THE WORLD BANK

EDT 33

Discussion Paper

EDUCATION AND TRAINING SERIES

Report No. EDT33

Public vs. Private Schoolsin Developing Countries:

Evidencefrom Colombia and tTanzania

George Psacharopoulos

July 1986

Edt cation and Training Department Operations Policy Staff

The views presented here are those of the author(s), and they should not be interpreted as reflecting those of the World Bank.

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Discussion Paper

Education and Training Series

Report No. EDT33

PUBLIC VS. PRIVATE SCHOOLS IN DEVELOPING COUNTRIES:EVIDENCE FROM COLOMBIA AND TANZANIA

George Psacharopoulos

Research DivisionEducation and Training Department

July 1986

The World Bank does not accept responsibility for the views expressedherein, which are those of the author(s) and should not be attributed tothe World Bank or to its affiliated organizations. The findings,interpretations, and conclusions are the results of research or analysissupported by the Bank; they do not necessarily represent official policy ofthe Bank.

Copyright © 1986 The International Bank for Reconstruction andDevelopment/The World Bank

Abstract

The paper presents evidence on differences between public and privateschools in Colombia and Tanzania on a number of indicators like cognitiveachievement, unit cost and labor market outcomes. The findings are mixed,in the sense that in both countries, statistically control:Ling for studentability and socioeconomic background, private school students outperformtheir public school counterparts on academic achievement, whereas thereverse is true regarding achievement on specialized subject matter. Onepossible explanation of this finding is that parental press3ure (socialdemand) on private schools makes them tacitly emphasize academic subjectswhich are viewed by their customers as leading to a higher level ofopportunities after graduation.

PUBLIC VERSUS PRIVATE SCHDOLS IN DEVELOPING COWNTRIES:

EVIDENCE RO14 COLOMBIA AND TANZANIA *

Since publication of the more recent "Coleman retport," the

literature on comparisons between public and private schocils has mushroomed

in the United States. 1/ The issue in that country is mainly cast in terms

of "tuition tax credit", i.e., a tax rebate to families that send their

children to private schools. The controversy in the literature has

centered around two points: first, methodological, i.e., how to test for

differences in outcomes imparted upon the student by the t:wo types of

schools; second, value judgements, i.e., how to weigh any positive versus

negative effects of public and private schools. Two lines of thought have

developed on the issue: those who believe that greater reliance on private

schools would introduce competition and choice into the system, and thus a

higher level of efficiency; and those who argue that privatization of the

school system would lead to greater social and economic st:ratification in

society.

Very little has been published on private schools in developing

countries, let alone on comparisons between public and priLvate schools

(see James 1985, Tan 1985). The issue is important because, in spite of

the fact that the tax system in these countries is not as developed for a

tuition credit scheme to be considered or enacted, the encouragement of

private schooling may (a) provide incentives towards a better utilization

* I am indebted to Tarsicio Castaneda and Emmanuel Jimenez for theircomments on an earlier draft of this paper.

1/ For a summary of the "Coleman report" see Coleman (1981). For areview of a number of related issues see James and Levrin (1983).

-2 -

of social resources allocated to schools, and (b) relax the limited public

financial capacity to support an educational system. Inadequacy of the

public purse to support the expansion of education, and inefficiency in the

use of resources are the two most salient problems plaguing the educational

system of most developing countries today. However, any positive

efficiency effects of private schools would have to be assessed against the

potential loss of equity.

This paper attempts a contribution on this issue by providing

some evidence on differential student outcomes between private and public

schools in two developing countries: Colombia and Tanzania. In what

follows I first give a description of the samples on which the evidence is

based in the two countries, present the empirical results and discuss their

implications.

I. Colombia

Colombia has a well developed secondary school system with nearly

one half of the relevant school age group children enrolled at this level

(Unesco, 1984). Of those enrolled in secondary schools, one half

attend private institutions (James 1985, Table 1). The sample on which

this study is based was raised in 1981 in connection with the "DiSCuS"study

(Psacharopoulos and Loxley, 1985). This was an evaluation of the

diversified public secondary schools called INEM (Institutos Nacionales de

Educacion Media) judged against a control group of other (conventional)

public schools and private schools at the same level of education. 2/

2/ Diversified schools teach academic and pre-vocational subjectsunder one roof, whereas non-IMEM schools (private or public) focusmainly on one subject, like academic studies, industrial arts orcommerce.

- 3 -

Table 1 presents the structure of the sample used in the

following analysis by school type and subject. In all, a little over

6,000 students were randomly polled in 95 schools of the three types. The

reason two types of schools are distinguished within the public sector is

that the INEM correspond to an educational innovation that was supported

by the World Bank and such schools were built and equipped on different

standards relative to the other public schools. Therefore, any quality

differences between schools might be attributed to such different

standards rather than the fact that INEM schools belong to the public

sector.

Table 1

The Number of Students (and Schools) in the Sample: Colombia

Subject ------Public ------ Private TotalINEM Other

Academic 871 (*) 779 (18) 692 (18) 2,342

Commercial 957 (*) 614 (12) 359 (14) 1,930

Industrial 869 (*) 669 (11) 276 (6) 1,814

Total 2,697 (16) 2,062 (41) 1,327 (38) 6,086 (95)

* INEM schools offer all three subjects.

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Information was raised from several sources. A school

questionnaire was used to document the level of facilities of each

individual school in the sample. A student questionnaire documented the

background characteristics of each student, along with financial

information on school-related expenditures. A specially designed test was

administered to each student to assess his or her level of cognitive

knowledge in the area of curriculum specialization. Information from the

ICFES test (administered by the national examination board for entry into

higher education) was merged with the student file in order to obtain the

student's verbal and mathematical aptitude before graduation from secondary

school. Finally, each student was traced one year after leaving secondary

school and administered a questionnaire to obtain information on activities

since graduation and current status.

Table 2 gives summary statistics on differences between the three

types of schools on a number of indicators. Thus INEM schools have an

advantage over the rest in terms of the teacher-student ratio and teachers'

qualifications. However, they have a higher operating cost, relative to

other public schools and nearly double the cost of private schools,

presumably because of the higher standard that they were designed to

meet.3/ Regarding the student characteristics, there is a sharp difference

between the socioeconomic background (family income and parental education)

of those who attend private school on the one hand, and those in

3/ The private unit cost (item 3 in Table 2) was assumed to be equal tothe fees paid by the students given the fact that private schools inColombia do not receive state subsidies.

Table 2

Mean Sample Characteristics by School Type: Colombia

Characteristic ----Public---- PrivateINEM Other

School

1. Student-teacher ratio 27 30 322. Teachers' qualifications (in years) 15.9 13.5 14.03. Operating cost per student (pesos per year) 15,620 13,380 8,344

Student

4. School fees (pesos per year) 576 886 8,3445. Other School-related exp. (pesos per year) 3,694 4,901 4,3306. Family income (pesos per month) 22,928 27,106 40,3197. Father's education (in years) 6.0 6.5 7.8

Graduate

8. Attended training course (percent) 24.5 27.9 26.09. Looking for work (percent) 33.1 31.1 27.610. Monthly earnings (in pesos) 9,732 9,723 9,546

Direct Unit Costs and Financing

11. Social cost (3+5) 19,314 18,281 12,67412. Private cost (4+5) 4,270 5,787 12,674

Share of Private Contribution to:

13. Social cost (percent) 22.1 31.7 100.014. Monthly family income (percent) 1.6 1.8 2.6

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the public school system--in schools of either the INEM or the conventional

type. Regarding external outcomes, private school graduates appear to be

better off in terms of finding employment after graduation from secondary

school, although there is virtually no difference on the earnings received

by the graduates of the three types of school.

Table 3 summarizes the results of the achievement tests by school

type and subject. INEM schools outperform all others on the specialization

test. But there are some interesting differences in the level of aptitude

by those who are drawn into the INEM academic program, and the rest. It

appears that within the INEM system, the most able students follow the

academic stream, whereas the rest are streamed into the commercial and

industrial pre-vocational subjects. Non-INEM and private vocational

schools draw higher ability students relative to their INEM counterparts.

Explaining Achievement Differences

School quality is a multifaceted concept. Stripped to its

essentials, it can be measured by either input or output. 4/ We already

noted some differences on the input side between public and private

schools. There are also differences on the cognitive achievement, output

side (see Table 3). But to what extent are the latter statistically

significant when other factors, like the student's ability and

socioeconomic background that positively correlate with achievement, are

controlled for?

4/ For a discussion of alternative definitions of school quality, seeFuller 1985.

-7 -

Table 3

Cognitive Achievement and Aptitude Scores by Curriculum Subject: Colombia

Curriculum Test -----Public----- PrivateSubject Score INEM Other

Academic Academic Achievement 54.3 50.0 50.1(17.7) (20.1) (21.5)

Verbal Aptitude 52.6 50.6 51.1Math Aptitude 51.8 51.2 50.8

Commercial Commercial Achievement 59.6 58.2 54.4(19.8) (20.3) (19.6)

Verbal Aptitude 49.7 53,4 51.9Math Aptitude 49.5 53.,8 52.1

Industrial Industrial Achievement 55.6 52.6 46.6(18.5) (20.0) (21.3)

Verbal Aptitude 49.3 52.7 53.2Math Aptitude 52.0 55.4 57.5

Note: Numbers in parenthesis are coefficients of variation.

Table 4 presents regression results of cognitive achievement as a

dependent variable on school and student characteristics. The functions are

fitted within groups of students following the particular subject. "Private

school" and "INEM school" are dummy variables having a value of I if the

student attends the respective school, and 0 otherwise. Hence the control

group against which the school-type effect is evaluated, is the non-INEM

public schools. Sex is a dummy variable having a value of 1 if the student

is male and 0 otherwise. Father's education (measured in years) is used as

a proxy for socioeconomic background.

Regression (1) brings out the clear positive effect of attending

an INEM school relative to a conventional public school. Attending a

private school does not have a significant effect on academic achievement.

In regression (2) the function is fitted within the non-INEM and private

schools sub-sample as to provide a stricter comparison between ordinary

(i.e., non-innovative) schools in the public and private sector. The

results show that there is no difference in academic achievement between

the two sectors.

Regression (3) brings in two additional controls for student

background: his or her score on the verbal and math aptitude tests. (Note

that sample size is reduced relative to regression (1) because not all high

school seniors aspired to entry into higher education and hence the test

score is not available for those who did not). Given this limitation,

within the subgroup of university aspirants, the positive effect of INEM is

maintained. However, attending a private school is associated with a

statistically significant two points gain on the standardized academic

achievement test. Another point worth noting in this regression is that

the introduction of the ability measures diminishes the effect of socio-

economic background (father's education in this case) to about one third

its size relative to the previous regressions (1) and (2). Regression (4)

-9 -

Table 4

Within Subject Achievement Functions: Colombia

Test Score: -------------Academic-------------- Colmercial IndustrialIndependentVariable (1) (2) (3) (4) (5) (6)

Constant 47.256 46.908 21.722 20.818 44.842 30.604

Private School -.221 -.314 2.025* 1.974* -5.043* -7.659*(.42) (.59) (3.61) (3.60) (5.95) (8.02)

INEM School 4.036* -- 4.823* --

(8.08) (9.09)

Sex (Male = 1) 1.516* 1.354* .759 1.000 -2.191* 3.38(3.59) (2.54) (1.79) (1.83) (2.11) (.93)

Father's Education .302* .361* .122* .124 .261* .120(5.81) (5.62) (2.34) (1.89) (2.25) (.90)

Verbal Aptitude -- -- .393* .449* .219* .264*(16.14) (14.43) (4.43) (4.76)

Math Aptitude -- -- .112* .071* .020 .085(4.81) (2.31) (.40) (1.64)

R2 0.060 .025 .261 .274 .102 .129

N 2,217 1,401 1,720 966 689 711

Notes: Functions are fitted within sub-samples of students specializing in academic,commercial or industrial studies.The dependent variable is the test score on the student's own specialization.Numbers in parenthesis are t-ratios.

"--"means variable not included in the regression.

* indicates statistical significance at the 5 percent probability level or better.

- 10 -

repeats this last functional specification within the group of non-INEM

students showing that the advantage of private over public schools on the

academic test is maintained. Also, the effect of socioeconomic background

on achievement disappears (at the 5 per cent level of significance). A

comparison between regressions (1) and (2) on the socioeconomic variable

shows how its inclusion without proxies for ability may sometimes lead to

the spurious result that achievement is determined by social class rather

than other student or school characteristics. (For a discussion on this

topic, see Heyneman and Loxley, 1983).

Finally, regressions (5) and (6) repeat the last functional

specification within the commercial and technical sub-groups of students.

In both cases, public schools outperform private schools in vocational

achievement. The probable reasons for such mixed performance of private

versus public schools is discussed in the last section.

- 11 -

II. Tanzania

In sharp contrast to Colombia, Tanzania has a very constrained

secondary school system: only 3 percent of the relevant age group is

enrolled at the secondary level (Unesco, 1984). Yet about one third of the

country's secondary school students attend private schools (Tanzania

Government, 1980). The sample on which this study was based covered over

4,000 students attending Form IV in 39 public and 18 private secondary

schools in 1981.

Table 5

The Number of Students and (Schools) in the Sample: Tanzania

Subject Public Private Total

Academic 713 (8) 311 (5) 1,024 (13)

Commercial 747 (13) 538 (6) 1,285 (19)

Technical 405 (4) 87 (3) 492 (7)

Agricultural 1,157 (14) 223 (4) 1,380 (18)

Total 3,022 (39) 1,159 (18) 4,181 (57)

Unlike Colombia, all secondary schools in Tanzania had to

diversify in the early seventies and declare a curriculum "bias" in which

they would specialize. However, implementation problems resulted to the

continued teaching of traditional subjects in many schools.

- 12 -

These are denoted as "academic" or "control" schools in our sample. (For

the history of and a discussion on the diversification policy in Tanzania

see Psacharopoulos and Loxley, 1985).

As in the case of Colombia, information was raised by means of a

student, school and follow-up questionnaire, the latter administered one

year after graduation from high school. Specially designed tests measured

the student's verbal and mathematical aptitude, as well as his or her

cognitive achievement score on the subject-matter of each curriculum bias.

Table 6 gives a summary of differences between public and private

schools on a number of selected indicators. Thus public schools score

significantly higher (relative to private schools) on three conventional

measures of educational quality, namely, they employ more teachers per

student, their teachers are better qualified, and they spend more per

student. Unlike Colombia, there is not much socioeconomic differentiation

between students attending the two types of schools. For example, father's

income of those in private schools is only 13 percent higher relative to

those in public schools. Regarding external outcomes, private school

graduates appear (weakly) to be better off in terms of the incidence of

unemployment after graduation and the size of earnings among those

employed.

- 13 -

Table 6

Mean Sample Characteristics by School Type: Tanizania

Characteristic Public Private

School

1. Student-teacher ratio 18 282. Teachers' qualifications (in years) 16.2 13.63. Operating cost per student (sh. per year) 3,549 1,957

Student

4. School fees 83 1,9925. Other School-related expenses (sh./year) 349 4996. Father's income (sh. per month) 5,137 5,7907. Father's education (in years) 5.6 6.8

Graduate

8. In furhter education or training 53.4 17.79. Looking for work (percent) 6.6 5.910. Monthly earnings (shillings) 696 708

Direct Unit Costs and Financing

11. Social cost (3+5) 3,539 2,45612. Private cost (4+5) 432 2,491

Share of Private Contribution to:

13. Social cost (percent) 13.5 101.414. Monthly father's income (percent) .7 3.6

- 14 -

Table 7 gives the mean achievement scores in the various

subjects, along with the mean aptitude scores by curriculum track. Without

exception, students in public schools score higher on aptitude and cognitive

achievement, and in some instances by a wide margin.

So, are public schools "better" than private schools? Not

necessarily so. In the first place it was observed above that private

schools spend significantly less per student relative to public schools.

Hence, their inferior score on cognitive achievement may be due to the fewer

inputs that enter their "educational production function". Second, the

figures in Table 7 are averages, i.e., uncontrolled for other

characteristics in which students attending the two types of schools

differ. Table 8 presents achievement functions fitted, as in the case of

Colombia, within subgroups of students. Controlling for family background,

sex and aptitude, private schools appear to do significantly better on

academic subjects (English and Mathematics) relative to public schools.

However, private schools do worse in specialized subject matter (commercial,

technical and agriculture test).

- 15 -

Table 7

Cognitive Achievement and Aptitude Scores by Curriculum Subject: Tanzania

Subject Test Score Public Private

Academic English 52.3 50.9(16.9) (25.3)

Mathematics 51.3 50.4(19.4) (20.0)

Verbal Aptitude 51.7 48.3Math Aptitude 51.3 47.0

Commercial Commercial Achievement 54.9 51.9(20.5) (18.1)

Verbal Aptitude 49.8 45.2Math Aptitude 50.0 44.1

Technical Technical Achievement 59.1 48.6(19.9) (17.7)

Verbal Aptitude 53.2 45.6Math Aptitude 56.2 44.8

Agricultural Agricultural Achievement 53.9 46.0(19.8) (17.6)

Verbal Aptitude 52.4 42.8Math Aptitude 51.9 44.9

Note: Numbers in parenthesis are coefficients of variation.

- 16 -

Table 8

Within Subject Achievement Functions: Tanzania

Independent Test Score: - - - Academic - - -Variable English Mathematics Commercial Technical Agriculture

Constant 18.050 14.960 37.26 30.459 35.870

Private School 1.056 1/ 1.455 * -1.165 * -4.658 * -5.304 *(1.89) (2.55) (2.25) (3.65) (6.86)

Sex (Male=l) -.591 4.849 * -.607 -.577 -1.965 *(1.06) (8.49) (1.22) (.32) (3.07)

Father's Education .140 2/ .039 .164 * -.008 .236 *(1.74) (.470) (2.08) (.06) (2.81)

Father is Farmer .250 -.545 .459 .900 .876(.48) (1.03) (.85) (1.01) (1.60)

Verbal Aptitude .350 * .179 * .121 * .110 .227 *(12.44) (6.22) (4.14) (1.87) (7.48)

Math Aptitude .304 * .470 * .215 * .407 * .114 *(10.15) (15.33) (7.43) (7.53) (3.77)

R2 .348 .432 .123 .271 .150

N 1,024 1,024 1,285 489 1,380

Notes: Functions are fitted within sub-samples of students specializing in academic,commercial, technical or agricultural studies.The dependent variable is the test score on the student's own specialization.Numbers in parenthesis are t-ratios.

* Indicates statistical significance at the 5 percent probability level or better.

1, Statistically significant at the 5.6 percent probability level.

2/ Statistically significant at the 8.2 percent probability level.

- 17 -

III. Discussion

The results of the foregoing analysis are mixed regarding the

performance of private versus public secondary schools. 5/ But one common

feature emerged in both countries: Private schools do better on academic

subjects, although the reverse applies for specialized/vocational

subjects. In Colombia, public sector INEM schools belong to a separate

class of their own. To put it in a nutshell, the standards according to

which they were built and equipped makes them better schools, at least in

terms of raising cognitive achievement in all subjects. 6 Second,

concentrating on non-INEM schools--which may provide a fairer assessment of

the public versus private sector issue--academic private schools do better

than their public counterparts. But the reverse is true regarding schools

specializing in commercial and industrial studies. One possible

explanation of the results, is selectivity bias in the sauLple, i.e., those

who attend the two types of school differ systematically in some other

characteristic that is not captured by socioeconomic background and the

aptitude tests that were used as control in the achievement functions.

In Tanzania, the inferior performance of private! schools on

specialized tests may be due to the fact that although such schools had to

declare a bias, this was not as well implemented as it was in public

schools of the same bias because of financial constraints.,

5/ It should be noted that there exists substantial differentiation inachievement within the public and private sectors, as judged by thecoefficients of variation reported in Tables 3 and 7, above.

6/ However, INEM schools scored lower than other types oiE school inColombia on a set of external evaluation criteria like the absorbtionof graduates by the labor market or further training. (SeePsacharopoulos, Velez and Zabalza, 1986).

- 18 -

The common finding in the two countries that private schools are

better in boosting academic achievement whereas the reverse is true

regarding specialized/vocational subject matter could be explained by

another hypothesis: Private schools attempt to satisfy the demand of their

customers which is stronger for academic relative to vocational subjects.

The reason for such demand preference is that students and their parents

view academic subjects as leading to more opportunities after graduation,

like entering university of following a non-manual career. Hence, through

the power of the fees they pay, pressure is exercised on private schools to

tacitly emphasize the academic subject matter. It is a common observation

that the social demand for education in all types of countries is for

general rather than vocational education. Hence, when an element of choice

is involved, as in the case of private schools, the customers eventually

obtain what they want. 7/

Taking the results at face value, it is clear that any policy

decision regarding the encouragement of one type of school over another

must hinge on some additional criterion to the relative ability of public

or private schools to raise student achievement. Two such possible

criteria are, first, the beyond school, external outcomes imparted upon the

graduates and, second, the relative cost or financial considerations in

7/ This hypothesis could be tested by introducing a private versus publicschool distinction in assessing the demand for education. For anexample of such study, although without a type of school variable, seePsacharopoulos (1982).

- 19 -

general. The external outcome criterion was already used to discriminate

between INEM and non-INEM schools in the DiSCuS study, and tipped the scale

in favor of the non-INEM schools in Colombia and academic schools in

Tanzania (Psacharopoulos and Loxley, 1985).

Turning to financial issues, Table 2 shows that in Colombia the

operating cost of private schools is on average 42 percent lower 20 than

that of INEM and conventional public schools. Therefore, although private

schools spend substantially less per student, they have been effective in

raising academic achievement relative to public schools. In Tanzania also

the operating cost of private schools is significantly lower than that in

public schools. But private schools have been more efficient in

transforming limited resources to learning outcomes.

The differential cost/achievement relationship between private

and public schools could be explained by the fact that academic schools are

inherently cheaper to run because it is relatively easy to obtain teachers

in language and mathematics. By contrast, vocational schooLs are more

expensive to run because of the need to hire specialized teachers and

purchase technical equipment. As a result, only schools relying on the

public purse may be able to be fully equipped to teach vocat:ional subjects,

the private schools tacitly restricting themselves to excellence in

academic subjects.

Of course a more dramatic difference emerges on the financing

aspect of the costs. Students in private schools in both countries fully

contribute to the social cost of their education, whereas students in

- 20 -

public schools contribute only a fraction (line 13 in Tables 2 and 6). To

the extent that the possibility of public financing of the expansion of

secondary schooling is an issue, encouragement of private schools may

relieve the state of a budgetary constraint. Alternatively, if the state

subsidy now channelled indiscriminately to public school students (by means

of free attendance) were targeted to the most able and low family income-

students, the overall efficiency of the system would improve, as well as

its equity.

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REFERENCES

Coleman, J., "Public Schools, Private Schools and the Public Interest,"The Public Interest, 64, Summer 1981: 19-30.

Fuller, B., "Raising School Quality in Developing Countries: WhatInvestments Boost Learning?" Discussion Paper Series #7, Education andTraining Department, The World Bank, 1985.

Heyneman, S. and Loxley, W., "Influence on Academic Achievement Across Highand Low Income Countries: A Re-analysis of IEA Data," Sociology ofEducation 55 (January 1983): 13-21.

Hinchliffe, K., "Cost Structures of Secondary Schooling in Tanzania andColombia," Education and Training Department, The World Bank, 1983(mimeo).

James, T. and H. Levin, eds. Public Dollars for Private Schools, TempleUniversity Press, 1983.

James, E., "The Public/Private Division of Responsibility for Education:An International Comparison," Department of Economics, StateUniversity of New York, Stony Brook 1985 (mimeo).

Psacharopoulos, G., "An Analysis of the Determinants of the Demand forUpper Secondary Education in Portugal," Economics of Education Review,Vol. 2, No. 3, Summer 1982: 233-51.

Psacharopoulos, G. and Loxley W., Diversified Secondary Education andDevelopment: Evidence from Colombia and Tanzania, Johns HopkinsUniversity Press, 1985.

Psacharopoulos, G, Velez, E. and Zabalza, A., Una Evaluacion de laEducacion Media Diversificada en Colombia, Bogota, Enlace, 1986.

Tan, J.P., "Private Enrollments and Expenditure on Education: Some MacroTrends," International Review of Education, May 1985.

Tanzania Government, Basic Facts about Education in Tanzania,Dar-es-Salaam: Ministry of Education, 1980

Unesco, Statistical Yearbook, 1984.