of cost compared to the percentage of benefits for all
income groups, the system of financing HE here is indeed equitable: 10%
of
the
cost
goes
to
hi gh
income
groups,
and
they
reap
10%
of
the
benefits.
Likewise,
the remaining 90% of the benefits from HE goes to
low
income
groups,
who also support
the
same proportion
(90%)
of the
costs.
The
last
criterion,
the
ability
to pay,
which
requires
that
the
-
14
-

---

ratio of cost to benefit
rises with the income level, contradicts both
the
fi rst and the second criteria.
The cost benefit ratio of the poor
(equal to one) is the same as that of the rich, though by definition the
rich have a higher income level
and should therefore participate in the
financing of HE by a higher cost-benefit ratio.
The program is not only
inequitable, but also discriminates against the poor.
Though the choice of criterion may affect the conclusion drawn from
the
results,
the
analysis
itself
is
not
hampered.
In
order
to
thoroughly
tackle
the
issue
of equity
in
financing of HE
in the
Ivory
Coast we
shall
consider all
three criteria
in our analysis as well
as
recent approached suggested in the literature.
5.
Income Versus Earning
Following
a
now
well
established
research
tradition
in
the
Economics
of
Education,
we
shall
use
University
students'
parents
"earnings"
rather
than
their
"income"
when
assessing
the
equity
in
benefits
reaped
from higher education.
One
reason
for this choice is
because of the way the data are collected.
Earnings, also called labor
wage, is more accurately reported in a survey-type research than income,
which may originate
from many other sources
inclUding earnings.
it is
also possible to verify the accuracy of answers
to the survey by using
public
and
private
sector
wage
scales
existing
in
the
country.
The
second
reason
for
using
earnings
instead
of
income
is
that the
labor
wage
is
supposedly determined by the
productivity of the worker, which
is
also
assumed
to
be
imparted
by
education.
Income,
which
may
originate
from
property,
capital
or
heritage,
has
less
obvious
connection to the
education
of
its
owner.
Using
"earning"
instead of
-
15
-

---

"income" helps therefore, to isolate the "pure" effect of education.
It
is
then
possible to develop an
appropriate educational
policy
based on
that
effect.... Ther.e
is. one drawback
to .the
use
of
"earning~_ however.
Labor wage constitutes only a small
portion of the income in high income
brackets.
Any educational
policy may therefore have a limited impact on
Ule overall
distribution
of total
income.
flhenever
possible, we shall
introduce
an
estimate
of
all
other
sources
of
income
related
to the
educational
level.
We
shall
also
loosely
use
labor wage,
income
anrl
earnings, when a clear distinction is not warranted.
Another possible way to group wage earners is by socio-profession:
managerial
work,
professionals,
employee,
laborer,
plantation
O\\<ner,
small
farmer,
etc.
Income
level
classification
does
not
always
correspond
to job classification,
because the social
prestige attached
to
some
jobs
does
not
necessarily
translate
into
monetary
terms.
Doctors,
for instance, are not well
paid in the
Ivory Coast but enjoy a
high social
prestige.
The effect of financing HE on the distribution of
Ivorians
into
prestigious
jobs
will
be
ascertained
along
with
the
earning distribution.
Like
in many
under~eveloped
countries,
the
government
employs
the
majority of HE graduates.
Wages in the public sector are not determined
by
the
labor
market
but
according
to
rigid
regulations.
The
consequences of such practices on earnings will be fully evaluated later
when we discuss the benefits of HE.
C.
A Review of Theoretical
Issues
In
the
remainder
of
this
chapter,
we
review
some
of
the
theoretical
and
empirical
studies
existing
on
equity
in
e~ucational
-
16
-

---

finance
in
the
Third
World
in
order
to assess
the
current
status
of
knowl edge with
respect to the effect
of the
fi nanci ng of education on
the
redistribution
of
income.
We
discuss
the
directions
that
the
research
has taken
before examining equity
issues
in the economics
of
education.
The
short
digression
helps
us
to
examine
the
main
theoretical
issues
in
education,
economic
growth
and
income
distribution.
1.
Education and Economic Growth
The research in economics of education in the Third World has
been
motivated
by
policy
concerns
of
nations,
rather
than
by
the
internal
dynamics of the various theories.
Because most of the people
who analyze the issues are based or trained in developed countries, the
research has often followed trends from that part of the world.
Hence,
in
the
early
sixties
when
economists
were
concerned
with
designing
strategies
of
development
for
the emerging nations,
they
followed
the
path
set
by
Schultz
(l961)
and Denison
(1962)
in
the
USA.
This
path
invol ved
investigation
of
how,
at
the
macro-economic
level,
education
can account for "the unexplainable"
part of U.S. economic growth between
1909 and
1927.
For the Third florld,
Harbison and Meyer
(l964) have an
important
influence
in
inspirin9
belief
that
a
massive
investment
in
"human
capital,"
especially
at
the
secondary
and
hi9her
level
of
education, can increase the per capita income of individuals.
A new wave of interest then evolved in the mid-sixties, which tried
to ascertain more precisely the extent to which investment in education
was
economically
"profitable,"
compared
to
alternative
social
investments.
This
marked
the
be9innin9
of
an
era
of
studies
in
the
-
17
-

---

economic returns to education.
The literature on this' issue abounds in
any economically advanced country, starting with the pioneering work of
Hansen (1963) and the landmark book of Becker (1964).
In
the Third World an
impressive
number 'of studies has also been
carried out
in this
field
by Carnoy
(1967,
1970, 1972), Blau9
(1969),
Pscharopoulos
(1973),
and
others.
For
a more
complete
list
of
such
studies in the Third World, see Blau9 (1978).
The computation of rate of returns to education pointed to the fact
that
different
returns were attached to different
levels of education,
and to different income groups.
It was therefore important to isolate
the income differential
attributable to education alone.
This type of
investi9ation
led to studying the
role of
labor markets and other non
educational
factors in shaping the earnin9 stream associated with levels
of education.
In this re9ard, the conventional competitive labor market
assumption of early human capital
theorists I<as continually questioned,
as
was
their
contention
that
direct
relationship
exists
between
education,
productivity
and
salary
levels.
Ber9
(1970)
and
Fuller
(1970)
show
that
even
amon9
people
.lith
similar
productivity,
more
schooling was
given higher reward,
regardless of their contribution to
output.
Thurow
(1972)
also
contends
that
"trainability"
is
the
main
concern
of
employers
rather
than
productivity
imparted
by
school ing.
Workers
"queue-up",
as
he
argues,
for
the
most
productive jobs,
which
are also the best paid ones.
Productivity is an attribute of the job,
not of workers.
They acquire their skills on the job, not necessarily
through school.
This Vlew of the
labor market
rejects, therefore, the
alleged direct contribution of education to economic growth.
-
18
-

---

Similarly, other authors in the early 70s have come to question the
assumed
contribution
of
education
to
economic
growth.
They
can
be
roughly
grouped
into
"screening
theorists"
and
"social
class"
theorists.
The first approach associated with Arrow (1972), Taubman and
~Iales (1974), and others, suggests that school acts as a mechanism to
"screen"
potentially
"good"
workers
from
the
"less
desirable"
ones.
Arrow
also
shows
that
even
i f
school
as
a
"screen"
increases
total
output
by
lowering
the cost of
labor
search,
it transfers
savings to
employers alone, which does not lead to a "better-off" economy.
The second approach in the U.S. is associated with economists such
as
Bowles
and
Gintis
(1976),
Carnoy
(1974),
and
Levin
(1978).
They
argue that school
transmits the prevailing
ideology of the society to
future
generations,
and mediates
contradiction
between work
place and
society.
They are even more skeptical about the alleged contribution of
education
to
economic
growth.
Even
"hen
they
concede
such
a
contribution, they argue that other social factors overshadow its value.
2.
Education and Income Distribution
In the mid-seventies, with the political strength acquired by
countries (China, Cuba, Tanzania) in which equity in the distribution of
the modest growth whi ch had already been achi eved, was as important a
goal
as increasing that growth, economists rediscovered the virtues of
the distributional
aspects of development.
The economics of education
also rejoined the debate.
The di fferent views on the role of education
in economic development such as the cognitive skills provider view, the
"screenitJ9 view,
or
the
"reproduction
of
class
structure" view,
each
develop a theory on school
and income distribution.
They respectively
-
19 -

---

see
education
as
income
equalizer,
income-neutral,
and
"deteriorating
factor" in income distribution.
The discussion in education and income
distribution
has
separated
two
issues:
the
role
of
education
in
the
distribution
of
income
within
a
generation,
and
the
distribution
of
income between generations.
The
existing
literature
on
inte,'generational
distribution
in
the
Third World and elsewhere overwhelmingly indicates that parents'
income
is strongly correlated to the offsprings'
type and amount of schooling
(see
Carnoy
(1967);
Carnoy,
Sack,
and
Thias
(1975);
Fields
(1975);
Jallade
(1974)).
There
is
an
unsettled
dispute
over
why
such
a
correlation exists.
Human capital theorists such as Becker and Chiswick
(1966) blame the imperfection in capital and labor markets, while social
class
theorists
point to the historical
and objective social
relations
of the different classes to the production process.
For human capital
theorists poocoarents must pay more, because of high interest rates, to
invest in their children's education than their
rich counterparts
(who
may not even need to borrow money).
Rich childrenfmay'~also benefit from
~\\\\.A KI~'4~
better contacts in the labor market,
higher ihhe~i~t'~l~ligence, and
i - l,c,q
\\ ~
nondiscrimination.
On
the other hand,
sOf~a\\ ~C'l.aSS(>~hr'j,;ists examine
the existing economic system of production 'in depth by ;Z.6~ing at which
\\. ,
.,'
,"/<1,...
J-.~\\e
J
social
class
holds
political
power,
and
whoonrow'ns
the
means
of
production,
while
human
capitalists
merely
criticize the mechanics
of
the
market.
The
social
class which
is
1ikely to
possess
the
afore-
mentioned attributes will seek a larger amount of education for its off-
springs and place them in higher paying jobs.
For
the
intrd-generational
distribution
of
income
we
are
less
interested in individual's mobility than change in the structure of the
-
20'-

---

distribution.
Two sets of evidence are often presented: they are on one
hand,
cross-section
analyses
of
education
and
income
inequality
at
a
single
point
in
time
for
several
countries;
and
on
the
other
hand,
longitudinal
data
for
a
few
countries
over a
certain
period of time.
The first type of analysis is often associated with the work of Kuznets
(l955),
but
also
with
Adelman
and
Morris
(1973),
Chenery
and
Syrquin
(1975)
and
Ahluwalia
(l967A
and
B)
for
the
Third World.
Kuznets
and
Adelman and Morris in particular argue that
in general, distribution of
income
is
more
equal
in
both
technologically
advanced
countries where
the
level
of education is also higher,
and traditional
societies where
modern
education
barely
exists.
For
underdeveloped
countries,
the
inequal ities are temporari ly needed to reward entrepreneurs.
This is a
temporary situation because the economic growth which should follow will
have a
trickle-down
effect
on
the
poor.
This trickle
down effect
is
possible because economic growth wi 11
necessitate more educated workers
sharing
a
larger
part
of
the
total
modern
output,
thus
leading
to
reduction
of
inequal ities
between
both
entrepreneurs
and workers,
and
amongst workers.
In the Third World Adelman and Morris (op. cit.), and more recently
Ahluwalia
(op. cit.), have shown that
income inequalities have lessened
with
improvement
in
education,
or
at
least
with
a
reduction
of
illiteracy.
Psacharopoulos
(1978)
and ChisVlick
(1971)
using a measure
of
dispersion
of
educational
attainment,
associate
greater
income
inequality with greater dispersion of schooling.
But this evidence only
suggests
the
role
education
can
play
in
reducing
income
inequality.
What we need is evidence over time for each country, so we can ascertain
the concommitant
role of government
fiscal
and wage pol icies,
the
role
-
21
-

---

of multinational corporations,
and all other factors. that affect
the structure of income distribution.
The
few
pieces
of
evidence
available
from
longitudinal
studies
within
countries
are
found
in
Langoni
(1973),
Carnoy
et
a1.
(1979),
Jallade (1979), and Fields
(1978).
Langoni, for instance, suggests that
income distribution has become more unequal
in Brazil
because education
distribution has also become more unequal.
Other authors
(for example,
Malan
and
Wells
(1973))
indicate
that
income
inequality
has
not
been
reduced significantly despite tremendous economic growth performance in
these
countries.
t·lore
factors
determining
inequality
reductions
are
macro-economic
rolicies
related
to
wage
structllre,
regional
inequalities, and unemployment.
3.
Financing of Education and Distribution of Income
To what extent does financing of the education system affect
the distribution of earnings
in a specific country?
This question has
not
received
much
attention
in
the
developing
world,because i t is a
:cela:tively new debate in developed·. countries.
Foreign
assistance
in
developing
the
educational
system
of
poor
countries
has
overshadowed
national
concern with the
political
economy
of
educational
finance,
therefore
very
few third
world
countries
have
conducted this
type of
inqui ry.
We are aware of only four studies 4 in
the Thi rd l,orld which
attemrt
to
find who is paying
for
the education
system and
who
receives
the
subsidies
for
and
benefits
of
education:
FieldS'
(1975) paper on Kenya's higher education, Jallade's (1974) study
on
Columbia's
distribution
of
public
expenditure
on
education,
Szal's
(1979) work
in Botswana
and Foxley's et a1.
(1979) study in Chile.
Vie
- n -

---

shall consider the main theoretical arguments of these papers.
Jallade's
paper
pioneered
this
type of study
in
the Third World.
But,
he
confined
his
effort
to
public
expenditure
in
school.
and
therefore
overlooked· the
important
private
investments
made
tiT-higher
income groups
in private schools.
He also neglected the controversial
issue
of
the
present
financing
schemes'
long
term
benefits,
and
therefore
ignored
future
earning
power
made
possible
by
the
present
system of education.
The main conclusion Jallade draws from his study
(Table
2-2)
is
that
"the
publ ic
financing
of
education
in
Columbia
contributes
to
redistributing
income
from
the
rich
to
the
poor,"
(p.
69).
Although the lower income group receives less public subsidies for
education,
they
also
pay
proportionally
less
of
the
costs
of
education.
For Jallade,
a progressive tax and subsidy for educational
purposes may give less fortunate children greater access to education.
Another
pioneering
work
on
equity
in
distribution
of
costs
and
benefits
of
education,
this
time
about
Africa,
is
Field's
study
of
Kenya's higher education system.
He looks at the distribution of total
(private
and
publ ic)
costs
and
total
benefits,
whereas
Jallade
was
interested only in public sector costs and subsidies.
However, Field's
study was limited in scope since he only looked at higher education, and
neglected
lower
levels
of
education.
He
proceeds
by
outl ining
three
criteria
of equity on which he tests
the Kenya sUbsidy scheme:
(1) the
equal
opportunity criterion,
(2) the cost/benefit criterion, and
(3) he
ability to pay criterion.
By the first criterion a system is equitable
if each income group has access to the program
in the same proportion
as
they are
represented in the overall
population.
Costs and benefits
are not
taken
into account.
According to this criterion,
he suggests
-
23
-

---

TABLE .2-2
Urban Colombia:
Allocation or TaX~8 and Public
,
Subsidies tor Education Among Income Croups
Subsidies
Allocation
per child
Allocation ot
Subsidies
Income
or Taxes
Subsidies Per
in eoch
r.nrollment Public Subsidies
as
)'ro~)ort 1.
Bracket
Distribution
(H1111ons ot Pesos)
Child Enrolled income Sro~p
'I'Atio
For Education
of Taxes
7-
(f"c50s/Ycar)
or f.nmilies
Alt. 1
Al t. 2
(reOOg)
(pe.os)
(5)
(4 )
(H1111ono ot Peso.)
. "I t . 1
,\\ Ll .
(I)
(2 )
(J)
(4)
(5)
(7)
(8)
(9)
(la:
0-
6,000
2.1%
23
14
1,315
640
.49
71
1. 9%
309
507
6,000- 12,000
12.6
183
119
1,136
490
.43
217
5.7
119
182
12,000- 18,000
15.2
438
306
1,217
552
.45
370
9,7
84
12 I
18,000- 24,000
15.1
658
454
1,.~ 76
711 .
.48
530.
13.9
81
117
N
24,000- 30,000
10.0
560
392
1,414
688
.49
41)
10.8
74
105
"'" 30,000- 36,000
7.5
548
382
1,716
816
.48
345
9.0
63
90
16,000- 48,000
9.5
949
688
1,674
869
.52
477
12.5
50
69
48.000- 60,000
],3
826
590
2,103
1,145
.54
410
10.8
50
6~
60.000- 72,000
4.3
675
517
2,020
1,064
.53
301
7.9
1.5
56
72,000- 84,000
3.6
616
455
1,325
751
.. 57
163
4.3
26
)b
84,000-120,000
5.9
1,500
1,137
1,210
705
.58
196
5.1
13
17
120,000-180,000
3.7
1,405
1,897
1,370
887
.65
189
4.9
13
10
180,000-240,000
1.9
1,048
1,628
873
579
.66
62
1.6
6
4
Ove r 240,000
1.3
2,894
4,225
986
605
.. 61
69
1.8
2
2
Total
100.0%
12,32)
12,804
1,469 .
746
.51
3,81)
100.0%
31
30
Source:
Jol1.de (1974), Tob1.o 3.15 ond 3.17

---

that higher education in Kenya is not "equitable" because the proportion
of students from low income families is less than their actual
ratio in
the
total
population
(Table
2-3).
Using
the
second
criterion
(of
cost/benefit), the system is equitable when the cost paid by each group
is
proportional
to
the
benefits
received
by
similar
groups
of
equal
size.
No account is taken here of the access to the program.
According
to
this
second
measurement,
Kenya's
higher
education
appears
rather
equitable,
though
mid-income
groups
tend
to
be
favored
over
higher
income
groups.
The
last
criterion
(ability
to
pay)
uses
a comparison
between
the
cost-benefit
ratio
and
the
income.
If
the
cost
benefit
ratio rises with an
increase in
income,
then
the
program is equitable.
He suggests that higher income and mid-income groups are favored by this
criteri on.
Why do Fields's findings reveal contradictions?
The answer lies in
the
different
equity
issues
considered:
vertical
equity
(comparison
across
income groups), or horizontal
equity (between individuals of the
same
income
group).
"The
main
inequity
in
Kenya's
higher
education
system ••.
is horizontal," concludes Fields.
The two remaining studies dwell
mainly on Jallade and Fields' work
in
terms
of
methodology
and
concepts,
and
do
not
need
further
development.
Foxley,
et
al.,
finds
that
the
financing
of
Chile's
educational
system
is
very
progressive.
By
the
ability
to
pay
criterion,
the
system
is
equitable.
But,
it
is
not equitable
by
the
equal
opportunity criterion since the
lower class
bottom group
(60'; of
the
Chilean
population)
is
disproportionately
represented
in
the
education system.
- 2S -
,
:
I

---

TABLE 2-3
a
Incidence of Tsxea and D18tt"lbutton by Income: ot Students' .)"Hent" I Kenya, 1971
% ot Income
Students' Parents'
Income - %ot R~ncr
To1C.~n by
t ot Income
% ot T8X~8
IncOltlc
Indlrcct
Taken by All
% ot Tax-
"old Ly
Bracket
TaX!H 10n
Taxe.& (Direct
Payers in
TSllpayers 1n
Primary
Secondary
Unlver&:il:::;
(Sh •. /Vr. )
Alono
and Indlr~ct)
That nracket
ThDt DrAcket
lTC.
TTC"
o( N;IIt'!'.!!.'_
(1)
(2)
(3)
(4)
0)
(6)
(7)
(8)
0- 2,400
8.7%
12.5%
90.5%
67.9%
70.7%
74.7%
60.2%
0,222) .
(D6)
( 138)
2.400-,3.600
7.3
10.9
.1.B
4.0
5.4)
8.8j
i66)
(18 )
")
0)
1,600- 4,800
5.4
8.1
1.1
2.2
6.2
4.9
2.2
(JOB)
(22)
(5)
4,800- 6,000
·4.6
7.6
0.7\\8.4
1.4 ~16.)
5.6
4.4
19,8
11.8
(97)
23.7
(20)
6,000- B,400
4.8
8.2
0.5J
l.5J
6.2
4.7
N
(107)
(21)
::~J
(27)
'"
8,400-12,000
5.9
9.5
O.S
2.4
1.9
1.8
2.2
(J3)
( B)
(S)
12,000-16,800
4.5
16,800-24,000
~.5
9.0
1.1
11.7
O.B
t
" ]
3.4
0.9·
OB)
(4)
5.6
2.2
5.5
9.6
(14 )
j
. (10)
( 22)
Over 24,000
4.4
11.9
1.4
2.4
(24)
(11)
Total
100,0%
100.0%
100.0%
100.0%
100.0%
0,729)
(4 Sp)
(n9)
~umber of student8 given In parentheses.
Source:
Held.
(l975b). Tabl. III pg. 252.

---

Similar
findings
are
reported
in
Botswana
by
Szal.
The
publ ic
subsidy.
education and tax distribution by
household are
indicated in
Table
2-4.
His
study
shows
that
an
ever-increasing
proportion
of
educational
funds
are
going towards
higher household
deciles;
this
is
considered
unequal
by
the
equal
opportunity
criterion.
Howeve r,
the
cost-benefit
ratio
rises
with
income,
hence
satisfying
the
redistributive
aspect
of
income
from
the
rich
to the
poor,
within
a
gene rat i on.
The
review
of
literature concerning
the
redistributive effect of
educational
finance
on
income
in
the Third
World,
indicates
there
is
inequity in access to education in most Third World countries.
At the
same time. higher income groups are contributing in higher proportion to
the financing of education, which indicates there
is a progressive tax
system in
these
countries.
The system of taxation
is
viewed
by many
analysts
(Jallade
in
particular)
as
a powerful
means
of
giving
lower
social
classes of a country access to education.
He also stresses the
role
played
by
private
schools
in
shaping
present
and
future
income
distribution.
D.
A Synopsis Review of Some Empirical Studies
It
should
be
pointed
out
that
no
consensus
exists
ln
the
literature on what methodology most adequately grasps the issues.
Hence
the
debate that
fol1owed
the
Hansen
and ,Ieisbrod
paper
(op.
cit)
has
focused mainly on methodology, and little on policy recommendation.
We
shall not attempt a thAlrough review of all points of view in the debate
since it can be found in Nelson (I978) and elsewhere.
Rather, we select
four methodologies for analyZing empirical issues.
The choice of papers
- 27 -

---

TABLE 2-4
Rura 1 Botswana:
Incidence and Distribution of Taxes and Public
Expenditures in Education by Deciles.
1974/75
Household
Di s tri but ion
Distribution
Incidence
Distribution of
Incidence of
Cost-Benefit
of Deci 1es
of Income (%)
of Taxes (%)
of Taxes (%)
Educa tiona 1
Educational (%)
Ra tio
( 1)
( 2)
(3 )
Expendi tures{%)
Expenditures
(2)/{4)
1.
1.71
1. 42
7.28
3.56
6.16
0.40
2.
2.76
2.39
7.58
4.06
4.35
0.59
3.
3.27
2.87
7.70
4.06
3.67
0.71
4.
4.35
3.72
7.50
5.57
3.78
0.67
N
00
5.
5.40
4.73
7.70
6.63
3.63
0.71
6.
6.43
5.63
7.70
7.90
3.63
0.71
7.
8.46
7.10
7.37
11. 01
3.85
0.64
8.
10.25
8.65
7.41
10.44
3.01
0.83
9.
15.47
12.89
7.32
13.17
2.52
0.98
10.
41.89
50.59
10.60
33.61
2.37
1. 51
-
- -
100.00
100.00
8.71
100.00
2.96
Source: Szal (l979)

---

is made according to originality, as well as extent to which they cover
world
issues
on equity in
financing of education.
In
vi ew of these
criteria,
the
following
work
will
be
reviewed:
Hansen
and
Weisbrod
(1969A),
Windham
(1970),
Jallade
(1974),
Fields
(1974).
For sake of
clarity and for comparative measures we regroup these four studies in
Table
2-5.
It
appears
from Table
2-5 that whatever the methodology
used,
a common
thread
appears:
computation
of
costs,
computation
of
benefits and computation of incidence.
The conclusions reached in the
table
suggest
overWhelmingly
that
benefits
of
education
are
redistributed in favor of the rich, except in Colombia.
E.
The State of
Knowledge in the Pol itical
Economy of Educational
Finance in the Ivory Coast
A review
of
the
literature
and
empirical
studies
revealed
no
relevant
research
in
education,
growth and income distribution in the
I vory
Coast.
Neither
could
we
cite
any
literature
relative
to
educational
finance.
In the Ivory Coast there is a striking paucity of
research
in
this
field,
a
surprising
fact
considering
the
relative
ri chness of data and studi es on the development of the country's· economy
and
in
other
social
sciences.
The
existing
body
of
literature
on
economics and education in the Ivory Coast is dominated by cost studies
conducted by
international
or national
agencies for
(1) assessing the
feas i bi 1ity
of
programs:
World
Bank
(1969),
Chau
(1972A),
(1972B).
1vory Coast S.E.E.P. LE.
(1968, 1972), Daniere and Orivel
(1977);
(2 )
evaluating the cost of the program after its implementation: Hallak and
Poignant
(1966),
Cerych
(1967),
Klees
and Jamison
(1973),
Klees
and
Jamison (1976), Klees and Evans (1976), D.P.!.
(1977), Eicher and Orivel
-.29 -

---

TAHLE 2-5
A SYlIQPSIS,
REVIEW
Of 4 EIlPIRICIiL STUDIES 0/1 EQUITY 1'1 EOUCATIOtIAL flNAt'CE
STUDY
OBJECTIVES
METHODOLOGY
OATA
CONCLUSIONS
REMARKS
Hansen &
I.
Esttmate'
the subsidies
1. Computation of benefits
1.
To Comnute Be~efits
I.
The ta,fng unIt that
No net
Weisbrod (1969)
received by families
accruing to tndividuals
-1959 Census data on
subsidize!
HE does not
Income
through the inst1tut10ns
attending HE. Adjustment
1ncome and salaries
benefit from ·the
on income
of H,E, tn California tn
was made for level of
- Survey of Call fornia
f1nanc1ng scheme.
groups
1965.
Cal f fornta income tn 1965
2.
appears.
t ncome tn 1965
Necessity to sub-
2.
Evaluate variatfon
ability, migration. mortaltty
Income used
- 5% discount rate
sidIze low tncome
1n subsidies rece1ved
unemployment.
from 18 years to 65
famtl les to compen-
are average
by type of HE·
2. Computat1on of costs of both
sate for their fore-
tncome of
- probabtl tty to enter
3.
Evaluate varIation in
public and private under-
gone Income
.
famllles in
the job market.
subsidy received by
graduates HE.
3.
PublIc subsidies
each Insti-
- expected number of
students, by SES
3. EquIty jud9ement based on:
go In a higher pro-
tution not
graduates by sex.
of the students.
- the extent to which the
portIon to hl9her
Individual
2. To
Compute Costs
4.
Ascertal" a net transfer
beneficlarfes of public
tncome brackets.
familY
- tnstruction costs
of subsIdy to family with
subsidies pay back through
- cap'tal costs
'ncome.
or without chlldren
lffe-long taxes.
Many dls-
- books and supplies
attendln9 HE in Calff.
- the dIstribution of sub-
parit les
costs
sldtes to and
taxes for HE
may have
w
-foregone earnings
o
among Cali fornhns
been lost
-rOOm &. board Costs
In the
3. To Compute Incidence
aggregat Ion.
taxes by 1evel of
tncome
students enrollments
by 'ncome groups and
type of /lE
See Tabl e 2-6
Wi ndham
Tes t hypothes is tha t the
1.
Computation of tax payment
1. To Compute Benefits
1.
Higher Income
- 8udgetary data
(1970)
effect of stite financed
by Income groups ane
- distribution of
groups recetved
leads to over-
HE In Florida Is to re-
distrIbution of these Income
students by Income
proportfona ll.vrrnre look private costs
distribute Income In
groups tn type of HE
group and by type of
education sub-
by tvoes of HE
favor of hIgher Income
HE.
stdies than they
class
2.
Computation of net burden:
2. To Comsute Costs
oald taxes
-Assessment of
-cost supported by an Income
-e~pen \\ture categor1es
2.
Ihe sys tems 0 f
long term e (feet
group Is subtracted from
for each type of HE
flnancfng could
of flnanctng HE
benefits received from HE
-tax collected from each
make
future
Is rather specu-
(evaluated by public tnvest-
Income group going to
tncome dlstri-
latlve and not
ment tn HE going to each
financing types of HE.
but ton worse.
supported by
income 9rouP).
(see Table 2-1).
data.
- net burden computed for each
type of HE.
3.
Equfty judgement based on
"net gain- of each Income group.

---

TABLE 2-5 (Cont'd)
STUDY
OBJECTIVE
METHODOLOGY
OAT A
CONCLUSIONS
REMARKS
Jallade
I.
Impact of pUblic education on
1. Computation of tax burden by
I. To cornrute Tax Burden
1 . The 5 cheme to
hhaustlve analy-
(1974)
expenditure on Income distrf-
Income groups.
-dtstr butlan of income
redistribute 1n-
515 for all
button in Colombia.
2. Computation of subsidies to
by households, for urban
come from the
levels of
2.
Distribution effect of tax paid
education by income group.
and rural groups
rlch to the poor.
education and by
to
subsidize education
3. Equity judgment based on ratio
-dfstrlbution of taxes
2. lower Income re·
regional dfs-
J.
!nc'dence of taxatfon and
of subsidy Over burden
paid by 'ncome groups.
ceives less public
tribut Ion
expenditure on income distr1-
4. Equity judgment applied to
2. To Compute Subsidy
subsidy but also
- Private cost
but Ion
different regions of the
-number of children
pays less taxes
of educa tion
country.
by Income groups
Ignored.
-enrollment in levels
-No long term
of school
effect of the
-public expenditure
scheme.
per pupil per school
1evel .
3. To Compute Incidence
ratio of tax p:id and
w
subsidy received for
~
educa t Ion.
(See T'bl e 2-2)
Fields
I.
Analyze effect of govern-
1. Define three criteria.
1. For Erual Opportunity
-System not equtt-
Only HE consider-
( 1975)
ment expenditure on income
- equal opportunity
-enro lment by type of
abl e In oppor-
ed
dfstrlbution within one
- Cost-benefit ratIo
HE and Income level
tunlty ~o access
Analysis too
generation and across
- ability to pay.
-Income of students
-equitable by
restricted to
generations In 1971.
2. Evaluate life tIme
parents.
cost-benefit
hypothesis
2.
Examine horizontal equity
benefits from attending
-number of taxpayers
criterion
testing.
aspect of school finance.
HE.
by income level
-By abll Ity to
J.
Compute enrollment of
2. for Cost &enef1t
pay criterion,
students by income group
-distrfbutfon of taxes
lower income
and compare tt to that of
by Income level
are dlsfavored
taxpayers .
-distribution of
~. Distribution of tax paid
enrollments tn types
by 'ncome group compared to
of HE.
benefit received from HE
3. Ability to Pay
by tncome group.
- income distribution
5. Ratios of tax paid and
In Kenya.
beneftts received are com-
puted by income group.
(See Table 2-J)

---

TABLE 2-6
AVERAGE FAHILY INCOHES, AVERAGE HIGHER EDUCATION SUBSIDIES RECEIVED, AND AVERAGE
STATE AND LOCAL TAXES PAID BY TYPE OF INSTITUTION CHILDREN ATTENDED IN
CALIFORNIA, 1964
Families with
Families without
Children in Calif.
Children in Calif.
Public Higher Education
Public Higher
All Families
Education
Total
J.C. *
S.~*
U.C. *
(1)
(2)
0)
(4 )
(5)
( 6)
1.
Average family
income
,
8,000
7,900
9,560
8,800
10,000
12,000
w
N
2.
Average higher
education subsidy
per year
o
880
720
1,400
1. 700
3.
Average total state
and local taxes paid
620
650
740
680
770
910
4.
Net transfer
(Line 2 - Line 3)
-650
+140
+40
+630
+790
Source:
Hansen and Weisbrod (1969-A)
*J.C. Junior College
S.C. State of California Universities
U.C. University of California

---

TABLE
2-7
ESTIMATED DISTRIBUTION OF TAX PAYMENTS BY INCOME CLASS 1960:
Gillespie (In Millions of Dollars)
Income Classes
Income Classes
$5,000
$7 ,500
$10,000
All
7,499
9,999
above
Classes
$0
$2,000
$3,000
$4,000
1,999
2,999
3,999
4,999
22,171
12 ,192
40,385
95,075
Total Federal Taxes
2,385
4,222
5,437
8,282
16,046
9,556
38,312
77 ,379
Total
Federal Taxes
Revised
1 ,571
2,787
3,494
5,613
Income Group as a %
of Total
Federal Taxes
w
w
Revised
2.0%
3.6%
4.5%
7.2%
13,278
5,492
8.072
39.072
Total State and Local
Taxes
1,655
2,521
2,916
5,137
11,549
4,329
5,591
32,306
Total State and
Local Taxes Revised
1 ,505
2,259
2,520
4,553
Income Group as a %
of Total State and
Local Taxes Revised
4.7%
7.0%
7.8%
14.1%
27,595
13,885
43,903
109,685
Total Revised Taxes
3,076
5,046
6,014
10,166
25.2%
12.7%
40.0%
100.0%
Income Group as a %
of Total Revised Taxes
2.8%
4.6%
9.3%
Source: "Gillespie, Effect of Public Expenditures on the Distribution of Income," and calculations by the
author.
Extracted from Windham (1970).

---

(1977).
In a recent book,
Oiarassouba
(1979)
describes
the
National
University
and
its
main
activities.
In a previous
study,
the
same
(1973)
author
examines
the
investments
in education
in
light
of
the
Ivory Coast's 1971-75 economic plan.
A few manpower studies have also
been conducted in the country: Monson and Pursel
(1976), Wells
(1978).
Three books on the economi cs of the I vory Coast dedi cate a few pages to
the economics
of education
in the country:
World Bank
(1978),
Goreux
(1977); Bourgoin (1979).
Finally, a few sociological works completed or
in progress now, are bringing new insight to educational
issues in the
Ivory Coast:
Foster and Clignet
(1966), Bentata
(1975),
Cires
(1974),
Charlick (1978).
- 34 -

---

CHAPTER I I I
MODEL DESIGN AND DATA TREATMENT
In the mid sixties, Clignet.
and Foster,
.
(1966) published the
fi rst major study on secondary school students of the I vory Coast under
the title
"The Fortunate Few."
The phrase was meant to emphasize the
particular nature of that
level
of education in the Ivory Coast.
They
show
how
the
policy
of
admission,
selection
and
graduation
made
the
students who completed secondary school a special
group of the Ivorian
population.
Approximately ten years later, Charlick (1974) conducted a
study on Ivorian students in Higher Education.
He analyzed the origins,
the
determinants,
and
the
aspirations
and
career
choice
of
the
students.
He concluded
that
although
inequality
by
sociO -economic
background affects
access
to
higher
education
in
the
Ivory
Coast,
a
relatively equal
chance
is
given
to
students to enter the carrier of
their choice.
Since the completion
of the Charl ick
study in the mid-seventies,
the Ivory Coast has gone through a rapid period of social, economic and
pol itical
transformation.
It was
timely to assess the impact of such
changes in enrollment in higher education.
We began such evaluation by
conducting
a
surveIJ on
the
student
population
in
the
fall
of
1980.
Because of limited data on other HE
institutions we were compelled to
confine our study to students of the National University who constitute
80% of the higher education population.
Our objective in the survey was
twofold.
First we sought to reassess the degrees of inequality found in
previous studies in higher education enrollment.
Secondly we wanted to
look
into the distribution
of
costs
and
benefits
from
attending
the
- 35 -

---

National
University
among
Ivorians,
an
aspect
neglected
by
previous
studies.
In
the
first
section
of
this
chapter
we
briefly
examine ~the
historical
evolution
of
the
National
University
and
its
impact
on
administrative and academic policies.
In a second section, we suggest
two models for:
(1) explaining access to schools of higher education;
(2)
evaluating
the
equality
of
chance
in
academic
achievement
of
students from different socio-economic variables.
In the last section
of this chapter we describe the survey procedure and the treatment we
made of the missing values and other data of the survey.
A.
The National University System
1.
A Brief Historical Review
The
National
University
evolved
from
a sub-campus
of
the
French
university
system
located
at
Dakar
(Senegal)
in
195B,
to the
University
College
of
Abidjan
in
1964.
The
institution
was
then
composed of four departments: Science, Law, Letters and Medicine.
These
,
departments grew into full
fledged
"facult~s"
(schools) from 1964 to
1972.
Three other schools were added to the system between 1972 and
1974.
The first one was the School of Economics which was separated in
1972 from its traditional French mold of "School of Law and Economics,"
to
become
a full-fledged
"School
of
Economics."
The
Institute
for
Dentistry was developed in the geographical
vicinity of the school
of
f1edicine
in the same year
(1972).
In 1979, a School
of Pharmacy was
created
to
complete
the
training
of
pharmacists
in
the
Ivory
Coast.
Originally the first two years of pharmacy training were in the school
of sciences,
and
the
last years were spent in another country.
Many
- 36 -

---

I nst itutes
and Research Centers
(16 exi sted
in
1981) were created
in
each school to conduct research and specific training.
In 1974, the presidency of the university ("Recteur") was assumed
for the first time by an
Ivorian Professor of Economics breaking away
from
a long
tradition
of
French
"Recteurs"
at the
institution.
The
change from French to Ivorian "Recteur" marked the beginning of a more
rapid
process
of
transformation
at
the
local
university.
This
transformation culminated in 1977 with a change in denomination from the
"University
of
Abidjan"
to
the
"National
university
of
the
Ivory
Coast."
The
change
in
name
was
to
be
a
reflection
of
a
radical
transformation of the university, that served the needs of the country
in a broader context of the Education Reform Act adopted by the Ivorian
Parl iament in 1977.
The changes at the National
University was to take place not only
in terms of physical growth but also with respect to policy.
The first
major change was the Baccalaureat
(BAC) degree
(deli~red to those who
succeeded at the fi nal
hi gh school
exam) was no· longer the only means
of admission to the university as was the case in France.
As we shall
see
in
a
later
section,
many
other
factors
were
to
be
brought
into
consideration when admitting a student.
The
second
change was
that
the
State
of the
I vory Coast was
to
assume a larger and larger share in financing the National
University.
The financial
contribution of France to the University has been slowly
phased out, as we indicate in Chapter 5.
Concomittantly the Ivory Coast
has
been
increasing
its portion
in the
budget of the institution.
,Jith
its
accrued
financial
responsibility,
the
Ivory
Coast
ventured
further in curriculum and awarding diplomas.
- 37 -

---

Degrees delivered by the National University are no longer diplomas
of the French University
system as
has
been the case until
recently.
Under
the
new
agreements,
degrees
delivered
in
both
countries
are
certified as equivalent.
The equivalency in diplomas is policed by the
French
through
legal
agreements
but
also
through
informal
control
channels
such
as
control
for
recruitment
and
exchange
of
qual ified
teachers
and
the
maintenance
of
a
high
level
(through
text
books)
academic
contents
of
the
curriculum.
In
1980,40
percent
of
the
teachers at the National
University were of French nationality.
Of
the 50 percent of Ivorian teachers, 95 percent were trained in France.
This
French
influence
in
the
teaching
staff
constitutes
a
further
guarantee for maintaining the degree eqLlivalency.
Another change introduced within the agreements with France is that
the
Ivorian
faculty members need no longer compete with
their-French
colleagues
for
career advancement.
Today CAMES
(an
inter Francophone
African
Committee)
recommends
career advancement
after evaluating the
publications and teaching record of the candidate in consultation with
any professor
in
the world
capable
of
providing the expertise in the
evaluation.
2.
Organization of the University System
The National University has kept its highly centralized French
administration pattern.
Figure 3-1 describes the management system of
the university.
The "Rectorat" or central
administration has a strong
control over the everyday operation of schools through two offices: the
"Centre Universitaire d'Information et de Programmation" (CUIP) and the
- 38 -

---

MINISTRY OF NATIONAL EDUCATION I
\\
DIRECTOR OF HIGHER EDUCATION
rcuTIl
RECTOR OF THE
DIRECTOR OF TEACHE RS
DIRECTOR OF
I CUlPr--- NATIONAL UNIVERSITY
TRAINING SCHOOL (ENS)
STUDENT SERVICE
r
(CNOU)
Dean
Dean
Dean
W
Schoo 1 of
i l l
r
Dean
Oi ,cc toe
Dean
School of
School of
School of
School
~
School of
of
Letters
Pha rmacy
Law
Economics
Science
Medicine
,
,
- -
7
-
I
'~
DEPARTMENT
~ ~
DD
DI=JD
U
Institutes
and
Research
Centers
rl
I f
o[-1 LJ
Cl
Fig. 3.1
The Management System of the University"

---

"Centre Universitaire de Traitement d'lnformation" (CUTI).
The CUIP is
in
charge
of
planning,
execution
and
evaluation
of
such
varied
activities as publication of the university magazine, employer-student
relations and forecasting the number of students and faculty members.
The
CUTI,
a
center
for
information
processing,
is
in
charge
of
computerizing
data
on
students,
as
well
as
the
finance
system
and
library system of the university.
The
six
schools
of
the
National
University,
Law,
Economics,
Medicine, Science, Letters and Humanities, and Pharmacy are each headed
by a "doyen"
(Dean) elected for three to five years by the faculty of
the school.
A candidate must be at least an Associate Professor.
Four
ranks exists in the teaching position: Professeur Titulaire (Professor),
Maitre de Conference (Associate Professor), Maitre Assistant (Associate
Professor),
and Assistant
(Assistant
Professor).
The
modalities
for
evolution
from
Assistant
Professor
to
full-fledge
Professor
varies
accordi ng to the school.
Another service related to, but independent
of
the university, is
the CNOU (Centre National des Oeuvres Universitai res).
The CNOU is more
than a student services center contrary to what the name may suggest.
Under direct control of the Ministry of National Education, it provides
services
to
university
students
but
also
to
all
students
of
Higher
Education (HE) operating in the vicinity of the Cocody Campus.
Hence HE
schools
such
as
Ecole
des
Statistiques
(statistics),
Ecole
Normale
Superieure
(Teachers
Training),
Ecole
~Iationale Superieure des TravaLIX
Publics l (Civil Engineering), Institut National Superieur d'Enseignement
Technique, are served by the CNOU.
The main activities of CNOU are to
provide
housing,
restaurant,
sports
activities,
transportation,
and
- 40 -

---

recreation,
but
it
is
also
in
charge
of
any
matter
affecting
the
student's
welfare.
Clearly
CNDU's
responsibilities
preempt
the
uni versity
of
any
students'
concern
which
is
not
related
to
grades
or teaching.
This
artificial
division of roles
has often led
the university authorities to assume responsibility over social matters
which
originaten
at
the
CNDU.~
If
not
reconsidered
the
current
relationship
between
these
two
institutions
will
continue
to
spark
animosity
between
the
students
and
the
members
of
the
university
administration
and
teaching
staff.
Administration
and
teaching staff
represent
a
repressive
authority to stuctents, while CNOU
represents
a
supportive institution.
B.
The Mode 1 De s"igns
We
saw
that
the
new
policies
in
admission
of
students
into HE
introduced
by
Ivorian
policy
makers,
are
no
longer
based
on
the sole
success
at
the
BAC
exam.
The
complexity
of
the
admission
process
requires
that
we
have
a
clear
understanding
on
the
inter-relations
existing between
socio-economic background
variables
and
the schooling
process
of
the
students.
We
propose
in
Figure
3-2 a
recursive model
which explains these relationships.
1.
110del
1: Access to Types of HE Schools
[n the model
Vie
have
selected
11 main
variables
among
many
factors
which
may
influence access
to type of HE schools.
Figure 3-2
indicates that factors
do not
relate to each other in a linear fashion.
Hence
the
choice of
school
of HE
(variable x2) which directly affects
the student's access to a school
(Xl), is in turn .aff,,"ctedby th",," sex of
- 41 -

---

-7
x)
Literacy
of
P)7
Type of
X
~I
10
porents or
nAC
Kln9man
l' "- I>./,)
-
Areo~~l ~~ /
lIVl~-
"\\ ~ Xl
x 2
'" Access to
~ lypes Cl f
HE
Choice of I Pl2
'l. 01
~..-1 liE
I I
Et hn I c
X
p
X
4
B
" 1'<>
,
c"~,,, ~~
'1. ,,'1
IType of
Parent's
.".
N
\\ieolt h
I
P4B
_11I18h School
/:>
9
//
"58
X 9
Y!>'3
I
~v
,
I
P59
'
Kinsman's
Po lit le 01 Po"~r
\\ienlth
of Porents or
P95
Kinsman
/ '
P2
Figure 3.2
A proposed recursive Inodel explaining access to types of higher education
in the [vor,' Coast.
Note:
x. are standardized variables; P.. are the path coefficients (see text).
1
1 J

---

student
(x6)'
the type of BAC degree earned in high school, and a host
of other variables.
One can compute in a formal
fashion the Pij values
which
indicate
the
magnitude
of
influence
of
each
variable
in
a
student's access to a school.
Path analysis
is a statistical
analysis
quite appropriate for
treating
such a model.
Theoretically,
the model
solves as follows.
Model
1 as
represented
in
Figure
3-1
contains
11
variables which
can be expressed with a system of 9 equations.
Two variables, sex (x6)
and ethnic group
(xII)
are predetermined and do not need to be solved.
The variables xi are in a standardized form:
x - x
x.1
o
where
x
is the means of x and
0
is the standard deviation of x.
The
objective
in
the
path
analysis
is
to
reduce
the
intricate
system of equations to a simple linear function of the form
y
I Py
( 1 )
J
1 J
J 1
where J
1, ... n
p .. = path coefficients between the variables
1 J
y ..
= correlation coefficients between the variables.
1 J
Pij coefficients are determined by the g equations of which 4 will
be written here:
- 43 -

---

(2 )
=
(3)
=
P2 ,3x 3 + P2 ,7 x 7 + P2 ,BxB + P2 ,4x4 + P2 ,5x5 + P2 ,gX 9 + U2
(4)
( 5 )
U ,
U
I
2 , ",U n
are
the
stochastics
terms
and
assumed
unrelated.
Pij , the path coefficients are verbally interpreted as in P4,B for
example:
for one standard deviation change in
"type of high school ", on
average
there
should
be
P4 ,B magnitude change in standard deviation
(C.S.O) in "Parent's wealth," P
5 CSO
4
in "pol itical
power of parents or
,
kinsmen,·
P46CSO change in "sex" and P4 9 CSO change in
,
"kinsman
wealth."
The coefficients of the reduced form Eq.
(I) gi ve us a more precise
idea
about
the
interrelations
between
the
variables and
the
dependent
variable
(xl)'
However,
in this
study
these coefficients are not very
helpful
for
subsequent analyses when we aggregate coefficients
between
models
or when
we
compare
our
results
with
those of previous
studies.
The model will
therefore be approximated by a linear relationship.
Y = a + b x
x
x
2 2 + b
+ •• , + bllx
3 3 + b4 4
11 + U
where
a
is the intercept
bs are the regression coefficients
Xs are non standardized variables
- 44 -

---

U the stochastic term.
The estimates of these coefficients will be made in Chapter 4.
2.
Model 2:
Scholastic Achievement
In
the
second
model,
we
seek
to
determine
factors
that
influence
achievement
of
students
in
a
school.
This
type
of
investigation
has
been
at
the
center
of
many
controversies
since
the
early 60's under the label
"educational
production functions."
(see for
instance
Bowles
(1974),
Coleman
et
al.
(1966)).
In
this
type
of
research, the analyst tries to relate the educational
output, be it the
score
of a test or the
result
of an exam,
to a series of inputs that
they
bel ieve affect
that
particular output.
The
lack of agreement
in
the
number
and
type
of
inputs
to
be
i nt roduced
in
these
product i on
functions illustrates one major problem in that area,
that no one knows
how
the
educational
process
takes
place,
and
with
what
inputs.
In
general
the
inputs
related
to
teachers,
schools
and
to
students'
characteristics
are
thought
to
affect
the
educational
output
in
the
following non explicit manner.
o
Q(TKS)
where 0 is the educational output,
T, a vector of teachers characteristics,
K, a vector of school characteristics,
S a vector of student's characteristics.
Q is
the
function
which
translates
the
inputs
to
outputs.
The
particular
functional
form
used
by
researchers
vanes
but
usually
the
- 45 -

---

linear additive functional
form is adopted.
The
literature
in
educational
production
functions
takes
two
separate directions depending on the level of development of the country
where
it
is
appl ied.
In
developed
countries
(Coleman:
1966;
Jencks,
1972;
Bowles,
1974)
it
indicates that
inequalities
in education output
also
is
associated
with
inequality
in
socio-economic
background.
In
underdeveloped
countries,
however,
(Heyneman,
1976,
1980;
Schiefelbein
and
Farrell,
1973;
Carnoy,
1975)
schools
inputs
are
more
strongly
related to aChievements, than socio-economic background inputs.
We estimate two types of educational
production function,
one for
the determinants
of achievements
in each
school,
and
a second for the
achievements of individual
students.
In the first production function,
the dependent variable is the average promotion rate in the schools.
A
number
of
independent
variables
which
we
bel ieve
affect
the
average
promotion rate in the schools are introduced in the analyses.
We assume
a
linear
relationship
between
the
independent
variables
and
the
dependent variable.
VI
a + b T
+ b T
+ ... + bsT
+ C K
+ C K
+ ... + CnK
+ U
1 1
2 2
s
1 1
2 2
n
1
where
VI
average promotion rate in a school
T
~ vector of teachers characteristics
S
Kn
vector of school characteristics.
In a second production
function we measure the dependent
variable
as "the number of years it actually takes a student to complete a cycle
over and above what 1S normally required."
A
host
of
other
independent
variables
are
introduced
in
the
- 46 -

---

analysis.
In
particular,
in this
second model
we include a vector of
socio-economic
variables
of
the
student.
The
model
is
therefore
modified as follows:
where
Y2
number of years used to reach a particular "form"
St 0
number of student socio-economic background variables
Other variables have their previous meaning.
Finally, we assess the enrollment of students at the university by
ethnic group, area of birth, size of city where they attended elementary
school,
the area
of
residence
until
12,
the education of the parents,
and the socio-profession of the student's father.
For this assessment
we use an
index
often
used
by
sociologist,
(see for instance Charlick
(1977)
and Foster and Clignet
(1966),
but
also by
political
scientist
under the label
"ratio of advantage."
The selectivity index S is computed as follows:
S·1
s
0
where Si is the percentage in the sample whi ch has the cha racteri st i c i
and
Pi
is
the
percentage
in
total
population
which
has
the
characteristic
i.
The
results
of our estimates of the models of this
chapter are reported in the next chapter.
In the last section of this chapter we describe the collection of
- 47 -

---

our data.
C.
The Data Base
1.
Data Collection
Two sorts of data were used in this work.
The first type is a
compilation
of
financial
and
statistical
data
provided
to
us
by
University officials
for
the academic years
1975-75, 1977-78, 1978-79,
1979-80,
and
1980-81.
The
precise
nature
of
these
data
will
be
indicated
in
the
appropriate
tables.
We
refined
these
statistics
by
collecting additional qualitative data consisting of interviews with the
President, professors and students and by visiting the schools.
We also
relied on our personal
experience as
alumnus
of the institution in the
evaluation of data or interviews given to us.
The second type of data was colleted through a survey we conducted
~.
from September to December 1980..
We inserted 15,000 questionnai res in
the
registration
material
of
all
Ivorian
students
enrolling
in
the
institution for the academic year 1980-81.
As stipulated by university
authorities
each
student
of
Ivorian
nationality
was
to
fill
out
our
questionnai re before they could be consirlered
registered.
In spite of
this
regulation,
a
few
students
turned
our
survey
in
blank.
These
unfilled
surveys
went
undetected
by
the
busy
registration
office.
Neither
could
we
identify
students
who
partially
filled
the
questionnaire
because
we
required
anonimity on the questions
to allow
freedom in the answers.
We
random·ly selected
(using a table of random
sampling) 20% of the completed questionnaires from clusters representing
each school.
The clusters were weighted proportionally to their actual
number
in
the university. The
total
sample
population
on
which
we
- 48 -

---

performed our analysis was 1,274.
Table 3.1 indicates the distribution
of
students
by
school,
and
the
returned
rates
associated
with
the
:-"
;;.
schools as well as the proportional weights applied to each school.
:~,
The returned
rate of the survey varied according to school, and a
total
number
of
6,215
completed
questionnaires
was
received
by
our
office.
He obtained 66.66% returned rate on the survey which raised the
question
of
a
cheaper
alternative
survey
method.
1·le
chose
the
systematic sampling procedure (as opposed to selecting first a sample of
the student population to which one applies the questionnaire) based on
our
previous
research
experience
with
university
students.
First,
a
preselected sample always loses the original characteristics on which it
was
constructed:
target
students
are often missed,
time
period chosen
stretches,
complicated administrative
issues
arise
concerning why some
students are chosen and others not.
Secondly, there is no way to insure
that students participate in a survey unless it is mandatory.
Third, by
conducting the survey at the beginning of the year (the only time period
when students register for the academic year) we were sure to reach all
the
students.
Finally,
in
using
a
systematic
sampling
approach,
we
wanted to permit other researchers to draw a sample different from ours
for other types of research.
2.
Missing Values
A
survey
with
unequal
returned
rate
and
noncompleted
questionnaires poses two theoretical
issues.
First, there is a problem
of' vali di ty;--If-·the respondent has showw some-reservat i on vi s--avi s the
survey by not adequately answering some questions,
there is nothing to
insure
that
the
remainder
of
the
surveys
really measures what
it was
- 49 -

---

TABLE 3-1
Population size, returned rate, and weighted sample size by
school for Ivorian students at the
--
- ... _~ ---~ -
National Univers ity
Population
Number of
Returned
Weighted
Sc hoo 1 Name
(a)
Retu rned
rate (%)
samp 1e size ( b)
N
%
N
%
N
%
Law
2,331
24.98
1, 315
59.02
318
25.0
Economics
1,572
16.84
1,215
76.46
214
16.8
Medicine +
10S (c)
971
10.4
515
54.06
133
10.4
Sc i ences
Pharmacy (c)
1,513
16.2
1,180
75.59
207
16.2
Letters
2,944
31.55
1,980
66.04
402
31. 6
TOTAL
9,331
99.98
6,215
1,274
100.00
Notes: (a)
Only undergraduate students were surveyed except in the case
of Medicine where it is impossible to dissociate graduates
from under9raduates due to the organization of the school.
(b)
The 20% randomly drawn samp 1esby cluster was then propor-
tionally weighted to reflect the share of the clusters
(schools) in "the observed population.
(c)
Medicine and the Institute for Dentistry (10S) were aggregated
because they share many academic, administrative and financial,
arrangements.
The same situation applied to sciences and
pharmacy until 1977.
We chose, however, to continue the
procedure for sake of simplicity when comparing with past
data.
- 50 -

---

intended to.
Indeed the problem of validity arises in all
surveys and
there
exists
no
sure
method
for
assessing
the
validity
of any
survey
except
perhaps
in psychological
tests
(cf Novic,
M.
1966).
We shall,
like in most surveys, rely on the "face validity" of the answers.
A second
problem
raised
by
missing
values
is
the
problem
of
reliability.
The question here is how accurate on the average, are the
estimates done from our sample,
compared to the true parameters of the
population.
In
psychological
tests
it
is
possible
to
scientifically
compute
one
of the
several
coefficients
of
reliability
to
assess
the
overall
reliability
of
a
survey
(see
for
instance
Novick
and
Lewis
(1967)).
In
our
survey we did not
measure attitude
or
opinions.
We
will
therefore
rely on different
approaches to assess the reliability.
First, we select answers given to questions related to household items,
and
apply
a
Guttman
scaling
test
(cf Guttman,
L.,
1945)
to
them
for
evaluation
of
a
predictive
trend.
Second,
we
compare
statistics
on
variables between students who did not fill
the questions and those who
did.
Finally, we use a comparison of our results with those of Charlick
(op.
cit.),
as
an
additional
means
to
assess
the
reliability
of
our
sample.
The Guttman scale test
is explained
in more detail
in Appendix B.
The coefficient
of reproduclbility
(which assesses the extent
to which
the
score
obtained
by
the
respondent
is
a predictor
of
the
response
pattern), is relatively high (0.9130) in our sample (see SPSS, 1979, for
the computer program).
We also obtain from the same test a coefficient
of
scalability
of
0.58
indicating
how
the
items
we
chose
are
unidimensional
and cumulative.
The test of Guttman scale is considered
one of the many possible specification of a test of reliability.
Given
- 51 -

---

the stringent
requirements of these tests,
a result close to the ideal
magnitude of the coefficients (0.90 and 0.60 for the two coefficients we
computed)
assures
that
the
true
reliability
of
a
sample
is
always
higher.
In our survey, the coefficients we obtained
(0.9130 and 0.58)
assure
uS
that
the
responses
given
to
questions
related
to
household
items
are
good
predictors
of
the
respondent's
answer
pattern,
a
good
proxy for reliability.
We
further
verified
the
reliability
of
the
answers
given
in
our
sample by comparing the statistical distribution of students who did not
answer the questions about thei r parents' income with the overall sample
of students.
We chose the variable related to income because we later
regrouped students by their parents' income.
We want to be certain that
those who did not provide information on that variable did not belong to
a specific group of the students
population.
Table 3-2 compares these
two
groups
in
terms
of
percentage
distribution.
We
chose to
do the
comparison
with
five
variables
that
provide
information
on
the
department attended, the year at the university (not the number of years
spent), the distinction obtained at the high school degree
(a proxy for
academic
performance),
the
size
of
the
city
where
students
attended
primary
school
(a
proxy
for
social
origin)
and
whether
or
not
the
student
obtained
assistance
from
individuals
other
than their parents
for thei r education
(a
second
proxy
on soci al
ori gi n).
The foll owi ng
remarks arise from Table 3-2.
The
sample
of
students
who
did
not
provide
information
on
the
income
of
their
parents
is
on
the
average
similarly
distributed
by
categories of variable as the overall
sample.
Although in four out of
five variables the mean index of selectivity (which indicates the extent
- 52 -

---

to which the group of students with missing values is better represented
than the overall
sample) is higher for the group with missing values.
The
difference
in magnitude
is
almost
insignificant
in the variables
"year at the university"
(0.01),
"size of primary school
city"
(0.01)
and
"department attended"
(0.02);
and
acceptable
for
"distinction for
SAC" (0.15).
As for the variable which measures assistance obtained by
the students outside of their family (and government) circles, the group
with
missing
values
for
their
parents'
income
is
under
represented,
although by a small magnitude (0.02).
The overall picture given by Table 3-2 indicates that students with
missing
information
on
income
are statistically similar to those who
provided the information.
Finally, our personal observations on circumstances which may have
led to the reported missing values on some variables, or the failure to
return the questionnaire confirm the two previous tests of reliability
on
our
sample.
First,
students
look
for
ways
to
simplify
the
complicated
registration
process.
Filling out
our questionnaire with
negligence was one to simplify that process.
Second, in Table 3-1 we
observed that departments with lowest percentage returned rates (Law and
Medicine)
are
also
administratively
independent
of
the
central
registration
office of the university.
These schools did not closely
follO;l
the
new
registration
instructions
related
to
our
survey.
In
these schools the students could have failed to turn the survey in, or
answered
some
questions
only
partially
and
still
have
registered.
Third,
students
had
approximately
a week
between
the
day
they
could
collect their reglstration package and the day they needed to complete
their registration.
During that lapse of time some students lose their
53

---

Table 3-2
Selectivity indices on five variables for the student group
which had missing values on variables related to· income of their parents.
1 .
. 2
3
4
Variables
Sample constituted by
Final
Index of
missing values (%)
Sample (%)
Sel ectivity
2/ 3
Deparment Attended
Law
25.8
25.0
1. 03
Economi cs
14.3
16.8
0.85
Medicine
10.1
10.8
0.93
Science
24.4
16.2
1.5
Letters
25.5
31.5
0.80
Mean index
*
*
1. 02
Year (toward graduation)
1st year
42.5
42.0
1. 01
2nd year
25.8
26.7
0.96
3rd year
18.2
19.2
0.94
4th year
11. 0
9.6
1.14
Mean index
*
*
1. 01
Distinction Obtained
for BAC
Very good
0.5
0.4
1. 25
Good
1.4
1.0
1.4
Fa i r 1y good
15.8
16.7
0.94
Average
82.3
81. 5
1. 01
Mean index
*
*
1.15
Size of City of
Prlmary Schooling
Abidjan
24.3
19.4
1. 25
Boua ke'
6.8
6.5
1.04
Prefecture
20.4
20.6
0.99
Sous-Prefecture
18.6
19.9
0.93
Village
28.8
33.1
0.87
Mean index
*
1. 01
Assistance obtained
outside the parents
for education
Yes
33.0
36.6
0.90
No
67.0
63.2
1. 06
Mean index
*
*
0.98
- 54 -

---

questionnaire,
don't
replace it,
and assume the registration
personnel
will
overlook the
loss.
Finally,
our questionnaires were coded in the
Ivory Coast
and entered into a computer system in the U.S.A.
We were
surprised
to
find
that
English
speaking
typists
had
difficulty
deciphering
French
speakers
handwriting.
These
diffi cu It i es
rendered
some
results
in
the
data
analysis
as
out
of
the
range
value of some
variables
and
they
were
therefore
interpreted
as
missing
values,
or
dropped from the analysis.
From the four possible causes for
missing
values enunciated above
we cannot
infer that the questionnaires with missing
values followed a
particular pattern, consequently there is no reason to believe that the
"mi ssi ng values" group of students was stat i st i ca lly di fferent
from the
sample population under study.
The problem still
remains concerning how
representative our sample is for the universe from which it was drawn.
Unfortunately
we do not
have
many
variables
from the
universe
to
compare
with
our
sample.
The
three
variables
from
the
university
population we had data on are reported in Table 3-3.
From Table 3-3, we
see that
our sample is on average accurately
representative of the sex
distribution on campus, even if the females are under represented by an
index of
representativity of 0.01.
Our sample,
however, seems to be a
less
accurate
representation
of
the
university
populations'
age
distribution.
In particular younger ages,
18 to 20, and 21 to 23 years
old
are
over
represented.
Such
a di sproport ion
ari ses
from the
fact
that our sample excluded graduate students whereas the statistics on the
original
population
combine
graduates
and
undergraduates,
without
distinction in age.
We could not isolate the age of undergraduates from
the university population statistics on hand.
The overall average index
55 -

---

TABLE 3-3
percentage distribution of students in original population and
sample population.
1
2
3
4
Actual university
student population
Selectivity
in 1980-81
Our sample
Index (3/2)
Variable
(the universe)
1 - Student's sex
Male
83.4-
83.7
1. 00
Fermale
16.6
16.3
0.98
2 - Age of Student*
18-20 years of age
5.10
5.0
0.98
21-23
"
"
2.80
5.0
1. 78
21-25
"
"
50.30
69.8
1 .39
26-29
"
"
26.80
12.3
0.46
31- and up
17 .20
12.9
0.75
Mean Index
1. 07
3 - Male Students
Law
77.3
80.4
1. 04
Economics
87.8
89.3
1 .01
Medicine
75.8
79.0
1. 04
Science
92.4
88.4
0.95
Letters
77 .9
80.4
1. 03
Mean Index
1 . 01
* The frequency distribution of the variable
"Age of
student" does not sum up to 100 because we omitted the age
group 16 to 17 considered negligeable in our survey. Also
the
age 21-23 is counted twice because included in 21-25.
-
56 -

---

for age is however biased
only by 0.07 index points.
The mean age in
both
groups
is quite
similar
(25
and
25.44)
and the modal
age
is the
same
(23).
Sex
is also fairly
represented by department, with only a
0.01 point index margin.
In
overall,
our
sample
is
a good
representation
of the
original
population and though many students
did not answer some questions, the
tests
we
performed
indicate
that
the
non responses
are
randomly
distributed, although not so, by subcategories in some variables.
- 57 -

---

CHAPTER IV
THE NEW FORTUNATE FEW
In the previous chapter we suggested that one needed to re-evaluate
the
socio-economic
background
of
university
students
in
1980-81
to
better assess today's inequities.
We then described a survey designed
to collect the necessary data for the task.
In this chapter, we present
the major results attained.
We start by estimating results of the test
of the model of admission into the different schools of the university.
We
proceed
with
the
results
of
the
test
for
assessing
equality
in
academic achievements of students, but also their chances of obtaining a
diploma
from
that
school.
Finally,
we
discuss
the
current
socio-
economic composition of students enrolled at the university.
A.
Equality in Admission to the University
One of the changes, introduced by Ivorian authorities with their
newly acqui red power over higher education,
was that
the SAC was no
longer the sole criterion for admission into higher education.
It then
becomes important to delineate what factors determine acceptance into
the
University
system.
What
gap
has
been
created
between
the
government's official policy of admissions and its implementation at the
National University?
1.
The Official Policy of Admission
In the French tradition of higher education, the university
organizes a national exam called Saccalaureat or SAC for senior students
of
secondary
schools.
The
SAC
is
supervised and
controlled by
the
- 58 -

---

university to insure that students completing the secondary schools have
attained the level
of education required for higher education.
In the
sixties for
instance,
exam papers were graded
in France or by French
Professors
to
further
guarantee
that
students
comply
with
the
requirement.
The
SAC
degree
is
therefore
very
competitive
and
on
average 51 percent of the candidates are successful.
Success in the SAC
exam
assures
automatic
admission
into
a
school
of
the
university
system.
In
addition,
students
who
prefer
to
attend
one
of
the
prestigeous
institutions
of higher education
called
"Grandes
Ecoles".
are
required
to
take
a
specific
exam
organized
by
that
particular
school.
Entrance into the "Grandes Ecoles"
is even more competitive,
for
these
schools
train
engineers,
high
level
management
personnel,
administrators, and prestigious secondary school teachers.
Until 1970, the Ivory Coast conformed with the French tradition in
admissions
policy
to
higher
education.
The
country
had
often
been
criticized for adopting a pol icy which served a purpose in France but
had
no
bearing
in
a
country
which
imported
70%
of
its
high
level
manpower.
As
the
number
of
students
at
the
National
University
increased
from
2,700
in
1969/70
to
10,772
in
1979/80
a
change
in
admissions policy was contemplated.
Indeed, since higher education is
tuition free and university services are highly subsidized, the increase
in student number increases the financial burden.
Figure 4-1 indicates
a steady increase in student numbers in all
schools, but especially in
Law and Letters, during the academic years 1975 to 1980.
Faced with an
increase
of
students,
a
new
policy
of
admission
which
had
actually
existed
since
the
late
60's
was
revived.
The
new
university
admission
policy
is
articulated
around
three
criteria.
First,
the
- 5.9 -

---

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- 60 -

---

manpower needs
of the country
expressed
by the Ministry
of Planning;
second, the availability of reSources in higher education institutions;
third,
the
choice
of
higher
education
institution
expressed
by
the
students when taking the SAC.
From the students's
perspective,
the choice of school
in higher
education
is made
in the fi rst year of the second cycle of secondary
school
(classe
de
seconde).
The
type
of
"seconde" where
they were
di rected by the government, (Social Science and Humanities or Scientific
Seconde) determi nes the type of SAC they wi 11 take, hence the choi ce of
higher education
institution opened to them.
Once the students
have
been assigned in a school, or department, no changes may be considered.
The
Ministry
of
Planning
evaluates
the
manpower
needs
of
the
country according to manpower surveys conducted
in the
jJublic
and
private
sector
of
the
economy.
Experience',!\\tl>fadvanced
planned
economies of Eastern Europe has indicated that a gap exists between the
manpower needs expressed in a sector of activity and its fulfillment by
the educational
system.
Manpower needs
surveys
are seldom accurate.
The
assumptions
behind
manpower
planning,
fixed
input
coefficients
(equipment,
teachers,
classes),
lack
of
substitution
between
skilled
people, and lack of change in the economy are quite unreasonable for an
emerging nation.
The third factor affecting a student's assignment to a school
is
the resource availability in the schools.
~10re than anything else, the
lack
of
teachers
has
been
the
major
constraint
against
opening
a
particular department to student enrollments.
Needs for more auditoria
has
not
been
so acute until
the
last
five years.
In the school
of
science where the lack of laboratories is well known, the deans' request
- 61 -

---

for
resources
have
not
centered
around
the
needs
for
teaching
equipment.
The major
batt 1e engaged between departments to fi 11
the
requi red
quotas
of
fi rst
year
students,
has
centered around student's
academic
qualification.
The
task
of
allocating
students
to
the
schools
lS
accomplished
by
a
special
commission
called
National
Commission
for
Orientation and Scholarships
(N.C.O.S.).
The commission
is composed of
representatives
of all
ministries
in
charge
of
education,
a
member
of
the
teachers
union,
the
students
unlon,
and
the
parent
students
association.
The
career
choice
for
a
particular
department
by
the
student
is
determined
by
examining
the
specialty
of RAC
obtained
in
high
school
(there
are
at
least
10
specialities),
the
distinction
obtained for the BAC, the Ministry of Planning's requirements and spaces
available
in
the
schools.
About
half
of
the
students
(48.%
in
our
sample) find themselves in the first school
for which they applied.
12%
of the students in our survey said they were assigned to a school which
was
not
among
the
three
choi ces
they
were
requi red
to
l!lake
in
hi gh
school.
26% received their second choice and 14% attended schools which
they indicated as third in the order of their preference.
Our
sample
is
constituted
by
the
privileged
group who
did
obtain
admission to the university.
The other group lS composed of RAC holders
who
are
assigned
to
police
academies,
teacher
training
school
or
the
school
for
training
physical
education
teachers.
A survey
in
these
schools would certainly indicate a much higher proportion of discontented
students.
ln
view
of
tile many
criticisms
addressed
to
it,
the
~I.C.O.S. has
glven
the
follo,ling
explanations
for
the discrepancy between
students'
- 62 -

---

choice and their final
assignment 10 a school.
(1) Students who apply
to
schools
for
which
their
SAC
specialty
did
not
prepare
them
are
assigned
a
school
by
the
commission.
(2)
Students
who
had
a poor
performance at the SAC are not
assi91wd to the schools of their first
choice
especially
not
in
schools
known
to
be
difficult.
(3)
In
an
attempt
to
acqui re
the
best
students,
deans
1imit
thei r
quota
of
students than what they can really absorb,
they
render the task of the
commission, more arduous.
Indeed Fig.
4-2 indicates the difference in
rate of
increase of first year
student Dj school.
,Ihereas Law School
has
had
an
exponential
rate of
gro"th,
t·\\edicine has
had a relatively
stable enrollment over the years.
In
light
of
the
criticisms
of
the
commission
outlined
above,
we
seek to exami ne in the
rest
of this section the characteristics of
students who are admitted to the school of their first choice.
2.
Who Enters Which School
It
is
important
to stress
that
the
group of students we
analyzed
here
were
the
most
fortunate
ones.
They
are
amon9
the
51
percent who
succeed
at
the
SAC,
and
are
admi tted
to
a school
at
the
university.
In
terms
of
academic
qualification,
the
students
shoV'
the
characteristics indicated in Table 4-1.
Only 18 percent of the students
allocated
to
a school
at
the
univI'rsity
had
an
academic
distinction
above average on their SAC degree.
A bad distinction for SAC does not
seem to be
a handicap
for'
admission
to
the
university.
In
terms
of
special izat ion
for
8AC,
the
social
sciences
SAC
(A4)
is
better
represented
(48%)
than
any
other.
It
is
followed
by
the
rnath
and
- 63 -

---

EV0LUTI0N 0F NUMBER 0F FIRST YEAR STUDENTS
'I
,
I
I
r
I
I
i
I
I
I
I
I
1- I i 'l I .~ •
(J)
1--
z
1500
LtJ
o
=:J
f-
(J)
()~
-<
w
>-
1000
f-
en
~
.~
~-
IL
<15
IJ _
J
..---------:
- - c
(SJ
1/
~
0/
IJJ
- - - 4 "
m
500
~
____________3 ----
L::
~
~ -::.------
=:J
-7
I
cl
rl
rj-~~
L
A
1
I
!
!
_::1
=:r==::o
I
I
!
I
J1.
I
I
I
I
41
I
!
I
75
76
77
78
7~
80
ACADEMIC YEAf~
l"'LA\\1 2=LEHERS
3=ECON
4=SCIEliCE
5=f1EDECINE
FIGURE '4,2

---

TABLE
4-1
Distribution of university students by type of distinction
obtained for BAC,
specialization of BAC,
and attribution of school
Variables
%
1.
Distinction for BAC
Very good
0.4
Good
1.0
Fairly good
16.7
Average
81. 9
2.
Specialization of BAC
Classical studies (Al,A2,A3)
0.9
Social Sciences (A4)
47.9
Economics and Business (B)
5.7
Math and Physical Science (C)
4.2
Math and Natural Science (D)
35.0
Math and Technology (E)
0.7
Technology and S.ciences (F)
0.3
Business (B SEC, G)
3.1
Spec i a1 Law Exam (Capa)
1.2
Special University exam
0.3
3.
Choice of School Granted
First Choice
48.1
Second Choice
25.9
Third Choice
13.9
No Choice Granted
11.8
Choice Granted outside BAC
Specialization
0.3
- 65 -

---

natural science BAC
(BAC 0: 35%).
However, the statistics cited above do not provide us with enough
information
about
factors
determining
school
assignments.
We
will
therefore
introduce
other social
factors which may explain a student's
assignment to a particular school.
We suggest that different factors
affect the assignment of a particular school to a student in the manner
described
in f10del
of Chapter 3.
We construct a dependent
variable
'",hich '1'€asures
ho" students are assigned their
first
choice
of
school
(i.e.,
the
fi rst
preference
whi ch
was
made
1 n
hi gh
school).
Our
hypothesis
is
that
many
socio-economic
and
school
factors
affect
the
decision of flCOS school
attribution
in the manner expressed in Fig. 3-
2.
Students
"ho
have
a member
of
thei r
fami Iy
in
an
upper
income
bracket or whose "kinsman" have political power, have a better chance of
obtaining their choices of school.
fie tested this hypothesis by running
the regression analysis Shown in Table 4-2.
The dependent
variable was
obtained by asking students to
indicate the order in which they listed
their preferred
schools,
and
the actual
school
they were assigned to.
Th" preference is categorized as
indicated in variable 3 of Table 4-l.
Each
category
of
choi ce
was
gi ven
the
same
wei ght.
1ndependent
variables
measuring
the
SES,
the
academic
history,
and
some
charac-
teristics uf the current school vlere introduced in the regression.
Only
thp
six
variables
vlhich
appear
in
Table
L2
vler'e
signi ficant.
The
results in Table 4-2 indicate that. social
science Bf,C appears to be the
most impnnant factor
(6 = .('6)
in elE-terminin'] ilcllllittancp to the first
school
chosen
in
high
school.
I'or
nJeelical
students
having
ranked
me di c i ne
1 n
the
1i st
of
choices
~vi'ls
the
1l10St:
siynificant
variable
affecting
the
NCOS
(8 = .18).
The
most
important
vari ab 1e
was
- 66 -

---

TABLE 4-2
Regression of the 'fulfillment of the preference for
school expressed by the student"over six
independent variables
Standardized Coefficients
Independent Variables
Beta
Ty~e of Secondary School
.06
Distinction obtained for BAC
.09
*
BAC for Social Science and Literature
.26
**
Grouping of Student by Household Item
.08
Student Admitted ln Law
- .15
Student Admitted in Medicine
.18
2
R
=
0.098
Number of cases = 803
All coefficients were significant at 0.01.
*This variable was constructed by aggregating classical and social BAC.
** See Appendix A for explanation of the construction of this variable
- 67 -

---

including medical school among their choices.
(They do not usually take
the social
science BAC).
For Law School
students on the contrary, the
choice of their school may have led to the refusal of first choice
(e ~ - .15).
Law school
has traditionally been the outlet of students
who do not display academic achievement in the subject areas taught in
secondary school.
Law is
not taught
in
secondary school
and students
think they may have a hetter chance of success HI it as a new discipline
at the university.
However, since the number of students in first year
of Law has increased disproportionally in comparison with enrollment in
other schools,
decision makers
have tried to restrict entrance to the
school. Becauze the economic advancement of the'country has opened
better paying jobs for law graduates, competition to entSr the
School has increased. This explains the risk of not obtaining the
fir~t choice displayded by the beta factor coefficient.
The
distinction
obtained
for
the
SAC,
though
lower
in
beta
coefficient than we expected
(e ~ 0.09),
is actually the single most
important
variable that concerns
all
students.
It is also one of the
two variables related to secondary school education.
The other variable
is
type
of
secondary
school
(private
or
publ ic)
aggregate
in
one
variable
(e 0 0.04).
The
other
variables
apply
only
to
students
enrolled in other schools.
The explanatory power of our model
was
low (R 2 ~ 0.09).
The only
SES variable which '-ias sicjni ficant,
but negligible in the model, is the
SES
of
the
students
measured
by
household
items
available
in
their
home.
'le
1ater
expand
on
the
9roupi ng
of
the
students
by
SES
1 n
Appendix 8.
We should not conclude that SES plays no significant role
- 63 -

---

in the assignment of schools before considering another type of analysis
on the issue.
We propose a discriminant analysis of factors which may explain the
university admission policy.
We dichotomize the dependant variable into
o and 1:
zero
for
those who did not obtain their first choice and one
for
those
who
did.
The
list
of
independant
variables
used
in
the
analysis
is
'liven
in Table 4-3.
Tile discriminant analysis W2S
done on
all
students
according
to
their
social
class
which
had
been
assessed
according
to
household
items.
The
advantage
of
the
discriminant
analysis over the
regression analysis
is
that if the dependent
variable
is
dichotomized,
we
can
introduce
a much
larger
number
of
independent
variables
which
cOllld
explain
the
P011CY
In question.
Another
reason
for
the
use
of
the
discriminant
analysis
IS
that
it allows
us
to make
use of the fact that approximately 5U percent of the cases belong to one
category of the dependant va ri ab 1e and the other 50 percent of the cases
share
the
four
remaini"'l
categories
in
the
dependent
variJhle.
The
analysis
allows
us
to
distin'luish
between
those
who
have
their
first
choice and those who do not.
Consistent
with
past
results,
Table
4-3
of
the
discriClinant
analysis
indicates
that
the
social
science
BAC
is
also
the
most
important
factor,
both
in
terms
of
discriClinant
coefficient
(1.06
is
interpretated like the beta coefficient in a 1ll1l1tivariate analysis) and
also
in
terms
of the
group mean
(.62).
I·ihen stueJents are separated by
socio-economic class, the social
science BAC becomes Illore
illlpol'tant for
hi'lh
class
(0.81)
and
lower
class
(O.ll)
students,
but
hinders
the
middle class
(-0.08).
For the middle class stlldents,
having
I isted the
School
of
Sci ence,
(where
they
may
study
pilarlllacy or enter erH)i neeri ng
- 69 -

---

TABLE 4-3
Discriminant analysis of students who obtained their first
choice of university school, and those who did not, by household items grouping
Group t~eans
Discrilllinant Coefficients
First Choice Assigned
First ChOlce Not Asslgned
Variabl es(l)
----mT
Low
Middle
High
All
Low
Middle
High
All
Low
Middle
High
Students LeveL Le~el___ J~~~ ___ .Students
Level
Level
Lev.e 1
,
-
S. tuden ts
._-.
.. Level
Leve I ... LeveL
.
'
Baclet
1. 06
.71
.08
.81
.62
.61
.65
.58
.46
.48
.38
.38
Baceco
0.21
-.05
*
-.22
.06
.04
*
.08
. 11
.09
*
.16
Ba Ma th
0.07
-.05
*
*
.03
.02
*
*
.06
.06
*
*
Economic
-0.08
- .03
.41
-.17
.07
.16
.12
.09
.19
.16
.28
.18
Science
0.26
.34
.43
*
.12
.14
.02
*
.17
.18
.14
*
Medecine
0.83
.90
*
*
.11
.11
*
*
.04
.03
*
*
Letters
0.27
.22
-.39
*
.39
.39
.46
*
.28
.31
.19
*
Mention
0.28
.23
*
*
.23
.21
*
*
.16
.15
*
*
Notwork
0.00
-.00
-.24
*
.50
.59
.32
*
.45
.53
.23
*
BACSex
0.28
*(2)
.34
*
.28
*
.16
*
.34
*
.38
*
Number 0 f
cases
837
636
140
lOO
(3 )
,J
61.51
60.1
62.28
60.07
Notes: (1)
The nleaning of the variables is given in Appendixcby alphabetic order
/
( 2)
* indicates values which were not statistically significant at least at 0.01
(3)
[J:
denotes the percentage of "grouped" cases which was correctly classified.
It lIIay be inte,'p,-eted
like the R2 in a regression analysis.

---

schools)
best
explains
why
they
were
admitted
to
that
school.
The
Economics department
is their second best
predictor
(0.41).
Having a
social
science SAC is a definite obstacle for students of these social
classes who
aspire
to
be
pharmacists
or
businessmen.
The
second
best
predictor
of
school
for
all
students
lS
the
ex-post
information
that
they have been assigned to medical
school
(0.83).
An analysis by social
origin
indicates that this
factor
is determinent only
for
lower social
class
status
students.
lt is statistically insignificant
for
the
two
other classes.
The distinction
obtained for the SAC is the third most
significant
variable
(0.28)
in
explaining
school
assignment
for
all
students.
The regression analysis contains
similar
results.
However,
this
variable is only significant for
lower social
class students.
For
this class the variable which explains best the admittance to the first
,choice of school
is the
fact
that the fi rst choice was medical
school
(0.90).
If
lower
class
students
are
given
their
first
choice
in
medicine,
more
than
in
any
school,
this
suggest
that
this
class
of
students
follow
more
closely
the
requirements
of
the
commission.
r1edicine
is
the
favorite
choice
of
the
lower class,
while middle and
upper
class
students
prefer
science
and
economics.
This
dichotomy
exists
because
doctors
are
among
the
lowest
paid
graduates,
although
tiley
enjoy
high
social
prestige.
The
prestige
may
be
the
best
compensation to lower classes for the income differential that salaries
alone cannot close within a generation.
In
the
discriminant
analysis
Vie
primarily Vianted
to
iso'late
the
explanatory
power
of
social
class
variables
ln
the
assignment
of
schools.
For
that
purpose we
introduced
variables
pertaining
to
the
job, education, and income level of the student's parents.
The only SES
- 71 -

---

variable
which
was
statistically
signi ficant
in
the
analysis
was
the
"no-job"
category
in
the
parents'
occupation.
The
variable
had,
however,
zero explanatory
power when
students were not
differentiated.
It lost its statistical
significance for upper class SES students,
and
had a negative
sign
for middle
class
students'
admittance to a school.
in the "no-job" category we include the retirees and the unemployed.
In
the
four
models
of
explanation
of
school
allocation
in
Table
4.3,
more
than
60
percent
of
the
variance
was
explained
by
the
variables.
At
least
100
cases
were
,'sed
in
each
model.
The
discriminant
analysis
model
basically
supports
what
we
perceived
globally
with
the
regression
runs,
that:
(1)
when
students
choose
a
school
similar to their high school
specialization, they
generally
get
it.
(2)
Although
an
ahove
average
SAC
distinction
increases
the
likelihood of obtaining one's
choice
of shoal,
the
lack
of distinction
does
not
decrease
the
likelihood.
(3)
One
has
a
better
chance
of
obtaining one's choice of school,
if one earns a social
science BAC and
choose the
appropriate
school.
For middle
class
students,
however,
a
social science BAC is a handicap.
(4) Contrary to the popular belief in
the country,
the education,
political
affiliation,
and
income
of the
student's family do not inflllence the attribution of the student's first
choice.
One
reason 'for which
our
study
does
not
support
thi s popul ar
bel ief
is that
only
recently
have upper class SES students entered the
National
University,
instead of overseas
schools.
Our
sample does
not
include
those
who went
abroad
to
study
in
the
field
of
their
choice
because they were
refused adlnission
to the
same scbool
at the National
University.
A second
possible
reason
OUI'
data
does
not
support
this
popular belief is that
the young bour'leoisie bave
visible influence 1n
- 72-

---

securing
public
secondary
schools
when
their
children
have
failed
on
national
exams.
These
children
have
not
yet
reached
the
university.
Therefore, a test of this popular belief, if it can now be supported at
the
secondary
school
level,
will
not
be
verifiable
at
the
university
1eve 1 for several yea rs.
B.
Equality in Academic Achievement
The high probability of repetition in the education system renders
a mere equality
in access to schools
of the university an insufficient
step
if
one
is
interested
in
a
meaningful
reduction
in
iniquity
in
education.
In many countries the ability to survive in a school system
is
often
related
to
economic
background
of
the
student
(World
Bank,
1979,
1980,
Simmons,
1980).
The
pervasive
view
in
the
Ivory
Coast,
however, is that academic success rate has no relationship to children's
economic status.
This assertion
has
been empirically verified in many
underdeveloped countries,
but
not
in the
Ivory Coast.
In this section
we seek to assess the relation between academic achievement and economic
background
of
the
student's
parents.
First
we analyze
the
policy
of
repetition in and expulsion from the university.
1.
The University Policy of Repetition and Expulsion
The
financial
burden
created
by
the
number
of
students
ln
schools
has
forced
university
policy makers to deal
with
the high rate
of
repetition
in
the
system.
It
should
be
mentioned
that
in
many
schools
students
take a
comprehensive
exam at
the
end of the academic
year (June).1
Only those who rass the exam are allowed to enroll
in the
following year of the school
cycle.
Let us call
the year of the cycle
- 73 -

---

by
the
British
term
"Form"
to
differentiate
it
from
the
actual
year
(time period) spent in a school.
For instance, a student may take three
calendar
years
to
be
enrolled
in
"Form
I!."
Classes
are
organized
exclusively
by Form.
Form
IV
is
the graduation year for many schools,
except
in
Pharmacy
and
Medicine.
Students
are
required
to
reach
at
least "Form 11" by the end of 3 years spent in a department.
Failure to
do so leads to expulsion from that particular department.
Theoretically
a student may
re-en roll
once again in another department
but will
lose
the
government
scholarship,
and
access
to
the
highly
subsidized
university
housing,
restaurant
and
other
school
facilities.
Tuition
remains
free
however.
In
practice
the
loss
of
the
government
scholarship
constitutes
expulsion
from
the
university,
for
very
few
students can afford the high cost of living in Abidjan without working.
Holding a job prevents attendance of classes and almost assures failing
exams since courses are held during working hours.
Another
factor which
leads
to
the expulsion
of
students who fail
Form
is
that
their
acceptance
in
another
department
theoretically
requi res
the
approval
of
the
NCOS.
Students
entering
the
university
from high school
must be assigned a school
before
repeating
university
students are considered.
We saw
in the
previous section how difficult
it
is to obtain
the school
of
one's choice.
Expelled students
rarely
obtain the school
of their choice and are not guaranteed to succeed in
the school attributed by the NCOS.
The policy
of repetition and expulsion we outlined above concerns
students
of
Form
I.
After
Form
I,
students
are
required
to
complete
Form 11 and Form III vlithin four academic years.
Failure to do so leads
to
a
loss
of
scholarship
but
the
student
may
still
pursue
his/her
- 74 -

---

education
in the
school.
Students
in this
situation tend to continue
their
education
even
when
they
lose
government
assistance.
The
repetition
rate of the students
tends
to increase in relation to their
ability to support themselves.
This
complex
policy
has
a
tremendous
effect
on
the
number
of
graduates the system can produce and the amount of resources required to
operate
the
schools.
In
Table
4-4
we
more
formally
outline
the
repetition
policy
and we
compute a probability
formula
related to the
number of students the system can
graduate each year.
The exponential
rate at which grows the repetition
rate indicates that students have a
slim chance of getting into the next form.
As
an
illustration,
we
take
the
actual
average
probability
to
graduate
for
the
law
school
in
1980-81.
We
obtain
the
following
results.
Let
us
ca 11
n
the
probability
of
passing
and
p
the
probability of repeating a form.
n
0.39
p
0.60
Assuming a negligible
rate
of drop-out
and
1007
students
in the first
year, we compute the number of graduates within four years as follows
1007 x (0.39)4
23 graduates
In year T
5, G, the number of graduates is
4
G
N x 4 n p
1007 x 4(0.023)0.60
56 Graduates
- 75 -
.~ ; ,

---

TABLE 4-4
PrObabl1ity table for graduating N numbers of students at year T
Form
! !
!! I
IV
Graduate
..
----l-----~~r~.~~.~~. ~~~~.-~.~-.-"T" ~~~~~ .
•J
I
.------i------+---------:-------+-------I------j
i
~:;o i ;:~
I
o :: ;;()
P
-;Xi"i
,'le t
R ~ ,c"
R ~ 0
2
[j \\ Jawed
[
~ 2,ln
[
~ cl
p ~ 0
p ="X~X;l
P
2,-;" x ."
R ~ 0
[
2" 2
2
.,
;1
E ~
3
I
R
!legl iglble
P
2;;./ \\..
P :: ];;i:, x "iT
S =-;;3 x ;;-
--II_:__:_::_'I_:_9_;b_l_e-+-_:_~_:_n~_.)__2_'__t-_:_:_:_:.,3_~?:_'__t-__~_n_43"-__
_ ·
II
1
I
I '" 0
p ~ In'} x')
G ~ 4IT "
n
X
4
.'_-----+,1------;--1
+--I_:_~_:_:_~'_-3_'_·_+_-:-:-:-:~,-:oIX-', I__
l
~_F~'~O~--I
~
~ ~ 3 1
:
P
Cl
'
1n
3 x
G
9n 0
x ,
R~I"I.,3X;1
R~9n<I,<o ['
=9n3}
1
j
[~114
E"14 33
,
I
I
2
G
i4"J
I
D=5n
<1 XTi
I'
o J XiT
I
3 J
I
" 14"4,3
R~14'3"'x
1
I
I
E ~ 19n '.
1
!
I
I
R " 19,,\\' , , '
i G = 19T;J,,')4
I
4 4
I
"
:: 19n 0
,I
19no I
i
I
I
I
R = negl1C]lo1e
I
j:ote,,;
T·
ihe yei'll- tlme Derlod
The orobablllty of oromation
T~e 0rolJability for repetition
o
Pall~()tion from prevl01ls rorrn
.~
Rendition In UHo same Form
E
Tot<'ll
entrance Hlto the next Form
G
Probability for graduating
? t
R
- 76 -

---

In year T = 8
G =
N x 19rr 4p 4
1007 x 19 x 0.023 x 0.1296
57 Graduates
From
the
probabilities
one
may
also
compute
the
number
of
students
enrolled in every Form of the school
system if we introduce the actual
probability for repeating each Form.
The example above indicates how the high rate of repetition leads
to a reduced number of graduates for the 1abor market and an increased
cost of education.
2.
Promotion Rates at the University
Figure
4-3
accurately
illustrates
the
different
rates
of
promotion in the schools over the past 5 years.
Though promotion rates
has been increasing for Medical School and the School of Economics, they
have been decreasing for Letters, Science and Law.
The decrease is even
more
drastic
for
the
School
of
Letters
where
an
overall
rate
of
promotion of 56.79 percent registered in 1975-76, and dropped to 43.87
percent in 1980-81.
In Law School
the peak of promotion rates (57.95)
reaChed in 1977-78 has not been repeated in recent years.
After 1977-78
the rates begi n to decrease agai n with a low rate of 41.56 percent re-
gistered in 1979-80,
just above the lowest record registered
for the last five years
(39.64%)
in 1975-76.
In the
School
of
Economics
the
rates
have
been
increasing
since
1977-78 when they dropped to the lowest point of the 5 year time-period
(51.74%).
The
best
performance
registered
for
the
school
was
made
during 1978-79 with a promotion
rate of 77 .50 percent.
The School
of
- 77 -

---

.-
EV0LUTI0N AVERAGE PR0M0TI0N RA TE BY SCH00L
'--'--'-1 I
80
~~
[ : ; /
1~~\\
~
70
~
L~
r;:~-~~--
r--i
W
~,
f-
<
I
0:::
co
e-
Z
60
I
o
'Si
r--i
f-
l
C'J
~
"-
;;-
C:,,)
0:::
~,~/='~~
. 50
n
4-
><-~~
\\
~
2~
~_
~~
--'2
j
40 t
L
l
~
I
I
1/,
!
I
!
!
I
!
I
!
!
!
~
1
74
76
78
80
\\I.
l=LA\\-J 2=LETTERS 3=EC0N L1 =SC1ElKE: 5=l1F:.OECINE
Figure 4.3
<'

---

Medicine has continued to improve its rates since 1975-76, with a low of
68.76
percent.
This
rate
is
even
better than the highest
rate for the
Schools
of
Law,
Letters
and
Science.
Medicine
now
has
the
best
promotion
rate of all
the schools with a record rate in 1979-8 of 82.30
percent which it almost duplicated in 1980-81, with 81.13 percent.
Except
in the Schools of Medicine and Economics,
the
rates are in
general
below
50
percent
at
the
National
University.
In
other words
half
of
the
student
population
in
these
schools do not enter
the next
Form in the following academic year.
Another picture in promotion rates
or
(assuming a
low
rate
of drop-out)
the
rate of
repetition,
is
given
when
we
observe
these
rates
according
to
Form.
Table
4-5
gives
an
evolution
of
the
promotion
rates
over 5 years
for
the 4 Forms in each
school.
A general
feature
of the
table
is that the
promotion
rate of
Form I students is, on the average,
loV/er than the other Forms.
The promotion rate for the graduation year
(Form IV) is the highest
rate for all
schools except in the School
of Letters.
This last school
has a dramatically low rate of success for senior students.
The average
rate over 5 years for Form [V students in Letters is 12.46 percent.
The
lowest performance for
the
last
Form in the
school
was made
in 1977-78
with
8.00
percent
and
the
highest
in
1975-76 with
17.80 percent.
The
low rate of success in the School
of Letters has drawn the attention of
university
authorities.
Professors
argue
that
students decrease thei r
effort
once
they
reach
the
final
year.
Students
blame the evaluation
system which
is
based
on
one
comprehensive
exam.
Students also argue
that
foreign
professors,
who
constitute
approximately
half
of
the
teaching staff (44.94% in 1980-81), intentionally fail
students for fear
of
being
replaced
by
graduating
students
who
often
take
teaching
- 79 -

---

TABLE 4-5
Evolution of promotion rates over 5 years by form, for each school
Promotion
Promotion
Promotion
Promotion
Average
rate
rate
rate
rate
Promotion
Law
FOnll I
FOnll I I
Form III
FOnll IV
rate
75-76
28.00
37.86
75.00
85.00
39.64
77-78
50.00
31. 95
80.00
54.00
57.95
78-79
36.23
46.00
71.37
69.83
47.14
79-80
36.52
31. 95
68.34
57.56
41. 56
80-81
46.62
37.86
78.10
58.37
49.10
Letters
75-76
59.00
67.50
52.70
17.80
56.79
77-78
60.00
54.00
43.00
08.00
48.49
78-79
53.08
56.77
43.10
08.04
45.04
79-80
45.02
52.00
37.12
14.15
43.43
80-81
50.84
63.43
36.82
14.33
43.87
Economics
75-76
62.00'
48.00
85.00
97.00
65.65
77-78
33.00
55.00
83.00
98.00
51. 74
78-79
65.31
91. 07
82.08
97.12
77.50
79-80
45.11
60.38
83.47
97.56
68.03
80-81
68.85
70.82
81.91
98.95
75.87
Science
75-76
60.80
32.80
47.40
55.50
50.52
77 -78
52.00
53.00
60.00
47.00
52.16
78-79
42.03
50.26
48.90
59.96
53.60
79-80
47.44
53.18
54.00
45.21
51.40
80-81
47.75
37.96
47.07
41. 59
47.36
Medicine
75-76
76.12
87.50
75.00
91.10
81.13
77 -78
72.25
98.00
88.00
82.00
82.30
78-79
63.73
80.22
89.80
96.77
78.39
79-80
72.25
88.37
84.15
91. 40
82.30
80-81
76.12
85.82
79.53
88.31
81.13
Source:
Rapport (Op cit:
75-76,76-78,78-79,79-80,80-81).
Note
Promotion rate is computed by dividing the number of students who
pass the exam by number of students who take it.
- 80 -

---

positions which are
the
highest
paid
jobs
for
their degree.
Whatever
its
object i ve
causes
the
1C/o'I
rate of success
is a seri ous handi cap to
the policy of self-sufficiency in high-level manpower trainees.
A high
proportion
of
science
students
also fail
in Form
IV.
The
average
rate of
promotion
over 5 years
for the school
in that Form is
49.85
percent,
compared
to 97.72
percent
for
the School
of Economics,
which has the highest average performance of all schools.
The
students
in
our survey
(Table 4-6)
display
approximately the
same
propensity toward
success
as
the
total
number
of students at the
National University.
On the average, 50.8 percent of them indicate that
they have not repeated a Form during their academic years, as opposed to
57.98
percent
for
the
5
year
average
computed
from
uni versity
statistics.
Part of the discrepancy between the two rates may be due to
the
different
time
period
that
these
two
statistics
cover.
Our data
covers
a longer time
period
than
the
university
statistics.
Like the
university
statistics
our
statistics
show
that
our
sample
students
repeat
more
in
the
fi rst year
(31.8%)
and
less
in
the
thi rd year 0.7
percent.
What
factors
account
for
the
di fferent
success
rates
for
school s
and for individuals were not provided in the above discussion.
We shall
attempt to do so in the
rest of th is· section.
3.
The Determinants of Academic Achievements
~Iore
than
any
other
problem,
the
issue
of
educational
achievement as it relates to social status has received attention in the
Economics
of
Education.
Under
the
label
of
"Educational
production
functions",
many
researchers
have
tried
to
relate
the
educational
- 81 -

---

TABLE 4-6
Percentage of students who have reoeated a form in the sample population
Repeated Once
Not Repeated
Form I
31.8
64.8
Form II
11. 9
85.7
Form III
3.7
94.7
Form IV
0.7
99.1
At any Form
of the
49.2
50.8
University
- 32 -

---

output, be it the score of a test, or the result of an exam, to a series
of inputs that they believe affect that particular output.
The lack of
agreement
in the number and type of inputs to be introduced
in these
production functions illustrates one major problem: no one knows how the
educational process takes place, and with what inputs.
In general, the
input related to characteristics of teachers and students are thought to
affect the educational output in the following non explicit manner:
o
Q(T ,K,S)
where 0 is the educational output,
T, a vector of teachers characteristics,
K, a vector of school characteristics,
S a vector of student's characteristics.
Q is
the
function
which
translates
the
inputs
to
outputs.
The
particular functional
form used by
researchers
varies,
but the linear
additive functional form is usually
adopted.
The
literature
in
educational
production
functions
takes
two
separate di rect ions dependi ng on the 1eve 1 of development of the count ry
where
it
is
appl ied.
In
developed
countries
(Coleman:
1966;
Jencks:
1972; Bowles,
1974) it indicates that inequalities in education output
are also associated with inequal ity in
socio-economic
background.
In
underdeveloped
countries,
however,
(Heyneman:
1976,1980;
Schiefelbein
and
Farrell,
1973;
Carnoy:
1975)
schools'
inputs
are
more
strongly
related to achievements, than
socio-economic background inputs.
No study in the 1vory Coast
has, to our knowledge, addressed
~tself to the issue of educational achievement as it relates
to socio-economic
83 -

---

factors.
In
Table
4-7 we
regress
the
average
promotion
rate
in each
school
for 5 years over 4 independant variables.
The first independant
variable,
the
Ivorianization
rate of the teaching
staff,
accounts
for
the
idea
that
students
may
relate
better
to
I vori an teachers;
but
it
also deals with the conspiracy theory mentioned before: foreign teachers
intentionally fail
students to obtain a longer contract
in the country
since a trained Ivorian corresponds to a dismissed foreign teacher.
The
second
variable,
the
university
recurrent
expenditure
in
each
school,
deals wi~h the issue of educational resourcesalloted by the
university, not the total expenditure. The third variable,
the
teacher - student - ratio,
is a proxy for classroom size.Final-
ly, we introduce variable "expenditure per student"
to account
for the difference in resources allocated to schools by the uni-
versity, once the number of students is controlled for.
The beta coefficients in Table 4-7 suggest that the expenditure per
student
is
the
most
influential
factor
(~
1.27)
0
in
the
average
promotion rate for a given school.
'This V"
3ble is followed
(8 = -0.88)
by
a
second
variable
relaLcu
to
school
resources,
the
recurrent
expenditure
in
the
schoo1.
However,
this
last
variable
is
negatively related to promotion rates,
indicating that schools which are
al10cated
recurrent
expenditure
found
by
the
university
do
not
necessarily
improve
the
promotion
rate
of
the
school
with
their
expenditure.
The third variable in influence is the Ivorianization rate
of
teachers.
Contrary to our expectation,
the
Ivorianization
rate
is
negatively
related
to
success
(D = -0.32).
This
suggests
that
the
more
Ivorian
teaching
staff
is
hired,
the
less
student
performed
academically.
When we drew the attention of some students and teaching
- 34 -

---

TABLE 4-7
Regres s i on of average promot ion ra te over four independent var iables
Standardi zed
Coefficient
Variables
(Beta)
Ivorianization rate of teachers
-0.32
University expenditures
-0.88
*
Teacher-student ratio
0.24
Expenditure per student
1. 27
N = 25
2
R =0.62
* = variables significant at less than 0.01
- 85 -

---

staff to these results, they suggest an alternative explanation: schools
with high
Ivorianization
rate (Letters, Science) also have the lowest
promotion rates.
There is a tacit competition between expatriates and
local
teachers which may have some effect on the grading of students'
papers.
A good student
for one
group
of
pr'ofessors may
be
injustly
considered
bad
by
another
group.
Our
data
did
not
allow
us
to
investigate this issue further.
If it appeared to have some bearing on
reality, the lvorianization process in the schools should be re-examined
in
an
entirely
new
light.
Finally,
the
class-room
Slze
variable
measured by teacher student ratio which
is often cited by teachers as
the
cause
of
students'
poor
performance
ha::; the least explana-
tor,! power
(~= 0 . 24) .
After examining the issue of promotion rate within the schools we
proceed by analyzing the same phenomenon from the students' angle.
In
order to do ·this, we ran the regre'ssion analysis rep'orted in
Table 4-8.
For lack of an alternative measure of achievement
(grades
obtained at the same exam, or test scores), we constructed the following
dependant variable based on the number of years spent to reach a given
"Form."
If a student had used the required amount of academic years to
reach the corresponding "Form," he/she was given a maximum score.
This
score was reduced proportionally by the extra number of years used to
reach his present "Form."
The most
important
factor contri but i ng to explai.ni.ng our measure of
scholastic achievement was the total number of students in the school
(6 = 0.43).
flell
below that
factor but second in importance was the
school attended:
for students in Economics the standardized coefficient
beta was equal to 0.12, and
6= -0.09
for science students.
The factor
- 86 -

---

TABLE
4-3
A regression analysis of a measure of scholastics achievement(l)
on nine inde.pendeFlt variables
Regression 1
Regression 11(4)
Variables
Beta **
Beta **
Total number of students in the schools
0.48
0.48
Distinction obtained for the BAC
0.09
0.09
Student
is enrolled in Law
-0.06
*
Student is enrolled in Economics
0.12
*
Student is enrolled in Science(2)
-0.09
*
Father's education level
0.06
0.06
BAC for Economics and Business
* (3)
0.08
BAC for Science
*
0.05
Parent helps in studies
0.10
*
2
RI = 0.27
Rl = 0.25
N = 566
N = 566
All coefficients were significant at 0.01
Notes: (1)
The dependant variable was obtained as follows:
If a student had spent the required amount of ye~rs to reach the
corresponding "Form", he was given the maximum score.
That score
was proportionally reduced by the extra number of years spent to
attain the present Form he attends.
(2)
The school of Letters and Medicine did not appear significant and
was dropped.
(3)
* VarialJl c not used in that regression run.
** Standardized beta coefficients
(~)
This second regression run drops variables which were
not
significant in the first run.
- 87 -

---

which
followed
in
explanatory
power was
whether
or
not
the
students
received financial
help from their parents, a measure of socio-economic
status
(~= 0.10)
Finally, of all
BACs introduced in the analysis,
the most influential
one was the Economic BAC (0 = 0.08). The father's
education follows with ~ = 0.06.
A second regression was run after
we dropped from the analysis factors which were not significant in the
first
regression.
The explanatory
power of the two
regressions were
2
2
relatively high
(R
=
0.27 and R = 0.25).
1
2
The only significant variables related to socio-economic status in
the regression were the
"financial
aid received from parents" and the
father's education.
We suspect, however, that the academic achievement
may· vary with socio-economic class.
We set to test this hypothesis by
using a discriminant analysis.
The results of the analysis are reported
in Table 4-9.
The discriminant variable is whether or not the student
has
repeated
a Form duri ng an
academi c yea r.
Only
students who had
spent
at
least
one
year
at
the
university
were
incluued
in
the
analysis.
One should remember that a positive answer to the question
posed by the discriminant
variable means that the student
has
indeed
repeated
a class.
Table
4-9
indicates
that
the
most
discriminating
variable (discriminant coefficient is equal to 0.86) for all students is
whether
or
not the student was
enrolled
in the School
of Letters,
a
result consistent with the previous analysis.
For low level students,
the
same
variable
plays
the
most
important
discriminating
role.
However,
the fact that students are enrolled in Economics is the most
significant
variable
for
middle
income
famil ies
(coefficient
.51) ,
when
8AC
for
math
and
science
plays
the
major
role
for
upper
class
students (coefficient = 0.69).
- 88 -

---

TABLE 4-9
A discriminant analysi_s ofhaving repeated or not repeated
a "Fonn" at the university by income level-of"-parents
~-
Discriminant
Group Means
Coefficients
Has Re pea ted
Not Repea ted
Variables
All
1
2
3 (4)
All
1
2
3
All
1
2
3
*(2)
BACLET
-0.17 -0.6
*
.55
.56
*
*
.61
.62
*
*
BASCCEX
-0.13
*
*
-0.6
.29
*
*
.43
.24
*
*
.21
BACHMATH
0.25
*
*
.69
.03
*
*
.01
.05·
*
*
.15
ECONOMIC
-0.26 -0.21 -0.51 -.21
.15
.14
.36 .06
-.06
.05
.11
.03
MEDICINE
0.49
.64
*
*
.04
.04
*
*
.08
.11
*
*
LETTERS
0.86
.87
.32
.67
.27
.33
.17 .17
.49
.52
.35
.45
MENTION
0.21
.28
*
*
.22
.23
*
*
.23
.30
*
*
NOTWORK
-0.09 -.19
*
*
.46
.55
*
*
.54
.61
*
*
FAEDUC
*
*
.02
*
*
*
1.19
*
*
*
1.83
*
HHGRUP
*
*
.44
*
*
*
1. 37
*
*
*
1. 73
*
AGRI
*
*
- .45
*
*
*
.28
*
*
*
.08
*
WHICOL
*
*
.28
*
*
*
.10
*
*
*
.27
*
Number of
cases
587
423
99
89
(3 )
p
64.17 62.20 67.9 74.51
Notes:
(I)
Meaning of variables are given in Appendix
(2 )
* the value of the variable was not significant at 0.10
(3 )
p: denotes the percentage of "grouped" case2 which was correctly
classified.
p is often interpreted as R
in a regression
analysis.
(4 )
All me~ns all students, 1 ~ low 1evel ; 2 ~ middle level;
3 ~ high level.
- 89 -

---

Enrollment
in
the
School
of Medicine
is
the
second
factor
which
helps to explain repetition in the schools for all students (coefficient
" 0.• 49).
In
this.
social
ra.nking
we
find
that
the
same
variable
(coefficient" 0.64) is important for lower class students,
but appears
not to be significant for middle and upper class students.
This result
is
similar
to
the
allocation
of
student's
choice
of
schools
analyzed
earlier, where the School of Medlcine played an essential
role for lower
class
students
but
an
insignificant
one
for
the
middle
and
upper
class.
The second most powerful
discriminating variable for the middle
class
is
related to whether or not the students parents are working in
the agriculture sector.
In other words,
rural
area
students belonging
to the middle class tend to succeed more (coefflcient
-0.45).
For the
high
class,
enrollment
in
letters
often
leads
to
more
repetition
(coefficient
0.67)
The next
powerful
discriminating variable for all
students
is the
SAC
specialization.
A social
science
SAC
best
helps
to
discriminate
between
students
who
repeated
a
form
and
students
who
did
not
(coefficient" -0.17).
The negative coefficient suggests that this type
of
SAC
contributes
to
non-repetition
for
all
students.
The
third
ranking
of
coefficients
includes
the
SAC
for
lower
class
students
(coefficients
~ 0.28) and enrollment in the Economics department for
upper class students (coefficient" -0.21).
Can we draw any conclusion from the analyses made above concerning
the contribution of socio-economic factors to academic achievement?
For
all
students,
socio economic
factors
are insignificant with
regards
to
repetition.
More important are the schools
in which they are enrolled
and variables
related to high school
academic
performance.
For middle
- gO -

---

level income students, the socio-profession of the student's parents
as
well as the father's education are important, a finding consistent with
empirical ()bservation in the country...._~_.
C.
The Socio-Economic Background of the University Students
1.
Met hodo 1ogy
A major problem any researcher faces when analyzing the social
background
of a population
is
the
choice
of traits which distinguish
individuals within that population.
Although theoretically there is no
upper limit as to the number of criteria one may use in differentiating
the members of a group, in practice, standard demographic measures are
often used.
The most common ones are fami ly economic background, place
of birth,
the
race,
the father's education,
the father's
occupational
status, etc .•.
In the USA sociologists (Duncan, 1966; fi.lltherman, Duncan
and Further and others) have developed a relatively accurate scale for
grouping
individuals
by
occupational
status,
levels
of
income
or
earning, and region of residence.
However, in a country
like the Ivory
Coast this sociological work has to be done by the researcher himself.
Even in countries where accurate measures have been developed, they may
only
be proxies
for
other
real ities which
cannot
be easi ly
captured.
Hence
if we find that students
from a particular ethnic group in the
Ivory Coast are over-represented at the University
level, what we are
measuring actually may not be the ethnic group per se, but may be the
availability of schools in the region, the relative welfare of the area,
the
early
opening
of
the
region
to
colonization
and
therefore
to
schooling, etc.
We
have
developed
in
Appendix
B a method
for
classification
of
- 91 -

---

university
students
by
socio-economic
background
based
first,
on
some
common
household
items,
second
on
the
parents'
income
and
finally,
on
the
occupational
studies of
the
father.
Jt
should
be
noted
that
the
information on these items was provided by the students and not by thei r
parents.
,le were therefore very cautious as to the reliability of their
answers.
As
indicated
in
an
earlier
chapter,
we
were
pleasantly
surprised
to
find
a
relatively
high
(0.91%)
Guttman
coefficient
of
reproducibility - a measure of the extent to which a respondent's scale
score
is
a
predictor
of
one's
response
pattern
on
the
household
items.
These
items
also
appeared
to
be
very
scalable
(0.58)
-
a
coefficient of scalability over 0.60% indicates that the scaling of the
items
is
truly
cumulative
and
unidimensional.
Encouraged
by
these
results,
we
grouped
students
according
to
the
availability
of
the
household
items,
after
they
had
been
appropriately
weighted
(see
Appendix B). vie chose to divide them into group of three.The upper
group
possessed
the
top
ten
percent
of
household
scores,
the
middle
class,
the next
20 percent
and the
lower
class,
the bottom 70 percent.
The results appear in Table B-2.
Another
more traditional
approach
to grouping student
is
by
level of
parents'
income.
In Appendix B we explained how the income for various
socio-profession
without
reported
annual
income
was
computed.
We
adopted
the
same
percentage
division
point
for
grouping
by
level
of
income accordi ng to househol d items:
top 10 percent
, mi ddl e 20 percent
and
low 70
percent.
These
percentage
division
points were adopted
in
vieVl of the distribution of the data and because Vie are interested in a
broad analysis given the qual ity of the data used.
In order to account
for
the
strong
influence
of
individuals
outside
the
family
group
in
- 92 -

---

raising and providing education,
for a student who may originally come
from a lCM level income, we included in our survey, questions related to
thi s phenomenon.
We were able to i nt roduc~ a _thi rd__ grouping_b3!Sed on
this informtion.
The details in our approach are given in Appendix B.
Finally,
we
regrouped
students
according
to
the
socio-profession
of
their father.
2.
The Results
Up
to
this
point
we
have
analyzed
the
enrollment
at
the
National
University
first
according
to
input
variables
that
were
endogenous
to
the
university
systelll.
We
are
now
going
to
consider
variables that are exogenous to the system.
This dual division is often
an artificial one, because variables that affect student enrollments in
a particular school are inter-related as we show in Fig. 3-2.
We shall,
however,
follow
the
division
between
endogenous
and
exogenous
variables
to the
university
for
analytical
reasons,
and
in
order to
pinpoint
in
our
last
chapter
factors
that
can
be
acted
upon
by
the
university
and
education
authorities,
and
those
which
escape
their
control.
The variables exogenous to the education system we analyze here are
essentially
socio-econolllic
background
variables
such
as
region,
education and socio profession of the student's parents.
2.1 Distribution of Students by Region
Although education and the rapid economic growth of the Ivory Coast
have
moved
Ivorians
from
poorer areas
(essentially North and Center)
toward richer ones (south). it is useful to recognize the initial origin
- 93 -

---

of the students.
This recognition is important, due to recent changes
in the political system.
Because members of parliament are now elected
by .. geographical
district rather
than
on
a national
basjs,
economic
programs
will
be
more
and
more
regionally
based.
Inequities
may,
therefore, be accentuated in the future.
We assess the regional division of students through four variables
which
sometimes
measure
the
same
phenomenon:
ethnic
group,
residence
until
12, the student's primary school
city and the parents'
place of
residence.
For many students,
especially
those whose parents work
in
the
public sector or are
seasonal
agricultural
workers,
the
place
of
birth may not
be their area of origin.
Even if the parent's current
residence
is
not
the
same
as
their
origin,
knowing
their
current
location is preferable to having no information about their location.
The variables "place of residence until twelve years old" and "city
where primary school was attended" grasp better the social
variables of
the region that have influenced the student's primary schooling: school
availab1ilty,
the
people
of the region's propensity to attend school,
and regional nutritional and health defficiencies.
In previous studies on education in the
[vory Coast and in Africa
focus
has
been
on
the
issue
of composition
of
student
population
by
ethnic
group
(sometimes
wrongly
termed
tribe).
In
this
study we
acknowledge the phenomenon of ethnic group differentiation, but only in
so
far
as
it
reflects
the
original
geographical
provenance
of
the
student
which
can
no
longer
be
ascertained
through
easier
types
of
investigation.
In our thinking the ethnic issues as much as they relate
to economic
inequity,
have
less
potential
for
social
upheaval
in
the
Ivory Coast
than
other
social
factors we will
examine,
and
therefore
-94 -

---

need
not
be
overemphasized
in
studies
on
equity.
Inter-marriages
between ethnic groups, movements from one area of the country to another
for
new
opportunities,
"rapprochement"
of
traditionally
rival
groups
made
possible
by
modern
means
of
communication,
have
shifted
inequity
issues
(or
are
likely
to
do
so)
from
the
level
of
ethnic
group
confrontations to that of socio-economic class struggle.
Students Ethnic Group Distribution
As
indicated earlier,
by using the variable
"ethnic group" we seek
to
measure
the
original
area
of
the
students'
provenance
before
migrations,
intermarriages,
and
other
social
changes
thei r
parents
experienced.
In
Table
4-10
we
indicated
the
ethnic
origin
of
the
father, mother, and relatives.
lis
expected,
the
ethnic group closest to the
capital
city and the
ocean
(lagoon
people)
where
colonization
(hence
schooling)
started,
makes up the largest share of university students, when we consider the
father's group (20.1%) or the mother's group (20.3%).
The lowest shares
are made up by
the Mande
(7.0% for the father,
and
7.4% by the mother)
and the
senoufo-voltaic
(8.5% and
8.5%),
both
farther
from
the
south.
Ethnic
groups
settled
in
areas
where
education
is
more
available
(central
south)
are
also
highly
represented
at
the
university:
Baoule
(25.7%), other Akan
(25.5%), and lagoon people
(17.8%).
This
is easily
understood because kinsmen played a fundamental
role in providing for or
assisting
in the
student's education,
and could
be found
only
in areas
where
schooling
has
developed.
It
may
also explain why
in Table 3.13
the ethnic
groups
a
long
distance
from the capital
city and the coast
contain the lowest percentage of students who have had a kinsman in that
- 95 -

---

TABLE 4-10
Distribution of Ivorian students at the National University
by the ethni c group of thei r fa ther, mother, kinsman
Fa ther
Mother
Kinsman
N
'/
N
'I
"
"
N
%
Ethnic Group
(1)
(2 )
(3 )
(4 )
(2l
L§.L
Baou le'
230
18.1
238
18.7
327
25.7
A l
gm
126
9.1
135
10.6
156
12.3
2
Other Akan
69
5.4
72
5.7
168
13.2
3
Lagoon people
256
20.1
259
20.3
227
17.8
4
Krou
246
19.1
241
18.9
163
12.8
5
Mande-South
89
7.0
94
7.4
112
8.8
Malinke~6
119
9.3
103
8.1
52
4.1
7
Senoufo-Voltaic
109
8.5
109
8.5
49
3.8
African and non-
African group
34
2.7
23
1.8
12
0.9
TOTAL
1,274
100
1,274
100
1,266
100
Notes: 1. Agni includes Samwi, 1ndenie
2. ~ther Akan: Abron, Appolo, Ando
3. Lagoon people: Abe. Abidji, Aboure'. Adioukrou.~hizi, Aladian .
.~ttle', Avikan
4. Krou: 8akoue , Bete , Dida, Godie, Guere • Kenya, Neyon,
Niamboua, Niea~boua, Ubi, Wara, Yocoboue
5. ~ande-south: Dan, Yacouba, Gouro, Guan, Toura, Yaour~, Wobe
6. f1al inke: Bambara, Foula, Koro, Koyara, ~1ahou, Malinke, Sia, Dioula
7. Senoufo-voltaic: Senoufo, Tagouana, Djamala, Djimini Koulango,
Lobi, Pakala, Sen, Gouvin, Karaboro, Tiefo
- 96 -

---

ethnic
group
(senoufo-voltaic:
3.8,
Malinke:
4.1),
although
they
represented
17 and
18 percent
respectively of the Ivorian
population.
In _fact, _when we compare
columns
3 and 6 in Tables 3-D, a stronger
tendency is revealed and may need further investigation:
ethnic groups
along di stance from the south
are
1ess often
re 1at i ves to students,
than they are fathers to students. Why that is
so,
stemmed from the
economic situation and distribution of schools in the area of living of
these
ethnic
groups.
If
the
above
hypothesis
is
substantiated
by
further studies, it may suggest that the informal social security system
(which consists of
"paying back" whoever assisted the students during
their period of education), wlll again benefit those same ethnic groups
from
the
south and
center who served
as
kinsmen
and who are al ready
better-off.
The
1975 census
avai lable
to the
general
publ ic
divides
ethnics
lnto
five
groups:
Akan,
~Iande-North,
Mande-South,
Krou
and
Voltaic.
This broad division is interesting for ethnol09ical
studies, but hides
the
regional
groupin9 of the ethnics that was of
interest to us.
We
therefore
had
to
rely
on
previous
population estimates
(Ministere du
Plan:
1965).
In
using
these
estimates
we
assume
a
unique
rate
of
population growth for all the ethnic groups in the lvory Coast.
We were
then able to compute three indices of selectivity of students for the
ethnic groups of thei r father, mother and kinsman as reported in Table
4-11.
The indices support the same phenomenon that we reported using
the
percentage
distribution,s:
the
cluser the
ethnic
group
is
to the
coast (or the capital city), the higher its index of selectivity of the
university students.
Hence, the indices of the Akan group (2.41,2.58,
4.04) and the lagoon people
(1.89,
1.91, 1.68) are the highest on the
- 97 -

---

TABLE 4-11
Indices of selectivity of university students by the ethnic
groups of their father, mother and kinsman
% in Ivory3
Fat her's
Mother's
K'
-,,----'--=-"---f
.
"
d
1 nsman
2
Coast
%
rnc!eX
/0
j n ex
%
Index
Ethnic Group
(1)
(Z) _,~_~1L~~. ~~ .. L4L~~~~ ~J5J_.~~~~~~..L2L=~~~iZL~,=-_~_
Baou 1e'
20,6
18. I
08]
18.7
0.90
25.7
1. 24
Other Aka n
6.3
14.5
2.41
16.3
2.58
25.5
4.04
Lagoon Peopl e
10.6
20.1
1.89
20.3
1. 91
17 8
1. 68
Krou
18.4
19.1
1. 03
18.9
1.02
12.8
0.69
Mande
7.3
7.0
0.95
7.4
1. 01
8.8
120
Ma 1 i nke
18.0
9.3
0.51
8.1
0.45
4. I
0.22
'"
co
Senoufo-voltaic
19.0
8.5
0.44
3.5
0.44
3.8
0.2
Notes:
I
The indices Ivere computed by dividing the percentage of father,
mother, or kinsman's ethnic
group of the students by the actual
percentage of those ethnic groups in the Ivorian population ..
2
We used the same ethnic group classification as in Table 4-10.
3
Data obtained from Charlick (1974).

---

respective
triple
account
of
father,
mother
and
kinsman.
The
lowest
indices
are
found
in
the
nothern
area
with
the
Senoufo-voltaic
group
,(0.44, 0.44, 0.20) and the Malinke (0.51, 0.45, 0.22).
If the unequal
ethnic group distribution of university students we
described
above
is
a
reflection
of
past
geographical
population
distribution,
to assess the present distribution of students we need to
consider
variables
that
better than ethnicity capture the current
regionaldistributior of ivorian
students. We shall consider
the following three variables: area of students'birth'area
~here student lived bntil ~2. and the cUrrent area of residence
of the student's family.
The Birth Place
Although our objective
is to study the distribution of students by
region, we isolated the two major cities Abidjan and
Bouake' from their
region
(south
and
center
respectively)
because
they
play
a
particular
role
in
the
regional
divisions
of
the
country.
As
tile
capital-city,
Abidjan
has received many educational
investments from both the central
government
and
from
the
local
city
government.
Bouake' has
played the
same administrative
role
in
the
central
region as AbidJan
before being
slowly
overtaken by
Yamoussokro,
the
new development
pole
of the area.
\\'Ie also isolated the prefectures,
for
they enjoy
similar
advantages
as
headquarters
of
regional
administrations.
For
instance,
villages were
required to build their own primary schools and teachers'
housing units
before
they
applied
for
a
permit
to
actually
open
public
primary
schools.
In
the
cities
these
school
are
built
by
lecal
municipalities from budgets allocated by the central
government, or they
- 99 -

---

are built by government Oo'Ined construction corporations.
A perusal
of Table
4-12
indicates
that
the
highest
proportion
of
students (19.6) are born in the south, a findin9 which was substantiated
by previous measures of regional division.
Abidjan alone delivered 11.6
percent
of
the
students,
while
the whole
western
region
saw only
7.8
percent
of
the
total
student
population
born.
Column
5 of the table
gives us a better picture of the distribution with respect to the total
Ivorian
population.
The
selectivity
indices
(meaning
the
extent
to
which a particular group holds a fair
representation at the university,
considering its actual
proportion in the Ivorian population) in column 5
indicates
two aspects of this distribution:
the distribution
by
region
per
se
and
the
distribution
between
large
cities
and
small
ones.
According to
regional
distribution
by
region which occupies us
in this
section, students from the North, West, and East are over represented by
their area
of
birth.
These areas are also the
least developed
ln the
country.
This
indicates that opportunities to enter university is
not
denied
to
students
because
of
the
area
of
birth.
However,
these
statistics
do
not
al100'l
us
to
conclude
that
students
from
the
North,
West and East have more opportunities to enter the university than their
counter parts in other regi ons of the country.
Preci sely because these
areas
are
poor,
the
population
tends
to
migrate
towards
areas
with
better
economic
opportunities.
Students
may
be
horn
in
these
poor
regions, but move to richer ones to attend school.
The isolation of
Bouake'
, the major city of the center, shoul d account for the low index
(0.46).
We can conclude that in general
students are not denied entrance to
the
university
on
grounds
of
their
area
of
bi rth.
The
fi rst
three
- 100 -

---

TABLE 4-12
Di stri bution of Ivorian Students by Area of Birth and Index of Selectivity
at the 'lational University
~~umber
Area of birth of
Students
Percentage of
Index of
students
in our
Percentage
Ivorians
refl ectivity
(1)
sample
in sample
in 1930
= (3)/(4)
l2 )
l3 )
(4 )
\\ 5)
Abidjan and 1
~Ieighborhood
143
11.6
10.9
1. 06
Boua ke and
Nei ghborhood 2
77
6.1
2.6
2.34
3
Other prefectures
199
16.0
7.6
2.1
Southern
4
sous prefectures
242
19.6
19.6
1
Northern sous
prefectures 5
116
9.4
7.8
1. 20
Eastern
6
sous prefectures
109
8.8
7.4
1. 13
Western
7
sous prefectures
297
28.3
22.0
1. 28
(enter
8
sous prefectures
126
10.2
22.1
0.46
TOTAL
1,238
100.00
100.00
'Jotes: 1 -~bidjan and neighborhood includes the city of Abidjan (capital
city of the country!and its official municipalities
2 - Same administrative division of Abidjan was applied to Bouake,
the second largest city
3 - Regional administrative division.
Onlv the capital-citv of these
administrative divisions were included in this line. There are 26
prefectures in the country.
4 - Sous-prefecture is an under division of prefecture.
In the South
sous-prefecture we included the territories of the prefecture of
Abidjan - Aboisso - Adzope
Agboville, but excluded their
Capital city itself.
The same method was applied to other regions.
5 - Northern sous-prefecture: Odienne - Bondiali - Korhogo - Ferke.
6 - Eastern sous-prefectures: Abengourou - Bondoukou - Souna
7 - Western sous-prefectures: Guiglo - Sassandra - Man - Danane Biankouma
- Touba - Daloa - Gagnoa - Seguela
8 - Center sous-prefectures: Souake - Katiola - Dimbokro-Bouafle~
n, ~;, ~, 1a .
- 1nJ -

---

columns of Table 4-12 capture another type of distribution of students
also
revealed
by Table
3-13:
the
size
of
the community where students
\\vere born or attended primary school.
Size of the Community
In column 5 of Table 4-12, we see in the first three rows that
the major city
in
the center,
Bouake',
is better represented in the
distribution
of
students
by
community
size.
The
nearly
balanced
representation
of
Abidjan
at
the
university
(1.06:
a perfect
balanced
representation
is
given
by
an
index
of
1.00)
can
be explained
by
two
factors.
First, Abidjan, the capital
city has seen a major development
only after independence in 1960 and more precisely after 1965.
Students
born during that period were 15 years old at the time of our survey, and
are
not
included in our sample where the modal
age is 23 and also 23,
for
the original
population of university students.
The second
factor
explaining the
balanced
representation
of Abidjan
is the
high
rate of
immigration
of
citizens
from
other
countries
who
acquire
Ivorian
nationality only after settling in the country.
This group of Ivorians
increases
the
population
of Abidjan
and
therefore
underrates
the
real
selectivity index of the city by bi rth place.
Table 4-13 shows the same phenomenon of distribution of university
students
by
community
size,
but
for
the
size
of
the
city
where
the
students attended primary
school.
This
variable and the
next
variable
that we will examine,
(the distribution of students by area of residence
until 12), account better than the previous variables, for the impact of
the
community
of
origin
on
the
opportunity
to
enter
the
university.
Because primary
school
was
not
readi ly
avai lable
in every area of the
- 102 -

---

TABLE 4-13
Distribution of university students by the size of city where they
attended primary school
'lumber of
% of
% of
Selectivity
Community (1)
Students
students
Ivorians,
index
(1)
( 2)
(3 )
(4)
( 5)
Abidjan &
Neighborhood
246
19.5
10.9
1. 79
Bouake
82
6.5
2.6
2.5
2
Prefecture
262
20.7
7.6
2.72
3
Sous-prefecture
252
19.9
11. 9
1. 67
4
Villages
420
33.3
67.0
0.50
TOTAL
1,262
99.9
100.00
Notes: 1 - Percentage based on the result of the 1975 census.
An annual
90pulation increase of 0.4% was used following the estimates
of the Ministry of Economy.
The same source of information
considers that 0.2245% of the population is foreign.
We computed
the percentages based on this information.
2 - The prefectures are regional administrative divisions.
There
are a total of 26 in the country.
The percentage computed here
is the total percentage population of the capital-city of the
prefec tu re.
3 - The prefectures are subdivided into sous-prefectures.
Here we
took the population of the capital-city of the sous-prefecture.
4 - ,~re con~idered villages,
towns that are neither capital-city
of prefectures nor the capital city of a sous prefecture.
- 103 -

---

country
in
the
early
60' s and
because many
groups
saw
schooling as
a
plot to separate them from a much needed child labor, all
children did
not
have
the
same
opportunity
to
attend
school.
Because
expensive
private schools are the only alternative for students who fail
at exams
i
in
pub 1i c
schools,
education
opportunities
are
restri cted
for
poor
individuals and poor regions.
Column 5 in Table 4-13 clearly supports
thi s
statement.
Students
born
in
vi llages
are
represented
two
times
less at university
(0.50)
than the others.
In fact,
they are the only
group who may not
get
the chance to reach the unl versity
level
because
of
the
size
of
the
community where they
attended
primary
school.
We
unfortunately do not have the distribution of villages by region
in our
sample.
I-le would have certainly found that the villages from the North,
West
and
center are all
the
least
represented at the
university.
The
prefectures,
and
Bouake' are
the most
represented
(2,72 and
2.5).
We
do,
however,
have a distribution
of students by the area they lived in
until
age
12.
This
variable
though
less
precise
than
the
"city
of
primary
school"
in measuring schooling opportunity,
gives
us some
idea
of educational
opportunities open to 12 year olds.
It is less precise
because students may attend school
in one community and move to another
,
to take the difficult secondary school entrance exam (Entree en Sixieme).
The students of this
last category are still
included in
our variable
"area of living until
12".
Area of Living Until
12
Students
are
requi red
to
take
the
Secondary
SChool
Entrance
Exam
(SSEE)
between
the
ages
of
11
and
15.
Most
students
start
primary
school
at
6 or
7.
With
the
high
repetition
rates
of
pre-educational
- 104 -

---

television
students,
the average age at which students
completed the 6
year cycle was 14.
A change in date of birth on a birth certificate,
followed
by
a migration
to
another
city
was
the
only
chance
left
to
students who do not succeed at the exam before the mandatory age 1 i mi t
of
15 years.
Late
growth
and
lack
of
opportunity
at
an
early
age,
forever close the chances of an individual to pursue his education; this
constituted
a
major
source
of
loss
of
manpower
trainees
for
the
country.
Supposedly
the
introduction
of
the
Educational
Television
System
(ETS)
at
the
primary
school
level
was
to
address
this
issue.
However,
the
age
restriction
and
the
highly
competitive
SSEE
(approximately
20%
of
the group
enter
secondary
school)
survived with
the ETS, and therefore left the problem of manpower loss unsolved.
Table 4-14 indicates that the majority of the students
(23.4%)
in
our
sample
lived
in
the
Center
until
age
12,
followed
by
the
South
(21.7%) and Abidjan
(19.1).
The regions least represented are the East
and
the
North,
as
a
previous
measure
of
regional
distribution
also
indicate,
(the lowest
index of
selectivity
(0.47)
found
in the Western
area contrasts with the 1.28 index for the same area according to Table
4-12 of "the area of birth."
Students born in the west tend to move to
other areas to attend school, a phenomenon empirically observable in the
country.
A second contrast between Table 4-12 and 4-14
is presented by
the Central
region,
which
has
the
lowest
index of selectivity for the
area of birth (0.46) but appears relatively well
represented (1.05) when
we
consider
the
area
where
people
resided
until
age
12.
Possible
explanations are that people from other areas (North, West) tend to move
toward
the
Center;
or
the
area
where
they
resided
may
have
been
administratively
reclassified
into the
center at
a later date,
as
has
- 105 -

---

---

TABLE
4-14
Oistribution of students by region of residence until 12 and the indices of selectivity
II )
(I)
CL)
( 3)
( 4 )
Area of residence
['umber of
Percentage
Percentage in
Index of
up to 12 years of age
students in sample
of the sample
le Population (1980)
Sel ectivi ty
Abidjan and municipalities
L43
19.1
10.9
1. 75
Bouake~
66
5.2
2.6
2
Other prefectures
52
4.7
/.6
U 54
~
Sous-Prefecture South
0
<76
L1. 7
19.6
1. 10
m
Sous-Prefecture North
113
!:l.9
/ .8
1.14
Sous-Prefecture East
n
7.2
7.4
0.97
Sous-Prefecture West
132
10.4
22.0
0.47
Sous-Prefecture Center
298
L3.4
22.1
1. 05
rOTAl
1.274
100.00
100.0
,
Notes:
1 - The areas are defined as in Table 4-12.

---

often been the case.
Apart from these two oddities, students are fairly
represented, by the region where they reside until
12.
Dur
discussion
on
the
distribution
of
Ivorian
students
at
the
National
University
by
regions
of
country
has
revealed
the
following
traits.
(1) The ethnic group consideration which describes a historical
regional
distribution
shows
that
Akan
group,
located
in
the
South and
East
are
overrepresented
at
the
university
level,
while
the
Senoufo-
voltaic
living
in
the
Northern
areas
are
under
represented.
(2)
Students
born
in
the
central
region
tend
to
be
scarce
at
the
university.
Other
regions
are
fairly
distributed
1n
the
student
population
when
it is
designated
by
area
of
bi rth.
(3)
Students who
attended
their
primary
school
in
a
village
have
less
chance
to
be
represented at the university level, whereas those born
in a prefecture
may
have
the
best
chance.
(4)
Finally,
if
students
resided
in
the
Western area
until
12, Uley
had
fewer
chances
to attend the university
than a resident of the North or the South.
Distribution of Students by Education of Their Parents
Table
4-15
gives
the
distribution
of
students
by
the
family's
level
of
education.
As
one
should
have
expected,
the
parents
in
our
sample
have
a
level
of
education
much hlgher than that
of the
general
1vorian
population.
If
we
reduce
the
percentages
lndicated
for
the
level
of
education
of
the
1vorian
population
to
account
for
the
fact
that not all male 1vorians are fathers, the percentage given in column 3
1S
even lower, and the selectivity index should be inflated.
Even with
an overestimation of the Ivorian population education level, we see that
the
index
of
selectivity
increases
with
an
increase
in
the
level
of
- cO? -

---

TABLE 4-15
)
Father and mother level of education and their selectivity indices
Father
Mother
(1)- - - -
(3)
(4)
(5)
(6)
(7)
Ivorian
Selectivity
Ivorian
Selectivity
Educational Level
Our sample
Population
Index
Our sample
Population
Index
Does not speak French
41:\\.5
63.5
0.76
81. 3
81.8
0.99
Primary school no CEP
23.9
27.0
0.83
12.D
15.4
0.77
CEP, Secondary School
No
3[PC
15.9
7 .8
2.03
3.4
2.0
1.7
BEPC. no [lAC
6.7 J
1.7
0.0
~
0.6
14.3
0.9
0.0
o
tXJ
BAC. no higher Education
I.g
2 Years of Higher
Educa t i on
0.7
Bachelor degree
D.1
0.5
6
0.1
0.0
Graduate Studies
2.2
':-:-:;;,;,: ''::'. ,=--;..~:.-:,:'!:~ ~- ~ - ~._~,~.~ -:, ~:~ r ~
;' _,:" " L~~~:'" ,~
~' ..'.. ~__ ,.:,_ ,5 \\~~-:."
..........
,: '" ~.
,'.
..- ~
_:~::.".
• ---, -
'~
~
< •
- • •
. "
"
.'
ili"
-',-.'
"'"
;,.

---

education.
The
increase
is
more
abrupt
for
the
father's
level
of
education.
The majority of students' father (48.5%) and mothers (81.3%)
do not speak French.
This
indicates that th~y do not hold jobs in the
city, and are most certainly occupied in the rural sector.
The index of
selectivity
for
the
mothers
who
do
not
speak
French
is
surprisingly
close to
one
(0.99):
Mothers
in our
sample are evenly represented as
they
are found
in
the
Ivorian
society
in
so far
as
learning
to speak
French is concerned.
The unusual
high
index of selectivity
(14.3) for
fathers with BAC level
of education is difficult to explain.
Oistribution of Students by Fathers Occupation
From our survey we classified parent's occupation in one of the 89
employment categories indicated by the 1975 census.
\\le later regrouped
the
professions
in
the
categories
indicated
by
Table
4-16.
Our
own
classification of job categories may differ from that of the census, and
we could not obtain the job classification of the census to readjust our
own
for
the
computation
of
selectivity
indices.
For
instance
we
classified teachers, doctors, pharmacists, and lawyers in the management
position
category
without
knowing
whether
the
census
adopts
the
same
classification.
In our sample we have a high proportion of unemployed
working and
retired
(48.3%)
for which we could not
find
correspondence
in the census.
The rural worker group in our sample seems unusually low
(21.6%)
for
a
country
1He
the
Ivory
Coast.
I,e
suspect
that
many
students reported in 1980, their fathers
retired,
due to old age, while
these
fathers
reported
a
rural
occupation
to
the
1975
census.
The
fathers
most
likely
own
today
a
farm
which
is
probably
exploited
by
other people.
In other parts of the survey where we asked students the
- 109 -

---

TABLE 4-16
Socio-Profession of Student's Father
Our
Ivorian Population
Index
Socio-Profession
Sample (%)
1975 Census (%)
(2)/(3)
( 1 )
( 2)
(3 )
(4 )
Not workin9 or retired
48.3
8lue collar worker
7.4
13.9
0.53
Rural Occupation
21. 6
72.8
0.29
White Collar worker
8.3
8.2
1. 01
Management position
14.4
2.9
4.89
- 110-

---

sector of their parents'
occupation we obtained 51.6 percent
for
rural
activity
indicating
their
actual
occupation,
when
these
parents
were
working_
Wealso had a very high percentage of missing values_ in this
variable.
Even when account
is taken of
the caveats indicated above,
parents
with
rural
occupations
are
more
often
represented
at
the
•
university
than
any
other
profession
(21.6%).
When
we
cons i der
the
representation
of
rural
workers
in the
Ivorian population,
we obtained
0.29 index of selectivity, which is very low.
Even if we take the 51.6
percent
proportion
of
parents
occupied
in
the
rural
sector
given
in
another part of the survey, we still
have a selectivity index of 0.70,
which
is
low.
The rural
population
is clearly under represented at the
university
level,
considering
their
proportion
in
the
lvorian
population.
ln
contrast,
management
level
positions are overpresented
by
four
times
(4.B9)
their
normal
index
of
selectivity.
White collar
workers
are
sl ightly
over-represented
(1.01)
and
blue collar workers
under-represented (0.53).
The
general
picture given
by the distribution
of
Ivorian
students
at
the
university
by
socio-profession
is a
tendency
to
over-represent
profession with higher economic status.
D.
Comparison with·Charlick's Study
Although
our
work
and
that
of
Charlick
(1974
op.
cit)
were
conceived
from
different
angles,
we
did
on
occasion
measure
the
same
variables.
It will
be interesting to see how we differ in our results,
taking into account the 6 year period which separates the two studies.
The
variable
which
appeared
ln
both
works
are:
father's
education,
socio-profession,
size
of
city
of primary
school
education,
choice of
- 111 -

---

higher education and the student's ethnic group.
Table 4-17 shows a striking feature: the results from our own study
are
in many
instances
very close to Charlick's.
This again
indicates
that our survey is fairly accurate.
1.
Father's Education
As
must
be
expected
a
larger
proportion
of
our
group
had
parents with a
hi gher
1evel
of educat i on
than
Charl i ck' s
study
showed
(27.5%
vs.
20.0%).
The
proportion
of
"does
not
speak
French"
in our
sample is, however, higher.
This result may be discounted because it is
likely that Charlick's "no formal
education" which has no correspondence
in our work, can be equated to our "does not speak French". In that case
the
trend
toward
better
educated
parents
apparent
in
our
sample
is
verified here (48.9% vs. 54.4%).
2.
Father's Profession
For the father's
profession,
the two authors
did
not
use the
same measurement
of
socio-profession.
Only
two
sectors
which
may
be
assimi lated
are
reported
in
the
table.
The
number
of
students whose
parents have an occupation in the rural
sector is slightly lower in our
sample
than
in
Charlick's
(52.5%
vs.
53%).
Our
sample
contained
a
higher
proportion
of
parents
working
in
the
modern
sector
(2fL8
vs.
28.3), a result which was to be expected given the economic evolution of
the count ry.
- 112 -

---

TABLE 4-17
Comparison of Charlick and Yao Studies from 5 Variables
Variables
Charl ick (1976)
Yao (1980)
%
Of
"
1.
Father's education
Does not speak French
35.1
48.5
No formal education
54.4
Education up to CEPE
25.5
23.9
Education beyond CEPE
20.0
27.5
2.
Profession of Father
Rura 1 sector
53.0
52.5
Publ ic sector
28.3
28.8
3.
Size of city of Primary
Se hoo 1
30.0
Village
33.3
56.5
Small cities
40.6
13.6
Citi es
26.0
4.
Allocation in Student's
Schoo 1 Chol ce
~edical School
67.6
73 .3
Economics
6Z.7
31.8
Science
55.0
40.6
Law
53.3
46.1
Letters
46.7
5Z.8
Total University
55.4
48.1
5.
Student's Ethnic Group
~aoule-
15.8
18.1
Other Aka ns
16.2
14.5
Lagoon Groups
19.4
20.1
Krou
ZO.5
19.1
Mande-
6.5
7.0
Malinke'
12.9
9.3
Senoufo-voltaic
6.8
8.5
- 113·

---

3.
Si ze of Pri ma ry School City
As
far
as
the
size
of
the
city where the student attended
primary school is concerned, we notice a tendency over the 6 years 1apse
- -
-- ---
of
time
toward
lI ur banization ll
of
the
uni ve rs ity.
This
tendency
parallels
the
direction
of
the
country.
City
primary
schools
have
graduated 26 percent of the students in our survey when 6 years before,
they graduated only 13.6 percent.
The phenomenon of urbanization tends
to draw more
from medium size cities
rather than from villages which
graduated
33.3
percent
in
our
survey
compared
to
30
percent
in
Charl ick 'so
4.
Student's Choice of School Approval
There has been a stricter government control
over allocation
of students to the school of their choice.
Charlick found 55.4 percent
of students obtaining their choice of school when we noticed only 48.1
percent.
From Charlick's survey it
is not clear whether the students
obtai ned thei r fi rst, second or thi rd choi ce of school, cases whi ch may
still
be considered as
"enrollment in the school
of one's choice".
He
does
not
differentiate enough between obtaining one's first
choice of
school
or not obtaining it.
The schools of Medicine and Letters have
seen more students obtaining their choice than
in the past
(73.3% vs.
67.6% and 52.8% vs 46.7%, respectively).
Students have come to know the
requirements of these schools with time and do not bother to apply to
them.
There has been a stricter policy of admission in
the
rest
of
the schools.
- 114 -

---

5.
Ethnic Group Composition
As far as we consider ethnic group distribution as a regional
distribution of students, we can see from variable 5 in Tabl~ _4~17 that
the Akan group in which one also includes the
Baoule' and Lagoon Group,
has
not
on average
lost
its
position
of leadership at the university
(54.4% in Charlick
vs.
52.7 in ours).
Thi s group whi ch
is genera lly
better-off than others, has not increased noticeably, its position among
other groups however.
The poorer Senoufo-voltaic are better represented
than they were 6 years before (8.5% vs. 6.8%).
The Malinke' have lost
some representation in 6 years (12.9% vs. 9.3%) so have the Krou (20.5%
vs. 19.1%).
- 115 -

---

CHAPTER V
THE FINANCING OF THE NATIONAL UNIVERSITY
Before we attempt to estimate the economic costs of the resources
used at the National University in the next chapter, we need to present
the institutional context in which the costs evolve.
More precisely, we
analyze the institutions which are in charge of gathering, analyzing and
spendi f\\g the resources of the uni ve rs ity.
,le al so exami ne the di fferent
sources which provide funds allocated to departments and the administra-
tions
of
the
university.
Finally,
we take a historical
look
at
the
evolution
of
the
main
aggregates
which
affect
the
financing
of
the
National university.
The budgets we analyze in this chapter constitute
only a small
portion of the total
cost of the university (19% in 1980-
81).
However, because these budgets constitute the only autonomous part
of the total cost which university authorities control, the analysis of
the budgets will
give us a better picture of the university's internal
financial resources.
A.
The Institutional Context of the University Finance
It is important to understand the many administrative surroundings
of
the
National
University's
financing
system,
to
avoid
the
double
counting or omissions so often encountered in cost analysis.
To help US
in such an understanding we first examine the administrations in charge
of managing the university.
In a second approach we will
analyze the
budget preparation of the university,
and finally we will
present the
process by which resources are allocated in the schools and institutes.
- 116 -

---

1.
The Financial Organs of the University
Figure 5.1 shows that a budget proposal
made by a school passes
through
at
least
five administrative organs before its
final
approval.
The
number
of
institutions
in
charge
of
examining
a
budget
proposal
render
the
financial
decision
making
process
very
slow.
It should be
mentioned also that the budget elaboration process we are examining here
concerns only the so-called
"operating budget" of
the university.
The
operating budget is approximately equivalent to a "recurrent budget" in
a cost study.
~~e do not consider the budget of the CNOU, the Investment
Budget
(directly executed by the Ministry
of
Finance),
and the cost of
administrative and teaching personnel salary (handled by the I~inistry of
Civil
Service
and t·\\inistry
of Flnance because university
personnel
are
ci vil servants).
The budgets under study here concern only the everyday
operation
budget
of
the
university
and
schools,
allocated
to
the
university, every year, by the Ministry of Finance.
In March the Office of Budget
(OB)
requests
a budget proposal
for
the
coming
academic
year
from
the
schools
and
institutes.
The
proposals,
once
gathered
hy
the
O.B.
are
examined
by
the
Restricted
Finance
Committee
(R.F.C).
The
latter
is
required
to
submit
its
findings
to
the University
Budget
Committee
(BC).
The work
of the BC
must then be approved hy the councll of the uni versity before it reaches
the
desk
of
the
Ministry
of
Finance.
Such
a
long
process
could
be
significantly
reduced
if the office of
budget was
granted enough
power
to
negotiate
the bUdgets
with
schools
and
submit
them directly to the
Ministry
of
Finance.
f1uch
Vlaste
would
also
be
avoided.
Indeed,
administrative organs in charge of approving school
budget rarely reduce
a budget
proposal.
Instead they
lobby
for a larger and larger portion
- 117 -

---

FIGURE 5.1
UNIVERSITY ORGANS AND THEIR ROLE IN THE BUDGET PREPARATION
".. ...
-
INSTITUTIONS
TASKS
~---T-IM-E
J
L -
S_C_HE_D_UL_E_I.
!
MINISTRY OF
~ ALLOCATES BUO'ETS
. NOVEMBER
I
FINANCE
ACCORDING TO OWN
DECEMBER
CRITERIA
....
COUNCIL OF UNIVERSITY
Approves Budget Proposal
-Rector
,
submitted to Ministry
/
-Deans -Directors
JU. E
Allocates budgets to
~
-Tenured Professors
-General Secretary
schools & institutes
""
of University
;t..
Budget Committee (B. C. )
Approves the RFC
Budget Proposals
--
-Ministry of Education
>
-Rector
-Deans
-Di rectors
""
Restricted Fi nance Commi ttee
(R.F.C.)
Study Schools and
.....
Institutes Bu~get
~
-Rector
/
Proposals
-General Secretary of
MAY
Un i vers ity
-Chief of O.B.
-Director of CUIP
~
f1\\
Schools and Institutes
~ares
rAPRIL
-Dean or Director
.-.
>
-Administrative Assistant
Next Academic Year
I
I
. 8~dgets for
I
,
1'
_
Office of Budget (O.B.)
Request Budget Proposals
MARCH
)
- lIB -

---

of
the
university
budget
to
be
allocated
to their
constituency.
The
people
directly
involved
in
budget
approval
are sometimes
representa-
tives of the various institutions making the budget proposals.
2.
Budget Procedure and Resource Allocation
Figure
5-1
also
delineates
the
role
played
by
various
uni vers ity admi ni strat ions
in prepa ri ng and execut i ng the budget.
The
figure
reveals
a rather
authoritarian
budget
decision making
process.
After the schools and institutes have made their budget requests to
the
university
budget
office
they
have
no
contact with
that
office
until
they
find
out
what
budget
they
will
receive.
Almost
no
negotiation
between the schools and the office takes place.
A similar process takes
place at the highest decision making
level,
between the university and
the Ministry of Finance.
Although an additional
fund may be allocated
to
the
university
if
its
budget
appears
insufficient,
this
secondary
allocation
process
appears
arbitrary
and
inefficient
in
comparison
to
the
first
process.
The
consequence
for
such
authoritative
bUdget
decision making is that all
budget proposals are inflated in hopes that
each department will
receive a share of the budget related to its needs.
The basis for budget allocation is the budget proposal
furnished by
the
schools,
institutes
and
services
of
the
university's
central
administration.
The
budget
proposal
is
examined
according
to
three
criteria: (1) haw beneficiaries used previous budgets allocated to them,
(2)
the
number
of
students
expected
and
therefore
the
additional
teaching and administrative staff needed,
(3)
the level
of maintenance
work
required
in
that
particular
school.
Because they do
not
report
previous budgets to the next fiscal
year,
schools tend to use up their
- 119 -

---

*
Note:
1.0.S. = lnstitut d'odonto Stomologie (Dentistry).
Data provided by "Rapport" (1980-81) op. cit.

---

savings
in the
last months
of
the
university
fiscal
year
(October)
so
that the next year's budget wi 11 not be reduced by the amount of savi ngs
made.
Also
because
the
Ministry
of
Finance allocates
the
university
budget
without
negotiation,
it
is
difficult
for
the
university
to
distribute the resources according to the schools'
actual
needs.
Some
sort
of
"equitable"
distribution
of the
resources actually
granted by
the Ministry is then imrlemented by the university.
Table 5.2 indicates
the allocation of budget to the schools in the year 1980-81.
The three
social science schools have approximately the same absolute value in the
university subsidy while the rest
of the schools
have a higher subsidy
because they require expensive teaching materials.
The rCM' of Table 5-1 related to the ratio of subsidy and number of
students
in
1980-81
indicate
a
variation
in
ratio
from
9.87
for
the
School of Letters to 16.34 for the School
of Economics, as far as Social
Sciences and Humanity Schools are concerned.
This ratio fluctuates even
more
when
we
consider
the
other
group
of
schools,
from
99.75
for
sciences
to
745.64
for
Dentistry.
The
wide
variation
in
the
ratios
indicates that the number of student who may enroll
in the school
does
not determine allocation of the subsidy.
The statistics on hand do not
allCM'
us,
however,
to
further
analyze
the
determinants
of
bUdget
allocation
for
each ·school,
once
the
student
population
is
accounted
for.
In
conclusion,
the
multiciplicity
of agencies which
take part
in
the
definition
and
allocation
of
resources
to
the
schools
renders
an
attempt to ascertain the determinants of budget allocation for a school
almost
impossible.
This cumbersome administrative network is,
however,
an
asset
when
one
needs
to
identify
the
sources
of
the
resources
- 121 -

---

allocated to the schools, because many cross-references can be made for
verification purposes.
B.
The Sources of Financing the National University
Again,
we
remind
the
reader
that
the
resources
under
study
here
are
those
which
come
under
the
di rect
or
indi rect
control
of
the
university.
Long term and heavy investments are di rectly controlled by
the Ministry of Education
in conjunction with the Ministry of Finance.
The resources are apportioned from the
Investment Budget of the country
(B.S.l.E.) and managed by the two Ministries.
Also expenditure related
to
teaching and administrative personnel
are supported by the Ministry
of Finance and not by the university.
The important CNOU budget also is
not
within
control
of
the
university.
We are
only concerned
in' this
section with the operating budget of the university.
In a later section
devoted
to
cost
estimates
we
shall
consider
all
the
sources
of
the
resources used.
Three
possible
sources
of
revenues
exist
for
the
university:
(1)
the university's own resources, (2) the subsidies received from national
agencies and (3) foreign aid.
1.
The Internal
Sources of Revenues of the University
Because
the
university
is
a
public
administration,
it
is
legally forbidden from making a profit.
However,
it can raise fees for
some
of
the
services
that
it
renders
to students.
Since education
is
free even for
foreign
students,
the university cannot
raise tuition to
cover all of its operating expenses.
Table 5-2 indicates the areas ¥lher'e the university
raised
its OI<n
- 122 -

---

TABLE 5.2
EVOLUTIO'I OF lINIVERSITY'S 11!-Jf! RESOURCES Mln THEIR ORIGINS
Categories
1961
1970
1975
1978
Exam Fee
95
2,805
7,931
111,119.4
~e'li s tration Fee
50a
2,053
3,570
d,02fl.I
Library Fee
280
1,7£16
3,261
d,152.2
Laboratory Fee
1,380
9,264
11 ,940
14,696
Receipts
73,973
73,037
2,605.8
Other
32
13 ,250
5,4d6
2,2;)2.9
TOTAL
2,287
103,091
105,185
37,824.4
Source: Oiarrassouba (1979)
- 123 -

---

revenue,
and
the
evolution
of
this
revenue
from
1961
to
1978.
Unfortunately,
the
recent
statistics
we
obtained
did
not
provide
a
simi lar breakdown.
If we exclude the year 1961 when we did not have a
---
- - .
full
fledged university status, we notice that
for
the last 8 years of
the
table,
the
university
internal
resources
increased
by
2
percent
every
year
between
1970
and
1975.
After
that
peri od,
we
observe
an
average annual
decrease in revenue of 92% for the last 3 years.
Such a
decrease is due to the fall
in cash flow from university aCtivities from
73,037 to 2,608.8.
1·le could not
identify the nature of this source of
income,
nor
could we
determine
the
causes
for
such
a
decrease.
The
first
four
categories
of
revenues
in
the
table
have
been
increasing
steadily because of their relation to the number of students.
I n
the
academi c
yea r
1980-81
an
attempt
was
made
to
ra i se
the
registration fee for foreign students.
Such a decision was met by many
protests from African countries
less fortunate than the
Ivory Coast who
send their students to the university; and also by France
threatened
to
do
the
same
to
Ivorian
students
in
France.
The
1980
university
budget
does
not
show
a
si9nificant
increase
in
internal
cash
fl OW.
Therefore we may conclude that the attempt to raise the registration fee
for
foreign
students
failed.
Another
source of
the
uni vers i ty' s
internal
revenue
which
does
not
appear
clearly
in
its
aggregate
statistics is the revenues from contracts obtained by some institutes to
conduct
research
for
national
or
international
agencies.
This
last
source of revenue is
increasing both in number of donating agencies and
amount of money
received,
as
can be seen
in Table 5.3.
Unfortunately,
previous
statistics did not separate research projects and therefore we
could not give their evolution here.
In any case this source of revenue
- 124 -

---

TABLE 5.3
UNIVER51TY IN5TITUTES AND SERVICES AND TilE SOURCES OF THEIR FINANCE IN 1980-81
Origins
I REEP
I E5
ILA
loT
IHAA
CERAV
CUEFF
ILENA
CIERRA
CRAU
CRI MONO
CIREJ
CIRES
CUll
Univ.Subisdy
5,100
12,575
I I ,475
12,575
8,500
10,625
9,180
S,950
6,025
4,675
4,675
4,000
6,800
18,275
Addi t ional
Subsidy
1,411
585
1,33
411
3,083
I ,176
1,341
832
2,726
1,906
718
968
-
5,368
N. E.
7,185
10,072
8,433
8,433
10,720
--
4,160
--
5,605
--
--
10,483
UNESCO
1,680
AGE COOP
--
II ,133
Ministry of
~
Pl ann; ng
- -
15,000
'"
--
en
Canada
- -
24,000
14,000
--
- -
--
--
- -
--
--
-.
28,785
WHO
- -
- -
10,150
Other Ministries
- -
- -
--
- -
- -
--
- -
- -
11 ,661
FORO
--
--
--
. -
- -
. -
- -
- .
--
-.
--
13,074
Other
Foreign Finance
- -
- -
--
- -
- -
--
926,576
-.
- -
--
4,947
University
- -
. -
- -
--
-.
- -
--
- -
-.
-.
--
4,125
ONFP
France
Internal
Resources
_.
- -
- .
- -
--
--
..
- -
--
. -
--
--
4,125
TOTAL
8,512
11,025
54,813
70,670
10,016
1,254
10,521
10,941
8,751
13,847
5,393
4,968
78,214
27,768
Data provided by "Rappon 1980-81" Op. eil.
--==-1

---

is one which must retain the attention of decision makers in a time
when public subsidies are reduced.
2.
The Nat i ona 1 Sou rces of Subs i dy to the Uni vers ity
When the nations's bUdget is adopted, it includes subsidies to
the
university.
However,
a
recent
government
decree
states
that
government agencies, save for a few exceptions must be under the di rect
financial control of the Ministry of Finance.
This has changed the way
government
subsidies
are
received
and
especially
the
way
they
are
utilized.
Information
gathered
from
Table
5.1,
5.3
and
elsewhere
is
synthesized in Table 5.4 to indicate the national sources of revenue for
the university operating budget, and the research grants received by the
departments.
The
university
has
been
more
and
more
successful
in
securing
funding
for
its
research
from
a wide
variety
of
national
sources.
In
particular it
has
received
research grants from at least
six ministries and from many national
agencies.
This
result
indicates
that
national
agencies
and ministries
are more and
more
confident
in
hiring national scholars for conducting their studies, a task which used
to be entrusted to international
researchers.
In opening its expertise
to local research needs, the university is also breaking a barrier which
has
traditionally existed
between
the university
and the
rest
of
the Ivorian society.
Finally, hard earned foreign.urrency obtained by
trading
primary
goods
can
now
remain
in
the
national
accounts
when
Ivorian
ministries
and agencies
rely
on the university
for
consulting
services rather than unnecessary outsiders.
Table 5.4 also displays an aspect of the university administration
- 126 -

---

TABLE 5.a
NATIONAL INSTITUTIONS AND THEIR PARTICIPATIO~ IN THE FINANCE OF THE COST OF
THE NATIONAL UNIVERSITY
Uni vers i ty
Ministry
t1inistry
Ministry
National
Ministry
Ministry
Ministry
tli n is t ry
Agencies
of
COST CATEGORY
BUdget
of
of
of
of
of
of
N.E.*
Planning
Health
Finance
Housing
Civil Serv.
Research
1.
Recurrent Cos ts
0 0pepartments)
x
x
mlnus salary
2.
Research Grant
to Institutes
x
x
x
x
x
x
x
X
3.
Un i ve rs i ty
Opera t i ng
Budget
x
~4.
....,
Teachers and some
Staff Housing
x
5.
Carita 1
Inves tments
x
x
6.
Capital Cost of Univ.
Administration
X
X
7
Teaching and Staff
Sa 1ary
X
X
X
,
Notes: N.E.
National Education (in charge only of secondary non vocational schools, the National
University and the Ecole Normale Superieure).

---

already
mentioned:
the
multiplicity
of
agencies
intervening
in
any
,
I
action.
For instance, when a faculty member is hired by the university,
the administration
forms
needed
for
recruiting
her.are
handle~_ by the
Ministry of Civil Services. She receives her salary from the Ministry of
Finance.
The
Ministry
of
Housing
will
lodge
her.
She
recei ves
her
research
grant
from
one
of
the
national
agencies
or ministries.
She
obtains
her
instruction
material
from
the
uni versity
admini stration,
which
in
turn
received
its
budget
from the Ministry
of Finance.
The
recent decision to classify the university among the
"E.P.A." does not
help in alleviating this cumbersome administrative tutelage.
The
national
sources
of
funding
are
not
the
only
area
of
administrative
imbroglio.
It
is
also
necessary
to
add
the
foreign
sources of funding.
3.
The Foreign Sources of Funding of the National University
Si nce
its
creat ion
in
1964
the
uni vers ity
has
attempted
to
di vers ify
its
sources
of
forei 9n
aid.
In
particular,
the
French
90vernment
has
decreased
its
absolute
sha re
as
well
as
its
area
of
funding
of
the
National
University.
Tab le
5.5
shows
the
historical
decline
of
the
French
government's
contri but ion
to
financing
the
university.
The period from 1975-76 to 1980-81 is covered by the table
and
indicates
a
rapid
rate
of
decrease
in
the
effort
of
the
French
government
to
help
meet
the
university's
operating
costs
from
45%
in
1974-75 to 3.2% in 1978-79.
Since 1979-80, the operating costs category
is entirely covered by Ivorian public funds.
Before
the academic year
1971-72,
the French
government
not
only
supported the recurrent costs
of the uni versity but also all
the costs
- 128 -

---

TABLE 5-5
EVOLUTION OF THE CONTRIBUTION OF FRANCE TO THE OPERATING
BUDGET OF THE NATIONAL UNIVERSITY
-
--
. - -
.__..
TOTAL UNIVERSITY
IVORY COAST CONTRIBUTION
FRANCE'S
YEAR
BUDGET
TO THE BUDGET
CONTRIBUTION
Tota 1
%
Total
%
1974-75
890
490
55
400
45
1974-76
989
642
65
347
35
1976- 77
1,050
670
64
380
36
1977-78
1,088
913
84
175
16
1978-79
1,257
1,217
96.8
40
3.2
1979-80
1,598
1,598
100
0
0
1980-81
1,348
1,348
100
0
0
Note:
lJata provided by "~ap:Jort - d 'activite 1980-81
- 129 -

---

of personnel,
including that of
Ivorian staff wembers.
Start i ng with
that year, the Ivorian government financially took charge of the Ivorian
personnel and also those French teachers hired within the "Globalization
- .._-
- - - - - _ . __
..
- - -
-
-_.----....._-- -
- -
....
- .
-
---------._----------
Agreements. ,,1
In 1980-81 except for a few cases, the forei gn teachi ng
and administrative
personnel
was
financially
supported
by the
Ivorian
government.
The
French
government's
financial
assistance
has
not
stopped, but
has changed in nature.
Table 5-6 indicates the areas in
which the French contribute.
Their assistance comes mainly in the form
of research grants given to specific institutes (especially scientific
laboratories)
and
also
postgraduate
awards
to
junior
teaching
staff
members of the university (scho1. ln Table 5.6).
Table
5.6
also
includes
all
external
sources
of
university
financing during the academic year 1980-81.
In absolute terms, Canada
is second to France as the major external
source of funding.
If one
adds to these figures the cost of French teachers supported di rectly by
France, then France plays an even more significant role as University's
principal
external
source
of
funds. Unlike the universities of many
third world countries, the number of foreign countries which lend direct
financial
support
to
the
Ivory
Coast's
university
is
very
limited:
France, Belgium, and Canada.
The
rest of the external funding comes
from
international
agencies
or
foundations:
UNESCO,
WHO,
The
Ford
Foundation.
The language barrier may prevent university officials from
more
success
when
seeking
funds
for
the
university,
from
non
French
speaking
countries.
This
barrier
may
also prevent
other
non
French
speaking
countries
from
venturing
into
the
Ivory
Coast.
A second
alternative
explanation
for
the
relatively
small
external
assistance
received is that the Ivory Coast is still perceived by many countries as
- 130 -

---

TABLE 5.6
EXTERNAL FUNDING DF THE UNIVERSITY AND ITS BENEFICIARIES
Sources of
in 198-81
Funding
FORD
Beneficiaries
FOUNDATI ON
UNESCO
CANADA
FRANCE
BELGIUr1
lmO
TOTAL
IES
1,680
--
- -
1,680
ILA
--
--
21,000
1,500
- -
--
j22,500
IGT
--
--
24,000
- -
--
10,250
34,250
CERAV
- -
--
--
1,500
- -
- -
, 1,500
Cl RES
13,074
--
28,785
--
--
- -
41,859
CUFOP
--
- -
--
4,000
--
- -
4,000
~
IREN
- -
- -
- -
22,275
--
- -
'22,275
w
~
IREEP
--
- -
--
1,500
2,000
- -
3,500
Library
--
- -
- -
25,000
- -
--
25,500
Law
--
- -
- -
5 schol.*
Letters
--
--
--
2,500
--
--
2,500
+ 6 schol.*
Economics
--
--
--
2,500
- -
- -
2,500
+ 3
schol.*
Pharmacy
- -
- -
- -
7,500
--
--
7,500
Medicine, IOS
--
--
--
235
+ 2 se ha 1.*
Sciences
- -
--
--
44,740
--
--
44,740
+
5 schol. *
,
CUTI
--
- -
--
1,025
- -
--
1,025
TOTAL
13,074
1,680
73,785
114,040
2,000
10,250
214,829
*Scholarships for one year awarded to junior level teachers to study and work on their dissertation Thesis in France.
Data provided by Rapport 1930-81 op.cit.

---

the
"Chasse-gardee"
of
France.
[t
is
therefore
possible
that they
assume
any
assistance
needed
by
the
university
will
be
graciously
provided by France. _~.tnally, the relative_economic success_ of _the __ Ivory
Coast
may
have directed the little international
aid available toward
more needy
countries such as Upper Volta, r~ali, Togo or Benin.
Whatever level the funding of the National University has reached,
one
needs
to
take
a
historical
look
at
its
evolution
to
better
appreciate its trends.
C.
Evolution of Some Economic Aggregates and the University Budgets
In
this
historical
analysis
we
will
consider
the
evolution
of
university budgets in relation to some national economic aggregates such
as
the
Gross
Domestic
Product
(GDP),
the size
of the
nation's total
budget and the Ministry of National Education's budget.
It would have
been
more
appropriate
to
include
in
this
list
of
national
economic
aggregates, the total budget spent not only on the uni versity, but al so
on
the
lower
levels
of
education,
other
institutions
of
higher
education,
such as the
"Grandes Ecoles,"
and
on the non prestigeous
vocational
institutions
of
higher
education.
Such
an
undertaking
requires
a
tedious
document
searching
and
cross-referencing
of
information
because
of
the
intricate
relationship
between
ministries
which contribute to Education.
For this task, the complexity in tracing
the
sources
of
funding
is
compounded
by
institutions
and
ministries
which
have
been
created
and
have
disappeared
during
government
reshuffles.
,le cannot accomplish that project in this dissertation and
therefore
will
limit
our
analyses
to
the
aggregates
chosen.
In
examining the evolution of aggregates over time, we shall
pay attention
- 132 -

---

to two particular problems:
first, we shall compare the country's budget
allocation over the years to finance the university, with its effort to
meet
other
social
needs.
I n a
second
approach
we
sha 11
analyze
the
evolution
of
school
budgets
in
relation
to
the
number
of
students
in
each school
at the uni vers ity,
Thi s
sha 11
be done in conjunction with
traditional
indicators
of
resource
allocation
to
education
such
as
expenditure per student,
teacher
- student
ratios,
and
number of books
per student.
1. C~iversitx Budgets and National Economics Aggregates
Traditionally,
the effort
made
by
a
country
toward its educational
system is measured
by
looking at the proportion
of
the
GNP,
or
similar
national
economic
aggregates,
which
goes
into
education expenditure.
Empirically
one· may
test a country's effort
by estimating the following demand
form equation
over a certain period
of time.
Log E = a + SLog P
where:
E
Education Expenditure per capita
P
GDP per capita
a
constant
fl = coefficient
of
Log P measuring the elasticity
of demand
for education.
f
can also be computed using the statistical
formula for computing an elasticity
PjE
B
2
dpjdE
- 133 -

---

£
which
is
often
taken
as
a demand
elasticity
is
actually
an
income
elasticity of education expenditure.
d is an increase in the variables.
P and E have their previous meaning.
Obviously
many
problems
are
associated
with
such
a
measure
of
a
country's
effort.
The
first
problem
recognized
by
all
economists
but
often dismissed by many of them for
lack of better alternatives, is the
imperfection
in
the
instruments
used
to
measure
growth
or
economic
achievement:
the GNP, GDP,
NNP, National
Income, etc. In- order to have so-
me cowmon grounc for discussing international comparison one may need
to
use
these
instruments.
However,
when
trying
to
assess
a
single
nation's
efforts
toward
education
the
imperfections
of
the
instrument
are overwhelming.
The free labor, free construction material taken from
the forest,
and free
food
often
provi e1ed
for
teachers
by vi 11 agers are
not accounted for
in the national
accounts.
However,
these things need
to be estimated by researchers when they are
ascertaining the costs of
education.
It is
difficult
to
interpret
and
give meaning to the
sign
of the
elasticity
we
compute,
wi thout
extremely
careful
statistical
evaluation.
A measure
of elasticity
obtained
between
the GNP
and the
school
expenditure,
may
be
interpreted
as
a
measure
of
the
national
effort toward education
(the investment aspect of education) but it can
also
be
seen
as
a measure
of
the
demand
for
education
(a
consumption
aspect) 'which
may
not
leael
to
any
economic
growth,
especially
when
education
is
viewed
as
"a
conspicuous
consumption".
It
is
not,
therefore, clear what meaning should be attributed to the elasticity
- 134 -

---

coefficient
computed,
especially
when
we
want
to
relate
it
to
the
"effort of a country."
___A!amo~e tri,:,-iill_~e:,~l,--_thesig~
of th_eelas!icitY'llaL mi_sle_ad the
analyst.
Between
1970
and
1975,
after
the
first
"oil
shocks",
many
underdeveloped
countries
registered
a
decrease
in
their
GNP.
Simultaneously
they
had
to
increase
their
investment
in
education
in
order to
face an ever
increasing
social
demand for education.
On the
annual accounts of the computation of elasticities such a decrease leads
to affecting
a negative
sign
to the
coefficients
of elasticity.
This
sign
may
wrongly
be
interpreted
as
a
decrease
in
effort
toward
education,
or
a
decrease
in
demand
for
education,
when
in
fact
the
opposite is true because coefficients have increased in absolute value.
The statistics we present in Table 5.7 and the behavior of Fig. 5.2
give us a more thorough idea of the evolution of the GDP, the resources
of
the
national
budget
and
the
~'inistry of Education's budget.
All
these variables are related to the university's bUdget.
Figure 5.2 for
instance illustrates the evolution of these aggregates in absolute terms
over the 11 year period of our observation.
In this figure it appears
that
except
for
the university
budget,
the
three
remaining
variables
have been increasing steadi ly over time.
The
rates of increase in the
variables,
however,
differ
in
magnitude,
as
seen
in
Table
5.7.
The
national
budget
registers
the most
rapid
average annual
rate
increase
(24.4%).
The
lowest
average
annual
increase
is
seen
in the
university
budget
(11.4%).
The GDP and the number of students have had an annual
average rate of increase of 17.26% and
14.63% respectively.
One should
bear
in
mind
though
that
the
bUdget
we
are
examining
here
is
the
operating
budget of the university and does not inclllde the investments
- 135 -

---

TABLE 5.7
ABSOLUTE MID HlLATIV[ INCREASE IN NATIONAL A:JD SCHOOL ECOIIOHIC AGGREGATES
FR0!1 19n to 1931 IN CFA FRAt/CS (CURIIENT)
S ta nda rd
!~_.__ ~__--+~l_. __--+__ ~_
mL
J2n
1973
! 271 ~~"l'1l5 ._~) 27~"L27L_.__L2Z!1. "_~EL._"l 980
1981
Mean
Devj~Jion
I.
GDP
(100 HI
440
471
565
738
834
1,113
1,539
I ,783
1,944
1,154
1,187
1,160
101. 79
2.
tlatiOflal Budget
(100 fl I
106
107
114
152
187
119
449
518
531
651
756
345.54
140.61
3.
National Education
Operatlng Budget
14.9
16.8
9.66"
13.17
15.11
16.99
18.83
14.06
30.63
39.40
46.15
11.41
11. 77
(100 HI
4.
University Operating
Budgetin9 (1001<)
0.469
U.536
0.66
0.746
0.890
0.989
1.050
I. 088
1.157
I. 593
I. 348
0.961
0.35
5.
Ivory Coast
Population
5.16
5.96
6.1U
6.46
6.71
7.01
7.16
7.56
7.78
8.18
8.51
6.99
0.99
(mi 11 ion)
6.
Urlivet'sity Student
~
w
Population
3.09
3. 3I
4.17
4.73
5.36
6.07
7.21
8.34
9.83
10.77
11. 97
6.80
3.59
en
(Thousand)
7.
Ratio GDP /IVOt'y Coast
Population
83.65
79.19
91.11
114.14
114.10
158.54
111.98
135.84
149.87
163.31
168.41
11'6.38
154.45
8.
Ral-io Urllversity Budget
Urliver'sity Student
151
161
145
157
166
151
145
130
117
148
111
145.90
16.84
9.
~atio University Budget
:~atior\\al Budget x 100
3. 15
3. 19
6.17
5.61
4.75
4. 51
1.33
1.10
3.16
1.45
I. 78
3.50
I. 53
10. Pel'centage increase
in GOP (fl'OIll past year)
6.01
7.17
19.70
30.61
13.0
33.4
38.2
15.8
9.00
10.8
6. I
1'7 . 16
I
11. Percentage increase
in National Blldget
.91
0.94
15.89
11.58
13.0
17.
105.0
15.3
1.7
21.3
16.1
14.4
17.39
( f ,'om pa s t yea r)
12. Percerltage increase
...
in university Budget
N.A.
14.19
13.06
13.10
19.30
11.11
10.6
10.36
15.53
11.n
-15.65
1;1 .44
103.9
(from past year)
l3.
Percentage increase in
student population
14.44
7.11
15.9
13.43
13.31
13.33
19. 17
15.67
17.36
9.56
11.14
14.63
5.08
GDP figures indicated here correspond to the French term "Produit Interieur
Brut
(PIB)
which may sllghtly differ from the computation of GNP in
so far as the net transaction with rest of world is not included in PIB.
GOP mav be a closer term.
..
.
The decline in the budget is due to the fact that the Ministry of Education has been divided into J ministries after 1972: the Ministry of Education,
* .. the Ministry of Primary School Education, the Ministry of Culture.
not available

---

,n
EV0lU1WN 0F AGGREGATES
<
o
c
-',
Cl
lJl
--
-
-
-1
=-
--'
-'
~ 2' t
l
G)
:'~
,
c
t7
!
L I
I
~~[
\\
\\
-,
z r,~·
-j
>
~
-l
~!\\
er;
~ \\
\\
6'~~
f7,
~
,
'\\
-
-n
w - n
""
~
n
. ,
.
"
,
-,
fTl
I
~
ro
0
c -
~
'"l:-> ~~"'\\
--J
-,
CD '-
ti \\
-i
c
IJ.,\\
g I
\\
""
"1
;.~~~ 'I
~
-j,
-,
ca,c
\\
l
-,
~ t ~
\\
J
r0
'\\ ~
rn_Cl \\
\\
J
, ,
§ ~ L-~
\\
'
t1
<
j
Cl 0
~
L
,
lJ
J
(Q ~.
~,
cc
f'\\.J
- 137 -

---

in facilities,
or the contribution of
the National
Budget to the CNOU,
or the salary of teachers and staff members.
When we include all
these
_ o!_~e!,_e!~endityr~s, as we do in the analys_is of th~_i!.nive..r~Jty'_s_costs
in
the
next
chapter,
we
observe
a
degree
of
increase
in
university
expenditure similar to other national
aggregates.
The relatively
low increase in the university's
recurrent
resource
allocation
may
indicate
that
the
social
pressure
to
invest
in
the
university does not come from the need for investments expressed by the
university
administration,
but
rather
from
the
potential
political
danger
involved
in
not
yielding
to
the
material
demands
of
the
students.
We
shall
return
to
the
role
of
students
in
resource
allocation
to
higher
education
in
the
section
on
private
costs
of
educat i on.
If we isolate demo(jraphic variables
in the allocation
of resources
at the university we see in lines 7 and 8 of Table 5.7 that the increase
over
time
is
less
drastic.
Line
8 also
shows
that
the
ratio
of
the
university budget to the number of students has been steadily decreasing
since
1975.
An
even
more
rapid
decrease
is
shown
in
line
g for
the
percentage of
university
budget taken up
by
the
university's
recurrent
budget.
The
decrease
observed
in
the
two
variables
of
line
8 and
g
contrasts
with
the
increase
seen
ln
ratio
of
GDP
over
the
total
population of
Ivory Coast
(line
7): the per capita GDP of the country.
This
last
ratio
has
been
increasing
during
the
period
of
our
observation,
indicating
a
healthy
economic
growth.
The
decrease
observed in both the university expenditure per student, and also in the
university's
share
of
the
national
education
budget,
which
occurred
while an
increase
in
per-
capita
GDP
was
registered,
indicate that the
- 138 -

---

•
allocation
of
resource
to
the
university
is
independent of
the
relative economic condition of the country.
This observation has also
been verified world wide (see Eicher and Ori~el, 1979)
2.
The Oeterminants of Budget Allocation to the National
University
The
evolution
in
budget
allocation
is
better
illustrated
by
Fig.
5.2 and Fig.
5.3
The most drastic change in the
rate of increase
of the four
variables in Fig. 5.2 occurs after 1977 when the coffee and
cocoa boom occurred and raised the resources of the country.
The GDP is
the
variable which
registered
the most
important
variation
in
rate
of
increase
(the
elasticity
over
time).
Again,
Fig.
5.2, shows
that
the
university's budget has
remained almost stationary in rate of variation
and registered a decline in 1981.
In
Fig.
5.3 we
present
the
evolution
in
variation
of the
annual
rate for the GDP, the national
budget, the university budget.
Although
the
four
rates
have
fluctuated
over
the
II
year
period,
a
general
stationary trend in rates of change appears.
Of all
the variables, the
National
Budget
has
registered
the
most
impressive
change
in
directions.
The budget
has
generally been stable
in
the past,
hOvlever
in the last two years its decreases have changed that trend.
Figure
5.4
in
turn
gives
another
insight
into
the
relationships
between the various aggregates of Table 5-7.
It shows the evolution of
university and
national
budgets when the demographic aspects
have been
accounted for.
The university budget-number of students ratio has been
declining steadily since 1976,
the year when
it crossed the rise in CD;:>
per
capita
that
had
started
in
the
sixties.
Otherwise,
the
ratio
- 139 -

---

EV0l YEAR iNCREASE- GDP,NAT,UNJV BUOG,STUD Pelf'
"r-'1"
r--l--'I--,--r--l-'l-"r
r- "r--r---,TT7 r ·-r\\-.-I--,.---r-r----r- I--r 1"'-
f; i\\'-
LU
U)
""LJJ
CL:
~ I I -
U
z
~
I-J-t
;1/\\
A
\\
I
0
.0-
r-I
~
<r:
\\-
2Cl.·-
Z
w
u
er
w
0-
r- I--:l.~. 2
D
'-.---<-
------L-...1.-.L.-1
l
Lt
L,
!
I
!
I
t
I
l
I
!
!
I
!
!
LL_L.DJ----L
1'~i'1)
\\972
197~
\\976
1978
1(.180
1<::\\82
H~DI).2·NA T BUOG.J=UNIV 8UOG.~·STUO P0P
Fi~ure 5.:'

---

EV0LuTI(JN OF RATI0S
=
- ' ,
:= - I
: ,
~
:r
'- -
~
\\
=: -,-' :.
r
'.
-
,-.
'-...I,
II ; ....' ':-
-.
c
(.)
-,
]
-',
\\ ,
J,
\\
\\
~.
~\\
- l~l-

---

Between the University Budget and the number of students enrol led at the university
has remained constant, with only a si ight deel ine registered after 1980. In fact,
the justification given in the official bUdget document (B.G.F., 1981) for the
decrea~e in university budget, suggests that the increase in students entering the
National University wi I I be halted.
In the .prev.ious paragraph ·we measured ·in absolute terms the effort made toward
un i vers ity educat ion. What. relationship does this effort bear on the 'other
socio-financial variables computed in Table 5.7 ?~e assess the relation-
srrrprbytesting the ~imultaneous effect of factors which affect the ratio
of unive~sity budget to national budget once demography is accounted. for.
The dependent variable E thus constructed tests the process of allocating
the university budget.
E
IJI 51 NI P
t
t
t t
Where E = dependant variable
U = university budget
t
St= number of students
N = National Budget
t
P = Total
Ivorian Population
t
A standard regression analysis was run with the deper.denrt var.iable E',and
three of the variables in Table 5.7 which appeared statistically significant. The
results of the regression analysis are reported in Tabie 5.8.
Obviously, non financial factors as wel I as factors which are not quantifiable
should be introduced in this anal.ysis. However, the I imits imposed by our data compel
us to look only at the three factors reported in Table 5.8 : the ratio of the university
budget to the number of students, the rate of increase in national budget, and the
rate of increase in the number of students. The resu Its of the regress ion run i nd icates
that the ratio of university bUdget to the number of students is the most influential
factor on the effort to finance the university. This factor and other independent
variables are however correlated to each other and therefore may present a problem of
coil inearity. The tests we ran to check for this statistical problem were not conclusive.
The size of our sample (10) may have prevented us from investigating further the
statistical significance of the variable. However, considering that our purpose is
only to suggest
142

---

TABLE 5.8
REGRESSION ANALYSIS OF THE EFFORT MADE FOR UNIVERSITY
_
- - - - - - -
. . .__ .
-
OPERATING BUDGET ON 3 INDEPENDENT VARIABLES
Variables
*
Reqression I
*
Regression 11
s**
t
s**
t
Ratio university budget
***
number of students
0.88
4.1
0.76
3.04
Rate of increase in
National Budget
-0.32
1. 50
-0.44
2.16
Rate of increase in the
number of students
0.20
1. 04
0.35
1. 61
2
R
0.70
0.83
N
10
10
*The dependant variable in regresslon I defines the University Budget
allocation as measured in the text.
The dependent variable in
regression 11 is measured by substituting the National Budget with the GDP.
**S = standardized coefficients
***All coefficients are statistically significant at 0.05.
-
143 -

---

elements
that
may
affect
the
allocation
of
the
university
budget
we
think the relationship found here is significant.
The ~ati? of u~iversity budget
to the number of
studfnt.s
is the
most
influential
factor
of
the
two measures
of
the
budget
allocation
(~=0.88 and
6=0.76).
The rate of increase in the national bUdget has
the
second
most
influential
factor
on
the
effort.
However,
this
variable
is
negatively
related
to
the
dependent
variable.
In
other
words,
when
the
National
Budget
registers
an
increase,
the
proportion
which
goes to the university will
decrease,
a
result also verified by
Fig.
5.3.
The
rate
of
increase
in
the number
of
students
is another
significant factor. It was, however, barely statistically significant at
0.05.
The commentary made on the
regression analysis with the dependant
variable
El
also
applies
to
the
dependent
variable
E2 .
However,
coefficients
in
regression
11
are
higher
in magnitude,
except
for
the
first
variable
(the
ratio
between
university
budget
and
number
of
students).
Both regressions have a predictive power above 78%
2
2
(RI = 0.78, R
0.87).
2
3.
Evolution in Resources Allocation by Schools
Table
5.q
indicates
variables
used
in
assessing
inequalities
in the allocation of resources for the five major schools
of the university
from
the academic year
1975-76 to the academic year
1980-81.
Although we do not want to return to the issues of repetition
and
Ivorianization extensively covered
in the first
part of this work,
we do indicate the promotions and Ivorianization rates for each school,
in order
to stress
their
importance
in
the allocation of resources
in
144

---

TABLE 5.9
SOME INDICATORS OF RESOURCE ALLOCATIONS BY SCHOOL
(YEARS 1975-76 to 1980-81)
ACADEMIC YEAR 1975-76
Teachers
Books
School Expend; ture
IIJor;zation
Promotion
5choo 15
Students
Students
Students
State of Teachers
Ra te of
(:)
ivorian Students
(in FCF41
(:)
Law
0.0274
4 -
.0
20,219
40.00
39.64
Economics
0.03\\
4.15
29,87\\
32.00
6\\.6\\
Letters
0.0\\2
3.3\\
20.86\\
50.00
56.79
Sciences
Pharmacy
0.150
6.06
1\\5,810
39.00
\\0.42
Medicine
105
0.159
12. 11
272.373
60.00
58.75
ACADEMIC YEAR 1977-78
Law
0.0340
,'ItA
28, \\98
\\0.00
S7 . 95
Economics
0.028
,'ItA
31,000
18.00
Si. 74
Letters
0.0420
.~t A
47,256
\\\\.00
48.48
Sciences ... Pharmacy
O. 1074
,'ItA
129.116
44.00
\\2.16
l'1ed i (i ne
105
0.1694
B.59
249,169
55.00
72.31
ACADEMIC '(EAR 1978-79
Law
0.0366
,'ItA
28.430
40.50
J. 7 .14
Economics
0.4\\7
8.24
37, \\80
21. 28
77 .50
Letters
0.0410
J. i i
44,500
\\1.3\\
45 04
Sciences
Pharmacy
0.11 D
,'l/A
1\\2.020
<12.90
53 .60
Mediclne
105
0.778
9.77
284,571
56.35
78. 39
_~DACEr1IC YEAR 1979-30
Law
0.028\\
3.33
23,399
4\\.71
<11.56
Economics
0.0408
5.275
27 ,394
28.35
58 03
Le tter-s
O. 041
].23
'3,78\\
53 .00
J].40
Se iences
Pharmacy
0 098
:10
172,334
45 21
51 . <l 0
,"ledicine
105
0 235
12.34
<l1'L61 9
66. 24
32.30
,\\CAQ_EJ1IC ·(E.~R 1980-031
Law
0.OJ45
l
2
18,3\\2
\\5 56
19.10
Economlcs
0.0398
l .6
i8,3\\2
35.90
75.37
Letters
0.0399
3 .3
67,222
56.06
'3.37
Sciences
Pharmacy
0.09J8
..~
387,819
c18.73
4) .35
,"1edicine -
!OS
0.14J5
.;;
619,644
70.00
31.13
~Iote
in this column we only lncluaed tne :-<:,current costs of the 5cnools as given by the
unlversity statlstics.
~ 145 -

---

the
schools.
The
low
rate
of
Ivorianization
as
we
show
in the next
chapter
affects tremendously the cost of educati on in each
school.
An expatriate teacher
of the
same qual i fication
and the same
years
of experience costs 1.99 times the salary of an Ivorian teacher.
As we mentioned earlier,. the high repetition rate of students requires a
corresponding amount of resources per year spent in the cycle until the
students graduate.
Table
5.~ and Fig. 5.0 reveal inequalities in allocation of
resources in the different schools of the university.
The per-student
allocation
of
resources
for
expenditure
including
those
expenditure
incurred
by
the
institutes
and
research
centers
associated
with
the
schools,
is
unequal,
even
in
schools
having
the
same
requirements
in
overhead expenditure.
Thus, the expenditure per student
(see Fig. 5.5)
in the School
of ~~edicine is the highest for all
the school s,
but also
higher
than
the
School
of
Science
(which
includes
the
School
of
Pharmacy)
which
may
have
the
same
requirements
in
teaching
material.
The high per student expenditure of medicine is largely brought about by
the
fact
that
we could
not
separate
graduates
from
under-graduates
in
resource
allocation.
The
number
of
Ivorian
graduate
students
do
not
exceed 1% in four of the five schools.
In medical
school
the percentage
of
graduates
in the department
is
5.3%,
a percentage still
too 10,.1 to
significantly
affect
the overall
picture of resources allocation.
The
School
of
Law
is
the
most
inexpensive
school
per
student
expenditure.
On
the
average
it
spends
180%
less
resources
than
the
School
of Medicine.
Among the non
"scientific" schools
(Law,
Letters,
Economics)
the
School
of
Letters
received,
on
the
average,
more
financial
resources than the other schools for the 1975-81 time period.
146 -

---

EXPEN[;]TU~=:
Pt:R STUDENT
IV
-
::J)
r'l
0
0
0
X
0
0
:J
"
0
0
:J
V
-">1
I
I
11 fTl
- ,
,
"
Z
r
::>-
0
:c
~
ilJ
---I
"
r
C
m
::::D
~
...,
,cn
m '-.I
I
Ul
l (J)
w
---I
"
C
m
rJ
0
...,
tSJ
[T1
Z
,-'"
c
.t>.
""
,
'"
1 Z---I
Ul
en
r J "
::;0
en
r~
:>-
---I
~
(Sl
CO
-<
(j)
n
l :c(Sl
11
(Sl
I
- 147 -

---

The teacher-student
ratio is another variable which is of interest
when examining the allocation of resources in the school.
We choose to
compute
here
the
ratio
of
teachers
to students,
instead
of
the
more
familiar
index student-teacher ratio.
This
helps
us to better
grasp
the problem of lack of teachers
(and
not the proxy for class room size
given
by the
ratio of students-teacher) and their
relation with school
output variables such as the repetition
rate.
Only in medicine one can
find
on average one teacher per hundred students.
The lowest teachers
student ratio (0.028) is found in Economics (see Fig. 5.6).
Again medicine has more books per student
(10 on average) than any
other
school,
a number which
is
very
low even
by
the standard of many
underdeveloped
countries.
Ironically
the
School
of
Letters,
which
requires
more
reading,
has
the
lowest
number
of
books
per student
for
the period covered (3 books on the average).
We
conclude
this
chapter
on
the
financing
of
the
National
University with
the
following
points
raised
in
the analysis.
(1) The
number
of
administrative
organs
which
intervene
in
the
process
of
allocation
of
resources
in
the
schools
leads
to
a
complex
rule
of
decision making.
A better control over the resources allocated
"to the schools
can
be
exercised
thus saving more by investing more power in the
hands
of
the
university
budget
office.
(2)
Since
France
started
its
progressive
withdrawal
from
financing
the
recurrent
budget,
the
university
has
made
an
effort
to
dlversify
its
source
of
funding,
especially by calling upon local agencies.
But, this effort needs to be
expanded
in
these
times
of
university
budget
cuts.
(3)
Finally,
1n
examining
the
evolution
of
over
time
resource
allocation
at
the
university we see that a genuine effort has been made by the country in
- 14~ -

---

---

favor
of
university
finance.
However,
this
effort
has
been
slowly declining not
only
in absolute
terms,
but
also with respect to
the
evolution
of the GNP or the total
budget of country.
In the next
chapter, we shall see more clearly the actual
cost of the university to
the country.
- 150

---

CHAPTER VI
A COST ANALYSIS OF THE NATIONAL UNIVERSITY
More
than
any
other
aspect
of
research
in
the
economics
of
education, the cost of the Ivory Coast's education system
has received
the attention of educational
analysts.
The cost of the university has
been evaluated recently by nearly half a dozen studies.
Unfortunately
many
of
these
studies
have
focused
either
on accounting
expenditure
alone (Pierre, 'I., 1979),
0<'
have looked at only one of the sources
of
finance
(Chau,
1974),ofhave
examined
the
expenditures
in
only
one
component of the costs, such as the cost of the CNOU (Cublier, 1969) or
have
addressed
only
one
level
of
expenditure,
such
as
the
public
expenditure
(Hallak and Poignant
(l966)).
None of the studies we are
aware of,
except
(Monson
1975) has
looked at the private cost of the
uni versity and
therefore
none have exami ned an
important compollent of
the
opportunity
cost
of
attending
the
university:
the
foregone
earning.
Another common trait of these studies is that each followed a
different approach in the itemization of costs.
They neglected, or did
not make explicit (except Monson, 1975), the treatment of time in their
study.
Thus,
the costs were
not
annualized when necessary.
However;
1ike us) many of these researchers had to face one major handicap:
the
secrecy
of
documents
related
to
actual
expenditure
incurred
in
the
schools, especially at the level of the CNOU.
,le could not, at the end
of 8 months of field research, get an appointment with the then director
of CNOU.
Neither could we obtain any document related to the allocation
of the subs i di es recei ved from the government.
We sha 11 be compe 11 ed to
rely
mainly
on
budget
data.
They
often
underestimate
the
real
- 151 -

---

expenditure since budgets are most of the time hastily used up at the
end
of
the
financial
year
for
reasons
we
analyzed
in
the
previous
chapter.
Additional funds apportioned may not be apparent on~ the budget
document.
In
this
chapter we
shall
try
to avoid the pitfalls of previous
studies by clearly indicating the cost methodology we shall follow.
We
shall
examine both the public and the private cost of the university.
For the public cost we shall differentiate between the total public cost
of
the
university
and
the
cost
of
training
one
student
by
school
attended.
For the private costs we shall
look into the costs supported
by the students and thei r fami ly.
A.
Cost Methodology
The
introduction
of
educational
reforms
and
the
use
of
new
instructional
technology
or
new
education
methodology
have
forced
economists
and decision makers
to examine more closely
the
issues
of
cost
analysis.
Jamison
et
al.
(1976),
Carnoy and Levin
(1975),
and
Levin
(1978)
have
provided
important
theoretical
work
in
this
area.
Some of their ideas relevant to our study are outlined in the following.
Contemporary economists adopt the "ingredient method" in estimating
the
cost
of
a
project.
They
assume
(to
the
di smay
of
many
non-
economists, especially of the Third World), that a social cost should be
attached
to any
resource
used
in a project,
even when money
has
not
actually been spent.
Hence time given by villagers to build a school,
and the 1and they donated on whi ch to bu i 1d it, shoul d be counted in a
cost estimate of the school.
These factors should be worth thei r market
value.
- 152 -

---

Once the different costs of a project are listed, it is useful to
organize them in a mathematical
function.
It is then easy to estimate
the "cost elements which may-be "used for -decision-mak"ing:-
Total
(TC),
Average
(AC),
Marginal
Cost
(MC).
The
actual
costs
functi ons
are
derived as follows;
Total cost ~ TC
TC (N)
where TC is the total
cost incurred to provide instruction to N number
of students,
Te( N)
Average Cost ~ AC(N)
N
where
AC
is
the
average
cost,
i.e.,
the
cost
of
the
system to
one
student.
It
is computed by dividing the total
cost by the number of
students.
Therefore
the
average
cost
also depends
on the
number of
students involved.
The more students covered by the system, the lower
the average cost
6TC(N)
Marginal Cost
MC(N)
6N
The margi nal
cost i ndi cates the cost of addi ng one more student to the
system.
The marginal
cost is computed by taking the derivative of the
total cost function.
The
ingredients
which
enter
into
the
costs
estimate
are
often
separated into fixed cost, variable cost, recurrent cost.
Hence a total
cost function may be decomposed as:
- 153 -

---

TC(N)
FC + VN
where TC has its previous meaning, and V(N) the variable cost per unit
and FC,
the fixed cost.
The variable cost is the cost element which
changes with the number N of students involved.
Example, the cost of
providing instructioonal
books vary with the number of stuoents.
The
fixed
cost
on
the
other
hand
does
not
change
with
the
number
of
students. Thus the cost of bui lding a classroom is not affected whether
the classroom contains 10 students or 30 students.
The
appreciation
of a cost
item such
as
the cost
of
a building
introduces
another
concept
in
the
cost
analysis,
the
treatment
of
time.
A building constructed today may last twenty years, therefore it
is not correct to make the student of today support all the cost of an
item which will
be used by
future
generations.
Economists
therefore
"depreciate" the cost of the building over its life-time, using a social
discount
rate. 1
Cost
elements
which
are
depreciated
over
a certain
length of time are termed "capital cost" as opposed to "recurrent cost"
which
appl ies
to
items
that
are
used
up
within
the
accounting
time
considered (often one year).
The cost concepts briefly outlined above
will be appl ied to studying the cost of the National University.
B.
The Public Cost of Instruction at the National University
He
used
the
term
"public
cost"
to
signify
the
cost
of
the
university to Ivorian citizens as a whole, whether they
have children
enrolled at the university or not.
The instruction cost refers to all
expenditure
related
to
providing
education
for
the
students.
The
different components of the costs of instruction at the university are
- 154 -

---

indicated
in Table 6-1.
We separate the costs
by school
to show the
magnitude
of
the
cost
differential
within
the
schools
of
the
un i ve rs i ty •
The main
cost
ingredients
used
are also outl ined in the
same table.
1.
Salaries
This element of the cost was difficult to estimate because we
did
not have the actual
figures
on the salary paid to each and every
teacher at the university in 1980-81.
Neither could we determine the
over-time hours for which the teacher may be paid either by his school
or by another school.
From the salary we could not detect the taxable
components which vary with the marital status, or the number of children
the teacher has.
It was also impossible to evaluate the fringe benefits
some teachers get in their jobs.
Our own experience suggests that this
benefit, though substantial for other civil servants in the Ivory Coast,
is rather negligible for teachers.
The estimates of salaries were based on the teacher salary scale
provided by the "Bareme."
The "Bareme"
(1979) indicates salary levels
according
to
professional
ranking
and
by
job
classification.
The
classification
corresponds
approximately
to
the
years
of
experience
since
almost
all
teachers
are
promoted
every
two
years
into
a
new
classification.
The more stringent professional
ranking is determined
by the university according to diplomas and experience.
The statistics
provided for us by the university gave the ranking of teachers. We used
an average 5 years of experience for all teachers.
The slow increase in
Ivorianization rate by school
and by year in Table 5-11 for the 6 year
period indicate that on the average the turnover rate and the absolute
- 155 -

---

change
in
number
of
teachers
may
be
approximated
at
5 years.
This
figure
is
also
confi rmed
by
our
own
observation
that
many
Ivorian
teachers have entered the -university only within the last 5 years.
In Table 6-1, we separate expatriate teachers from the local
ones
because they
are paid differently,
even with comparable experience and
the
same
job qualification.
Foreigners
may
also
receive their
salary
from
their
own
country;
this
is
especially
true
for
French
teachers.
The
French
teachers
may
be
hired
within
one
of
the
three
types
of
contract:
(l)
they
are
directly
recruited
in
France
by
the
French
government
and
receive a
salary
according
to the
scale
applicable
in
France.
(2)
They
may
be
hired within
the
"Globalization
Agreements"
which state that the French government may provide the Ivory Coast with
French teachers.
However,
only a certain quota of teachers,
negotiated
every year,
is
paid
by
the French government.
The
remaining quota
in
the
"Globalization
Agreements"
is
paid
directly
by
the
Ivory
Coast
government.
Their salary is not only higher
(about twice as much) than
local teachers,
but also "at least twice,
if not three times that which
he
would
have
earned
in
France"
(Monson,
1.
1975,
p.6).
The
precise
legislation governing foreign teachers states that they not only receive
1.5 the salary paid to an Ivorian teacher of similar qualification, but
in addition they are awarded non taxable fringe
benefits equivalent to
1.33 times
their
gross! salary.
An
expatri ate teacher
costs
therefore
1.995 more than an Ivorian.
The university could save about 100 percent
on teachers salary, if expatriates were to be replaced by Ivorians.
A
The staff member salaries were taken from the
"Bareme"
applicable
to non teachers, civil
servants, and foreigners salary were appreciated
by the 1. 995 factor.

---

TAlllf 6- I
THE
COST Ot HISfRUCT1011 AT THE 1I.A.T10llI\\L Utll\\'ERSlTY, BY S(f:()OL III 1980-81
(IU eFA FRAUCS. 10nol
I terlls
tJ\\'1
Lettc\\'S
EC\\,.\\l1omi:s
--_.-._-.. _._----.-_.-. . --_._---- _ . _ - - - - - - - ----,._,
._-~-,-----.. _ - - - - - - - - - - _ . _ - - - - - - - - - -
I , Sa 1a'" i es
-flat ional fa(ul t)'
\\6.1'4.90
'109,62'1,30
1l1,59586
-Expatriate Faculc)'
!1L\\ ,BJ(j. 77
~5G,Q93 48
417,2710
-Nat ional Sta ff
12,116.:' I
1l,187.30
4. 84.10
-Expall'late Staff
453.56
1,965.35
1 I. ID
SUD .. lotal- \\
314.3-15.03
779,7704J
534,358.34
2. Hl)us i 119 Cos t
-Nilt)onill
faculty
l11l .000.00
\\7) ,600.00
67,200.00
-[>-pdtl'iate Faeul ty
. 36 ~400 ,QO
.U2.J~O_ on
._!l0 ,000 ~~
~].9..~~l.=.L.
194,401 on
"316,80 i) on
187.1On.OO
3. AiJ\\llll1 \\S Vd t i Vl: Cos LS
~Ullivel'Sl ty
113.\\81.30
199.00352
Ill,214.7J
-Se/lools-lnstitute
46.750.00
19/,500.00
108.215.00
-OU\\€r
;I,dlllinist. Costs
_5.10 7.40
5,763.3
3,780.00
~
u- Sub lota~-3
105.141. 70
398.167.91
123,19973
'-.J - - - - - -
4.
Sub-Total
It2t)
713.086. n
1,494 .B38. 3
844,758.07
5.I\\II"Onizatiol1 Cost
o·
7 :
10:
15':
%_ .
.~~%.._~~.....2n~
2IJ~
---'0,;. ..
..2'':...-_..-.JI.'%
. 15%
_(01l5t.(0'.'('I'
20.1'1"5)
9.115.5
18.370.5
11,354.7
31,099.7
12,626.8
13,863.3
\\6.596 5
12,580
29,6811.1
40.398.5
7.066
13,340 :I
-Eqlllo(o'.'e l' 6.1'rs}
I .446.5
1.812 .5
1,99b
L,285.~
929.S
2,3~7.~
1.593.0
2,9GB U
] ,052 6
I , 32 <1 • 5
1,449
1,668
-SuP'tJ\\y({o'.'er 3.1'1'5)
13,635,3
27,020.6
78.515
30,955
30,701.8
35,099.7
37,053.8
40,J6n 4
17,166 6
19,618 8
20./08.7
21 .554
-Oi.'ecl fIE Equip
llB.5
I 50.43
16 4 .9
193 06
154.07
115 4
21~ 26
14801
'361
109 1
119 7
138 6
(6y,·, )
SUb-lota~5_
:\\4,926.4
4/,364.03
53.540.6
64.340.1
44,413.1
61.515.9
69,5491
83.9757
1S,371J
J4~.401.8
38.873.9
46,940.6
6,Toto.1 Inst. :ost
748.8]3.14
761.7S0.76 767.419.3778,116.71.539.151.4 \\,556.364.1 1.564,]78 51,578,814.
870,11937
879,160.8
- " - -
.~'-'-._.-..~._ _... 0 _ .,~,-""
-=~~.--'- ............... -. - ..... >-.,"'->-=_ ......... '"'~"'.~.-.....:..=- "-= _~"-.. '"-
"'-_ .. ~ •.• ~..:
1.Total No. of
,.
0
_ _
" _
,
..~. _ _
•
_.,.,,~ '-'_~._.. "-~ ... '--'- .... ~"'-_ ..... ~ ':;'--=-,.-,-~,~"","=<==<=
~8M2.L.9L ~4Li1.9§•.§_.
1.98J
Students
J , ?58
1, lOO
I.LAvg. Cost per
StLdent
2%.761
397.774
402,265
('ncluding :.:'
9·/\\'0'9·
co~t per
S tudel1 t
263. l3
414. j 4
41B.64
(including Sf

---

rABI.r G-l (ContiJ1lled)
Illstitutions
J U:Il1S
Sc i ence + Phd '·llIilCy
~"edicine t
lOS
----_., ------
__.-- ---,-
---~
- - - ' - ' - ._... _-. __ ._---.
-_.~.
- - - . _. - .- .. -- -_. - . - ... - - .- --
I.Salar-ies
-fJGtional
Faculty
"93.571.52
449.368 6
4[;q.hllr'iale FdCLllLy
HI6 , ]111\\. 7~)
1'1·1:-1,011 hI
-tlaliona\\ Staff
11.330.79
4 ,384 .10
-l:;.,patr'ii1lt; Stdl-f
._~ 1.663 _OL_
.~ ~~.!.,269~!)
Sub-loLal
1.321,722 00
892.97582
- - ~ - -
2. ~~0~f9~~ __
118.400.00
- r~ational
Facu]ty
18~.eOO.eo
_~.OOO.OO
_ [;"jhlu·iate Facu] ty
213.600.00
39B,\\OO~60
3" .400.00
~
Sub-rata]
~ 3. Adn~~~·~.':.I:..._Cos.~_
-UlliVet'slly
101,46 1.. 08
62,274.65
-SdlO01s-1nst 1 tutes
126,~50.00
156.600.00
OLllcr' Administ. CoStS
_ _ _ _
3)4118.80_
61.169.20
Sub-Total
331.359 88
281.1085
11.
Sub-totd]
[12t3
2.051.481 B
488.519.6
5_ A1nonizdlion Cost
O'
7'"
IOY.
15'~
O'b'-..,,-_ _
/'10
~o
151_
Const.
(over 20 YI'S)
1g;-m
37,1766
46,256.4
61.925.2---------T5-~'5i.3
i9.TIT5--36 .000.4
49,382
-Equipt (over 6 yrs)
958
1,207.08
1,322~04
1,5136
588
740.8
811.4
929
-SIIPply (ove.' 3 yl·S)
15.653.
17.8954
18.891.7
20.577~8
9.607.9
In.983.8
11.595.3
12,7437
Oil'eclol- of
H.E.
61.1
67.03
776
4f1.2
llllJlpt(ovel' 3yl·S)
78.5
99.6
109 1
726. ~
~~~:_!0 t ~1:_~
36,362.9
56,17H.GR
66,579.3
1l5,743
15, fi95. 11
aO,91)12
4H,7t'1.4.13
631l2.3
['.
Total Instruction Cost
1, S51 ,651.9
- - - - - - - -
1,003 ,H1l4,
2.lOH,l-l60.t1
t19J)61.12,223,967.B
] ,5] <\\ ,21 ~
1.529.<182.8
1.\\16.993.7
- - -
7.
Totd1 No. of Students
1.916
I .176
B.
Av~\\. Cos t P~I'
S[IJ(JL:nt (excluding 5)
1.0112J2
1.265_7~
9
AvU·
COSl per· Sllldelll
1•300 ~ 58
,ll 7':. (irlcludill~J 5)
I, P)O.65

---

Controversy
arises
in the
literature as
to what
salary
scale
one
needs
to
use
in
a
cost
estimate
when
foreign
aid
enters
into
the
picture:
the
donor
country's
or
the
receiver's?
Following
the
cost
methodology we
outlined
at
the
beginning
of
this
chapter we
chose to
apply
the
salary
which
is
or
would
have
been
supported
by
the
Ivory
Coast
bUdget,
if
the
teachers
were
not
to
receive
their
salary
from
their
home
country.
In other words we are estimating the cost of the
university as if no assistance were received,
for this real
cost of the
university
is the element which should guide pol icy makers.
They must
assume
(and
hope)
that
"the aid"
may
not
continue
forever.
In
this
respect
our
approach
differ
from
many
of
the
studies
we
previously
out 1i ned.
2.
Housing Costs
The
second
ingredients
in
our
cost
estimate
is
the
housing
costs.
Teachers are lodged freely
in government
owned houses or thei r
rent
is
paid directly
by
the Ministry of Housing.
Although there are
regulations
covering
the
number
of
rooms
one
is
entitled to by marital
status,
number of children, and professional
ranking, these regulations
are
rarely
applied.
Expatriates
usually
live
in
a
richer
and
more
expensive neighborhood of the capital city, hut on the average they live
in one bedroom homes since most do not have children.
For these reasons
we assumed that housing one Ivorian teacher cost as much as housing one
expatriate.
We assume the approximate average monthly cost of renting a
home
in Abidjan
is CFA
Francs
200,000. The total cost of housinq"
ay
department
ranges
from a 1fM of CFA Francs 187,2 Mi 11 ions for
the School of Economics to twice that figure for the School of Science.
- 159 -

---

3.
Administrative Cost
Under this heading we regroup the expenses which make up the
operating
budget - -of
the
schools,
institutes
- and
the--- ·central
administration of the university.
We also include the research grants
which are received by the institutes.
This last item should have been
more appropriately allocated partly to the cost of researchers' salaries
(who may not be teachers), partly to some teachers, partly to some staff
members and
partly to the operating cost of the institute.
To avoid
being
arbitrary
in
allocation
of
the
fund,
we chose to
regroup them
under one heading.
The total
cost of this item varies
from a low of
123,199.73 million for the School
of Economics to 398,267 millions for
the School of Letters.
This last school has the heaviest administrative
cost
because
it
has
the
highest
number
of
institutes
and
research
centers.
4.
Amortization Costs
The
cost
of
the
bui ldings
was
depreciated
over
20
years,
equipment
over
6
years
and
supplies
over
3
years,
following
the
guidelines
we
received
from
the
university
budget
office
and
also
following the procedure adopted by Monson (op. cit.)
In the choice of an appropriate discount rate we adopt the wisdom
nO;! common
in
the
literature
by
using
several
rates
for
sensitivity
analysis.
Actually we choose four rates of discount for four different
reasons.
The 0% rate of discount was to allO;! comparison with studies
which may have opted for no depreciation at all.
The 7% rate is the
rate at which the CAA (a government agency in charge of administrating
pub 1i c debt)
bond was
sell i ng
in
1980-81.
Thi s
is
the
rate that we
- 160 -

---

shall
adopt when a comparative discount rate does not appear.
We also
included
a
10% discount
rate
since
this
rate
seems
to
be
the most
. commonly used· for ·projectevaluation in the thi rd world.
Finally, we introduced the 15% rate
(which is sl ightly above the
estimated
rate
of
inflation
in
1981
in
the
Ivory
Coast)
to
allow
compari son to those who thi nk that at 1east the rate of di scount shoul d
be above the rate of i nfl at ion.
In
this
section
on
amortizations
cost
we
encountered
another
problem.
Most buildings of the university were erected in 1965 when the
university
was
opened.
In
fact,
the
buildings
time
table
is
as
follows:
1965:
Library
6 Auditori ums
Buildings for the Schools of Letters
School of Science
School of Medicine
1974-75
The
School
of
Law.
Part
of
the
bui lding
was
IJsed
by
the
School of Economics.
1975/76:
Completion
of the building of the School
of
Law
(still
used
partially by the School of Economics)
1977:
building of the School of Economics.
the COST.·. of construction must be figured with respect to the inflation
rate from year to another.
We could not,
however, obtain the cost of
each
school's
buildings
according
to
the
time
in
which
they
were
- 161 -

---

completed.
We
reluctantly
relied
on
the
best
cost
estimates
of
the
university
buildings
available
until
1975,
Monson's
(op.
cit.)
study.
After
1975; we- added to the Monson
estimates
the remaining element
of
buildin9
costs
available
in
the
budgets.
We
applied
the
relevant
discount
rates
to
his
estimates.
It
is
likely
that
we
missed
some
:2-
elements
of
construction
costs
not
available
in the many
budgets we
exami ned.
Or,
we
may
have
omitted
some
building
costs
paid
by
an
outside donor not mentioned in the Bubgets.
In any case, the estimates
of
construction
costs
in
Table
6-1,
should
be
considered
very
crude
estimates when appreciating the total cost of the system.
We
included
teaching
materials
and
vehicles
in
the
cost
of
equipment.
The supply mainly
refers
to office supplies which are used
more than one year.
We
included the cost
of administration
of the Director
of Higher
Education's administration in the amortization.
That administration was
recently
created
by
the
Minister
of
Education
to
adminster
the
university.
Administration of the
"Ecole Normale Superieur"
(ENS) was
also
added
to
this
director's
duties.
Theoretically,
we
should
have
made that school
share part of the admi ni strat i ve cost,
but we chose to
neglect
this
aspect,
partly
because
we
did
not
have
figures
on
the
number
of
students
enrolled
in
ENS
in
1981,
but
mainly
because
past
statistics show that this group of students constitute approximately one
tenth
of
the
university
population.
The
tenth
of
the
administrative
cost
of the
Director
of
higher education,
'IlOuld
have
been
negligible,
considering the error factor we could introduce in this broad estimates
of costs.
- 162 -

---

In allocating costs
by
schools,
the
following
rule
of thumb was
appl ied:
only
if
an
expenditure
was
clearly
made
by
a
school
or
--institue--did
we
attribute
it
to
them;
. Whenever
confusion-may
have
existed
over
which
school
an
expenditure
should
be
figured
for,
we
proportionally distributed the expenditure to all the departments using
the following formula
Si
where Si is the cost to the i school, Et is the total expenditure, Ni is
the
number
of
students
in
school
i,
and Tt
is
the
tota 1 number
of
students.
5.
The Results
As must be expected, the School of Sciences and the School of
Medicine are the two most expensive schools, not only per student, but
also in absolute terms. The least
expensive was the School of Law.
In
a
first
approach
we
neglected
the
cost
of
amortized
items
because of possible error in thei r estimation.
Here, the total cost of
all
the
schools
including
salaries,
teachers'
housing,
and
administrative
cost
amounts
to
CFA
Francs
6,594
millions
($26.378
mill ion in the 1981 exchange rate of $1 = CFA Francs 250).
One student
cost $2,227 in total cost of instruction "hen the cost of the buildings
are not included.
The cost per student by school
(1 i ne 8) ranged from a maximum of
CFA Francs 1,265.74 for the School of Medicine, to a minimum of 246.763
for
the
School
of
Low.
Of
the
three
social
science
schools
(Law,
- 163 -

---

Letters,
Economics)
the
most
expensive
school
was
the
School
of
Economics.
This school
spent the most on foreign teachers.
The higher
number of students in ~Letters leads to a-lower average-cost per~ student,
although the school is the most expensive in absolute terms of the three
schools.
We
introduced
the
cost
of
amortized
items
and
chose two discount
rates,
0% and
7% to illustrate the error margin one encounters when a
discount rate is not applied.
The margin of error in the estimates is,
for instance, a magnitude of CFA Francs 42,960,400 for the total cost of
instruction in the Law School.
The average total cost in the Law School
increases
by
14%
and
the
medical
school
by
21%
when
the
7
percent
discoun~ rate is considered.
C.
The Total
Publ ic
Cost of Training One
Ivorian Student
by
School
Attended
In this section we examine the total
cost of training an
Ivorian
student during the academic year 1980-81, and the total cost until he or
she graduates.
We introduce elements which enter into the cost of the
student's
education
besides
the
instructional
cost
we
examined
in
Section B.
We also examine the cost to the state of subsidized student
services:
monthly stipend, food, housing and other services provided by
the CNOU.
1.
The Students Scholarship
Most
Ivorian students who attend the university
(83.3% in our
sample)
receive a monthly
stipend
from the
government.
The amount of
the stipend was valued at CFA Francs 2~,OOO from 1965 to 1975, then was
- 164 -

---

raised to 35,000 beginning in 1975.
In 1981, CFA Francs 5,000 more was
added to the amount.
In addition,
students received a lump-sum of CFA
Francs
30,000 at
the
beginning
of each year as
an allowance
for
books
and supplies.
The
scholarship,
which
was
originally
designed
to
help
needy
students,
has
in practice been extended to all
students,
regardless
of
their
social
origin.
The
only
criterion
for
not
awarding
the
scholarship has been the academic
failure.
As we explained in Chapter
4, Section B, all
students are required to accomplish within four years
the 3 first
"forms" of their academic cycle.
Failure to do so leads to
the loss of the scholarship.
Students
in their senior year receive CFA
Francs 55,000 until
graduation, with the exception of Law and Economics
students.
The cost to the state of the student's stipend per year was
CFA Francs 455,000 for students enrolled in one of the first three Forms
of
the
university,
and
CFA
Francs
695,000
for
senior year students of
Medicine, Science and Letters.
Students graduating in Economics and Law
receive CFA Francs 450,000.
Students in Medicine do not graduate after
their 4th year,
but they are not separated in these broad estimations.
However, after their 4th Form, rredical
students are paid about the same
amount of stipend as graduating students of other schools.
Table
6-2
gives
the
total
subsidy
a
student
receives
until
graduation.
Again,
due
to
difference
in
rate
of
repetition
and
in
amount of suhsidy received, the total
amount varies according to school
attended by the student.
Students in Letters and Science obtain around
2.3
millions
in
subsidy
before
graduation,
while
Law
and
Economic
students
receive
1.5
million.
I~edical
school
students
receive
less
because they repeat less in thei r academic cycles.
- 165 -

---

TABLE 6-2
TOTA~ ANNUALIZED COST OF THE SUBSIDt BY STUDENT UNTIL GRADUATION, BY SCHOOL
(in CFA Francs 1,000)
(1)
(2 )
( 3)
(4)
(5)
(6)
(7)
(8)
(9 )
c
Annual
Years Spent
Annu i ty
NpV of
Annual
Di scount
flPV of
Tota I flPV
Subsidy rec'd
to complete b
Factor at
of Subsidy
Subsidy Rec'd
Factor
Subsidy
Subsidy
in each of
First 3 Forms
7%
Rec'd· in
in last Form
Applied
Rec 'd in
Rec'd for
School
a
First 3 Forms
First 3 Forms
to I as t
Last Form
Four Forms
(5H2)x(4)
Form at 7% (8)=(6)x(7) (9)=(5)+(8)
Law
450
4.32:: 4
3.387
1,524.15
450
.713
320.85
1,845
Letters
450
4. 98 ~ 5
4.100
1,845
690
.666
459.54
2,304.54
~
0'>
Economics
4.02 ~ 4
3.387
1,524.15
450
320.85
1,845
0'>
450
.713
Sciences
450
4.56 ~ 5
4.100
1,845
690
.666
459.54
2,304.54
Medicine
450
3. 30 :: 3
2.624
1,180.8
690
.816
563.04
1,743.84
Notes: a - All students receive
CFA Francs 35,000 per month plus 30,000 for books and supplies,
b - The years were computed using the average probability of graduation given by our survey for each
school.
c - Students in their last Form receive CFA Francs 55,000 per month plus the 30,000 lump-sum for
books and eXDenses.
Law and Economics students still receive 35,000 in their last Form.

---

The
fact
that
students
receive
scholarships
according
to
their
academic achievement
and not to their social
background,
has prompted
student unions to bargain for a raise in the stipend.
Their argument
has
been that the scholarship
compensates
for
the
income they
forego
while
attending
the
university
for
the
future
welfare
of
the
whole
nation.
As such, the amount of stipend should approximate the ongoing
public wage
for their maximum degree
level
(BAC).
The real
amount of
scholarship "owed" to them should be reflected in the two monthly income
differential
(142,270 -35,000) = 107,270.
Raising the student's stipend has often been used by the government
as
a political
leverage
on
student
unions.
Indeed,
student
unrest,
which
often
shakeS
the
otherwise
stable
political
climate
of
the
country has been the only noticeable social disturbance.
The government
has
therefore
been
very
sensitive
to
students demands.
The cost
of
renting a student
room has remained, CFA Francs
3,000 ($12) since the
sixties, and a complete meal
still
costs CFA Francs 75.
These prices
were scheduled to change in 1982.
2.
The Cost of Operating the CNOU
The administration of the CNOU has always been a focal
point
of controversy at the university.
The CNOU, which roughly compares to a
students' room and board service in the USA, plays a more extensive role
by also financing transportation and all other social activities of the
students.
The
CNOU,
as
we
mentioned
is
directly
controlled
by
the
r1inistry of Education.
It provides services to other students of higher
education whose schools are built in the vicinity of the Cocody Campus
location
of
the
university.
These
schools
are the
INSET,
the Ecole
- 16)

---

TABLE 6-3
ANNUALIZED COST OF CNOU IN 1981
(In CFA Francs Million)
Items
Cost
Time Period
Amortization
1.
Salary
696.439
o
2.
Administrative Cost
67.704
o
3.
Sub-total (1+2)
764.143
Amortized Items
I) %
n
1O~~
15~~
*
4.
Construction
2,726.570
20
136.32
257.36
320.26
535.6
5.
Equipment
10.593
6
1. 76
2.22
2.43
2.79
6.
Vehicles
29.0(1)
6
4.83
6.08
6.65
7.66
7. Subtota 1 Af;]ortization
142.91
265.66
329.34
546.05
8.
Total Cost(3+7)
907.05
1,029.81) 1,093.48
1,310.9
*
Notes
only construction cost of the year 1980-81 could be found.
- 168 -

---

Normale Superieure, and the Ecole de Statistiques.
These three schools
had about
1,500 students
in 1981.
This
fi9ure should be added to the
total
university
students who benefit
from scholarships when computing
the average cost of a CNOU service to a student.
Table 6-3 gives a non-
annualized cost of the CNOU which amounts to 907.5 million, and 1,029.8
million at 7% annual
rate.
Of the 11,843 university students 16.7% are
not beneficiaries of scholarships according to our survey.
The average
cost at 0% discount
rate to the total
11,365 beneficiaries
(INSET, ENS
and ESA,
included)
is CFA Francs
79,81O.
At 7% the average cost rises
to CFA Francs 90,541.
The cost components given in Table 6-3 obey the
same principles of computation as the one we described in Table 6-1 and
need no further expansion.
The total cost of CNOU provided in the Table
6.3
is an
underestimate
of the actual
cost.
Again the secrecy behind
this
institution
prevented
us
from
researching
our
cost
estimates
further.
3.
The Total Cost of Training One Ivorian Student by School
,le
may
look
at
the
cost
of
training
one
student
with
or
without cost differentiation
by school.
lie not only w.ant to recognize
the
difference
in
instruction
costs
by
school
attended,
but
also
to
account for the fact that the chance of graduating depends on the school
attended.
Two
new
elements
entered
here
in
the
cost
analysis.
The
average length of time it takes to graduate from a school, and the cost
of instruction in the school.
These results appear in Table 6-4.
From the
rough approximation made of time that an average student
takes to complete a degree, assuming the current rate of repetition, we
computed
the
annualized
cost
of
obtaining
the
degree.
The
cost
of
- 169

---

TABLE 6-4
ANNUALIZED COST OF INSTRUCTION FOR GRADUATING A STIJDENT, WHO ENTERS A SCHOOL
IN 1980-81
(in CFA Francs, 1000)
(I)
(2 )
( 3)
(4)
( 5)
(6 )
p:~gSt~~~~ta
Avg. Rateofb
Sp:~i'a~i~~hoOlc
Annui ty Factor
Annualized
School
non Repetition
at 7%
Cost
(6) = (5)x(2)
Law
263.13
.44
5. 76 ~ 6
4.766
1,254.07
,-""0 Economics 418.64
.34
5. 36 ~ 5
4.100
1,716.42
Letters
414.14
.66
6. 64 ~ 7
5.389
2,231.80
Sciences
1,100.65
.52
6. 08 ~ 6
4.766
5,245.69
Medicine
1,300.58
. 19
4. 76 ~ 5
4.100
5,332.37
Notes: a: Cost element extracted from Table 6-1
b:
From our Survey.
C:
Column was computed using a simple approximation of years spent, with the formula
[n ~ (n~f> }.J
where n is the number of years needed to complete the program and
.
h~"
"
p:1S t e~repetltlon rate

---

instruction
by
diploma
varies
from
CFA
Francs
1,254
million
in
Law
School
to 5,332 million in the School
of Medicine.
We considered only
the
first
4 years
of the cycle,
in order to allow for
comparison with
other schools.
The average cost of 4 years of training at the National
University by school
is CFA Francs
2.712 million per student.
Again a
comparison
within
schools
with
similar
overhead
expenditure
is
more
meaningful.
Thus,
the
least
expensive
school
for
instruction
in
the
Social Sciences and Humanities remains the Law School when the School of
Letters
becomes
the
most
expensive
diploma.
This
is
due
to
a
longer
average time spent in the school
{7 years).
In the sciences area, the
School
of Medicine
remains
the most
expensive
both
in school
per year
and cost of degree acquisition •
..
It
should
be
remebered
that
the
cost
of
obtaining
the
degree
is
supported
entirely
by
the
state.
We
computed
in
Table 6.5
the total
cost
to
the
state
of
training
one
student
who
received
a
subsidy
in
addition
to the
free
education.
This
new total
cost
constitutes
the
total
amount
of
education
subsidy
received
from
the
state.
Again,
di fferences
appear
by
school
attended.
Science students
receive more
overall subsidy than in any other school, whereas I~edical School
is the
most costly for instruction to the country.
Law students are the least
expensive
(3.5
million)?>
and
Letters
the
most
expensive
of
the
non
"Science" students
(5.02 million).
fie shall
incorporate these elements
in
the
private
benefits
derived
from
higher
education
in
the
next
chapter.
In the remai nder of thi s chapter, we sha 11 consider
what
it costs students and their families to attend the university.
- 171 -

---

TABLE 6 - 5
TOTAL ANNUALIz..ED PUBLiC COST OF TI<AINlNG ONE SUBSIDIZED STUDENr UNTIL
GRADUATION, BY SD-IOOL - (In CFA Francs 1,000)
(1)
(2)
(3)
(4)
(5)
(6)
Instructional
Annu3lized Operating
Arumali2.ed
Total subsidy
Total annualized
School
Cost per
Cost of
b subsidies received
cost
public cost
studento..
CNOU per Beneficiary
until graduation
'cS) = (3) + (4)
per student
(6) = (2) + (5)
Law
1,254.07
431.85
1,845.00
2,276.85
3,530.92
Economics
1,716.42
371.50
1,845.00
2,216.50
3,932.92
Letters
2,231.80
488.2'1
2,304.54
2,7lJ2.83
5,024.63
Sciences
5,245.69
431 .85
2,304.54
2,736.39
7,892.08
eledicine
5,332.37
"171.50
1,743.84
2,115.34
7,447.71
Notes
a: Annualized average cost of instruction until graduation.
b
The average cost of CNOU ",as annualized to reflect the time spent for receiving
CNOU services by school (from Table 6 - 3).
c : Total cost of a student receiving subsidy by school (fyo~Table 6-2)

---

D.
The Private Cost of Attending the University
1.
Methodology
Up to this section we have analyzed what the university costs
the
state of the
Ivory Coast.
However,
individual
students attending
the uni versity also face a few personal expenditures.
fie shall
refer to
these
costs
as
private
cost
as
opposed
to
the
publ ic
costs
analyzed
earlier.
In
this
section,
we
examine
these
private
costs.
As
in
previous sections of the cost analysis we use the ingredients approach
here.
We define
private costs as those which the individual
or his or
her family must pay because he or she attends the university.
From this
definition of private cost we retain the following elements:
The net income foregone
The cost of books and suppl ies
The cost of room and board
Registration fees
And aid given to members of family.
We
did
not
include the cost
of
transportation
or leisure
in this
1 ist.
Transportation
from the
university
housing
located
outside the
campus is operated by the CNOU free of charge.
Students may sti 11 need
to pay
for a taxi
or a bus if they miss the university bus.
We do not
consider
these
special
cases
since
they
are
probably
insignificant
compared to the annual cost of transportation assumed by CNOU.
Students
may
need
to
pay
for
their o.<n transportation to visit their family or
friends
or
for
their
own
pleasure.
These
cases
are
not
considered
either
since
they
may
be
grouped
with
student
leisure
activities
not
financed by CNOU.
_ 171
-

---

If students were not attending the university they would have to
pay
for
their
own
lesiure
activities.
This
cost
is
not,
therefore,
included
in private costs.
One may
argue that students
have acquired
new
tastes
from
their
new
level
of
education.
This
argument
is
particularly
true
in
thi rd
world
countries
where
the
coexistence
of
modern
and
traditional
society
leads
to
different
patterns
of
expenditure,
not
only
on
consumer
goods
but
also
in
investment
behavior.
Consumer behavior according to the
level
of education would
need
further
investigation
before
we
could
treat
students'
leisure
activities as a special
cost
item
related to education.
Even without
attending
the
university,
a BAC
degree would
open
the door to modern
leisure.
2.
Empirical Estimates
In Table 6-7 we itemize the private costs elements by school
to
allow
comparison
with
other
cost
items
computed
in
previous
sections.
Beforehand, in Table 6-6, we address another cost issue: the
net earnings foregone by the students.
Of all
the economic cost concepts,
the net
income foregone is the
most
easily
understood
and
felt
by
many
Ivorians
of
lower
level
income.
Defined broadly,
the earning foregone
is the income a student
does not receive because he or she enrolls at the university instead of
securing a job with the highest degree he had earned before entering the
university.
For many
students
the
BAC degree would have provided CFA
Francs 1,823,000 per year if the student was working.
Students in the
third world, particularly in the Ivory Coast, feel
stongly the effect of
the
income
foregone
because
of
the
great
necessity
to
support
thei r
- 174 -

---

TABLE 6.6
ANNUALIZED NET INCOME
FOREGONE BY STUDENTS, BY SCHOOL
In 1980-81 (In CFA Francs 1,000)
(1)
(2 )
(3)
( 4)
(5)
(6 )
**
Annual on-
Years Actually
7% Annuity
PV of Income
NPV
*
~Iet 1ncome
Schoo 1
Going Salary
Spent to Complete
Factor
Foregone
Tota 1 Govt.
Foregone
for a BAC Holder
(1) x (3)
Subsidy
(6) = (4) - (5)
- - - -
Law
1,823
5.76 " 6
4.765
8,686.59
2,276.85
6,409.76
- Letters
1,823
6.65 ::: 7
5.389
9,824
2,792.83
7,031.36
-.J
<.n
Economics
1,823
5.03 ::: 5
4.100
7,474.30
2,216.50
5,257.80
Sciences
1,823
6.08 ::: 6
4.765
8,686.59
2,736.39
5,950.20
Medicine
1,823
4. 76 ~ 5
4.100
7,474.30
2,115.34
5,358.96
* Figure from Achio (1979 op. cit.)
** For NPV of Total Govt. subsidy, see table on student annual subsidy discounted. (Table 6.5)

---

family.
University
course
schedules
are organized so that
part time
work is impossible.
If one wants to succeed academically, the choice is
between pursuing one's education and holding a job.
Because uneducated
parents tend to associate level
of degree attained,
(information which
they
hold
since
results
of
national
exams
are
announced
on
national
media)
with
a
certain
social
position,
it
is
difficult
for
them to
understand that the degree is worthless unless you secure a job.
Even
when
this
is
understood
the
difficulties
of
rural
1ife
obl ige
many
parents to rely on the only investment they have made: a child attending
the university.
Many students, in fact, chose to abandon the university
and assist thei r elderly parents.
Therefore,
the income foregone is
often a vivid economic reality for many students, not a vague economic
concept,
as
it
may
appear
to
be
for
many
students
in
developed
countries.
From this gross income foregone, one must deduct the stipend
received by students while in school to obtain a net income foregone.
When
we
started
our
study
in
1980,
there
was
very
little
unemployment of BAC degrees holders.
We therefore did not adjust our
income foregone for unemployment.
At
the
nat i ona 1
1eve l,
the
income
foregone
means
a
loss
in
production of output in a sector of economic activity. The level output
which may have been produced would vary with the ability of the indivi-
dual.
For
simplicity,
we
assumed
here that
all
students would have
provided the same ability.
There may be a slight difference in salary
by type of BAC earned. For example, the BAC G-2, a business oriented BAC
was favored by employers for middle level jobs and was better paid than
a BAC Al (the Greek and Roman literature specialization BAC).
We could
not show this difference again for lack of appropriate data.
- 176 -

---

In our private cost elements we have
introduced four items which
may not be retained by other studies; they are: rent, food, clothing and
aid to family.
In introducing these elements we wanted to account for
two issues, the strong ties between family members and the difference in
use of government subsidies by socio-economic background.
If students
were not attending the university, some of them would have stayed with
their
families
or
"kinsman"
and
would
not
have
incurred
these
expenses.
In fact, our survey indicates clearly those students who live
in student hous i ng and those who chose to 1i ve with a fami ly member and
avoid paying for rent and food.
The second issue we address by including the four cost elements, is
the difference in private cost expenditure between students of different
socio-economic background.
Students receive the same amount of stipend
without
differentiation
ln
family
revenues.
However,
lower
income
revenue
students
must
allocate a sizeable
share
of
their
stipend
in
expenditure such as
helping a younger sibling
in
financing
a private
school.
Thus,
line
7 of Table 6.7
(aid to family)
indicates that a
relatively
high
amount
of
students
resources
are
for
assistance,
a
reality that any policy in higher education should account for.
Table 6.7
gives
a complete
1ist
of
the
different
cost
elements
which I11ilke up the private cost of attending the university.
Like in
many analyses, the net income forgone in Table 6.7 is the most important
cost element
for
students
attending
the National
Univeristy.
On the
average students forego CFA Francs 6 millions before they graduate even
though we have deducted
from it the stipends they have received while
at school.
The income foregone as we indicated earlier, varies from one
school
to another.
This
is
because
students
have
different
earning
- 177 -

---

power dependi ng on thei r school
and al so because of a di fferent average
rate of repetition in the schools.
.Arts
students forego more earning
(7.03
mi 11 ion)
because
they
take
longer
time
to
graduate.
Economi co;
students
loose
comparatively
less
in
income
from
attending
the
university (5.25 million).
The second highest private cost element in Table 6-7 is the cost of
food.
For those students who live in university housing
(more than 90%
of
the
83.6%
of
students
who
have
a
scholarship
live
in
university
facilities),
dining
facilities
are available in the major dormitories.
On the average,
students spend CFA francs
140,200 until
graduation
for
their food.
For a four year graduating average, students will
spend CFA
Francs 35,000 for food (1981 US $104).
The meal
provided by the CNOU is
a complete French menu.
The Cublier
(op. cit.) study indicates that in
1969 the Ivory Coast subsidized each meal in a proportion of 53%.
If we
take the average annual
price increase in food from 1970 to 1979, which
amounts to 4.42% (BCEAO estimates), then the food bought by students was
subsidized
in
1981
by
476%.
In
fact,
the
full
extent
of
food
expenditure
by
the
CNOU
is
not
entirely
revealed
by
this
percentage.
One must add to the above figures the cost of food discarded.
This is
because
serious
statistics
on
students
who
actually
eat
at
the
CNOU
restaurants
are
not
available.
The
cublier
study
indicates
(using
a
It
questionable approximation)
0.7 meal
served to each student per day in
1969.
Our own
survey indicates that during a month only 39.9% of the
students
utilized
the
CNOU
restaurants
regularly,
29.4%
go
there
occasionally,
and
30.7% have
never eaten
in the CNOU restaurants.
If
these
statistics
are
correct
(as
they
appear
to
have
been
on
other
issues)
then
the
loss
in
revenues
is
even
greater,
since
meals
are
- 178 -

---

TAI3LE 6.7
TOTAL ANNUALIZED PRIVATE COST ~NCPRRED, BY ONE STUDENT/UNTIL GRADUATION/BY SCHOOL
(in CFA Francs,
1000)
Cost Items
Law
Economics
Letters
Sciences
Medicine
All schools
I. Net Income Foregone a
6,410
5,278.8
7,031
5,950
5,359
6001.
2.
U'
.
f
b
nlVersltj
ees
12.0
10.2
10.9
12.0
10.2
11.6
3.
Rent c
134.6
97.6
110.1
98.5
79.6
109.1
4.
Food c
176.2
126.4
137.9
123.1
109.1
140.2
5.
eloth c
17.3
13.2
14.1
15.7
13.6
15.0
c
6.
Books and Supplies
20.1
17.1
17.6
21. 2
20.2
19.0
c
7.
Aid to Family
74.4
45.6
62.4
54.0
46.8
56.6
TOTAL
6,844.6
5,567.9
7,384
6,279
5,642
6,343.6
Notes:
a:
From Table 6.6 .
b:
universityf'w~s averaged and annual ized to reflect the difference in average
number of years for graduating.
c:
These items were taken from our survey and annualized to again reflect difference
in time spent in school.

---

prepared not according to actual
consumption at the restaurants,
but on
the
official
statistics
of
number
of
beneficiaries
eligible
for
CNOU
services.
Table
6-8 gives a division of the CNOU restaurants utilized
by type of meal.
Following the French tradition, a heavy meal
is served
to
students
comprising
an
apetizer,
an
entree
and
a
dessert.
Non-
acholic drinks (except beer) are also provided at the restaurant, at the
full
(non profi t) cost to the student.
We have commented more extensively on the food item in the private
costs table to show the magnitude of the subsidy received from the CNOU,
and how we may have underestimated our CNOU costs in Table 6-3 for lack
of precise data.
The
third
highest
cost
item
is
the
cost
at
which
students
rent
their room.
On average they
pay CFA Francs 2,850 per month.
Actually
the cost of renting a CNOU housing is CFA Francs 2,500 per student for a
studio of double occupancy, CFA Francs 3,000 for a single studio and CFA
Francs
4,500
for
married
student
housing,
regardless
of the
number of
rooms.
The rent,
like the cost of food,
was the same in 1980-81 as it "as
at
the
creation
of
the
univers,lty.
A comparable
room
in
the
posh
neighborhood
of
Abidjan-Cocody
where
the
university
is
located
would
average
CFA
Francs
45,000
per
month.
On
the
average,
students
pay
2,850.
The
ai d
gi ven
by
students
to
the
members
of
thei r
fami ly
or
to
their
fiancee
constitute
the
fourth
most
important
private cost
item.
On the average,
students
spend CFA Francs 56,600 before they graduate,
on aid.
If we isolate the 45% students who said in the survey that they
did
not
give
aid,
then the average amount of aid given by students
is
- 180 -

---

TA~LE 6.8
MONTHLY UTILIZATION RAT~OF CNOU RESTAURANTS BY IVORIAN STUDENTS WHO HAVE SPENT AT LEAST
ONE ACADEMIC YEAR AT THE NATIONAL UNIVERSITY ([n percentage)
Number of times they
utilize the restaurant
Breakfast
Lunch
Dinner
Never
46.8
44.4
44.2
Less than 4 times
31. 6
16.3
17.4
4 to 10 times
10. I
14.2
16.2
>-'
""
>-'
II to IS times
5.3
9.0
8.5
16 to 20 times
2.7
7.6
7.0
21 to 30 times or more
3.5
8.2
6.7
... F"'orl' 01.>'" S1.J"''IQ~~

---

raised to CFA Francs 82,070.
In other words,
students utilize about 4%
of their stipend in aid to their family.
If one
looks
at
the distribution
of
private costs
by
school
one
sees that Law School
students .foll OW
Arts
students ,or the burden of
private
costs.
This
is
because
Law
School
admits
a
relatively
significant
proportion
(5.01%
in
our
survey)
of
students who
did
not
obtain the BAC, but who were successful
in the exams opened to those who
have
registered
in
the two years
Law initiation course given by their
school.
These
students
are
often
married
or
are
older
in
age
and
therefore support more private costs.
Students in
Arts
carry more
private cost again due to the higher rate of repetition.
In
concluding
this
chapter
on
cost
estimates
of
the
National
University
we
shall
stress
the
following
aspects:
(I)
the
cost
of
instruction
per
student
is
made
heavy
by
the
proportionally
higher
salary given to expatriates in the schools where the Ivorianization rate
is
low.
(2)
For
lack
of
precise
data
the
cost
of
amortized
items
appears relatively low although·it· is not.
(3)
the cost of the. National
University
is
made
even
higher
by
the
comfortable
living
allowance
received
and
by
the
existence
of
CNOU's
subsidized
services.
(4)
Students forego a substantial
amount of
income when they
pursue thei r
education
at
the
National
University.
This
foregone
income
varies
because it takes longer to graduate from some schools than others since
each has
a different
average
repetition. rate.
(5)
Finally,
the high
subisdy given to CNOU housing and
food
permits the student to balance
his or her budget which had remained stationary since the sixties.
In the next chapter, we shall
better appreciate the aspects of the
benefits received both by the state and by the individual
for attending
the National University.
- 182 -

---

CHAPTER 7
THE BENEFITS FROM THE NATIONAL UNIVERSITY
Few
dispute
the
benefits
the
National
University
and
higher
education in general provide to individuals in society and to society as
a whole.
The human
capital
theorists we
reviewed
in Chapter
2 have
produced an abundant 1iterature to support the vi ew that educat i on not
only
provides
benefits
to those who
obtain
it
but
also benefits
the
total
society.
There is no problem for those who invest in their own
education.
For,
at
a point
in time,
they
real ize
how much they are
willing
to
invest
for
the
benefits
they
expect
from
~ducation.
As
rational
decision
makers
they
may
"take" the appropriate
"amount"
of
education which will then provide them with the maximum benefits.
Less controversy would arise if every individual supported the full
extent of the cost of his or her own education without any subsidy from
the state.
However in third world countries,
especially in the Ivory
Coast,
education
is
almost
financed
entirely
by the state.
Even
in
economically advanced countries tuition paid to institutions, which are
not
entirely
state
supported,
rarely
covers
70
percent
of
the
full
cost.
Public
monies
are
therefore
used
to
subsidize
even
private
systems.
The issue then becomes to what extent from a social welfare
perspective, these pUblic funds should be used in education and not in
say
agriculture.
This
is
particularly
a
problem
in
third
world
countries where
leaders are faced with national
tood shortages.
Even
when money is given to education,
on what grounds should the money be
invested in primary school
instead of higher education?
Human capital
theorists
and
others
have
tried
to answer
these
questions
since
the

---

early
sixties.
No consensus
has
been
reached
in the
literature which
clearly
supports
the
allocation
of
public
funds
to
one
level
of
education
over
another,
or
even
to
favor
educational
investment
over
other
social
investments.
Windham
(1980)
and
Nelson
(1978)
provide a
review of the different points of view in this controversy.
The decision to create a
free
university
in
the
Ivory Coast also
followed
the
rationale
propounded
by
Human
Capital
Theorists.
The
investment
decision
seems
to
have
gone
even
further
than
the
Human
Capital
view,
however. This
is apparent
if one considers
the objective
of policy makers expressed by the emblem of the university provided in
Appendix O.
This
emblem
suggests
that
the
university
should not only
provide
Ivorian
society
with
scientists
capable
of
dominating
the
natural
and
supernatural
world
around
them,
but
it
should
also
make
students more humanistic.
Whatever the main reason for creating the National
University, the
financing and
the costs examined in Chapter 5 and 6 respectively, show
the
extensive
investment
made
in
it.
In
this
chapter we
shall
first
examine
the
benefits
individual
graduates
obtain
from
attending
a
particular
school
of
the
university.
We
shall
look
further
into the
financial
benefits,
society
as
a
whole gains by investing ir. the
university.
One
important
aspect
of
the
benefits
that
need
to
be
captured
here
is
the
non-monetary
value
attached
to
attending
the
university.
In a country where
only 40 percent of the population can
read and write, attending the university endows the student with social
prestige,
influence
in
his
or her community,
changes
in attitude,
and
many other non perceptible external
benefits not easi ly translated into
monetary
values.
We
shall
reluctantly
brush
aside
these
important
-
1 R4
-

---

aspects of the benefits from higher education to concentrate on what can
~ be ascertained in monetary terms.
A.
The Methodological Approach
In this
section, we look
into the financial
advantages the
Ivory
Coast deriverfrom investing in the university.
The financial
benefits
are assessed as follows:
n
E
=
(7.1)
s
n-m
t=m
(l+r.)
s+1
s
J
E
is the present value of the life long earning derived by individuals
s
who attend
school,
s .
Ys is the life-long additional earning stream
derived by individuals who attend school s instead of entering the labor
ma rket
wi t h the
SAC
deg ree.
ms is the average age in our sample at
whi ch
students
graduate
from
thei r
school.
n
is
the
ret i rement
age
which is 55 in the Ivory Coast, although many Ivorians work beyond this
age.
By
using
55
years
as
the
ceiling
for
working
age
we
do
not,
however, significantly alter our results since revenue obtained after 55
is discounted.
rj
is the
various applicable discount
rates.
t
is the
time period.
In the
life cycle of the student, the additional
earning
received from attending the university is computed as follows:
where
1rJ
salary for university degree holders
Y
salary for SAC
degree holders.
BAC
-
185
-

---

During
their
work.-life
individuals
obtain
an
increase
in
their
wages.
In
the
Ivory
Coast
wage
earners
of
the
level
of
salary
of
university graduates obtain an average ID'; increase in salary every two
years.
The ID'; increase in salary every two years can be approximated
to ID'; wage increase for half of their work-life.
Hence, our formula of
earning stream should be appreciated by the corresponding proportion:
n
1
=
L
Ys
Es
n-m +1
n - m
+ I
s
s
t=m
(I+r.)
(l + d )
s
J
J
2
where dj is the increase in wages obtained every two years.
From the future taxpayer who attend schools, the government will
derive
the amount of tax equivalent to:
n
=L
t-m +1
t=ms (I+r). s
J
T
is the total tax amount collected by the government from individuals
s
attending
school
s.
T
is
the
different
tax
rates
which
apply
to
individuals'
salary.
The other variables have their previous specified
meaning.
In
computing the benefits
derived
by
society we made three major
simplifying
assumptions.
First,
we
assumed
that
individuals with the
same degree enteri ng the 1abor force at the same time w; 11
have the same
earning stream.
While this assumption is often verified for individuals
who enter ci vi 1 servi ce jobs,
it
is not true for many of the graduates
of law and economics who may enter private or public sector jobs.
Those
individuals who enter private sector jobs are often paid higher salary
and therefore contribute more through taxes, to the country's budget. To
-
186
-

---

the degree
that
this
last
case
is more prevalent,
our estimate of tax
revenue
(derived
from taking the same earning stream for
graduates
of
the same school l,. will be underestimated.
Secondly
we make no allowance for
the fact
that different 1eve 1s of
ability
can
determine
different
salaries
for
people
with
identical
educational backgrounds entering the same job.
This assumption does not
seriously
affect
our
result
since
salary
determination
is
greatly
controlled
by the government.
Whi le
some companies
may pay more than
the
minimum
wage
required
by
the
government,
the
salary
regulation
requires that individuals with the same degree be paid the same minimum
entry salary.
A salary raise every two years is more or less automatic.
A refusal
to
recommend
for a salary
raise
requires
written
justifica-
tion.
Directors
are
often
reluctant
to
follow
this
procedure
and
unsually suggest an automatic raise
(see my article.
(Yao, 1981) on the
issue.
The third
simplifying assumption
concerning
the
life-time earning
stream
is
that
we make
no
allowance
for
the
graduate's
unemployment.
While unemployment did not exist among university graduates in the Ivory
Coast in 1980 when we started this work,
by 1982 the unemployment rate
had become a prime concern for
pol i cy makers.
We di d not have preci se
statistics on this politically sensitive issue.
The Ivory Coast economy
is
more
and
more
capital
intensive
and
will
require
individuals
with
higher education
training
if
the
growth
rate
of the
past
two decades
continues.
The
possibility
of
unemployed
graduates
seems,
therefore,
less
significant.
In
any
case,
the pressure put on the government by
potentially unemployed
university
graduates
will
compel
policy makers
to
more
actively
advance
the
policy
of
Ivorianization
(replacing
-
187
-

---

foreigners,
especially
the
French
with
qualified
Ivorians),
the
government
has
attempted
to
unsuccessfully
implement
since
the
early
seventies.
A significant number _of unemplDyed graduates may give
the policy, the additional boost it needs to be~Dme significant.
In other words; the assumption of full employment of g~aduates
does not significantly alter our estimate of future income stream.
Our
formula
on
the
present
value
of
the
individual
uses
the
parameter m
which is to vary according to the school.
This variation
s
in the average age at which students from different
schools enter
the
labor market was caused by the fact that the rate of repetition varies
from one school to another.
We saw in previous discussions and in Table
4-5 that the average promotion rate may vary frrnn 12.30 percent for Form
I V students
in
Arts
to
97
percent
for
the
School
of
Economics.
Students on average, may spend more time in one school than in another.
Another parameter in formula
7-3 is the tax rate applied to income
streams.
In Appendix E we provide a brief discussion of the different
income tax rates applicable to levels of income.
Recently
(1982) a new
tax to
support
theimemployed
was
instituted.
It
is
believed
to be
a
temporary and exceptional tax which may be abolished with the end of the
current
economic
recession.
We
did
not
incorporate
this
tax,
not
because
we
believe
it
may
really
disappear
in
the
near
future,
but
mainly because we could not find more information on it and because we
could not obtain the rate at which it applies to income levels.
B.
Empirical Estimates
We
start
first with the private benefits individuals obtain from
their higher educatlon diploma before we compute society's 9ain.
-
188
-

---

1.
The Private Benefits from Attending the University
Individuals
attending
the
National
University
receive
two
kinds of private benefits.
First, the benefits in kind represented by
the
individual's
share
in the
public
expenditure
on
instruction,
CNOU
services,
and
student's
stipend.
The
second
form
of
benefits
comes
after
graduation.
It
is
the additional. wage revenue obtained by
attending the National Unversity,
instead of entering the labor market
with a BAC degree.
Benefits from Public Expenditure on Schools
The
individual's share in public expenditure on the university has
already
been
computed
in
Table 6.5.
We saw that
students
in
Science
receive
more
public
money
than
any
other
school
(CFA
Francs
7.892
million-), 2.23 times higher than the Law students who receive the least
public
expenditure.
Medical
students
receive
approximately
the
same
amount of public subsidy as the Science students
(7.447 million) almost
twice
as
ruch
as
the
student
in
Economics
(3.932
million),
and
1.48
times more than the Arts Students.
If we exclude from the total
public expenditure on education,
the
cost
of
amortized
items
that
may
be
subject
to
errors
(due
to
imprecision
in
cost
elements),
the
science
st~dents again lead other
schools
in
public
expenditure
(7.410
million;.
The
proportion
of
expenditure
in
schools
between these
students
dnd
Law
school
students
rises to 2.45 (from 2.23).
All the schools keep the same ranking to one
another
in terms of benefits
from publ ic expendi ture:
r~edicine, second
with 6.93 million, followed by Arts
(4.44 million'"
Economics
(3.49
million) and
Arts
(3.021 million.).
-
189
-

---

Benefits from Additional Life-time Earning
We
indicated
earlier
that
students
who
decide
to
pursue
their
education beyond the BAC degree are paid above the salary level of BAC
holders.
This
is especially
true
for
graduates who enter public jobs
where the classification corresponds strictly to the diploma.
The
additional
earning
obtained
by
graduates
according
to
their
diploma is computed in column 1 of Table 7-1.
As we saw in Chapter 6,
law and economic students often enter pri vate sector jobs with a higher
initial
salary, therefore have higher initial
additional salary than
other schools (CFA Francs 2.077 million versus 0.703 million).
In
column
2
of
Table
7-1
we
take
into
account
the
fact
that
students
graduate
from
the
university
at
different
ages.
Our
survey
indicates
that
on
average
students
graduate
when
they
are
26
years
old.
Law
students
graduate
a
little
older
(28
years)
because
of
a
higher probability of repetition in shcool.
The youngest graduates (for
the
first
four
forms
of
the
school)
are
enrolled
in
medicine.
The
difference
in
age
of
graduation
translates
into
supplementary
wages,
since students stay longer in the jobt market.
We should have corrected the life period spent in the labor market
wi th the appropri ate morta 1i ty rate of the worker.
However; because we
discount the total
life time revenue from 55 years,
the probability of
death
between
26
and
55
years
is
nearly
negligible,
especially
for
higher education graduates.
We compute in column 6 of Table 7-1 a factor which should be used
to increase the additional
life time earning.
The factor accounts for
the
average
10% increase
in
wages
obtained
every
two years
by
higher
education
graduates.
We
approximate
this
increase
by
applying
a
-
190
-

---

Expected Additional Life-Time Benefit frpm Attending the tlational University, by School
(In CFA Francs, 1000)
(1)
(2 )
(3 )
(4 )
(5 )
(6)
(7)
School
Addi tional
Average Age
Expected Years
Annuity Factor
EXflected
Compound
Actual
Anllual Earning
at
b
of work
ApDlicable
Eilrning Stream
Factor
Expected
from Attendi ngd.. G,'adua t i on
(3)=55 years-(2)
to (3) at r,
at 7% Annuity
for 10%
Life-time
(5)=(l)x(4)
every 2 yrs
Earning
of Life-time~(7)=(5)x(6)
Law
2,077
't.7,867
27.136
11.986
24,394.92
3,792
94,526,0
Lette,·s
703
26.973
26.324
11.825
8,312.97
3.797
31,564.3
~
' ! )
~
Economics
2,077
25.676
28.027
12.137
25,208.54
3.787
95,716.8
Science
703
25.381
29.619
12.279
8,632.13
4.177
36,0564
fledi ci ne
703
25.286
29.714
12.~09
8,723.52
4.177
36,438.0
Notes: a - The additional earning column was computed by subtracting from the average annual wage of
the graduate the salary earned by a BAC holder
b - Taken from ""'survey.
c - An increase in salary of ten percent every two years is equivalent to a compounding factor
of 10% over half of the expected years of work.

---

compounding
factor
of
10%,
half
the
life time
of
the worker.
Thus,
science and medical
graduates have their lifelong wage multiplied by a
factor
of
4.177,
when
other
school
graduates
ITJJltiply
their
earning
streams by 3.797.
The results of our computations are given in column 7
of Table 7-1.
At
this
benefit
level,
Economics
students
derive more additional
wage than any group of students
(95.716 million) while science students
who
obtained
more
public
expenditure,
receive the
least wage
revenue
during their life-time (36.056 million:).
The proportion in life-time
earning between the two extreme earning groups
(Economics and Letters)
is 2.65.
Law students who received the least in public expenditure have
CFA Francs 94.526 million
in additional life-time earnings.
2.
The Public Benefit from University Investment
We stress
here again that the benefits we shall
consider in
this
section
refer
to
financial
benefits.
We are
ignoring
the many
social benefits often indicated in the literature.
Even for financial
benefits we could not assess
fully all
the tax resource the state may
obtain by taking the graduate's second income from "moonlighting."
We
lacked
the
appropriate
data for
such
exercise.
Our
results
here
constitute an underestimation of the total benefits the state obtained
from investing in higher education.
Our estimate of public benefit is based solely on direct income tax
paid by graduates.
Indirect income tax related to the new consumption
pattern
of
the
graduate
are
ingored
because
they
are
difficult
to
evaluate.
- 192

---

In
Table
7-2
we
compute
the
financial
benefits
the
Ivory
Coast
derives from its expenditures analyzed in Chapter 6.
The benefits come
in
the
form
of
high
income
tax
imposed
on
higher
income
brackets
in
which university
graduates will
fall.
In
this
table we also indicate
the different
income taxes applicable to levels of
income.
Appendix E
gives more details about the income tax system of the country.
If we analyze
the
total
income
tax
revenue
that the country will
extract
from
the
potential
graduate of a
school,
we see
in
Table
7.2
that
all
graduates
pay
nearly
half
of
their
life-earnings
in
income
tax.
However,
economics
graduates
wi 11
contri bute
more
to
the
state
than any other group.
The former student
in economics wi 11
pay during
his or her life-time a total
revenue of CFA Francs 49.126 million.
Law
school
students wi 11
contri bute the second
largest sum to the
treasury
(CFA Francs
48.515
million).
Graduates
from
Letters
pay
less
to the
country's
budget
than
any
other
school
(CFA
Francs
16.200)
which
is
three times less than that paid by economics students.
Three major conclusions can be drawn from this chapter.
First, for
the lack of data, we have confined oursel ves to estimating the monetary
benefits
individuals
obtain
from
the
university.
However,
important
non-
quantifiable
benefits
go
to
the
indi viduals
and
to
society
when
pUblic
expenditures
are
made
at
the
National
University.
Second,
science
students
obtain
more
public
expenditure
from schools
than any
other group of students.
Finally, economic students derive more private
benefits from their school
but also contribute most to the tax-revenue
collected by the state from university graduates.
-
193
-

---

TABLE 7.2
ADDITIONAL INCOME TAX REVENUE TO THE STATE FRDr1 GRADUATES, BY SCIIQDL I In CFA F'-anes, 1,000)
I I)
(1 )
(3 )
(4 )
(5)
(6)
(7)
(8)
fax Revenue
Tax Hevel1ue
Tax Revenue
Tota I Tax
Total Tax
Annui ty FactoI'
Total
Incon1e Tax
Additional
(I"OIll
the
f"olll the
from the (c)
Revenue
Revenue
of 7~ Applicable
Revenue per'
$c1100 1
[al'l1ing Stl'eam
·u
10'"
to Years in
Student at 7"10
C N T,,(a)
r. S. T"Ib)
1 . r,. R. TdX
(5H1j'13)'14)
Wl
! d
t
(d)
tIle Labor
Discount Rate
Ra te '" 10'1.
Ra te
= 1.5%
(4)' (1)'13) x 45·,
Tax lncrease
F
(e)
_,_.
......
~......_~ ~~
......._._~~_~
~~._~ ~.......~~_~ ........~.~~~_."'-~-'-~~
.~.,. .•.~, ... "~,.~ _--" _"_~= =_ ~~~IJ~l.j'-!~r.~....... .or:.:.
Law
1 077
107.7
31.15
817.16
1,066.D1
4,047.64
11.986
48,515.01
l.etters
703
70.3
10.54
279.97
360.81
1,37D.00
11.815
16,200.15
Econolllics
1.D77
2,07 7
31.15
817.16
1,066.01
4,047.64
11.137
49,126.10
Science
703
70 3
10 54
17997
3608!
1,507.1D
11.179
18,505.61
~\\e.d i c i [le
703
70.3
IQ.54
179.97
360.81
) ,507.10
11.409
18,701.60
~Iotes: a
C.N. COlltribution Nationale lax is a flat tax rate applicable to all income levels
b
T.S. Tdx
011 Salary (llllpotSlll'
haitelllent et salait'e) is applicable atvariilble tilx fate.
e - 1.G.R.
II1Ipot
Genet'al Slll- le Revell\\1
is cJpplicable t030:~ of tjr055 incollle.I'ev(:l1ues uLv,.If'iable rates.
We Intent10nally ignore that fraction
to cOlnpellsate for ·OUt- underestilllation of the' ~ross revenue.
.
d
The inCl'ease in ID'!. tilX revenue 'ridS computed by multiplying COlurllll (5) witl1 a compounding factor of the aver~qe time in the labor
force
(See Table 7,1 for detailed computation)
~
e - We indicate in Table 7.1 the detailed computation of the years in labor (on..:e to ..... hich ..... e have applied ttle discount rate.

---

CHAPTER VIII
THE REDISTRIBUTION EFFECT OF UNIVERSITY FINANCE
In this Chapter we finally attempt to answer the second ques-
tion raised in Chapter ~: What are the equity issues involved in
the financing scheme of the National University?
We addressed some aspects of the equity issues raised by the
financing scheme in Chapter 6 and 1 when we examined the distri-
bution of the costs of and benefits
from university education by
school of enrollement.
However, our main concern lies not at the
level of the distribution of COSts and benefits by career track,
but rather on the patterns of distribution of these costs and be-
nefits among income and socio-professional groups.
For, i t is at
tl,ose last levels of grouping that taxes are raised to finance the
University.
Previous analyses on these kinds of inquiries have raised many
debates.
In the first section of this Chapter we shall recall
once again the main conceptual issues alr~3dy raised in Chapter 11
and discuss their bearing on our study fo~ the Ivory Coast.
In
the.second section,
we suggest a methodol
:y for assessing the
distributional effect of government spend
Ig on education for dif-
ferent groups of taxpayers.
~nally, we : resent the result of our
findings both on intra-generational and ic.ter--generational equity.
A.
Issues in Redistribution and their Bearing in the Ivory Coast
In Chapter 2 we reviewed the concept and methods used in the
195 -

---

literature to assess the redistributive effect of an educational finance
scheme.
It
is
important
to refresh the reader wi th the
major conceptual and methodological
issues associated with this type of
exercise,
to better illustrate our own methodological
approach.
Before
we embark
on that path, we must clear one confusion which often arises
when
discussing
redistribution:
how
redistribution
of
revenues
differ
from the more familiar issue of distribution of income?
The income distribution discussions as they have arisen in welfare
states, describe the statistical data on income (more or less accurately
measured)
possessed
by
individuals
or
family
units.
Some statistical
index
(often the Gini
Coefficient) is then used to measure the relative
inequality
of
the
incomes
among
individuals
of
the
society.
Income
distribution studies often attempt to measure the effect of a government
policy
on
the
distribution
of
individual
or
family
income.
They,
however,
need
not
be
directed
towards
assessing
a
particular
policy.
For example, it is
possible
to study the distribution of revenues in
an anarchist (stateless) society by simply measuring the relative income
differential which exists among the people of the society.
On
the
other
hand,
one evaluates
the
redistribution
of
revenues,
income, or wealth in a society by examining the effect of an articulated
£:01.(.\\1
or a tacit
government
spending/on
the distribution
of revenues.
More
precisely,
in
redistribution,
one looks at the benefits individuals or
fami lies
deri ved
from
a
government
program,
and
how
these
same
individuals
or
families
were
taxed
to
finance
the
program.
The
role
played
by
the
government
in
collecting
revenues
from
the
individuals
through
taxation,
then
distributing
more
or
less
equitably
these
revenues
via
a program,
constitutes a redistribution policy.
However,
-
196
-

---

not
all
government
spending
is meant
to have a redistributive effect.
Mi 1itary
spending,
for
instance,
in a
poor non-weapon producing country
Cl
'
can hardly be argued as havingl';'edistributive effect on its non-military
population.
In
a
study
of
redistribution,
one
often
arrives
at
some
equity
judgement whereas
income distribution addresses itself to a statistical
measure of inequality, which may be exempt from equity concerns.
Equity
judgment
does
not
necessari ly
correspond
to
justice,
either.
Kolm
(l972),- Varian (l974), and Cazenave and Morrisson (1978) and others have
discussed
the
relation
between
equity,
justice
and
individual
preference.
Kolm
(l972)
in particular defines
justice as
"equity with
fundamental
individual preferences."
In
Chapter
2 we also discussed
horizontal
equity
versus
vertical
equity within one generation, but also across generations.
We shall not
return
to these
discussions
here
and we will
identify
only the equity
'I
aspect to which our analysis is addressil'lg itself.
One of the major objections raised in the Hansen-Weisbrod (op. cit)
study
on
Cal ifornia
higher
education
was
about
the
intergenerational
effect
of
the
financing
scheme.
Education,
we saw,
alters,
not
only
today's
income,
but
also
that
of
future
generations.
Hence,
it
is
necessary
to
differentiate
between
families
with
children
and
those
without
chi 1dren.
We
also
need
to
identify
the
population
age
group
affected by subisidies to education.
For instance, only the
family
group of 35 years and older benefit from university subsidies,
for only
thi s
age
bracket
may
have
chi 1dren
in
the
age
bracket
of
hi gtler
education students.
We address this
issue in
our study by recognizing
that in the Ivory Coast, the strong family ties among individuals makes
-
197
-

---

this distinction is less crucial.
Indeed, although in Some fami-
lies children's income may be the sole revenue of the family,
the
informal social securi.ty system.
constituted by assistance among
family members also transfers revenues within the family unit.
Also, we assume that children are born at the same rate to poor
and rich families.
The mortality rate of the children of the first
group is slightly higher, but this approximation must not seriously
affect our result.
Another issue raised by studies on the distributional effect
of government spending is the nature and tne amount of taxes col..,
lected from one group which mayor may not be used for expenditure
in favor of another group.
Slnce earmarking of taxes is often il-
legal in many public finances,
how does one identifies the X total
affiount of dollars paid by oocial grou~·J from wnich one allocates
(in its aggregate form of a national budC;"'_ ) the aOluunt of Y dollars
:or financing a project which social grou~ ~ only will benefit
from.
This complex issue has not been solved conceptually.
Pechman (1~71), for instance ha~ suggested :he use of the so-~alled
"propol'tionali ty principle": one should allocate indi f feren tly a
dollar raised, without any consideration ah,ut who has actually con-
tributed for it.
In the Ivory <.;oast,
we are"luckier 11 . ~.n aGsessing the al-
location of tax resources, insofar as earm~king of taxes seem to
be the rule (not the exception) in public' ·nance (see Appendix E).
~~enever we cannot identify the sourCe and ,mount of a tax, we Shall
apply the "proportionality principle" suggested by Pechman.
Finally, deficiencies in data, especially averaged cross-seC-
tion data/have been criticized for their relevancy in a study about
inter-generational effects.
Our study hac Jlso suffered from such
aggregations.
We averaged the distributions of revenue in this work
198

---

into three subgroups: low. mi ddl e and hi gh. hi di ng by so doi ng. the many
disparities within each group.
The quality of our income data compelled
us to use such grouping methods.
8.
Methodological Approach
The
nature
of
the
data
we
have
collected
and
the
methodological
criticisms
made
to
other
studies
require
that
we
devise
an
original
approach for analyzing the problem.
The question we are addressing once
again is the following:
given a set of equity criteria. what can we say
about the financing scheme of the National
University.
not only in one
generation.
but
also
across
generations.
It
will
be
appropriate
to
divide
into
two
steps
our
methodological
approach.
First,
we
shall
consider the issue in its less complex nature:
the distribution within
one gene rat ion.
Second, we cons i der the effect
of the program across
generations.
I.
Intra-generational Equity
At
this
level
we
are
concerned
with
equity
in
the
redistribution
of
revenues
between
individuals,
families,
or
socio-
profession of the same generation.
We
want to be sure that groups
starting
their
life
in
one
income
bracket,
complete
their
life
cycle
in. similar
bracket.
Thi s is the hori zonta 1 equi ty
aspect of the
intra-generational
redistribution.
There
is
a
second concern
which
needs
to be addressed
in intra-generational
distribution:
the vertical
equity
issue.
Here,
we
assess
the
extent
to
which
individuals
or
groups,
from
different
income
levels,
finance
university
expenditure
proportionally to their revenue.
-
199
-

---

Methodologically, we proceed as follows:
(1) we compare the distri-
bution of total government spending on University students (ref~red
to as public expenditure-subsidy),
by family income levels, kinsman
income levels and by socio-professions.
(2) We study the tax system
of the country to determine the amount of tax burden paid by income
levels.
The tax burden paid by the group is compare to the expen-
diture-subsidy it receives.
(3)
The private cost to the family of
to
University education is compared/the expected earnings derived from
the degree earned.
(4) Ratios between cost and benelit are taking
for each income level
for looking at the egui ty issues.
Let us exarcine each step in more details.
(1)
Distribution of government expenditure-subsldy to income ~rouo~-
The expenditure of the government on University education conG-
Lit~tes a transfer to the family of the students enrolled in a par-
Lic~lar school.
Since the expenditure vary with the school, studenL3
cnroll in more expensive schools (Mcdlcine, Science) receive more of
eLl.s expenditure-subsidy.
To determine the amount of transfer re-
cc; ved by
the average student from a particular fa~ily income group,
we aad up the total amount of expendi ture-subsidy received from"school
attended
, and divide by the number of students from the income
group.
The deviation between the average ex~enditure-subsiQY received
by one student, when fami~y lncome background is not accounted
for,
ar)ll
the average amount received by lncome levels constitute a posi-
t~ve or a negative transfer for the income group.
The Same analys~s
;.,:!I:
comparisons are done
for
the otner ty!}cs of groups.
In a more formal way,
let us ca~l:
i)
the rp-pre~entative of the Ivorian sociu-economlc Dack-
,'ound \\SSB) considered hlgh,
j,
that of the middle "EB, and k,
thin
of low SEB (sec Appendix Bl.
G,
the
tota.1 government expenditure-subsidy which
gou5
to
famili&6 who have children at
the University_
S,
the total University population.
Si' SjBnd Skare the number of students issued from respec-
tively high, middle and low ~E8.
G ,
G
and ~ are shares of expenditure-subsidJ [oine to
i
j
family i,
j
and k SEa respectively.
200 -

---

G , - Gj
and G
the average expendi ture-su bsidy received
by
i
k
each of the SEBs.
We derive the net transfer recelved by
the average student
issued
from each SEB by lookin~ at how much -
G , G
and ~ deviates
i
j
ri'Om G,
the mean e.xpendi ture-subsiJy
rr:ceived by the average StUC9!!t
when SEB is not accounted for
:
Si
G.
= G.
G
-----.L =
~ = G
1
k
S1
Sj
~
The amounts of net
tJ. ans fers are COffipU ted as fol.lows
G- Si = Gsi
G- G
= G ,
G- G
= G
J
5J
k
sk
G .
G .
and G
being net
trans fers.
Sl
sJ
sk
The absolute value and
the sign of the
transfer tell
the group whi,c;l
is beneficlary and the gl'OUp which loses.
The computations above done for
Lncome groupings Can
be done
,'or the other social groupings adopted \\see
Appendix B )
Tax-subsidy APoroach
~~
By this method,
we look at
the equLty of/financing scheme
from
VilO
perspectives.
First,
from
the point of view of students and
~iicl,r
i"a"ilies.
We compare the amount of tax pald
by
the average citizen
is"ued from each income group and relate
this amount
to the SUbS1dy
;'cceived.
The equity of the system can be looked at in different
ways.
But let us start up wi th a
few notations.
T :
the total amount of tax paid by all ci tizens includinG
~ureigners/in one fiscal year.
T
the amount of tax ?aid by
foreigners.
e
Tu
the amount of taxes going toward
financing
tne Oni-
vcrsity.
C<
the proportion of the budrret
Ln
1981
taken by the
l'Ollr ministries in charge of education in the Ivory Coast.
~
the propol"tion of education budget allocated
to
tllO
Un:L versi ty.
T ,
T ,
T
'
tne respuctive amount of tax paid by income
i
j
k
croups i,
j
and k.
Since tax increases with income we must have:
Ti>T
>
j
Tk
T = T
+ l'j
T
+ T
i
T
k
e
Tu = (T
T ~ )xCl-x~
thn analysis COllce~n
_
)111
.- ' . t

---

only Ivorian citizens,
the sole Ivoriau taxes should be retained
Tu '
and T
are the respective taxes paid by the
uk
citizens of group
and k which go to University finance.
Define Ri'
Rj
and ~ as
G.
R
---.J..- =
.
and
R
J
=
l<
T .
ul
Tu!<
To assess the equity of the financing we must consider the
t~ree possible situations
1 )
GJ >
T
by assuffiytion)
k
The
financing scheme is " fai 1'" .~ n this situat~on, since the same pro-
~o~tion of subsidy to tax goes to all citizens in proportion with its
fiscal
cantri bution to
the scheme.
Al thout.h this scnemc appears
11 fairH
nor
it ooes/correct past lnequities.
2)
I f Ri> R
:> ~
~
>
:>
j
Gi
Gj
~
This financing scheme is rather inequitable since the a":'lQun t 0 f the
subsidy received increases with income without being compensated by
the tax paid.
The existing inequity is being reinforced by such a
scheme.
3)
I f R.l < RJ < Rk =>
G.l. < U.J <
~
The amount of SUb0i(:y to taz d-€.r.reases
·..:i th inCG'18.
Such a po-
licy may help to reduce past inequities..but is not necessarily "fair".
From the
perspective of the state,
the financing sche[l!c
is profitable if the future tax revenue derived from
future graduates'
earnings is higher or equal to the total amount G of expenditure-
sU~Gidy going toward all the students.
Let us call
T
the present value of the additional tax paid due to Un1-
f
ve~~ity degree earned.
I f
T~ - G ~ o
the government financing scheme
is
prc-
fi;~a.ble.
If
T
- G
~ 0 ; the govern,nent should not be advised cS
f
i ,-,icemen t
the financinc; scheme.
(3)
Cost-benefit Approach
A third approach
for analysing intra-Generational equity consists
in computing cost-benefit ratios for each income level in order to ana-
lyse the vertiCal equity of the system.
Recall tbat the
financing
,.

---

scl,eue of the University is equitable if the ratio of the private
cost of this level of education to the benefit derived are propor-
tionnal:
within all the groups, no matter what the levels o1' ..in~·
Gome are .Let us call
B = total present value (PV) of benefit from higher education.
B = Bs + Bw, where
Bs = PV of government subsidy to the student
Bw = PV of benefit from additional life-time earning
C = total r-V of cost of higher education (expenditure-subsidy)
Cs = PV of direc t cost of schooling to the student and family
Tu = PV of taxes which will be allocated toward university
finance.
C = Cs + Tu
Bi, Bj, Ilk
PV of beneIits to groups i, j and k respectively
Ci, Cj, Ck
total PV of cost to group i,
j
and k respectively
Ci = Vi ; --f.L=
Vj
Ck
= Vk
Bi
Bj
Ilk
Vi, Vj and Vk must be equal i f equity is to exist in
the fi-
nancing scheme ( cf discussions of chapter 2)
2.
Inter-generation Equity
Here,
the problem is the following.
To. the extent tnat
education affects
future income,
a comprehensive analysls of equity of
the system should concern itself with distribution of revenUeS within
this generation of university students but also with its effect on the
distribution of revenues among future generations.
To address this
issue,
we need to have some information on the social mobility effect
of the
Iinancing scheme.
Such data are scarce in many underdeveloped
countries,
espeCially in the Ivory Coast.
By way of methodology,
we tihall only use the equal opportunity
analysis discussed in Chapter 2,
whereby proportions of enrollment of
universi.y students by socio-economic background are compared with
the
distribution of students'parents socio-profession in
the total Ivori~n
society.
This methodology gives us an idea about the mobility between
the past generation of parents and that of current university students.
We cannot, however, infer from i t the effect on
future income because
we lack data on past social mobility.
To summarize the inter-generation equity appl"oach we have these
notations.

---

P
= total population of Ivorian citizens
Pi
= numoer of p~opl.e of group i
Pj
= number of peop.l.e of group j
Pk
= number ut !' 0p.l.e of group k
Mobility 1s measured with the following indexes; often called indexes
of selectivity.
51 :x P =g1
5 :x Pi
5j x P = gj
S:·.x PJ
Sk x P = gk
5 :x Pk
S,Si.,. Sj, SI<
are total numbe-r of students from group i,j
.. 'and k ..r.especti vel'j.~.
If gi =1, group i has an equal opportunity for social mobility.
If gi > I, group i has a better opportunity for mobility than
other groups.
If gi
< " group.i has less opportunity for "'0-
billty.
The same analysis is done ror group j and k,
also by grou-
pin;; of students by socio-professions of their father.
c.
Empirical Estimates
In this section we apply the methodological approach developed
qbove to the data on hand.
1.
Distribution of Government Expenditure-subsidy
This subsection uses the methodological approach developed in
Section B-1.
The findings are exposed in table 8-1.
We compu te the
total government spending which goes to each student population accor-
ding to his or her socio-economic background.
The total government
spen:iing was taken from our estirnaLe of the total public cost made in
table 6.5.
In that table,
the total public cost was computed lor each
sch001, and separated lnto instruction costs, CNOU costs and the direct

---

TABLE 8.1
PV of Average Government Subsidy and Net Transfer, by Social
Groupings (In-CFA Francs 1000)
All Students
*
Low
*
Middle
*
High
1.
Grou ping by income
level of the family
5185
5121
5671
2.
Net transfer from
**
Average
-64
-25
+486
3.
Grouping by income
level of family and
kinsmen
5185
5103
5302
5505
4.
Net transfer from
average
-82
+117
+305
5.
Grouping by h0usehold
items in the family
5185
5247
4989
5171
6.
Net transfer from
average
+62
-196
+114
*
Note
The average government su~sidy is the total public cost computed
in Table 6-5.
This cost was then affected to each student of our
survey according to their
5c.1>001
**The net transfer was computed by subtracting the average subsidy
received by each subgroup from the average subsidy received by
all students.
- 205 -

---

stipend received by the students.
In Table 8-1, we move from allocating
the
average
public
cost
to
the
average
student,
by
school,
to
distributing the total government spending by levels of
income group or
household
items
groups.
This
government
expenditure
constitutes
an
education
subsidy
to
its
beneficiaries.
We
therefore
termed
it
"~J(penciiture.,.su bsidy".
Line
1 of
Table
8-1
indicates
that
the
high
level
income
group
receives
the
highest
public
spending
on
university
(CFA
francs
5,671,000)
per
student.
Until
their
child
graduates
this
particular
group
receives
a
net
transfer
of
CFA
francs
486,000
more
than
the
average student.
In the grouping by
income
level, only the high level
receives
a
positive
net
transfer
from
the
average
subsidy
collected
by
all
families
(see
line
2 of Table
8-1).
The
low
income
group receives a negative transfer of CFA francs 64,000 from the average
subsidy
going
to
the
average
student.
The
middle
income
group
also
lQ/ses CFA francs 25,000 of sUbsidy from the average subsidy.
When we
introduce
in
the
grouping
of
students
the
earning
of
a
kinsman as defined in previous chapters,
(line 3 of Table 8-1), the high
level
group
continues
to
receive
the
highest
amount
of
subsidy.
However,
the
total
amount
falls
down
to
5.05
million
from
5.6
million.
In this instance, only the low income group continues to loose
in transfer of subsidy (CFA francs -82,000), although the loss has been
reduced by CFA 39,000 from the kinsman's income
(line 4 of Table 8-1).
The
high
income's
net
transfer
has
now
decreased,
and amounts to CFA
. 305,000.
The data
in Table 8-1
suggest
that
"kinsmen"
come from a higher
revenue status than that of the students parents.
In assisting students
-
206
-
..,

---

in
their
education
the
kinsmen
raise
the
average
social
background
revenue of the students.
In line 5 and 6 we analyze the distribution of government subsidy
to
university
students
grouped
by
household
items
available
in
their
fami ly
home.
The
rationale
for
such grouping is that the
income data
which
served
as
the
basis
for
the
previous
groupings
may
not
be
reliable.
The household items grouping offer a comparative alternative
for
classifying
students
by
socio-economic
background
(see Appendix B
for
further
development
on
the
approach).
Line
5 of Table
8-1
shows
,.\\.....
again in this last
grouping that/high income group receive~on average
the
largest
share of
public
subsidy
to
the
university
('0.1 million ).
The low category in this grouping receivel the second largest amount {4.8
million ),whil-ein the two
other
grouping, this subgroup received the
lowest
share
of
the
public
subsidy.
Line
6 of
the
net
transfer
of
subsidy by household items groups suggests that the high group
receive
more
transfer than other subgroups,
while the middle subgroups receive
the least transfer.
I
The distribution
of
government
subsidy to university students
can
I
also
be
looked
at
from
the
perspective
of
socio-professional
groups
represented in the lvorian society.
Table 8-2 computes the distribution
of university
expenditure
-
subsidy
for
five
socio-professions.
In
- 207 -
"
."

---

J~solute terms,
ttlC
blue collar Cl'OUP ['CC~~V8S ~hc 111i~11CSt aveL'a~e
government sUDsidy (CFA Francs 4.05 million).
It is closely fol-
lowed by the students whose fathers hold a management level posi-
tion (4.80 million).
The lowest amount of average subsidy goes
to the white collar job position (4.3 million).
When we look at the net transfer of subsidy from the amount
of subsidy received by the average family,
we observe that students
from blue collar background received
the highest net transfer
(+ 223,000),
followed by the management level group (+ 175,000).
white collar and rural profession groups received the least net
transfer of government subsidy to the university (- 259,000 and
- 128,000, respectively).
The relatively low net transfer of go-
vernment subsidy to the white collar group is surprising especial-
ly when this group is compared to bluecoll~r bJckground students.
Indeed considering the selective character of the system, one
would expect the blue collar group to have less access to the
University hence receive on average less subsidy.
The amount of
subsidy is, however, also determined by the time spent in school,
the type of school where the student is enrolled.
All these
fac-
tors may therefore lead to the results reported in Table 8-2.
To summarize the estimates of government expenditure-subsidy to
- 208-
"i
• - , .
~

---

TABLE 8-2
PV of Average Government Subsidy to Socio-Professional Groups of
Students' Fathers (CFA Francs 1000)
Net Transfer
Average*
from Aver~~e
Socio-Profession
Subsidy
Student
o - Average fami 1y
4630
1 - Not working, retired
4618
-12
2 - Blue collar
4853
+223
3 - Rural worker
4502
-128
4 - White collar
4371
-259
5 - Management level
4805
+175
*
Note:
The average subsidy was the total public cost computed in Table 6-5
allocated to each student of our survey according to the socio-
profession group of their father.
**The net transfer was computed by subtracting the subsidy received
by each group from the average family's subsidy ..
- 209 -

---

social
and
professional
background
of
the
students,
we
stress
the
following
points:
(1)
whatever
the
grouping
adopted,
the
high
level
received on average more government subsidy to university education than
any other group;
(2)
students from the middle revenue group ,in general
do .not
enjoy
a
positive
net
transfer
of
subsidy,
except
when
the
revenues
of
a
kinsman
is
added
for
the
grouping;
(3)
the
10;/
social
group receive the least
from government expenditure-subsidies.
In the
grouping by household items, the 10;/ level group receives, however, more
resources
than
the middle
level.
(4)
Students whose parents
hold a
blue collar job receive more
government
subsidy than
any
other
socio-
profession.
Management
position
job
is
the
second
largest
group
of
subsidy
receiver,
the white
collar
profession
obtained the
least
from government subsidy.
t<lthough
we
can
make
the
above
remarks
about
government
expenditure-subsidy
from
a
purely distributional
standpoint,
we
cannot
infer
from them any
equity
jUdgement on the
financing system unti 1 we
analyze the amount of tax paid by each group.
2.
Distribution of Tax Paid Versus Subsidy Received
We saw earlier that the tax incidence issue remains one of the
most controversial topics in public finance.
We also suggested that due
to the high
number of cases of earmarked taxes
in the
Ivory Coast, we
are able to
better ii:lentify
group!Dn which a specific tax falls.
In t<ppendix E, we explain the main characteristics of pUblic finance in
the I vory Coast and we indi cate the different sources of the bUdget in
the year 1981 which was used to finance the university in 1980-81.
In this, section we
shall
first
estimate the share of tax paid to
_ 210

---

the government and rechannelled to fami ly groups in the form of subsidy
to the university.
Secondly, we shall compute the total amount of taxes
the
state
will
derive
from
the
additional
earnings
made
possible
by
university
education.
We
begin
the
section
with
the
latter
computations.
Distribution of Life Time Future Additional Tax on Wages:
The
relatively
progressive
income
tax
system
of
the
Ivory
Coast
analyzed
in Appendi x E constitutes
one
of the many sources of
revenue
the
state
uses
to
finance
the
National
University.
We also saw that
three major taxes applied to all
wage earners:
the CN,
the ITS and the
IGR.
In
Appendix
E we
discuss
these
taxes
on
wage:; and
provide
the
average amount
paid in each kind of tax on wages.
However,
to compute
the total additional
amount of taxes that each graduate will
contribute
during their working life, we need to know the additional
salary earned
above the high school
degree
(SAC),
the average worklife period of the
graduate, the average rate of increase in wages in the country, the tax
rate applicable to the income bracket under study.
Let
by
be the additional
wage earned above
the salary paid to a
SAC degree holder.
Let W be the worklife period of the graduate of the university.
Let F
be the discount factor applicable to the worklife period W.
s
Let r
be
the
CN
tax
rate
applicable
to
the
appropriate
wage
CN
bracket.
Let
rITS
be
the
ITS
tax
rate
appl icable
to the appropriate wage
bracket.
Let
r IGR be the IGR tax rate appl icable to the appropriate wage
211 .

---

bracket.
If we consider that workers receive on average an increase in wage
of rate i
every two years of thei r work 1ife w, we can approximate thi s
increase by appreciating
t.y
by (i )w/2.
The amount of 1ife long CN, ITS and IGR can now be computed with the
formula
CN
t.y x r
x
(i )w/2 x F
(8.6)
cN
s
has been approximately 10% for wage brackets of college graduates
in the past ten years.
We
can
now
rewrite
formula
(8.6)
by
substituting
the
variables
known.
CN
= t.y x 0.10 (0.10)w/2 x Fs
We use the same procedure to compute ITS and IGR
ITS
t.y x r
x
(i)
x
F
(8.7)
ITS
s
R
1.15%
ITS
ITS
t.y x 0.115 x (0.10)w/2
IGR
=
[t.y - (CN + ITS) x rIGRJ x (i)w/2 x F
(8.8)
s
_212
_
" _.
. . :-

---

=0·45
IGR
= [lly - (CN + ITS) x 0.45] x (O.10)w/2 x Fs
If
we
call
LT,
the
total
additional
lifetime
tax
paid
by
the
uni vers i ty graduate wage earner,
LT
= CN + ITS + IGR
In Table B-3 we compute LT for three methods of grouping students
of
our
survey
by
SES
background:
the
household
items
grouping,
the
parents income grouping and the parents and kinsman's income grouping.
We provide in line 2 of the table the amount of government university
expenditure-subsidy going to each social
grouping in order to compute
the net tax
paid during the worker's lifetime to the state
(line 3).
Finally, Table 8.3 provides in line 4 an idea about the transfer of tax
burden between levels of social status.
By
whatever
grouping
adopted,
Table
8-3
indicates
that
middle
social
groups have
the
heaviest
lifetime
tax
burden
due
to
thei r
future
earning
power
acquired
with
university
degrees.
Although
on
alf~ra£~ students will Pas 30.46 million in taxes before they retire,
theindiv·idual .. frolll middle soci-al groups will be taxed 32.46 million
i f we adopt the household items groupiqg, 33.22 million-when family
income grouping is adopted; and 31'.49 by .. the last· groupiDg.~. 'l'he row
level
social
grouping follows the middle level
in paying the most into
the revenues ~o"'tax on wages to the state (29.7 mi 11 i on , 30.21 mi 11 i on
"
_ 213

---

TABLE 8-3
Distribution*of Future Average Net Tax Revenues Collected on Future Graduates by
Social Group and Distribution of Average Net Transfer of Future Tax Revenues Among
Social Levels (in CFA Francs 1,000)
Average
(A)
(B)
(C)
for cll
Grouping by
Grouping
Grouping by Family
Students
Household Items
by
Parents
Income
and Kinsman Incor-le
Low
Middle
High
Low
Middle
High
Low
Middle
High
1
1.
Total lifetime
tax on wages
paid by student
of
30,462
29,749
32,161
32,041
30,215
33,226
26,692
30,264
31,490
29,674
2.
2
Total publ ic
N
,-"
subs i dy rece i ved
"0>
by student. of
5,185
5,247
4,989
5,171
5,121
5,160
5,671
5,103
5,302
5,505
3.
tlet tax revenue
rece i ved by
government from
students of
(3);(2)-(1)
25,277
24,502
27 ,172
26,870
25,095
28,066
21,020
25,161
26,188
24,169
4.
Net transfer of
tax from average
(4);(25,272 )-(3)
--
- 775
+1,895
+1,593
- 182
+2,789
-4,257
- 116
+ 911
-1,108
IOata computed in Table 7-2 by school and averaged
here for socio-economic groups.
20ata "cOrnputed in Table 6-5 by school and averaged here for socio-economic groups.
* See distribution methodology in the text

---

and
30.26 million for grouping A, B and C, respectively: see Table
8.3). The high. sClciJ,l
level in grouping B and C contributes the
least to the total lifet.ine tax resources.
Line 3 of Table 8-3 stows the beneficiaries of public expenditure-
subsidy for the three groupings A, B, and C. Cbntrary to what we
observed f'tuio",~~ for tax
contributions, the high level social
grouping receives the nost fran the government
exp=ndit=e-subsidy,
except in grouping A (CFA francs 5.67 million by grouping B and
5.50 million by grouping Cl. The low level social group which p3.id
the highest anount of taxes received the least governrrent expenditure-
subsidy (5.12 million and 5.10 million in social grouping Band C,
resp=ctively) .
When we
co=ect the total lifet.ine tax on wages p3.id
(line 1)
by the total public subsidy received, we obtain in line 3 the net tax
on wages p3.id by social grouping. In groupings A,B, and C, the middle
social grouping p3.ys the nost in net tax on wages to the state
(27.17 million, 28.06 million and 26.18 million"). In other =ms, the
state benefits the nost in investing in the higher education of the
middle inaJllle levels. The low social grouping is the second highest
net contributor to the state revenues by tax on wages except in
grouping A (25.09 million , 25.161 million
for grouping B and C
respectively) .
The column "All Students" of Table 8-3 indicates the average tax
revenues collected by the state on wages
and the average public
expenditure-subsidy given to all students regmhess of their social
,
level.
we observe from that column that the state is a net beneficiary
of its heavy
invesbTent !=Oliey in higher education by crA 25.27
millions, in the =rklife of every g:r

---

In tenns of transfer of the net tax paid be~ social groups
(line ""); middle level groups transfer rrost of their taxes to "other
social levels (+ 1.89 million, + 2.7 millions and + 0.9II millions
for groupings A, B ana e, respectively).
On average, the high group
receives the rrost in transfer of tax revenues on wages (- 4.25 millions
and -1.10 millions
for gIDuping B and C) .
In the results pIDvided in Table 8-3, cx>lumn A has «"consistently
pIDvided an exception. In fact, i f we observe that column C is
based on
the same type of data as column B, then two sets of results are revealed
by the table: one by inaJrre grouping neth:>d, and the other by h:>use..lnld
iten grouping.
The last grouping (column A) indicates that middle level
s;:lass paid
rrost in lifetine tax on wages (ITA francs 32.16 millions).
~"'01J.p
The lowest contributor in tax on wages is the low social level/ (29.75
millions) while by inaJrre the lowest cx>ntributor is the upper level
group (26.70). In terms of beneficiary of governrrent expenditure-subsidy,
Table 8-3 still reveals that when students are grouped by h:>useh:>ld itens
available at hJrre, the highest beneficiary is not the upper level group
as "'as fornerly the case, but rather, the low level group (5.24 millions)
The governrrent will receive the highest net tax on wages from the middle
social level (27. I million) as is the case in grouping B (28. I million)
I-bwever, the second najor pIDvider
of tax on wages is the upper group
(26.8 million) carpared with
21 million for the same level, when inaJrre
grouping is adopted.
For the transfer of net tax resources be~ groups, in either
grouping, the middle level group will pIDvide the rrost to other groups
(see line 4).
Alth:>ugh the low level group is a beneficiary of net
- 216 -
'~ "

---

transfer of tax (-0.77 million) in grouping A, this same grotL[J rerrains
in the same status rot with less arrount of transfer (-0.I8 million) than
in group B. The strongest contrast in the results by groupings is given
by line 4 concerning
the upper level social groups. In grouping
A this last social level is a net provider of taxes to other social group
levels by an arrount of 1.6 million, when in grouping B, the same group is
a receiver of taxes by 4.2 million.
'Ib = i z e , the results of the grouping by h:mseh::>ld itans (grouping A)
differs fron that of grouping by i.n<xxre (grouping B) when it cx:rnes to the
distribution of public expenditure-subsidy and the net tax paid by the
social levels to the state. l'1hereas in grouping A, the middle social level
is the l~st beneficiary of public subsidy, in grouping B the l~st
beneficiary is the low social level. For the net transfer of resources from
tax on wages between social group levels, the middle social level is the
rrajor distriWtor of taxes to other levels by the three grouping rnetlods.
However, the upper social level is a distributor of tax resource in
grouping A while it is a net receiver of taxes for the other tw::> rneth:xis of
grouping. From such results one canrot decide in aderinitive sense betw.een
the levels of social groups which benefit the llOst from future distriWtion
of tax resources fron graduates. We shall eJ<amine a fourth social grouping
to help us in the decision: the socio-professional grouping.
The analyses rrade on future lifetime tax resources by revenue levels in
Table 8-3 can also be rrade for socio-professional groups. The results for
such crnp.1tations are provided in Table 8-4.
Line I of Table 8-4 indicates that the blue collar group will pay the
llOst tax on wages (CFA francs 38 million). The student with "father not
- 217 -
'.
' r , '

---

:
TABLE 3-4
Distribution*of Future Life-time Tax un Wages Paid and Net Transfer of Future Tax
Resources, by Father's Occupation Grouping
All
Not World no
Rura 1
Blue
Hhite
fiananement
Students
Retired
Horker
Colar
Calar
Level
1.
Total life-time income
a
tax paid
30,462"'-
27,093
30.778
37,994
35,321
30,e88
2.
Tota 1 9ub~ i c subs i dy
received
5,185
S,051
5,099
5,067
4,693
5,075
e,l
3.
~iet life-tiille tax
~
C"
recei ved b;/ oovernlllent
2S,277
22,032
25,679
32,925
30,628
25,983
(3=1-2)
4.
I'et 1 ife-tillle transfer
of taxes from averaoe
tax received by the
-3,245
+
402
+7,649
+5,3:'1
- 706
novernrolent
. (4-25,277-3)
~Iotes:'
a- Extracted fro,,, lable 7-2
b- Extracted from Table 6-5
* See methodoloov for the distribution in the text.
H
ill! ~i'jures ;~e
"~HC\\'jed .

---

mrking or retired" will pay the least (27 million). The rranagerent
level socio-professionals will pay alnost the same anmmt as the blue
collar group (30.8 and 30.7 million respectively)
Except for the white collar groLlp/all the groups received alnost
the same anount of public ~diture:- sws"-cly (line 2). The rural group
received, ~er, slightly higher anount of public experiditure--subsidy
t:hm any other group (5.09 million).
In net future tax paid, the blue collar group again contributes the
lTOst in transfer of tax resources between students from WE five socio-
professional groups background (+7.64 million)
. The namagerent level
job in this grouping receives transfer of taxes on wages (-0.706 million)
'."I,;k at the same time it receives one of the highest share of public
subsidy. However, the "not mrking" social background graduates will
'receive the lTOst of the tax resources.
In surrrrarizing this subsection on the distribution of government
experrliture-subsidy to social group levels of the four metlods of
grouping students, we can indictlte that:
(I) the state, in the long run,
derives a positive return from its investment policy in higher education;
(2) when students are grouped by incane level of their parents, the middle
social level
will contribute the lTOst to future tax on wages, while
'the low social group will contribute the least;
(3) i f the h:mseh::>ld itens
available at home are used to classify students, the middle social level
group ,-rill still be the IT'ajor contributor in future taxes, towever, the upper
level social group
will benefit the lTOSt
fran other groups' taxes;
(4) students wrose fathers occupy blue collar job fXlsitions will pay the
lTOSt in taxes on wages to the state, while the "not mrking" group will
benefit rrost from transfer of taxes between group levels.
- 219 -

---

Distribution of 'IbtaLTax Burden"in 1981
In the preceding subsection, we analyzed the distribution of future tax
on wages arrcnS the three social level gr-oups. In this subsection, we concern
ourselves with the actual distribution of the burden of taxes for the three
incare levels. Although we wanted to analyze the sane distribution by socio-
profession, the data on hand was not satisfactory for such
~~ercise
In Appendix E, we presented in Table E-4 a detailed account of the various
sources of revenue of the 198J lk,tional budget. From that table, we present
in Table 8-5 a = i z e d percentage distribution of the major sources of
revenue of the 1981 budget. Column 4 of the table shOl-.'5 the total F€r-centage
distribution of all sources of tax revenues. The sources of direct taxes
c<;>nstitute only !2. 69%
of the resources of the total budget. Fran this
sr,'all percentage of direct taxes only the CN ani the IGR are paid by Ivodan
\\·;age earners. This rreans that wage earners"contribution to total tax sums
up to 4.59%. The remaining ingredients of the direct taxes are paid by the
self-employed, but rrostly by businesses. In 1980, the share of private
individual Ivorians in the total capital of private businesses \\vas consi-
dered negligible by the Office of National Statistics. One cannot expect
a drastic change in the following year, eSF€Ciall Y with the recession
that has been affecting the econany since 1980. The share of the direct
taxes paid by wage earners in the total budget should, therefore, be close to
4,59%. Line B of indirect taxes is constituted by tax on production,
tax on imp'::>rts and tax on exp::lrts. These taxes are always passed on to
constnrers, and in the case of goverrurent-subsidized products, they are
passed on to the major =ntributor of the crop s1;a])ilization fund
(Le., the fanner)'.
- 220 -

---

TABLE 8-5
A Sunnarized Percentage Distribution of the Sources of Revenues of the 1981 Budget
( 1)
(2 )
(3 )
( 4 )
BGF: CFA Francs
BSJE: 443,533
Tota 1 Budget
376,000
'01'3 S 3"0
A.
Direct Taxes
%
%
%
- Tax on profi t
8.53
3.91
-
ITS
1.64
2.26
1. 98
- Employers contribution
8.64
1. 19
4.52
- lGR
5.64
2.61
- Tax on Capital
1. 24
0.0
0.57
Sub-tota 1
25.56
~.4.'3'
12.69
N
'"
~
Tax on property
0.39
0.18
and patents
1. 01
4.38
2.37
'-1:-';'0-
<..'1-5
B.
Indirect Taxes
- Tax on production
18.57
8.51
- Tax on imports
40.09
18.39
- Tax on exports
10.18
4.66
Sub-total
b~
31.56
C.
Miscellaneous
4.13
2.04
3.00
D.
Debt
38.20
20.68
E.
Crops Stabilization Funds
(CSSPPA)
51. 75
28.01
TOTAL
q"J. ~J
~.~
99.90
- - - -
t("o!Y\\
\\~'\\'-~'t.

---

Agriculture production in the Ivory Cbast is in the hands of
srall famers (660,000 in 1980 for = a and coffee production) •
'I11is means that famers are, by and large, the rrajor I::earers of the
goverrnnent subsidy to the products. VItirrately, they support the
rrajor part of the in:h-ect tax J:::urden since they are affected by toth
the indirect tax on inp::Jrts and exports. 'I11is situation is ironic, for,
being a famer in the Ivory Cbast does rot allow for an equal participation
in the rrodern col1S1.lITPtion pattern as being a city dweller. Finally, Line E
of Table 8.5 indicates the share of the Crop Stabilization Fund (CSSPPA
also lauwn as"caisse"), in the total 1981 budget. To this percentage, one
must add a large percentage of the revenues used to pay the National Debt
(line D: 20.68%). Indeed, the National Budget indicates that the National
Debt is rranaged by the IlSIE--<:AA, which also receives sane earrrarked
revenues (see Table E.1) frcnn the agricultural sector and from the
industrial sector. Since industrial production is in the hands of foreigners
wln pass on theiYoost of prex::uction to consumers, it is correct to assume
that the agricultural sector will support
a large portion of the Debt. Frcxn th"se
broad discussions of the incidence of taxes, "'" rray construct in Table
8-6 a tax incidence by rrajor group of taxpayers.
In Table 8-6, "'" rrade twJ rrajor sinplifying assumptions: 1:0 the 1975
census di$tribution of population by socio-profession has rot changed
drastically in 1981;
(2) "'" assume that each socio-profession member
contributes proportionally to their income to the various taxes. Thio
last assumption does rot obviously lDld for direct
income
- 222 -

---

TAUU 8-[
~!
Percentage Distribution of 1981 Taxes Burden on Income Grou!Js
a
Total Tax
Low
f1iddle
UpDer
1.
IVDry Coast population
(% of 1975 census)
-
70
20
10
2.
Income distribution in 1973 74
5
(From Horld 8ank Estinlates)
-
30.05
48.4
52.5
3.
Taxes
- Direct (tax on wa~es
paid by Ivorians)
4.59
1.07
1. 70
1.84
- Indirect
31. 56
7.34
11 .66
12.64
- Debt
20.68
4.81
7.62
8.26
.\\
N
- Crop Stabilization Fund
N
w
(CSSPPA)
28.01
28.01
0.00
0.00
- Social Security
2.37
0.55
C.S7
0.94
- 11iscellaneous
5.37
1. 25
1.98
2. 15
4.
Tota 1 percenta~e tax pa id
92.58
43.03
23.84
25.83
5.
Total shaEe of taxes in University
Budget
0.61
0.28
0.16
0.17
a.
From Table 8-~
b.
btropolations made from the incol,le distribution fi~ure g1ven by \\,orld 8ank (1978)
c.
CS) = l4)x 0.61 (the prooortion of university budf]et in the education bud?et: see text):
!

---

taxes and probably for indirect taxes. For lack of data on the propensity
to ronsurre of each category of socio-profession, _
shall assurre propor-
tionality for indirect taxes, and naintain the assumption for the direct
taxes, since the total portion is relatively small (4.69%) for all groups.
tkr
The rough estinates of tax burden of Table 8-6 indicateja large portion
(43.0::) of the total tax burden, is supported by the lCM (70%) incare group
[Xlpulation.The middle incane group pays the lo_st portion (23.84%) and the
upper> level, the secon::J. largest share (25.83%) of taxes supp::>rted by Ivorians.
From these estinatesof total tax, one nay now approxinate the share of
taxes paid by each group which goes ;,,1 0 financing the university systero.
The 1981 budgets indicate that the four ministries in charge of education
in geheral (National
Education, prirrary school education, research, and
technical education) takes 44% of the budget. The National University
budget in 1981 was 1.4% of the total budgets of these four ministries.
In total each incare group will support the university budget with
0.616% of its total tax.
we 11\\3.y now approximate the share of the university budget supported
by each incare level using the proportionality assl.IDlption. Line 5 of
Table 8.6 indicates that the lCM income level invests 0.28% of the taxes
paid by Ivorians in university education wh>;!<:>the high level contributes
17% of its taxes and f"j.cldle level with > [6%.
After estinatirig the tax burden supported by the student and his
farriily, it is>now >[Xlssible to crnvute the total cost of university
- 224 -
' . .,-.',
...'.. "\\

---

education to himself and his family, the adopted tmit of our analysis.
We do such estinates in Table 8-7.
In line 2 of the table, ~ a:JITPUte the total anount of tax IBid by
each social level for financing the tmiversity. The tax anount was simply
CXXlIJUted by applying the pro]Xlrtions of line 1 to the total 1981
tmiversity budget (1.35 billion). The average anount of tax IBid by each
family group was CXXlIJUted by dividing
the total anount of tax burden by
the number of stu...dents in each social level. The low social level furnishes
the largest anount of tax to the tmiversity budget (619.6 million) followed
by the upper level (376.2 million). On average basis, each family of the
upper social level contributes the highest anount (2.87 million), and the
10\\~ level, the l~st tax anount (0.7 million). Of course, the
different
percentage of students in each social level explain the change in tax
burden by average basis.
Line 4 of Table 8-7 displays the ratios of subsidy- tax (A, B, C in
Section B-2). The equity criterion developed suggests that the university
financing systen
is equitable if relation
8.2 is verified. The argument
for such a relation is that even if all groups were to ffive an ~l share
of governrrent subsidy, the pro]Xlrtional contribution implied by a fair
tax systen must lead to a pro]Xlrtional decrease in A, B, C ratios with an
increase in income levels.
i = upper level, j = middle level, k = low level
G.1
= A = 1,976
T.1
- 225 -
.-', ,

---

TABLE 8.,
Distribution of Subsidy Received, Tax Paid and Private Cost-Benefit
Ratios of University Finance in 1980-81
Low
Middle
Upper
1.
Percentage of tax paid going toward
university budget a
0.28
0.16
0.11
2
Total amount of tax resources b paid
toward university education(FCFA million) 619.6
354.1
3,6.2
3
Average amount C of "tax paid toward
N
N
university education (FCFA million)
0.699
1. 38
2.8,
ry,
4.
Ratio subsidy receivedd/tax paid
,,326
3,139
1,916
'5.
Ratio total private cost/Total
private benefit at ,% discount rate
0.004,
0.0144
0.0346
a From Table 8.6
b Pnount computed by multiplying line 1 with total (CFA francs
1.35 billion) university budget
and divided by O,61b (total percentage of taxes going to the university).
c Average ar..ount computed by dividing line 2 by the number of students in each social level
( low: 886, middle: 25"
upper: 131).
d
"
Se<2 '2.'<1u::"c ..:: .. :) i'er subsidy received by income grouping levels.
e Total,priyate cost is constituted by private costs and tax paid, and private benefit is the
actualized future benefit from university education (see text)

---

G.J
=
B
=
3,739
Tj
Gk
=
C
=
7,326
Tk
where all the variables have their previous rreaning.
\\'ie, therefore, have relation 8.2 verified,
Le. i ) j:;> J.::-+A<B<C.
In other w::Jrds, our data suggests that there is a proportional decrease in
subsidy-tax ratio with an increase in in=ne. The financing schEme of the
tmiversity should: be equitable by this criterion. lb""""er, the social levels
share different proportions
of the total in=ne of the =untry and
therefore A, B, and C
should be appreciated in this light.
Group i, the upper level, =nstituting 10% of the student group,
enjoys 15.1% of the subsidy received per 1 CFA franc anount of tax paid.
Group j, the middle level group, taking 28% of tmiversity subsidy per
one tax franc,gathers 20% of the students. The largest proportion of
students (70%) grouped in the low lervel (group k) enjoys only 56.H of
subsidy per one tax franc paid in 1981. The shares of the various levels
in the subsidy per tax paid indicate that the financing schare at the
national tmiversity is inequitable and favors the upper levels,
although this distribution is less inequitable than the in=ne distribution
in 1973-74.
In section B-1
(3) of this chapter,
we defined the =nditions for a
fair financing system by using the =st-benefit ratios
Vj, Vi and Vi<.
\\'ie saw that an equitable finarui:ing suggests that we have equal =st-benefit
- 227 -
, .... ~

---

ratios i f the
groups
are of equal size.
The cost-benefit ratios were computed, dividing the total private
cost of attending the university
by the total private benefits. The
total private costs canprise the total private cost frrrn attending
the
university
corrputed in chapter 6 and the total tax paid in 1981 for
financing the university.
The total private benefit is the actualized
expected benefit frrrn attending the university computed in chapter 7.
Both the cost and the benefits are
allocated here to social levels
instead of schools as it was done for previous chapters.
In Table 8-7, the cost-benefit
ratios in line 5 are computed for
the average student in each social level. The social levels are, therefore,
of the sane size, but the values of the ratios vary with
in=ne. The
financing scherre can, therefore, re judged
inequitable frrrn our
cost-benefit criterion.
When the ratios are judged in the light of the number of students in
each social level, ~ see that in 1981, the
7':': pe;:ce.-;-t: low level
Fopulation SUPFCrted nearly 9 percent of the total private cost of the
university per one ITA franc receiVed. The middle level SUPFCrted 27
percent, and the upper level, 64 percent. These in=ne groups have
respectively, 30%, 48%, and 52% of the total in=ne in the Ivory Coast
in
1~73-74. From the standp::>int of vertical equity (requiring an increase
in cost-benefit ratios with an increase in ina:Jrre), the financing scherre
,"
'tabl
I1
lS equl
e.
4. Inter.,-generat::on 'c,istribution
In :OUl this section e, ~ have analyzed the equity of the systen
within one generation. 'lb assess fully the equity of the financing scherre,
~ must extend the analysis to the transfer of benefits of education

---

,
I
I
I
between generations. We als:J indicated in section B-2 that for lack of
data on inter-<jeneration nobility, we shall rely on the equal opt:Ortunity
of students to have aoo€Ss
to the system.
In chapter 4, we presented in Table 4-16 the distribution of students
by their father's occupation. This distribution gives us scme indication
concerning
inter-<jenerational nobility in the IVOry Cbast. The table suggests
that today's students are generally represented in a higher proportion at
the National University by socio-profession of their father than the same
sxio-professions are
found in the Ivorian society. Judging by the index
of equal opportunity developed earlier (section B-2), only the
mana-
gement
group has a fair chance for social nobility (g = 4.89).
If we ~e to base our e:ruity judganent only
on the above analysis,
we \\\\Quld be pessimistic about future social nobility in Ivorian sxiety.
M:lbility between generations exists in the Ivory coast and is illustrated
ul'l; 'h,O'CY
by the proportion ofjstudBnts of rural reckgroun:i (21.6%), "not v.Drking"
(48.3%) and blue collar group (i"-t,1c ).
The students from these backgrounds
are not likely to occupy the same job as their fathers due to university
education. In fact, they are nore likely to
occupy a white collar or
llB.Jlaganent jobs. What is at issue in the equal opt:Ortunity indices.;is the
relative chance for mobility anong students of different sxio-profession.
He could have he,d another idea about intergenerational ITObility using
the grouping of students by the family's inoome. However, our data, both
for the Ivory coast and the student populations are not satisfactory.
- 229 -

---

CHAPTER IX
SUMMARY, RECOMMENDATIONS AND LIMITATIONS
In this last chapter, we bring out the main findings of
our investigation..; we suggest SOme direction for dealing wi tIi
problems raised throughout this work; and we caution the rea-
der on generalizing our results to lower levels of education
in the Ivory Coast, or to other universities in Airica.
A.
Summary
This dissertation had three main objectives:
(1) To assess the current socio-economic composition of the
students enrolled at the National University and to determine
the factors which have contributed to its formation.
(2) To
analyse the financing of the National University to under-
stand the allocation of resources to schools and research cen-
terse
(3) To assess the equity issues involved in the current
university scheme.
With respect to the socio-cconomic composition of the
students by schools, we found that nearly half of the students
population was allowed to enroll into the first choice of
school expressed when applying to the University. Tne National
23U
"

---

Commission for Student Orientation tends to grant this first
choice when i t is in line with the stUdent's area of specia-
lization in secondary school. A distinction higher than
<
I
"average" obtained in the Bac exam increases the probability
of having one's first choice of higher education granted r
Higher socio-economic status, however, does not appear to in-
crease the probability of a student's satisfying his orher
first school choice.
When a student enters a school of the University,
factors
which seem to influence his success rate positively are, in
decreasing order of importance,
the number of students in the
school, the specialization of the school,
the distinction ob-
tained in the high school JAC, and the father's level of edu-
cation.
Thus,
the student who completes his or her Universlty
education with the least repetitiou is enrOlled in the school
01
economics, belongs to a middle income level family where the
father is employed in the agrlcultural sector.
Regional origin of the stUdent, a proxy fo:" cttnic bacK-
Lround,
is !lot a si.6r_2. .fj.CDr:t lCi-ctor in uf.:t.ermin.ing aCCess to Lt
appears to be a sigm ficant variable
I
I
2.31
-
, '.'

---

Those born in Bouakt:, in AbiclJo.n, :u: 2. " s ous-prefecture",
and in a village, tnve, I"cspeclively, leGs chancA or access
to the Unive~sity, although the highest proportion Cl
11
ur.j.vcrsit~ C~ltCc~ts (~3t3 %) ar~ borr. ::"[1_ ~. village.
The s(.u-
dcnt v;hose faLlle;' hi"l.s r..ad a hi.gher education or tro.ird.. nc; a:::d
O~r analys::.c of unJ,vE:':,c:::"Ly ~~ir.f'.r_cc ";.:-~(;~cc..'.·""t;~:
Lr-':'2.L Li!.c
internal source of lunti!:L C: ~ ....id s instt~ution is still net1j_-
~~en diversified.
The cll.i.dget alloc[lLed to the Uni V81'Sj,. ty ho.5 000ll c_ecJ :·.. r~j_r.g
The analysis 0 f a I'cri.od 0 f
ten ye(; IT. I c.8. :..c~ or. Jc'L p a:noun t
of the budget 0 f p.2.ch school,
the curriculum 0 f tile Sc400L,
':hp
LU~tRt5 2!'€
~l~.ocaL~)d according Lo these criteria.
232

---

I
i
\\
I,
The lClst.
task of tile dissertatioI'. wv..s L.G c;:.>::':jr;:.t..c the
i.ncon:e distributional impac t
0 f
the university I s
fino.ncing
pattern.
We vJcnt aboLLt th:is Ly 8Etimo..ttng Lhe cost ef .:"':.:::u
University.
fO~'C60ne is for students of' letters 2.ntl the lo':,-est
for F.cc-
no~i~ts.
Thlt Economi.c stud~nts contribute n!ost t.0 :hc ~tate
To assess the equity irnplicatj.cn of [he Dn~vcr?iLy':~
pattern of fina.ncing,
we classified th~ student po!:n::le.tloa
luto low, midcle, and up~0r soci~l level Groups; in odQi~iun,
,~i)C~i','- grouping by H.e SOC:Lo-p'olest:ion oftte
fDther-.
We
round that on a.verage,
tee upper soctal level :-8-
are grouped by incolne levels, or Ly
L~e hnUG81!01_~ i.terns
avai.lable at home.
The low sociol. leveJ. st.uC.';r.Ls VCE(~fit ~1:0
~_C:~,st from pUblic expenditure-suDsidy when Vie aLio'[)l.: UH~ ir,come
level grouping,
b\\;.t i f Vie denne soc~al CJo,Ec by household
items i t i,s tbc'mi,ddle social grou" '"hicli~iJe"efi.cS least.
When we cefine social class by socto-pro~r:sston, ttl080 Gtuden~s
from blue collar homes :::'ccel.ve the hj.ghest covernr:,cr.. L 0X-
233

---

· I
When we compute the amount of future income tax to be
II
paid by socio-economic levels, the heaviest burden falls on the
i
I
middle level, even when the future tax 1.8 2.djusted for the
I
subsic~.i-exr.F:r:C:iture rece:"ved.
The lo.l'gesL Ci~2;C of this
adjusted subs~dy is transferred to
tte UIlP{}I" social l.evel fI'om
I
I
the midfle onc.
When ~~ define socj.o-0cCCG~ic lev~l Ly socj.G-
through income tax Lo Govern!!'!enl. r0~OUrC8G, 2.nd :':cc: rir.ot '::O!'-
noi.versity tax- sliosi.G,y t.rans:er.
V.then \\'.'e
CO~!lj<:Ji:'S
Li.!.r; Ll_{JlJ~'~
~~'uhn~ u~ government expenditure on university ~tuderrts to the
~raciuates, i t appears that in total,
the state ~ill receive a
net profit from its current financing of the National Unj.versit,)'.
In 1981,· the IcVl 1 evel Eroup financed the largest share
of the Ull-~_versity budeeL. (28 %J.
But thj.s G2.rrc t::roup alDo be-
nefitt0d the most from the government expenditure-s~bsidy
in p~oportion with its contribution.
Th~ cOE',t-bcnefi:' r'n-LJ.o
of attEnt~tn[:; the University rj,ses "'jj.th
the 181/~1 of inclbme.
Wc conclude fro~ this that the finoncinB sch~~c is verti.cul.ly
eq\\litab-le.
23'+ -

---

Because soc:ial mobili.ty for students from rural o.l,d unm,rloyed
social background is low,
the financing sclleme is horj,z.lDntally
inequi table.
B.
Policy Reco~~endations
require appropriate r"emedj.es can be gro~ped into three cnte-
gories
\\ 1) The selec tlon o.~d oc.mtssion in to schoolf, 0 f t.he
Uni versi ty ;
(2) The hi.gh cost of Un:i.v0;-citj' education
~ and
0) The unequal dj stribution of tax burden for finan-
c:'ng th?- Un:i.versi. ty.
Soluti'J~s i'oC' ce::ding wj,th the first issue (admission
and select:ior.) ffillSt be s'lu[';ht in the policies of the l'l'ltinutJ.
Commission for Student
Orlentatlon which allocate students
into area of studj,es (Letters, Sciences, Technology and Voca-
cional Schools)
st.o.rting from the
first year of the second
level of secondary school (classe de seconde).
Clearly no one
Call detect all the intellectual capacities of a tiludent at
such an early age (on average sl:ud'~nts are no older crlall 17
wher. they reach 51-ace seconc.c).
Ivorian o.U t.hOl'itJ.es often
..': -."

---

justifiy this early orientation policy on its ability to best
specialize students and prepare them [or a more nppropriate
career prospect.
The literature on manpower planning and eccrlor;-,ic cycles
sucgest~-)that there vall necessarily be a r.JlSm<3 tch be tweeD the
projected labor market
ce!nand and the output of the educaticD
system,
especially ill -:hi::.; SI:CC! l'ic caGe wr.cr. j. t
,,'.'ill tak.':: at
least seven years [or ~he student assi.gned into a:t area of
"seccnde ll to ~ntcr the lator mar'1{et with Cl Lc.:.:.chclor's d8g~8C.
If cuch ~~ ~~rly specialization j.s avoided,
resources allocated
to ci ffercnt types 0 f higher educat.ion (grandes eco1cs and
un:'.vcrsi ties) pool"d together may help in ot)ening
,"ore s,,·ace
for more BAC holders.
Se2-cetj.Gn j.nto all <1I"C,-: or ~<,;ci~l.!..z.a.tion
should only be done after two years of university ec.uco.tion.
The w.sis for such a selection could be series o[ school and
socio-econo~ic background variables constructed [ro~ studies
on current success rate at the BAC exam but mostly from success
patterns detected in the schools of the University.
The second major iS2UP. ~·<li..scd in thLs G:Lsserta tion CO:'l-
cerns the high cost o[ University education.
236

---

The analysis of cost components ('['able 6-5) i.ndlcates t;hat
instructional cost represents for Science and Medicine more
than 70 % of the total pUblic expenditure per student and
at least 40 % for other schools.
Salaries paid to the faculty
represent 50 %of the instructionaJ. costs.
In Science in par-
tiCUlar,
62 % of the total salary pald in 1981
~o t;h0 faculty
go to expatriates wto represent 52 %of the teachers.
A pos-
sible direction for future cost
reduction appears
to be a
policy of recrui tine; qualified nati.onal
teachers vihose
salarieE:
are insti tu tionaly
set presen "Lly Cl t. !:lal f
the amoun t pn::Ld to
thetr expatriate colleagues)
for the sa."TIe degree and years
of experience.
In all the schools the amount of public expene.i ture-
subsidy received from the
University is increased by the
high repetition rates existing at the University.
A study
on the determinants of sUCCess in each school may help i.n
implementing policies which will reduce the years spent in
the school,
and hence the amount of expenditure-subsidy
237

---

I,
, :
I,,
I'
given to students by the University.
We touched OD the financial secrecy in which the
CNOU operates.
In view of the significantly large budget
,
allocated to ~his institution, and the impact of its mana-
gement on the stuci,,:~':..s·.iife, tIle cu!':rent admini.strative
separation between CNOU Dnd ~he Universlty is ill advised.
Savings can certai~lly be n!ade if th~se two institutions
pUL
their resources toeether.
In concluding Lhis wOl'k,
we wish to sug6cst its
COlltribution to
che ongoing discussion on equity in cduca-
tion finance.
Previous studies of educational production
function have dealt with inequabty in educational output
per se (for instance,
perfor~ance in scholastic achieve-
men t).
In the seventies,
researchers concerned themselves
with Lhe econo",ic ;Jc'o:i.tability of educational investment,
238

---

concentrated their effort on the role of education
in shaping the income distribution of a country.
In
the late seventies and early 80's the concern seems
to have shifted onto the role (or lack of role)
of
the state in educational policy, whether i t is in
the distributional effect of its educational fin~r.c0,
Or the apparent failure of ed~cation to induce social
mobility.
This study has
tried to SL.OYi tho.t. paf;l,.
concerns OVer educatiGn~l success, and todo.Y's about
inconc distribution are interwined,
especially in a
country like the Ivory Coast, and should be dealt
with globally.
We do so by integrating into one
analysis, inequities in admiscion policy, in~qui_ties
in scholastic achievements,inefficiencies in educa-
tional
investments and finally,
inequities in the
distribution of the cost and benefits of educational
investment.
239 -

---

I
,
c.
Limitations
We started this dissertation with our am-
bition of analyzing the redistribution of earnings
of lvorian students enrolled into all levels of the
education system, both in th~ Ivory Coast and abroad.
During the caUl'se of our research vc r'calized the
huge dimensions of the project ~nd were com~:clleci
to limit it to Ghe National Univers~ty.
Vie have
raised the policy implications of limiting our ana-
lysis in this way.
Given the fact
that university
students already represent a prj.vileged grou!),
any
policy that reduce inequali ty in the financing 0 f
university education could at most &ffect 5 % of the
already fortunate few s tuden ts.
To develop a Cla tional
policy for reducing earning inequality through educa-
tion one would have to extend the analysis in this
book to other levels of schools (see,for exe~ple,
Jallade, 1971+ ; 1977).
A Illajor problem wc faced all 2long In the d~b~e~t~
tlon was the lack of data,
the pauclty :Ji the data

---

1
1
I,
"
,I
available, or the restrictions put on the circulation
of data related to educational finance and income
distribution.
To the extent that the approximations
we have attempted are close to reality,
the analysis
in this work can be said to be a good approximation
of what more and better data would show.
~_nally, this warl: has SUf~Cl'cd from a laclc
of research alia data on ;
( I)
the :!!ajor costs inGre-
dients of the University,
(c)
the ta:c incidence for
socia-professional and income groups,
(3) recont in-
come distribution analysis in che Ivory Coast,and (4)
the social mobility Over time of Ivorians.
':lhcn these
data become available,
then we will be able to attempt
a more thorough analysis for' all levels of education.
With such an analysis conclusions we reach l'Iill serve
as a basis for a national poli.cy of educational finance.
-
241
-
. "'.' .. '

---

FOOTNOTES
Chapter II
1 •. page 6. The debate has centered around Hansen and Weisbrod' s
paper published in J.H.R. (1969) on equity in the financing of
higher education in California. The major protagonists in the
debate have been: Hansen and Weisbrod (1969). VS. Pechman (1970),
then a reply in Hansen and Weisbrod (1971). Other major
participants have been: Hartman (1970), Conlisk (1977) Miklius
(1975) Mc Guire (1976), Sharkansky (1970).
2. Page 7. The reader should refer to the proceedings of a seminar
on the issue published in the supplement of J.P.E. (May. June
1972), if interested in further discussion. Rawls (1971) is
another good reference but for a broader:discussion of the issue.
3. Page 11. This section dwells on Fields (1971) but has been
adapted to the purpose of this dissertation.
4. Page 22. Actually, .fiTe studies were published when we started
this review of the literature. However the fifth (Jallade,1976)
on Brazil has been subject to controversy (see Fields :1980) and
was therefore intentionally ignored.
Chapter I II
I. Page 40. The Ecole Normak Sup~rieure des Travaux Publics has
now moved to a new location in the city .,f Yamoussoukro and IS
no longer served by the CNOU.
- 242 -

---

I
2. Page 41. In 1971 a student's strike which began with
a discontent for the operation of the CNOU food service
1ed to an overall questioning of the University system
and ultimately to a general protest against the Ivory
government.
3. Page 48. The length of time corresponds to the time
period students are allowed to register for the academic year.
Chapter V
I. Page 30. The "Globalisation Agreements" between France
and many Third World countries (with the Ivory Coast in
particular) stipulates that France shall support the salary
of a determined number of technical assistants in various
fields, bur mainly in teactlliring. 8eyond the agreed upon r;uota,
the Ivory Coast must take the full cost
of the assistant.
Even when the assistant falls within "Agreements", the Ivory
Coast must often support the cost
of housing, the annual
vacation, and other minor expenses.
Chapter VI
I. 154. For a discussion about social discount rates in a
development
project see any standard World Bank manual on
project analysis, or for a more theoretical approach see
Baumol (1976).
2. Page 162. I wish
to acknoledge here the assistance of
Colette YAU in the search of appropriate data among the
piles of government documents.
3. Page 171. Starting fcom this section, all money figures
cited in this dissertation are expressed in CFA Francs If
not speci fied otherwise.
- 243 -

---

4. Page 1978. Cublier uses in his estimation of the cost of a
meal at the CNOU restaurant, the annual reported
food expenditure
extrapolated on 9 months, the official number of CNOU beneficiaries,
and the number of meal served per day. This approach underestimates
the cost of the meal, for
it ignores the 8ctual number of CNOU
restaurant users, and the number of meal discarded.
- 244 -

---

APPENDIX
A
QUESTIONNAIRE
CENTRE IVOIRIEN
DE
RECHERCHES
ECDNOMIQUES
ET SOCIALES
( C IRE S )
08· H.P. 1295 - AaIOJAN· 08 -
COTE
D'IVOIRE
Le que,co'm" ... ,e Q~e rv),,, """" dem.nc¥>'" <.le 'empl" "<In....,".' I)'lUl bul Je ,.,o,nnt>Itc, dn .J<'lnn-.
HonOm"l""" .1 ......ut, IW r':",Junr ,,""'~n. I" ( 1.1l..~ _,,_ I.... ""'We J~ ,"e' ,,,fmmllnn, po<D
"'''''''''
.J ... ,"""-l(1 .,,,,nl ~ C"O"na,lre un ~u m'<lJ' le ""1,..,, """<.1"""". I. , ... n~'. o<o.J.mlll"" Je en •...:,.,....
cMC'I >In .. <lU~ le ".".. ~I gk,h'h"" Of"" oI(Jnll~~' '''''''''Ue~l J~ ~ .. tr>r .. , ~ ... !.,ne' </",nonvmU
pour
'''',,' I"" p.l.f1l"p..'U ~ I"enqucle. ,\\I,n oJ·~"<tn<.lU rk"'emcn, ,~. "b,e~IlJ'. n",,> ,-..,,,. P' ......on. ,J·ob ...........
"".:I<'me"' I.., ~nn,.. n" ""unIt'
!"l
Il:ep.. ndr~ ~ ,n,,, .... le' q,u,,,n,,, .,~~ I' rn~me '''en''''n ., ,l~ r,\\,," '"'"
I""~ QUe p"~"Ole .
"'e """In '''.un~ qU''''WH' qu' "'H" C(JnCCTne.
3°)
/eUIUu
n~ ~.... d.""" • .. )(,~ Q"e,,~>n"~Il~ " '''u, ,·n .,," '<'\\u ..l~ ""p .. " " "'''IS n ~I~, pLO
l....-mlC'" ..l. nUIO".hl~.
D3"' I.. ..lou. ' ' ' . le "·I"",n~, ,lo .. , ~ j"",..l'~"" chIn.• ",.
J.
H.
P1G,\\rIEN,\\N
Dtre,lelll
Ju
r. I. R. E. S.
QUESTIONNAIRE
1°)
EN$EIGNEMENT SU?EHIEUR
Nom ae 1""IJDI,,\\pmenr
. 2 Pay\\
_
Eco1e. F.x:ulle et DpparTem~nr.
~
_
6
D"l~ cfenr'~~ dan\\ l'Enloe'gnernenl SUP""+:'Uf - - - - _ . _ - - - - - - -
A,.,nee(~l MedoutJre+:,\\ ,'\\10'" 0
5,
0
OVI
.Jnn,,+:,
'0,,0
fO'IO
:>luI
"
"'
~Ol \\ 0
0
" J1111~t
: ( ) I I O
",,0 p'UI d,
101\\
J'
,nn.."
IO'ID
.,,,0
:JIU\\
d'
0
rOI~
.,')
Jnn p ,.
'01,0
",,0
plu\\ d'
1~'1 0
,0
,
.,,,0
J"rw+:,
" " I D
2
plUI "
:0'\\ 0
,
5'
'0,,0
,n,.,,,~
2
f O l i O
plUI
" 2 ~O'I 0
I
!J
Fat:vlle. Dep.lrlem+:,nt Du Eca/e O'J .-au, .,\\i+:'l pdll+:' au mall1~ une dl1nee er J'Jel JD.)n'lOnne
N," 0
S,
0
Our
;:JC"I:,>
0"
:::co1e
- 245 -
......,:..

---

L· J
Nom d" I'kolt
_
L· <l NMu." de I'kol<l! S«ona.llre .
Publiaue 0
Prl~k
0
Contl"Hio"neHe
0
, 5 ClaHt(~1 Aeaoubl~~lsl
NanD
S. ou'
0
0,
6°
10'~
la,s 0 plus "
loil 0
0,
5°
~O,!
101s 0
plus "
la"
0
,u
0,
lo,~
lr)is 0 olu! 0.
to's 0
:;0
0,
:o'~
10'1 0
plu~ d.
10'$
0
,0
0,
,
10il
la"
0 plus " la,s 0
1°
0,
10'$
10'1
0 plus " 10" 0
0,
Tl"m,ndl~.
10"
10,~ Op:u, "
10'$
0
6 A~~l·~PUS deja ell~ eJ\\chJII~J )
Non 0
Si
0
OUi
CI.HS~S
Ann~~ d'oblenuon du BAC OU dUlre O,olom~ e<lulvalenl
~_~----=~-----
.\\1enllon . ire ~ B'en 0
9,en
0 AS\\~l S'en 0 PaHat>.I~ 0
/J
S~f1~ <lU BAC
., .'.J 0 ",0 aDeDoDEDFDG' 0 me 0
o
CJpKI r~ 1''' Oro'l
E~Jmen SI-lP.'C,dl 0
'>'utr~~
Iprecll~f! ~____
_
.
_
L 10 FdCulle. OeOa'l~menl DU Ecol~ cnO'$' en T~rm,nJle
(par old,e LJ~ p,~le,ence ~.pr,mee I
11)
_
i 2)
'"
- - _ . _ . _ - - - - - - - -
2 11
Faculle. Oepdrlemen[ ClU Ecole anr,;)ue
- - - - - - - - - - - - - - - - - - - - -
- 246 -
'\\"

---

}O)
ENSEIGNEMENT PRIMAl RE
L,eu(.1 d. 'reQuenlalion (10'1110':1'
villl! et quar\\ler I
_
J ~om Cle l'ecOlt
Publ'Que
o
o
J
5 ClaUt(11
Redoubleelsl
000
o
5' OUl o
ePl
o
~O'S 0, !O'S
Olt,a 0-
la,s 0
en
0,
o
'0'1
!O'l
OIUl d.
la,s 0
eEl
0,
o
!O'l
la,s
OIU\\ co
10'1 0
eE7
o
!00l 0, la,s
OIU! " 10 ,1 0
0,
CMl
!O'l
lo,\\. 0 :J"Jl <J.
(ail
0
C:'>1?
101\\ 0, lo,~ 0 D'ul '"
/ail
0
J
6 A~e~·~aus ~le delil exclullsl ?
'00 Cl
5, ou'
0 Clanel
~al
Durilnl lOule ~Olr~ 1C0lilrlle a...el· ... OUs ~te an'It~(el Cle ia<;an 1U011anllelle. 'inancu:r~ment. m~l~r;ellemenl ou ilulre.
OM une 0'.1 o!l')Siel..il~ pel">Onne~ ;;u\\re que ·.Dlle ~re, mhe. DU tu!eU! l~al )
I E:-emoles d'anllance . imal'lCemenl Ira', d'o!!udel, IU[eur au \\o!t:onda,re, etc .. 1
Non
0
Dui
0
Aopelans celle per~nne ... otre '·8IENFAlTEUR
Prec,ser : nalure de I·Jssiuance Ict. ~"emple e,..QeHus)
[ell. Ir~re. t,,,nce(el, iamille elOlgnee, aucun lien, erc .. 1
Pend"n! comb'en de lemps a dur~ celle aUlllanee __ ,.
_
J .
,:,. ... et· ... ous ele ~ la cnarge de ... otre oere b,ologlQue ou de ... Olle [uteur legal oendanllOute ... Olle sc.ol¥'le ?
o
o
o
P~re JdOpl,1
,'lOTE
Tout au long de ce ouelllonnaue. noul util,\\onl le lerme·· TUTEUR LEGAL ., dans son lerH lur;Clique c·eSl
,l dire loute person ne lenant I,l'u (ll' pe,e de ... anl la LOI ,l une autre dontle oi!re blololJlque ell df!ceoe ou lug!!
'ncapable oar le [rlbunal.
Le lermill'·· TUTEUA ,. oanl Ion
emOlo' cour;)nl en milieu ~lludlan!in, correspond 'Cl ~ norre le-rme-
.. BIENFAITEUR ". Amsl dans celle en<luele 1.1 personne Ct'lel OUl \\iOUI a\\fe~ sejourne penClanl ...0\\ etuCle-\\
·,o!t:ondaore ell \\fOlrC " 81ENFAITEUR ,. el non \\iOlre lUleur. lJeUllle~ en prendre aHm nOle Dour la IUlIP
du auell,onna,re.
- 247 -

---

I
'I
Ii,
i
Sf :)J,~(ll (j,plom~
D"'('\\t'f I~ (j'oIOm" 0Jr>\\ Id CJ\\~ c.Ju
QUI
S,nOn
,:n<:I"1".
I10f\\ IJ CJle "pprnD''''!,
;>~'e ou tuteu' '"gal
~,,,
a,enl~Lleur
00'
cnc
'JU;
'Cc
000
000
:" \\IE~\\U
I·.,om '0 o,pl'm
'n~ cL (ll()one
{rTm CL LloO)me
I
" »,ul"nld.. f',.ln<:,I"
~ .~ Eeo l .. ",'ma"" '.In, (ErE
I
,
,
::~ole ;>, 'ma" .. .,,,,·e cErE
I
I
S J Eeole S"conOJ" ~
\\
\\0 c,Cle '.JIlI tJ'O'ome
I
I
I
I
I
,IVt'C
"'Dlum'"
I
I
,
I
I
, Eeole S.'COJlIIJII"
"
20 cycle
"Jn~
I
I
" :)1,)lne
JVl'C
,1,Ol()me
I
'" Enle"lnemerll Suot',,~ur
I u C'/cle
·.Jn~
(],plome
,1Vt'C
(j,p'nrne
~ 'l tnlt"gnemen[ Su[)er,etH
j() cycle
'•.Jn~
,I,pIOI11C
-
JV\\'C
(j,nln,ne
I
; Erl~"''J''ern~nl Sur!""e~"
I J
JO C',cle
'..J"~ (J' PIO'l"~
I
I
.Ivec
':I::JionH~
'8 SlJ'J~\\ C;~ ::o,md,'on
',JIl\\
C'PI()")~
J"~C
' :".""rne
- 248

---

EMPLOI
;>~, ~ 'J\\J Tule", legal
'.\\e' e
3,ellta'leur
ICOCfle,
CJse JOP,op"l'el
UUI
11,)"
'JLi'
."on
0 0
coc
"
I
I
6- ,
~OncIlO(\\ Puhl,qul'
I
I
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- 252 -

---

Non 0
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cocner I~ ca~e
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FQNCTlQN
P~fe ou TUUWf leg.al
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Bi,nfllt'fUr
Membre 01.1 Bureau Poli\\lqull
Membt'1l du Comlte D,fecleur
Membre
du
Gpuverll~ent
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\\ Deput!!)
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Conselller ecOnomlQU!! et SociAl
Secn!uire Gl!nl!rAI de Sous·Section
Secfeuirll GenerAl de Svrxlicar
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Mihunt dl! lhe heurl~
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B-1
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253

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- 256 -

---

APPENDIX B
A METHOD FOR GROUPING STUDENTS AT THE
NATIONAL UNIVERSITY BY SOCIO-ECONOMIC BACKGROUND
Grouping a given population under a common characteristic is not an
easy task.
In the case of socio-economic status
research many methods
have been propounded in the literature.
More often one uses demographic
measures which may
rely
on the
income
or earning of the household or
that of each member of the household.
A second commonly used measure is
the geographical location of the individual, be it a region of a country
or a neighborhood in a city.
A thi rd approach, probably popularized by
the Coleman Report
(1969), and more and more used in studies of socio-
economic status in the Third World
(see for instance Fry, 1975) is the
use of household items possessed by the unit under study.
The rationale
behind the use of household
items
is that
during a survey individuals
may not report their true income while at the same time they may reveal,
willingly
or unwillingly,
their material
possessions.
The researcher
may observe certain household items on which he may rely to evaluate the
respondent's
reported
income.
To
better
assess
the
socio-economic
background of
Ivorian
students enrolled at the National
University
in
1980-81, we have adopted four methods.
The first approach uses household items avai lable in the homes of
the students.
We shall call
it the household items grouping.
A second
method we call income grouping,
relies on the income or earning of both
the
father and mother of the students.
The thi rd method adds to the
income of the father and mother, that of a "kinsman", Le., a person who
has
significantly
contributed
to
the
education
of
the
students:
the
- 257 -

---

kinsman
grouping.
Finally, we group students by the socio-profession
of their father in the socio-profession grouping.
1.
The Household Items Grouping
In question number 8-6 of the questionnai re
(see Appendix A) we
asked
the
students
a
number
of
questions
related
to
household
items
available in many
homes in the Ivory Coast.
The list of the items
is
provided in Table B-1.
In
order
to
assess
the
reliability
of
the
answers
given
by
the
students
on
the
questions
related
to
the
household
items,
we
fi rst
appl ied to thei r answers a test of Guttman Scale.
Each item was coded
o
in a binary form,
one
(1)
i f the item is
available and ~if it is not.
The correlation matrix between the items reported in Table B-1 indlcates
a
strong
relation
between
the
items.
The
va 1ue
and
signs
of
the
correlations
are
of
the
expected
magnitude
and
direction.
Four
statistics computed by the test are reported at the end of the table.
The first statistic is the coefficient of reproducibility
($)
It assesses the extent to which the respondant's scale score is a
good
predictor of
his
total
response
pattern
on
the
household
items.
Statistically
it
is
computed
as
follows:
Let
us
call
Error
(E),
a
negative response to a question about a specific item when according to
the
general
pattern
of
responses,
a
positive
answer
shoul d have
been
gi ven on~ a negat i ve
response to the question
when a positive one was expected.
Let US call
N, the "non missing"
(non
Error) response of the respondents.
The coefficient of reproducibility
$ is computed as follows:
-
258 -

---

T A B l
E
B
I
G U T T M A H
5
C A l
I
H G
•••••••••••••••••••••••••••••••••••••••••••••••••••
• • • • • • • • •
G U T T M A H
5 C A l
E
(
E F F E T 5
1
U 5
I
H G
• • • • • • • •
'..lASHM
',JASHIHG MHH!",'E
DIVISION POINT
I . 0 0
ElEC
ELECTRICITY
IH
HOUSE
DIVISIOH POIMT
I .00
SE~V
SERVANTS !H HOUSE
D(VISTO!'l POHH
I .00
P~I'IEH
PRIVATE VEHICLE
DIvISIOH popn
I .00
FllIG
l!'EFRIGERATOR
DIVISION PCIHT
I .00
JOB V EH
JOB
vEHICLE
DIVISION POIHT
I .00
sn:.~
STEREO
DIvlSrOH
POIHT
I .00
Haw
BlACK
WHITE "
DIVISIOM POIHT
I .00
" 0
"'..0.010
OIvISIOH palHT
I .00
rI/COL
calOR "
Dlv1510H POIH,
1 .00
,
CLlM
AlR COHDITIDMER
01Vl510H PO! H T
.00
CHFO
HOT lolATER
01'.115101"1
POINT
I .00
. • • • • • • • • • •
,
KESP
FOR VALUES EOVA l
TO
DIVISIOH POIHT AHO ABOVE
• • • • • • • • • •
YUl~'S Q.
IJASHM
ElfC
SERV
PR!VEH
FRIG
JDBVEH
ST ER
T\\lBW
RAO
IJASHM
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0 · 599~
0 .7'119
o. ~J1,3
0 • r;, <;, 0.3
o.
,.
,
ElfC
6994
,.
· COO!l
0 .~725
o. 9003
0 .9 :D7
0 .9322
o. 9 1 70
0 .96 6 7
0 · "
SERV
0 .~.342
0 ."725
I · 0000
o. 9290
0 ."62.6
0 . "2 32
0 .!o025
0 .7602
o.
,
PRIVEH
0 · !o 1~ 0
o. 900~
o. 9290
· 00 Q0
0 .!o552
0 . HH
o. 77 24
o. "] 7b"]
0 ·
,
,
"6:
fR 1 G
0 · 5998
0 .n.3]
· !o6 Z6
0 .!o552
· 0000
0 .7Hl
0 .64.3 4
o. 9 166
0 · ,.
,
JOBVEH
0 .7919
0 · on;::;::
,O! 2 ~2
0 .8679
o. "]Hl
I • j) 0 0 0
o. 14 l!o
0 .6!o 2 9
0 · J.
,
STER
0 ~~ .. )
o. 9170
0 .!o 0 2 5
0 .772"
0 , Ill, ~4
o. 74 l!o
I . 000 I)
0 .5!o67
o.
, ,.
T\\l8~
o. 4403
0 · 9!> 6 7
o. 16 02
o. iH"]
o. 9 I 6/:,
o. 6!o29
0 . 50! b "]
I · 0000
,
,
,
RAQ
o.
.,
~!o 9 4
0 .6.347
.
· 7S 07
o. 60Bn
0 .~2B
.3409
0 .4.352
0 .!o409
HCOL
.,
0 .M!o4
0 .9276
o. 1225
0 .'i05!o
0 · 9 I ! a
0 .7 no
0 .!o 3 \\ '2
0 ,t. ~ 9 5
0
,
CUM
0 . 85 ~ 7
o. 95 \\ ~
o. a79 ~
0 · !oH I
0 .o!22~
0 .!oOH
0 .!o 0 I 0
0 ' 7856
o. .
,
,
,
CHFO
0 ,H66
. 9!o 5 ~
o. 9006
0 .M79
0 .674~
.Bl04
0 .059Q4
0 .6"51
o.
BISERIAL CORR
SC~LE-ITEM
0.70"9
.6622
9400
.7721
o. "] ~6 4
0.7"061
· 7 0 '16
o. 4.
STATISTICS.
COEFFrCIE~T OF REPROOUCIBILITy = 0.91~O
MIN!~un MARG!HAL
?E?RDDUC1DILIT~
= 0,7926
PERCEMT TMPRO\\lEMEHT = O. 120~
COEFFICIEHT OF SCALABIlITY = 0.5~06
- 259 -

---

N
1
o < ~ < 1
E
The coefficient of reproducibility in our sample is 0.9130.
A second
statistic
given
by
the
test
is
the
minimum
marginal
reproducibility coefficient
(~). It indicates a minimum coefficient of
reproduc i bi 1ity
gi ven
the
cutting
poi nt
used
(i.e.,
1)
and
the
proportion of people passing or failing each item.
Let M be the maximum
margi nal response for each item.
Let i be the item.
Let T be the total
number of correct responses to the same item
T
~
= I
Mi
~
0.7926
The third statistic is the percent improvement coefficient
n.
Here,
n = 0.1204.
n indicates the extent to which
~
is actually due
to the
responses pattern and not to a clever selection of items.
The
smaller
n
is (closer to 0), the better it is.
The
last
statistic
is
the
coefficient
of
scalability
(f).
It
shows ho,; cumulative and unidimensional
the scale of the items is.
It
is computed as:
J
1-~
J = 0.6806 in our sample and indicates an acceptable unidimensionality
of the scale.
- 260 -

---

A biserial
correlation
is also gi<en for
each
item and
indicates
the correlation of one item to the sum of other items.
The four coefficients given by our Guttman Scale test allows us to
say
that the household
items
we
used
passed an acceptable
requi rement
for
unidimensionality
and
cumulativeness
and therefore
can
be
used
in
building
a
scalogram.
We
construct
such
a
scalogram
using
a
few
household
items
available
in
many
homes.
Table
B-2
indicates
the
different weights we applied to each item in a proportion that reflects
its frequency in our sample but also its availability and monetary <alue
in the
Ivory Coast.
The differences
be .tween weights does not measure
exactly the differences
in monetary
values
between the
items.
It also
takes
into account the social
value attached to the items in the Ivory
Coast.
From Table B-2, we constructed four variables which we use to group
students.
The
fi rst
variable
(HHscore)
is
essentially
based
on
the
fami ly
residence
(item No.
12 to 15 in Table B-2).
The second variable
(Item~ClP) used items 1 to item number 8.
A third variable (ITEMB) uses
items
9
to 11.
Finally
a last <ariab1e (score) was constructed using
the previous three variables:
Score
HHscore + ItemsCo + Ite~
The last step we took
in constructing the household items grouping
was
to
divide
the
cumulative
frequencies
of
SCORE
into three
levels.
The low level
comprises approximately the low 70 percent of SCORE, the
middle level
around the middle,
20 percent and the high
level
close to
the top
10 percent.
In choosing three divisions we wanted to caputre
-
261 -

---

TABLE B-2
Items and weights used in constructing a socio-
economi"c backgrou/"\\dfor students enrolled at the
National University
Scale in 1980-81
Number of
I t em
Wei9ht
Possessors
1.
Rad i 0
5
1,097
2.
Electricity
10
902
3.
TV (Black and white)
15
582
4.
Refrigerator
15
568
5.
Stereo
20
217
6.
~ir Conditioner
25
203
7.
TV (color)
30
178
8.
Hot (runnin9) water
40
185
9.
Servants
N x 50
208
10.
Private Vehicle
~~ x 100
318
11.
Job Vehicle
Nx 150
108
12.
Village for Residence
100
242
13.
Other cities for residence
200
723
14.
~bidjan for residence
300
233
15.
Rich neighborhoods In ~bidjan
350
64
Total number of cases
1,274
Note:
r~;s number of items possessed by each individual.
- 262 -

---

only
the
difference
between
the
extremes
in
the
distributions
of
household
items
score,
given
the
nature
of
data
on
hand,
and
thei r
distribution.
In
actuality we
could
not
divide
precisely
the
groups
according to these percentages because the distribution of data did not
allOn' us to do so.
The real percentages used are reported in Table B-3.
2.
The Household Income Grouping
Regrouping a population
by
income
is a more
common
practice
in
economic research.
A lot also has been written about the deficiencies
in relying on income as reported in a survey type of research.
(See for
instance
Atkinson
(1976),
Sen
(1972),
and
Levin
(1978)).
The
main
drawbacks
are
first
the
disagreement
about
a definition
of
income
on
theoretical
grounds,
and
secondly
hO</
accurately
one
can
measure the
adopted definition of income.
In this work, we rel ied on the income of the household constituted
by
the
father <lI~A mother of the students.
This
choice
has a serious
drawback
for students who are employed and may contribute substantially
if not exclusively to the total welfare of the househol d.
However this
group of students constitute a very 10n' percentage
(11.4%)
of the 1,274
students we analyzed.
A second
inconvenience of our data is that the
information on the income of the household was reported by the students,
and
not
by thei r
parents.
We
were therefore
very ca ut i ous
as
to the
reliability of the
responses.
When a monthly
salary of the parents is
reported
by
the
student,
we checked
for
consistency
in the answers
by
looking
at
other
information
related
to
the
salary:
employment
classification, degree obtained, type of job, work experience.
When the
parent worked in a publ ic sector job,
it was easy to estimate a minimum
- 263 -

---

TABLE
B-3
Scores, absolute and relative
frequencies for three variables constructed from hous eho1d items
*
*
*
HHSCORE
ITD~SCO
ITEM.-B
N
F
%
N
F
%
Cl
F
%
100
242
19.0
0
104
8.1
0
897
70.4
200
663
52.0
5
398
31.3
50
135
10.6
300
227
17.3
10
45
3.5
100
160
12.6
350
57
4.4
15
516
40.5
150
55
4.3
20
14
1.1
200
14
1.1
u = 191. 98
25
11
0.8
250
3
0.2
(J
= 85.54
30
2
0.1
300
7
0.6
e = 2.39
40
185
14.5
350
2
0.1
u = 15.70
u = 151
(J
= 10.6
(J
= 2977
e = 0.29
e = 8.43
~lote :
~ = Score obta i ned
F = Absolute frequencies of cases
*
The i terns i nc 1uded in the variables are indicated in the text.
u = Mean
(J
= Standard deviation
e = Standard error

---

monthly
salary
based
on
the
government
job wage
scale.
Otherwise we
relied
on
the
ongoing
wage
for cOlfllarable type of job
in the
private
sector.
We chose to use the minimum possible wage,
based on available
information,
to
be
conservative
tn our estimates.
For
self-employed
parents
other
than
farmers,
the
income
estimate
was
less
straight
forward.
We
rel ied mainly on the figure
given
by the students.
When
the self employed parents work in a sector of activity where the minimum
income could be estimated, we
relied exclusively on our own estimates.
In this category of job we include pharmacitst, lawyers, doctors.
We devoted more time on estimating the income of parents from the
rural area.
In question
5-2 we asked the students questions related to
size of lands, type of crops produced, the annual
production.
When the
type
of
products
were
cash
crops
(coffee,
cocoa,
cotton,
pineapple,
etc.) we were able to estimate the annual
income, based on the quantity
reported,
the type of crops and the government's annually fixed price.
Whenever we were not able to estimate an income, whether because of
inconsistencies
in
the
answers,
or
for
lack
of
information,
we
considered that the income was missing.
In a further treatment of our data we estimated the missing values
in one variable regressing all
variables that are correlated to it and
satisfy a statistical
test of significance.
This method is more robust
than the traditional
technique of using the mean.
We have expanded on
the
estimate
of
the
missing
value
in
the
section
on
missing
values
(Chapter 3, Section ,..1).
- 265 -

---

TABLE B-4
Distribution of three variables used to measure the socio-
economic background of Jjrian students of the National University, 1980-81
HHGROUP
INc;..!?ROUP
TINC.-bROUP
Absolute
Relative
Absolute
Relative
Absolute
Relative
Freq.
Freq.
Freq.
Freq.
Freq.
Freq.
%
~
10
%
Low Level
892
70
886
69.6
900
70.6
Middle
Level
276
21.7
257
20.2
248
19.5
High Level
1D6
8.3
131
10.3
126
9.9
Note:
Variables are defined in the text.
- 266 -

---

APPENDIX C
ALI'HABETIC LIST OF VARIABLES
#
VARIABLE
INFORMATION
LABEL
166
AGRI
FATHER'S OCCUPATION IN AGRICULTURE
117
AIDGIV
DO YOU HELP SOMEONE?
148
AREABAC
AREA OF
SPECIALIZATION OF BAC
45
ASSIST
ASSISTED BY SOMEONE ELSE?
150
BACECO
BAC WITH ECONOMICS MAJOR
149
BACLET
BAC WITH LETTERS MAJOR
152
BACMATH
BAC WITH
MATH MAJOR
31
BACMENT
HONOR AT THE BAC DEGREE
151
BACSCEX
BAC WITH EXPERIMENTAL SCIENCES
30
BACYEAR
YEAR WHEN BAC DEGREE WAS OBTAINED
97
BDAT
YOUR BIRTH DATE
54
BIACTIV
OCCUPATION OF KINSMAN
79
BIBDAT
BIRTHDATE OF
KINSMAN
75
BIETNG
KINSMAN'S ETHNIC GROUP
122
BINEDUC
KINSMAN'S EDUCATION
51
BINSTA
KINSMAN HAD ON THE JOB TRAINING CERTIFIC
165
BLUCOL
FATHER HAS A BLUE COLLAR JOB
98
BPLACE
YOUR BIRTH PLACE
110
BRFAST
TAKE BREAKFAST AT UNIV RESTAURENT
116
BUKEXP
BOOK
EXPENSE
107
BURS
IVORY COAST SCHOLARSHIP
95
CHFO
HOT WATER
102
CHILD
# OF CHILDREN
163
CHOIGIV
CHOICE OF DEPARTMENT SATISFIED
29
CLASDROP
CLASS WHERE YOU DROPPED OUT
6
CLASS
FORM AT UNIVERSITY
93
CLIM
AIR CONDITIONING
115
CLOTH
EXPENSES FOR CLOTHING
5
DEGROBJ
DEGREE OBJECTIVE
34
DENTPR
DATE OF ENTRANCE IN PRIMARY SCHOOL
16
DENTSE
DATE OF ENTRANCE SEC SCHOOL
7
DENTSUP
YEAR OF ENTRANCE AT UNIVERSITY
112
DINER
DINER AT UNIVERSITY RESTAURANT
4
DPTMENT
DEPARTMENT ATTENDED
144
ECONOMIC
ATTEND ECONOMICS DEPARTMENT
B5
ELEC
ELECTRICITY IN HOUSE
130
FAAGE
FATHER'S AGE
15
FACDROP
DEPARTMENT WHERE YOU DROPPED OUT
33
FACHOICE
CHOICE OF UNIVERSITY DEPARTMENT OBTAINED
52
FACTI V
FATHER'S OCCUPATION
120
FAEDUC
FATHER'S EDUCATION
73
FAETNG
FATHER'S ETHNIC GROUP
B3
FAHOUSE
FAMILY HOUSE OWNED
·134
FAINCOM
SALARY AND WEALTH FATHSR MOTHER
140
FAMINC
SALARY AND WEALTH FATHER MOTHER
76
FAMRES
PLACE OF FAMILY RESIDENCE
49
FASTA
FATHER HAS ON THE JOB TRAINING CERTIFICA
77
FBDAT
FATHER'S BIRTHDAY
156
FCHOICE
CHOICE OF DEPARTMENT IN HIGHER EDUCATION
114
FOOD
FOOD
94
FRIG
REFRIGERATOR
15B
HHGRUP
GROUPING TOTAL SCORE ON HOUSEHOLD ITEMS
125
HHSCORE
1ST GROUP OF HOUSEHOLD ITEMS
157
INCGRUP
GROUPING BY p~MILY
INCOME

---

127
I TEMB
2ND GROUP OF HOUSEHOLD ITEMS
126
ITEMSCO
3RD AND 2ND GROUP OF HOUSEHOLD ITEMS
88
JOBVEH
JOB VEHICLE
143
LAW
ATTEND
LAW SCHOOL
147
LETTERS
ATTEND LETTERS
131
LSALFA
LOG OF FATHER'S SALARY
111
LUNCH
LUNCH AT UNIVERSITY RESTAURANT
168
MANAG
MANAGEMENT POSITION JOB
101
MATR
MATRIMONY
145
MEDECINE
ATTEND MEDICAL SCHOOL
138
MENTION
DISTINCTION OBTAINED FOR BAC
53
MOACTIV
MOTHER'S OCCUPATION
78
MOBDAT
MOTHER'S BIRTHDATE
121
MOEDUC
MOTHER'S EDUCATION
74
MOETNG
MOTHER'S ETHNIC GROUP
50
MOSTA
MOTHER HAS ON JOB TRAINING CERFICATE
46
NASSIST
NATURE OF ASSISTANCE
119
NATAID
NATURE OF THE AID
137
NEWGRP
NEW GROUPING
159
NEWGRUP
NEW GROUPING
136
NEWSCOR
SCORE FOR ITEMSCO AND HHSCORE
164
NOTWORK
FATHER HAS NO JOB OR
RETIRED
108
ONC AMP
LIVE IN UNIVERSITY HOUSING
123
ORIGIN
GEOGRAPHICAL ORIGIN OF PARENTS
65
PABP
PARENT BELONG TO POLIT BUREAU
66
PACD
PARENT MEMBER OF COMITE DIRECTEUR
69
PACON
PARENT CONSEILLER
68
PADPT
PARENT MEMBER OF PARLIAMENT
67
PAMI
PARENT MEMBER OF GOVERNMENT
72
PAMIL
PARENT EARLY PARTY MEMBER
64
PAPOL
PARENT INVOLVED IN POLITICS
105
PARAID
AID RECEIVED FROM PARENTS OR FRIENDS
70
PASG
PARENT GENERAL SECRETARY OF THE PARTY
71
PASYN
PARENT TRADE UNION LEADER
87
PRIVEH
PRIVATE VEHICLE
57
PROBIN
KINSMAN'S PROFESSION
55
PROFA
FATHER'S PROFESSION
56
PROMO
MOTHER'S PROFESSION
35
PSCITY
CITY WHERE PRIMARY SCHOOL WAS ATTENDED
44
PSKDROP
PRIMARY SCHOOL DROPPED OUT
37
PSREPO
NO REPETITION
PRIMARY SCHOOL
38
PSREPl
REPEAT 1ST YEAR PRIMARY SCHL
39
PSREP2
REPEAT 2ND YEAR OF PRIMARY SCHOOL
40
PSREP3
REPEAT 3RD YEAR PRIMARY SCHOOL
41
PSREP4
REPEAT 4TH YEAR PRIMA
42
PSREP5
REPEAT 5TH YEAR PRIMARY
43
PSREP6
REPEAT 6TH YEAR OF PRIMARY SCHOOL
89
RAD
RADIO
47
RELASS
RELATION WITH PERSON GIVING AID
113
RENT
EXPENDITURE FOR RENT
100
RES12
PLACE OF RESIDENCE UP TO 12
84
ROONUM
ROOM NUMBER IN FAMILY HOUSE
160 . SAFGRUP
GRUPING BY FATHER MOTHER SALARY
63
SALBIN
KINSMAN'S SALARY
61
SALFA
FATHER'S
SALARY
133
SALFAMI
SALARY OF FATHER AND MOTHER
62
SALMO
MOTHER'S SALARY
48
SCHARG
,RELATION PERSON CHARGE OF EDUCATION
155
SCHOACH
ACADEMIC ACHIEVMENT
142
SCHOOL
SCHOOL ATTENDED

---

146
SCIENCE
ENROLLED IN SCIENCES DEPARTMENT
128
SCORE
SCORE ON HOUSELHOLD ITEMS
28
SECDROP
DROPPED OUT IN HIGH SCHOOL
32
SERIBAC
BAC SPECIALIZATION
86
SERV
SERVANTS IN HOUSE
20
SESKRPO
DID YOU REPEAT A CLASS IN HIGH SCHOOL?
26
SESKRPl
REPEAT IERE
25
SESKRP2
REPEAT SECONDE
24
SESKRP3
REPEAT 3EME
23
SESKRP4
REPEAT 4EME
22
SESKRP5
REPEAT 5EME?
21
SESKRP6
REPEAT 6EME
27
SESKRPT
REPEAT 1'ERMINALE
99
SEX
SEX
80
SIBPR
NUMBER OF SIBLINGS IN PRIMARY SCHOOL
81
SIBSE
NUMBER OF SIBLINGS IN SECONDARY SCHOOL
82
SIBSP
NUMBER OF SIBLINGS IN HIGHER EDUCATION
17
SKCITY
HIGH SCHOOL CITY
109
SKFUD
UNIVERSITY FOOD SERVICE
18
SKULNAM
NAME OF HIGH SCHOOL
129
SOPRO
SOCIO PROFESSION OF FATHER
90
STER
STEREO
104
STUSAL
YOUR SALARY
106
SUMAID
AMOUNT OF AID RECEIVED
118
SUMGIV
AMOUNT OF AID GIVEN
8
SUPREPO
HAS NOT REPEAT YEAR IN HIGHER EDUCATION
9
SUPREPl
REPEAT UNIVERSITY FORM 1
10
SUPREP2
REPEAT UNIV FORM 2
11
SUPREP3
REPEAT UNIVERSITY FORM 3
12
SUPREP4
REPEAT UNIVERSITY FORM 4
13
SUPREP5
REPEAT UNIV FORM 5
14
SUPREP6
REPEAT UNIVERSITY FORM 6
162
TINCGRUP
GROUPING USING FAMILY AND KINSMAN INCOME
141
TINCOM
TOTAL INCOM FATHER MOTHER KINSMAN
135
TOTLINC
TOTAL INCOM FATHER MOTHER KINSMAN
103
TRAV
DO YOU HOLD A JOB?
91
TVBW
BLACK WHITE TV
92
TVCOL
COLOR TV,
36
TYPRISK
TYPE OF PRIMARY SCHOOL
19
TYPSESK
TYPE HIGH SCHL
96
WASHM
WASHING MACHINE
60
WEBIN
KINSMAN'S WEALTH
58
WEFA
FATHER'S WEALTH
161
WEFGRUP
GROUPING BY WEALTH
132
WELFAMI
WEALTH OF FATHER AND MOTHER
59
WEMO
MOTHER'S WEALTH
167
WHICOL
WHITE COLLAR OCCUPATION
153
WRITCHO
RIGHT CHOICE OF SCHOOL MADE
154
YEARENT
YEAR OF ENTRANCE AT UNIVERSITY
- 269 -

---

0\\-\\\\V ER SIT(
(0!:'k(~ij:JjfJ
~',6~BIDji'-\\-I
APPENDIX D
UNIVERSITE D:ABIDJAN
-
27n
-

---

The c;L1.sk of the preceding page, no","' th2 eLlble~ of t.he ~;a tional
Universi~y. w~s used in initiatioll ceremonies ~y the secret
societies of the people of northern I~ory Coast. ?he ~~sk is
ooI'lpo.<-ed 0 \\
ele:nents of sacred aniJ:!'12..ls which have spl~cial
significance:
1.
the jaws of the crocodile ~hich is the s>~bol of the man
of po","'er;
2.
the tee th of the hyena, symbol of though t ?nd hwnan
knowledge;
3.
the ~usks of the hiPPopo~~Lus symbolizes n~an being and
wisnom;
4.
the be~k of the hornbill signifies the use of speech;
5.
the c2.lIleleon inc.icates t:E' a~ility ~o ad2.pt o!1eself to one1s
en'/iroI1IIient
and also s:{u:oolizes caution Ol...'ld o?portunism;
6.
the frog is the symbol of life and death,
the ability to
comrr~d fire, water and earth.
Tne choice of L,is mask as an enblem is the most explicit mission
given to tile IJational TJniversi ty.
271

---

APPENDIX E
NOTE ON PUBLIC FINANCE IN THE IVORY COAST
Higher education being mostly financed through public funds, it is
necessary
to
understand
the
financial
mechanism
which
channel
these
funds.
This
note
is
not
meant
to
be
an
exhaustive
stUdy
of
public
finance in the Ivory Coast.
Rather I<e wish to indicate here how money
is
derived
from
the
public
through
taxation
and
redistributed
in
the
form
of
subsidies
to
students
or
used
to
finance
the
National
University.
We approach the proolem ln two stages.
First, we describe
the
general
principle
of
fiscal
and
budgetary
policy
in
the
Ivory
Coa s t.
Second,
we
illustrate
the
general
principle
by
examining
the
19B1 budgets which are used in this study.
A.
Budgets and Taxes in the Ivory Coast
Since independence, the Ivory Caost has adopted a state capitalism
mode of economic development.
This option means that the state is the
major
investor
in
all
sector's
of
economic
activity
where
private
enterprise
is
inexistant,
insufficient
or
ill
directed.
Accordingly,
the budgets
adopted
by
the Parliament
of
the country are conceived tu
play these roles.
1.
The Iludget s
The
budget
sys tem
of
the
Ivory
Coast
is
very
complex.
Two
,
\\~~
types of budgets are adopted by/ Pari ialTlent: the ordinary budget (B.G.F.)
-
272
-

---

and the
Investment Budget
(B.S.I.E.).
A third group of bUdgets should
be
added.
They
are
the
so-called
"Budgets
Annexes" allocated to five
public institutions, such as the National Printing Company, the National
Press Agency, etc.
The
BSIE
is divided
into
three
subgroups:
the
BSIE-CAA
(BSIE
for
Debt Amortization Fund), the BSIE-Tresor (BSIE
for the Treasury) and the
BSIE-CSSPPA (BSIE for Producer Price Stabi 1 izat ion I'und).
In
general
BSIE
resources
are
used
for
government
investment
programs,
whereas
the BGF
is
used
for
recurrent
expenditure.
However,
this
general
principle
is
often
not
respected
and
the
two
budgets are
used intechangeably.
A few pUblic and semi-public corporations prepare their ChIn budgets
and
receive
earmarked
public
taxes
for
its
resources.
Municipalities
also adopt their ChIn budgets and levy specific taxes.
2.
The Sources of Revenues of the Budgets
One characteristic of public finance in the Ivory Coast is the
number of taxes which are earmarked.
Although the earmarking principle
is
generally
considered
inefficient
in
public
finance,
in
a
study
of
redistribution
of
taxes,
earmarking helps
to solve
the difficult
issue
of tax burden imputation.
The
Iyel
Finance
Law altered the sources
of
revenues
allocated
to
the different
budgets
of the
Ivory Coast.
The new resource allocation
is
indicated
in
Table
E-1.
The
table
pinpoints
the
complex
nature ·of
reSOtlrce allocation.
It also shows the precise proportion of the taxes
used
in
each
budget.
The
BGF
appea rs
to
take
up
mos t
of
the
tax
resources
and
has
the
most
diverse
funding
origins.
The
table
also
-
27~) -

---

TABLE E.l
Sources of Taxes and Their Allocation to the
Na t i ana 1 Budget
Nature of Tax
Applicable
Share going to Budgets
Rate
BGF
BSIE
BSIE
Municipalities
in ~
•
0(
, n 10
Tresor
CAA
•
0(
~
1 n 10
i n ~b
in %
*
*
8IC, BAC
Individuals
25
100
Corpora t ions
40
100
BNC *
25
100
ITS wage earners
1.5 +
1.5
*
CN
CN
*
ITS National Emp layer
12.5
9
1.5
ITS Expatriate Employer
17.5
14
1.5
*
IRVM
25. 12
100
2
*
[RCM
..
IRC
18
16
18
9
100
cons truc ted
12
la
nonconstructed
4,5 or 6
100
surtax
4,5 or 6
100
religious
0.2
Rea]
or 50
all
Es ta te
additional cent
20
100
profit on const.
5
100
'/alue of non const
100
sewage
100
-
274
-

---

TABLE E-l (continued)
Na ture of Tax
Applicable
SFG
SS E
Rate
Tresor
Tobacco Tax
100
~lcohol Tax
100
Fire Arm Ammunitions
5/6
Timber
100
Registration
100
Duty
100
Value added tax on import
13/1 9
6/19
Import of Beverage
Spec i a1 tax
100
Additional tax
100
OUS
100
DUS on Timber
55
Other Tax
lOO
-
275 -

---

TABLE E-l (continued)
Share go i ng to Budgets
Nature of tax
Applicable
BGF
BS!E
BSIE
Municipalities
Rates
Tresor
CAA
Fixed rights
18 to 350.000:
'8
CFA 10%
100
Proportional right
10
100
National contri-
but i on
10
100
Additional contri-
but i on
20
100
TVLLP *
50
100
Fixed rate
18 to 160,000
CFA
100
National contri-
but i on
10% of prl nc.
100
Additional cents
20% of princ.
100
Tax on commercial vehicle
100
Art and
principle
100
Craft
10% of principle
100
Value added tax
13/19
6.19
Tourism promotion tax
6
100
Oi 1 Tax
30
70
-
276 -

---

reveals
that there exists
almost
no domain
in
economic activity
in Ule
I vory Coast which is not taxed.
Table
E-1
does
not
show
the
sources
of
revenue
of
the
BSIE-
CSSPPA.
The
revenues
of
this
last
budget
is
constituted
by
the
difference
between
the
prices
of
the
agricultural
products
on
international
markets and the guaranteed price set by the government to
the producer.
Among
the
different
taxes
presented
in
Table
E-1,
taxes
on wages
affect most·
the higher education graduates we are studying.
\\oie shall
consider these taxes in the last paragraph of this section.
3.
Taxes on \\oiages
\\oiage
earners
in
the
Ivory
Coast
have
thei r
taxes
di rectly
deducted from their salary by the employer for the three applicable tax
on wages:
ITS, CN, and IGR.
ITS (Impot sur traitement et salaire)
The ITS applies only to wage earners from private or public sector
jobs.
Its
rate
of 1.5% is proportional
to 80% of the
gross
salary
of
the wage.
If B is the annual
gross salary
ITS = 0.80 B x 0.015.
The tax revenue collected from ITS goes to the BGF.
CN
(Contri but i on Not i ona 1e)
The
CN
is
a more
progressive
tax.
Its
rates
increases
with
an
increase
in
annual
wage.
In
practice
it
applies
to
the
monthly wage
according to the following rates:

---

Amount (CFA Francs )
Rates (in %)
0-50,UOO
U
50,UU1 to 13U,OUU
1.5
130,001
to 2UO,00U
5
20U,OUl and up
10%
lGR = (B - 5U,OUO) x Rcn
where Rcn is the applicable CN rate.
The
CN
becomes
proportional
and
therefore
regressive
for
salary
above CFA Francs
200,OUO,
the wage
category
of most
higher
educati on
degree holders.
Revenues from the CN go to the BSIE-Tresor.
IGR (Impot General sur Revenu)
The
IGR
is
also
a
relatively
progressive
tax
system.
Its
computation is more complicated
because
it
takes
into account
the
two
previous
taxes
on wages but also the marital
status and the number of
dependent children of the wage earner.
Students up to 25 years of age
are
still
considered
as
dependent
children.
Fami 1ies
with
several
dependents are allowed to divide their income among their dependents for
tax purposes (the split system).
Hence, higher income levels which are
subject to h-.eavy income taxes can also take advantage of this loophole
by
claiming
more
or
less. existing
dependents.
These
income
groups
benefit more from the split system than lower income groups.
For computing
IGR one needs to determine the number of deductions
permitted, and apply them to one's revenue category.
-
2. 7 8 -

---

Formula for Computing I.G.R.
(General Revenue Tax)
B
~
Gross salary (salary + other fringe benefits, except child alimony
and reimbursements: transport, travel, etc.)
R
Net taxable revenue before I.G.R. tax
R
~
[80/IOU B -\\ ·ITS + C.N.)J85/100
ITS
Impot sur Salaire (tax on wage)
CN ~ contribution Nationale (national contribution tax)
N
Number of deductions
IF R
Formula for computing
N
Annual
I.G.R.
Inferior to 3UO,UUU
U
30U,UOO to 547,000
(R x 10/100 ) - (27,273 x N)
548,000 to 979,UUO
(R x 15/1(5) - (4CJ,913 x N)
980,00U to 1,519,OUO
(R x 20/120) - (CJ4,375 x N)
1,520,UUO to 2,644,00U
(R x 25/125) - (135,000 x N)
2,645,UOO to 4,609,00U
(R x 35/135 ) - (291,667 x N)
4,670,000 to 10,106,000
(R x 45/145 ) - (54U,172 x N)
Superio' to IU,106,000
(R. x 6U/160) - (1,183,694 x N)
The
determination
of
deductions
illlowed
for
marital
status
and
number of children 1S Shown in Table E-2.
Although Table E-2 1S self
explanatory,
one
striking
relnark
needs
to
be
raised.
Onlnarried
taxpayers and married women
lose most 1n the number of deductions they
can
make.
Table
E-3
indicates
that
Iniddle
income
families
are
most
affected
by
the
tax
on
wages.
The
average
salary
of
university
graduates
falls
into
this
level
of
income.
Low
income
f ami 1i es
pay
-
279
-

---

TABLE E-2
Determination of Deductions
Chil dren
Deductions
11arital Status
in Charge
Exceptions
A11 owed
Genera 1 Ca se
1 Deduction
Bache 1or
Soecial Case
Divorce
without
wage earner with
Widow
- 1 adult child
- deceased children
1.5 deductions
- at least 40:,
veteran pension
fund, or dis-
abi 1i ty fund
- Veteran widow fund
Bache 1or
for wage earner
1.5 deductions
Di vorce
with
for each chi 1d
+ 0.5 ded.
Married
without
General Case:
2 deductions
Special Case:
- taxable married
1 deduction
woman
Married
with
for self
2 deductions
Widower
for each chi 1d
+ 0.5 deductions
Translated and adapted from "Barerne" (1979) ~Iinistere de Economie du Plan
Notes:
Maximum deductions allowed is 5
Maximum deduction is considered for cases of cumulative deductions:
Example:
r'larried man with 3 minor children, spouse and 1 minoY
paying: deductions = 1 for SpOUSEO+ 1 for liable child
+ 3 for head of family.
*All the information in_this annex is extracted from "Bareme des impo-ts sur
les salaries retenues a la source (Tarif applicable a cOr.lpl;l-ter du 1 Jam;.
1979) j'1inistere de l' Econornie et des finances.
-
280 -

---

TABLE E-3
Annual !\\mount and Average Rate of Three Direct laxes on Wages in the Ivol'y Coast
_ _ _
·
= ~ L ~ ' ~ ~ 0 7 w - ~ ~ _ .
..'""""........~-""'_....-
-
I\\nnua 1 I-Iage BI'dckets
Tax on Wages (1.5)
National Contribution (C.N.)
Tax on General Revenue(I.G.R.)
(in Fl'ancs c.f.A 1,000)
Amount
Averagf! Rate
Amount
Average Rate
Minimum
Average
Minimum
Average
Deduction (One)
Rate (%)
Deductions
Rate (X)
(%)
(;0
__
______
_ _
_.._.~_~~~~~
.._.~(f;vel~~.~~_
~_~Z~"""_1~~
- = - ~ = . · _ ~ .
~ ~ .
~
-~~~~~-~.~.-
5 - 400
(205)
2.46
0
0
0
0
0
0
0
405 - 1,000
8.4
1.2
0
0
15.27
2.2
0
0
(700 )
1.005 - 5,000
(3,000 )
36
1.2
56
1.8
257
8.5
42
1.4
5.000 - 10,000
i'_'
(7.500 )
90
1.2
:0
418
5,5
9.8
12.2
364
4.8
~
10.005 - 15.000
(12.500)
150
1.2
820
6 5
1.850
14.8
860
6.9
15,005 - 20.000
(17,500 )
110
1.2
1.218
6.9
2,82'
16 3
1 ,529
8.
30,005 - 2Z ,000
(21,000)
252
1.2
1,496
7. 1
3.613
17.2
1,883
8.9
22,005 - 13.000
(22,500)
270
1.2
1,616
7 . 2
3,952
17 . 5
2,092
9.3
23,005 - 24.000
123,500)
282
1.2
1.695
7 . 1
4,178
17.8
2,248
9.5
Computed hO!ll data in "Bal'CIII€"
(1979) i·\\inistere de 1 '£conomie et Plan.

---

almost
no ir(bme tax.
Upper
income classes
(CFA Francs 21 millions and
higher)
see
little change
in
their tax
burden.
The tax
paid
by this
last
group
remains
nearly
constant
to
7.2% for
CN
and
17.5% for
IGR.
When we introduce the maximum
(5)
deductions
families
are permitted to
make for their dependents,
the
IGR tax remains
almost
constant at 9.3%
for
upper
income
classes.
This
percentage
rate
is
nearly
double
of
those applicale to middle
income
levels.
For wage earners making the
r ~~Q.(
minimum deductions, the rate of IGR is 70%/for upper income levels than
that
of
middle
incomes.
High
income
unmarried
wage
earners
without
dependents
are
highly
taxed
and
pay
nearly
double
the
IGR
taxes
applicable to the same income level of those who claim dependents.
The
income
tax
system
of
the
Ivory
coast
favors
marriage
and
birth.
At the
same time
it
is
progressive and vertically equitable by
income
brackets.
Among
upper
level
income earners
the
system
becomes
regress i ve.
Two
last
remarks
need
to be made
on the income tax
system of the
Ivory Coast.
(I)
It should be noted that rural
sector workers do not
pay
income ta,t.
Hence,
wealthy
farmers
and thei r employees are exempt
from
di rect
tax.
However,
the
high
tariff
applied
to
the
export
products
(coffee,
cocoa,
cotton,
etc.)
constitute
a
heavy
indirect
tax.
This tax amount is the source of revenoes of Budget of the CSSPP/I
(The Producer Price Stabilization Fund), as indIcated earlier.
(2)
Because income tax is collected at the source there exists no
efficient
mechanisms
for
collecting
taxes
for
self-employed
or
from
workers
whose
employer
is
not
officially
relJistered
with
the
government.
These two groups of wage earners report very low Income and
do not pay any income tax.
-
282
-

---

B.
The 1981 Budgets
As indicated earlier two major types of budgets are adopted by the
yovernment:
the
BGF
and
HSIE.
Constitutionally,
the
budgets must
be
balanced before they are adopted by parliament.
Table E-4 gi ves a detai led account
of the sources of revenues of
the
BGF
in
1981.
The
CFA Francs
376
billions
total
revenues
of the
bud yet
is
mainly
furnished
by
taxes
on
import trade
(40%)
and income
taxes
(25%).
Internal
indirect taxes also give the BGF
18.5% of
its
revenues,
whi le
export
taxes
provide
10% of
those
revenues.
In
1981
revenues of BFG
17.4% of the GNP.
The second group of budgets is the BSlE.
In 1981 the three BSIE's
CAA, CSSPPA, Tresor) total CFA Francs was 443.750 billions.
Table E-5
gi ves
the
detai led
amount
of
the
BSIE
Budgets
and
thei r
sources
of
revenue.
The
BSIE-CAA
provides
38.20%
of
the
total
amount
of
the
budgets while the CSSPPA provides 51.75% and the Tresor, 10.05%.

---

TABLE E-4
SOURCES OF REVENUE OF 1981 BGF
Sou rces
Amount in
Million CFA Francs
A.
Direct Taxes
- Tax on profit
32,100
8.53
*
-
ITS
6,180
1.64
- Employers contribution
31,835
8.64
*
- IGR
21,400
5.69
*
- Tax on Capital (IRCM )
4,680
1. 24
Sub Total A-I
96,195
25.56
2.
Taxes on Property
1.
Real Estate Tax
1,500
0.39
3.
License and Patents
3,800
01.01
8.
Indirect Tax
1.
Tax on Product i on
- Value added tax (internal)
36,230
9.63
Tax on services (TPS)
23,070
6.13
- Tax on Tourists Activities
1,000
0.26
- Tax on Log Cutting
540
0.14
- Tax on Gasoline
_~_,OOO
2.39
Sub Tota 1
69,840
18.57
2.
Tax on imports
Duty
24,100
6.40
Import Tax
56,300
14.97
- 0.06% surtax on imports
1,700
0.45
Additional tax on Alcoholic Beverage
1,750
0.46
- Additional tax on petroleum products
16,500
4.38
- Value added tax on import
50,500
13.43
Sub Total
150,800
40.09
-
2 Sej
-

---

TABLE E-4 (Continued)
Amount in
Sources
Million CFA Francs
%
3.
Tax on Export
- Tax on raw material (DUS),
except timber
30,500
8.11
- Tax on Ti mber
7,100
1. 88
- 0.60% surtax on exports
680
0.18
Sub Total
38,280
10.18
C.
Stamps, Duties and Registration Fees
10,240
2.72
D.
Government Property
1,145
0.30
E.
Revenues from Government Agencies
1,335
0.35
F.
Others
2,865
0.76
Tota 1 BGF
376,000
100.00
Sources:
"Rapport de Presentation BSIE 1982"
*See text for the meaning of these taxes.
- =8 5 -

---

TABLE E-5
Sources of Revenue of BSIE (executed) in 1981
Amount
Sources
(i n Mi 11 ion CFA)
~
~
P.•
GSIE - Tresor (Tredsury)
1.
ITS
10 ,064
2.26
2.
Emp 1nyers contribution
5,292
I. 19
3.
Real estate tax
196
0.04
4.
License
377
0.08
5.
Tax on .fl,rt and Crafts
26
0.005
6.
Tax on :apital
2
0.00
7.
Tax on gasoline
4,533
1.02
8.
Revenues from Lottery (LON:.CI)
135
0.03
9.
Revenues from Investment Fund ( FNI)
2,200
0.49
10.
National Bonds (Emprunt. C';.4) -f
. 2,000
.0.45
11.
Loan from FNI
0
0.00
12.
Loan from Social Security (CNPS )
19,477
4.38
TOTI\\L [JSIE TRESOR
44,533
9.95
G.
GSIE - U\\P. (Debt f'mortization Fund)
1.
International FinQncial Institutes
6,953
I. 56
2.
National Financial Institutions
9,547
2.15
3.
Private Banks (Loan in US dollars)
89,027
20.06
4.
Private Banks (loan in Fl'ench Francs)
35,096
7.90
5.
Private Banks (other currencies)
15, 126
3.40
6.
Natioilal paid contracts (credit)
13,803
3.11
TOTM. GSIE - CAA
169,555
38.20
C.
GSH: - CSSPP,~
Resources (f"um stabilized crops)
229,662
51. 75
TOT!\\L BSI[s
443,750
100
Soul'ce:
Projet de Loi 13GF - 1982
-
2~G -

---

APPENDIX F
I~
!
I,i.c.
I
'-'_...:e..-..--
•_'-""_~__'>____ -..J
J:-.. u:.....
I'SIB
-
287
-

---

BIBLIOGRAPHY AND REFERENCE
1.
ON THE I~ORY COAST
A.
THE ECONOMICS OF THE IVORY COAST
Ahmed, Mamadou Konate
1977
Les rapports agriculture-finance publiques dans 1 '~conomie
ivori£ 'nne.
D.E.A. Thesis -University of Clal 'mont-Ferrand-Paris.
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1970
Le
developpement
du
capitalisme
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Cote
d'Ivorie.
Les
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Bedie, Konan
1971
La pql itique economi que du gouvernement de la Republ ique de
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d'IvOl ....~.
Bangue
Centrales
des
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Economie
ouest
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1979
La Cote d'Ivorie, Economie et societe - stock. Paris
Bulletin
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1 'Afrlque
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19,ill
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1975
La
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1J1abate, M.
1975
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The Ivory Coast
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L'Etat
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Etudes generales sur les economies africaines.
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Goreux, Louis
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Interdependence in planning - John Hopkins University Press.
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Les disparit~s de salai res au Senega I, Cameroun, MEldagascar
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1974
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---

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1975
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1975
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Marchang, A.H.
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La
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Revue de Droit des pays d' Afrigue.
No. 724
Avril, Mai, Jiun.
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No. 1, July.
1978
No. 2, September
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28 () -

---

B.
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Benta ta, C.
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Etude
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Berg, Elliot
1965
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In
Harbison
and
fleyers
(eds.),
Manpower and
Education:
Country
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New York: McGraw-Hill.
Bony, J: L'Enseignement superieur en cote d'Ivoirre, Penant, Revue du
Droit des Pays d' Afrique d' Afrique.
Charlick, Robert B.
1978
Acces s
to
"el ite"
education
in
the
Ivory
Coast
--
the
importance
of
socio-economic
origins.
Sociology
of
Education,
Vol. 51, July.
Chau, LN.
1972
The Ivory Coast: the cost of introducing a reform in primary
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In
P.H.
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(eds),
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1974
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1976
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Dia rrassouba, V.C.
1973
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Faujas, F
/
1971
L'Universite
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1966
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1974
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-
:'9U -

---

'.'
Klees, S. and D. Jamison
1973
Co~t
de
la
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Educative
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d'Ivoire;.
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"
1976
Ana 1 ses
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Cout~s
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