Policy, Planing, and Rlmsercl WORKING PAPERS EducmUon nd Employment Population awd Human Resources Department The World Bank August 1988 WPS 72 The Relative Efficiency of Public Schools in Developing Countries Emmanuel Jimenez, Marlaine E. Lockheed, and Vicente Paqueo Private schools are a cost-effective option for expanding secon- dary education in some developing countries. They may also provide some lessons for improving the efficiency of public schoois. he Pdicy. lamming nd Raash Cemplex disbibutes PPR Woing Papes to disseminate he findings of w inpkarss and to cneowuge the exchange ofidea among Bank saff and all other inted in developmet issues. lhese pape cany the names o the autho, reflect ordy their views, and should be used and cted accordingly. The findings. interpretations, and conclusiom are the authors own. Theyshould not be attributed to the World Bank, its Board ofDitois iumaageannt, oranyofitmanberswntris. Polky nnhng, *nd fteear | Educat on and Employment| In many developing countries, the national schools has important policy implications for commitment to universal education conflicts public schools. Some efficiency gains can come with the nexssity for fiscal restraint. One from replicating the input mix (teacher/student option for expanding education is to charge fees ratios, teacher qualifications) of private schools. for public schooling. The data show that private schools, among other practices, make more efficient use of teachers But recent World Bank studies of secondary and have better teaching processes (more tests, level data in Thailand, Colombia, Tanzania, and more homework, orderly classrooms). the Philippines point to a second, more cost- effective option: rely on private schools to Also effective would be to mimic the handle the growing demand for education. organizational incentive structures of private schools. Their administrators have considerable Private school students generally outperfonn economic and bureaucratic autonomy, and are public school students on standardized math and motivated to encourage better teaching practices language tests. This finding holds, even after - using staff more effectively and cheaply - studies account for the fact that, on averpge, because they must compete for students and private school students in these countries come remain accountable to parents who pay the bils. from slightly more advantaged backgrounds than their public school counterparts. In addition, This paper is a product of the Education and school expenditure data show that unit costs for Employment Division, Population and Human private schools are dramaticaUy lower than those Resources Department. Copies are available of public schools. free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Teresa The comparative advantage of private Hawkins, room S6-224, extension 33678. The PPR Working Paper Series disseminates the findings of work under way in the Bank's Policy, Planning, and Research Complex. An objective of the series is to get these fmdings out quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official policy of the Bank. Copyright @ 1988 by the International Bank for Reconstruction and Development/he World Bank The Relative Efficiency of Public Schools in Developing Countries by ummanuel Jimenez. Marlalne E. Lockheed, and Vicente Paqueo Table of Contents 1. I ntroduction ............................................. 1 2. Methodology and Data ............................................. 2 The Empirical Framework ....................................... 3 Data ............................................. 5 3. Findings ............................................. 6 Background and the Choice of School Type .............. 6 4. Relative Efficiency of Public and Private Schools ............. 9 Why Is There a Public/Private Differential? .............. 11 5. Policy Sigificance ............................................. 14 6. The Need for Further Analysis ......................................... 15 References ............................................. 17 1. Introduction Education in most developing countries is publicly provided, enrolling on average approximately 902 of primary a*id 702 of secondary students (Unesco, 1987). Most public sehools are free, or almost free, to students. However, tightening fiscs' cnnstraints have limited the ability of the public sector in many countries to expand provision of free public education, creating a particularly serious problem for the poorest countries, where demand for schooling is projected to increase dramatically over the next decades. Changes will be necessary if ambitious educational targets are going to be met in the near future. One option is to charge fees in public schools, and many countries have introduced some form of tuition fee in both primary and secondary schools. But another option is to rely on private schools to handle expansion. Economists reason that such schools should be both more effective in generating resources for education and more efficient, since private schools compete for students and are accountable to parents who pay the bill. As a result, their administrators are motivated to adopt teaching practices and use staff and educational materials effectively but cheaply. Although this argument is logically persuasive, empirical sup- port for it has only recently begun to emerge. In the United States, the debate was sparked by the Coleman, Hoffer and Kilgore (1982) report which concluded that private (Catholic) schools are more effective than public schools in imparting cognitive achievement. For developing countries, the evidence is even more recent. This paper summarizes several studies, sponsored by the World Bank, that contribute to the literature by analyzing secondary level data from several educationally 2 diverse countriess Colomb'la and Tanzania (Cox and Jimenes 1987, Psacharopoulos 1987), the Philippines (Jimenez, Paqueo and de Vera 1987), and Thailand (Jimenez, Lockheed and Wattanwah. li88). The next section (2) summarizes tho data and the common metho- dology employed in the analysis. Such a discussion is important since it is difficuit to attribute differences between the cognitive abilities of students in public versus private schools to school inputs alone. Unless non-school factors are controlled appropriately, estimates of school effects will be contaminated by what has become known as lselec- tivity bias." (see Murnane, Newstead and Olsen, 1985, for an assessment of the results of Coleman et al. and their critics). The main results of the papers are presented in sa t 3 and 4. In section 3, the paper addresses the issue of the differjrqial characteristics of those who go to public and private schools. While necessary for the selection correction, these results are of interest in their own right. Section 4 presents results on the relative effectiveness of public and private schools in enhancing achievement. Some of the papers reviewed go beyond this comparison. The work on Thailand, for example, inquires about the nature of public/private differences: what school characteristics are most responsible. All the papers also compre the per-student cost of public and private schools. The paper concludes with sections (5 & 6) on policy implications of the present findings and directions for future research. 2. Methodologv and Data The papers address the following question: would a high school student, randomly selected from the general student population, do better in a public or private school? In the absence of experimental data, a reliable answer can be obtained from a cross-section comparison 3 of public and private school students' performance in standardized tests --when student background, motivation and innate ability are controlled through statistical analysis. The empirical framework The ith private school student's achievement score (A) is a function of a vector of observed background variables (X) and unobserved variables (e)l (la) Aip - bp Xip + eip, where each component of b measures the marginal effect of a charateris- tic on achievement. The jth" public (or government) school student's score can be be similarly expressed by replacing the subscript "p" with Ng:" (lb) Ajg - bg Xjg + ejg. If the effects due to unobserved variables, e, are randomly and normally distributed, ordinary least squares regression techniques can then be used to estimate the parameters of equations (la) and (lb). Pri- vate/public comparisons can then be made using this information. For a student with the characteristic of the average public school student, the difference in achievement score if he/she were to attend a private school would be2: 'Alternatively, equations (la) and (lb) can be estimated as one equation, with a dummy variable for private and public types of schools. However, statistical (F-) tests led us to reject the hypothesis that the coefficients of all the other variables are equivalent in both types of schools. 2This can be e*aily shown. Subtract the estimated equation (lb) from (la). Then, add and subtract b.X1 on the right hand side of the resulting equation. The resulting difference can be xpressed as: Difference - bp (Xp - X ) + (bp - bg) Yg, where the first term is interprefLd as the endowment effect (i.e., the difference in scores due to differences in characteristics) and the sec- ond term is the school effect shown in equation (2) above. 4 (2) Effect - (bp - bg) Xg. Thus, on-school factors affect achievement too, such as socio-economic background, innate ability and individual motivation. Moreover, these non-school factors a so affect b'.iool choices made by families. This causes the selection bias problem. For example, if children from privileged backgrounds only attended private schools, it would be difficult to infer how they would do in public schools. Statistically, this means that the error terms e are no longer normally distributed and OLS shovld not be used to estimate tV2 above equations. To correct for sample selection, the papers use statistical corrections based on Heckman's (1979) two-step technique. First, a probit model is employed to estimate the determinants of choice of school type. Second, the results of the first step are used to hold constant for the probability of schcol choice in estimating achievement (equations la and lb). The results are promising. The greatest difficulty in this technique is identification: at least one variable should be included in the first stage that is not in the second stage. This variable is called the exclusion restriction. In the Philippines case, the relative distance to each type of school is used as such a restriction. Otherwise, the results hinge on specification to identify the parameters and the coefficients could be unstable. In such a case, the models should be subjected to sensitivity analysis by including different subsets of variables in each stage of the analysis. Another major innovation is the use of panel data to mitigate the effects of selection in the Thailand case study. As far as we know, only one other study (an independently and simultaneously conducted research effort by James Coleman at the University of Chicago) u3es 5 panel data in comparing public and private school achievement. Ours is the first to do so for developing countries. Data Each of the papers re. on data that were already collected for other purposes. The Colombia and Tanzania data were 6Anerated from a World Bank study of diversified education (Psacharopoulos and Loxley 1985). The Philippine data were collected by the Ministry of Education as part of its Household and School Matching Survey. The Thai data were obtained from Second International Mathematics Study conducted by the International Association for the Evaluation of Education Achievement IIEA). Despite their varied origins, the data sets contained similar core information. The main components are: household and student characterisites and achievement test scores on standardized tests of verbal skills and/or mathematics. In Colombia, Tanzania and the Philippines, this was supplemented by data on mental ability. For Thailand, extensive data were available on school and teacher characteristics and teaching practices. Table 1 summarizes their salient features. 6 Table 1: SAiary of Studles Year Data Sa ple Achievment Cw&ry Collected Students Schools Gads Indlcator Data Bao Colombia 1981 1004 129 11 Average scores DISS study (Cox & Jiz, on ath and (non-lNN) 1987) verbal tests tests Philippines 1983 446a - 7-10 Mathmatics test National (Jlnez, Paqmo Engl ish test hosehold & de Vera, 1988) Pillpino test sWvey Tanzanla 1981 1124 57 11 Average scores DISDt study (Cox & Jlmeoz, an nath ard 1987) verbal tests Thailand 1981/2 4030 99 8 athematics test Natibal school (JimA z, sirvw Loc* sed & wattanaah, 1eee) a Samle based on national houseld arvey; MNWer of schms u*nomn. 3. Findings The two principal sets of findings concern the relative access to public and private schools and the relative achievement of students once they enter those schools. Background and the choice of school type Unless there is excess demand for places, students and parents choose which type of school to attend. They do so by weighing the benefits and costs of each type of school. If school places are rationed, then, the schools' seleetion criteria affects who, among those who have applied, are given access. 7 Because the private schools in our sample countries are unsub- sidized while the public schools are almost free, the most important factors in the household decision are income (or incume-related vari- ables such as parents' education and occupations) and the relative cost of schooling. According to Table 1, average income indicators for stu- dents in privste schools are about double those for students in public schools in Colombia and t4e Philippines. Interestingly, in Tanzania, this difference is much lower, which suggests that subsidized public secLools are attracting and giving access to students from higher income backgrounds. These findings are corroborated bv higher relative indica- tors for private school students regarding mother's education and Table 2: Background indicators of private school students as a multiple of public school student indicators Colombia Tanzania Thailand Philippines Income (HH or father's) 1.94 1.20 2.07 Cooff. of variation of income 1.24 .83 .72 Mother's education (Z > primary) 1.87 1.27 1.61 1.23 Father's occupation (X white colar) 1.09 1.50 1.94 Per cent male 1.04 1.07 .91 .98 whether the father had a white-collar job (exrept for Thailand and the Philippines). However, the dispersion of income Is only slightly higher for private school students In Colombia and lower in Tanzania and the Philippines, suggesting a substantial overlap in the income categories of the public and private samples. Most of these variables were significant in the school choice equation. The relative quality-adjusted price of attending the two types of schools is very difficult to measure. Tuition tends to reflect school quality, which itself is a dimension of school choice. Thus, we did not include this variable, even when available. However, in the Ptilippine case, we were able to obtain the relative distance of public and pri7ate schools from each households and use this as a measure of relative cost. This variable was highly significant in explaining school choice. Although many of the pr:'vate schools are secterian, religion is nou included as an explanatory variable because the populations are so homogeneous. Sex of the student can be an important determinant of schoco1 choice because the proportion of segregated schools is higher the private system. Some parents prefer segregated schools. In Colom- bia and Tanzania, males dominate in private schools, while in Thailand and the Philippines, females dominate. In summary, private school students come, on average, from slightly more advantaged backgrounds than their public school counter- parts. However, the difference is slight and the variance is large. We have used these findings to make conclusions about selection into different types of schools -- and to correct for possible biases in the achievement equation. In the only study that contained strict cross-country comparisons, Colombia and Tanzania, correcting for sample selection bias revealed that, while Colombian students tended to choose the type of school where they would prosper, Tanzanian students were positively selected into the public system. This finding is important because in Tanzania, student choice is more limited and public schools are viewed as elite. 9 4. Relative Efficieney of Public and Private Schools Do private schools provide a better education, *nd at a lower unit cost, than public schools? The papers provide a consistent empirical basis to the issue of the relative efficiency of public and private schools in a number of developing countries. A principal finding is that, given student background, students in private schools, on average, generally outperform their public school counterparts on standardized mathematics and/or language tests. According to Table 2, this advantage varies considerably across countries, but is consistently positive for all subsamples and achievement tests, with the possible exception of mathematics achievement in the Philippines where the differ-nces are insignificant. A critical phrase is "given student background." It is generally not valid to infer differences among types of schools based on simple public/private comparisons of achievement in standardized tests because students' background vary so much in each type of school. In the comparisons, equation (2) is used to hold constant for background effects by measuring achievement effects at the average characteristics of public or private school students. Table 3: Private over Public School Advantage in terms of %-Differential in Achievement Score -- Secondary Levela Country Achievement Indicator Advantage (percent) Colombia Average math and verbal 11.6 Tanzania Averige math and verbal 17.4 Thailand Mathematics 163.3 Philippines Mathematics -1.0 English 19 5 Pilipino (nat'l lang.) 46.6 apercentage gain in achievement score if a randomly selected stu- dent, with the characteristic of the average public school student, attends private rather than public school, holding constant for that student's background. 10 It should b; noted that the case studies tended to focus on secondary school students and may not hold for other levels, even within the same countries. Moreover, it would not be valid to make any cross-country comparisons regarding the magnitude of the results. The tests are not standardized across countries. Also, because the data sets were designed by different researchers, the student background variables being held constant are only roughly equivalent. The question may be raised whether the differential between private and public school achievement changes sign as the socioeconomic status (SES) of students falls. The Phililpine study, which is the only paper that looked at the sensitivity of privete/public differontial to SES, found that varying the student's SES within a reasonable range did not produce a reversal in the direction of the private school effect. However, the magnitude of the private school advantage substantially decreasev with lower SES. This is consistent with the fact that the more elite private schools in the Philippines tend to emphasize the development of English-language skills and that children with higher SES have greater exposure to environments where Englibh is used often and where they have better access to English-language media. In Pilipino, on the other hand, there is no relationship between SES and the size of the private school effect. And in mathematics the disadvantage of private school students declines slightly with lower SES. What about efficiency? Preliminary calculations based on school expenditure data indicate that, on average, the unit cost for private schools is dramatically lower than that for public schools (Table 3). Combined with result above, this leads us to conclude that private schools are more efficient than public schools, at least for secondary level schools in the sample countries. 11 Table 4 Average Costs of Public and Private Schools Average Cost Private Cost/ Units Public Private Public Cost Colombia Pesos 18,281 12,674 69 Philippines Pesos 820 450 55 Tanzania Shillings 3,539 2,456 69 Thailand Baht 4,492 1,762 39 This finding should be interpreted with some important caveats. First, although it is agreed that the order of magnitude is generally correct, the cost estimates for Colombia and Tanzania are not precise because of the reluctance of some private schools to provide the necessary information. Second, in the Philippines, the average cost figure we obtained was not for the samples of schools used in the achievement study but a nationwide sample, unlike in Thailand, where we were able to go back and obtain school-by-school cost data for the sample. Also, it does not include family expenditures on children's education and the implicit subsidy provided by the priests and nuns teaching in sectarian schools. Third, there is considerable variability within each school type. Some types of public schools (say, those that are primarily locally funded) have lower unit cost than some types of private schools (say, the elite schools). It would be interesting in subsequent analysis to make use of this variability in the comparisons. Why is there a public/private differential? Unlike U.S. studies, the research attempted to inquire into the nature of the private/public difference in Thailand and, to a lesser degree, in Colombia and Tanzania. This is important since the 12 disadvantaged school type may be able to replicate some of the characteristics of the other and thereby gain in efficiency. There are a number of reasons why a private school advantage exists, including: peer group effects (in Thailand), a more efficient use of teachers through slightly lower qttslifications (in Thailand) and pay structures (in Colombia) for private schools and better teaching processes (more tests, orderly classrooms and homework in Thailand). (See Table 4.) These findings are necessarily preliminary because it is very difficult to assign achievement differentials among school inputs whose uses are sometimes complementary to one another. Nevertheless, the results can be used to indicate the direction of further research. 13 Table 5: Average Characteristics of Private and Public Schools in Thailand, Colombia and Tanzania Variable Description Private Public Thailand School-level characteristics Average district per capita income in baht 16,589.0 12,602.0 (4,318.4) (4,520.0) School enrollment 747.8 1,576.6 (493.9) (1,073.2) Proportion of teachers qualified 0.103 0.607 to teach math in student's school Teacher and class characteristics: Teacher's age in years 34.6 29.0 (11.0) (6.6) Proportion male 0.261 0.361 Proportion having in-service training 0.231 0.101 Proportion teaching enriched math class 0.308 0.200 Proportion using workbook often 0.263 0.238 Proportion spending > 15 minslweek maintaining order 0.601 0.484 Minutes/week spent on quizzes and tests 44.348 30.514 (62.429) (24.975) Number of students in target class 44.1 41.9 (6.8) (10.7) Peer group characteristics Average of average pre-test scores 10.87 8.84 Average proportion mothers > primary education .24 .15 Average proportion fathers prof occupation .19 .15 Colombia Mean teacher salary in pesos 10,752.00 20,659.00 (15,667.0) (15,053.0) Mean student-teacher ratio 19.9 23.3 (5.2) (5.7) Tanzania Mean teacher salary in shillings 1,316.00 1,143.00 (2,291.0) (596.0) Mean student-teacher ratio 25.4 23.7 (11.2) (9.2) Even after all measurable school characteristics are held constant, the private school advantage persists. This advantage can thus be due to urmeasured factors, such as x-efficiency, which is consistent with the hypothesis that there are inherent incentives to be efficient in private schools. This has important policy implications for public schools. Although some efficiency gains can be obtained by Nmimicking' the input mix (e.g., teacher/student ratios, teacher qualifications) of private schools, such actions are not likely to equalize the two systems. A 14 more effective, albeit less transparent, policy measure would be to mimic the incentive structures (including decentralized control) inherent in private systems. 5. Policy Sixnificance The findings presented here, showing that private schools are comparatively more cost-effective than public schools, are encouraging to thorn- who support refo,rms in favor of greater private sector partici- pation in the delivery of education. It should be stressed, however, that the relative efficiency of private schools is highly dependent on the institutional regime and structure of incentives under which they are currently operating. Thus, it is possible that reforms in support of private education (particular kinds of government subsidy) may not necessarily lead to greater efficiency in the educational system. These, for example, are reforms that would result in institutional changes that reduce the ability of schools to choose suitable input mixes, accountability and pressure on the private school to be efficient. What the exact nature of those reforms that lead to improved efficiency and equity is not the concesn of the present paper. They might involve the use of education service contracting (as is now being done in the Philippines), or even of some form of voucher system as in Chile. It could mean simply modifying overly restrictive rules and regulations that have been imposed to protect consumers, or legislating tax exemptions for private schools. Surely, all of these will have to be discussed in the larger context of the political economy of specific countries (James 1987). In this regard, it should be emphasized that 15 the paper is certainly not arguing for the abolition and privatisation of public schools. Yet, the findings should be carefully taken into account in the discussions of the aformentioned issues. For too long now the dis- cussions have been largely speculative and have lacked good empirical data. The usual assumption in considering government policies towards private schools is that the quality of education they provide is not commensurate with what in being paid by the consumers, due to the asymmetry of information b-tween consumers and providers. This assumption is widely held, together with the view that bureaucrats have a better information set regarding the technology of education and that there are no severe incentives incompatibility problems in the public school system. These papers provide contrary evidence that could be useful in judging the importance of the alleged inefficiency of market mechanisms (relative to direct government provision). 6. The Need for Further Analysis In the public/private comparisons, the rigorous methodology applied made some clear advances in the literature. However, additional work is warranted. First, the data bases were not strictly comparable across countries and it is not possible to make cross-country general- izations. Second, the scope of countries covered is also limited (two Southeast Asian countries provided the strongest data bases). Third, better information, particularly regarding the social and private cost of different school types, needs to be gathered. Finally, the studies covered only secondary schools. In Latin America and East Asia, the critical level for the future is going to be universities, which are the highest-cost components in many educational public budgets. In 16 Africa and the Indian subcontinent, the issue is also being discussed for the primary level. Thus, we recommend that the methodology applied successfully in the preliminary studies described in this report be extended. 17 REFERENCES Armitage, Jane and Richard Sabot (1987). "Efficiency and equity implications of subsidies of secondary education in Kenya." In David Newberry and Nicholas Stern, eds., The Theory of Taxation for Developing Countries. New York: Oxford University Press. Boissiere, Maurice, John Knight and Richard Sabot (1985). "Earnings Schooling Ability and Cognitive Skills," American Economic Review, 75(2): 1016-1030. Coleman, James, Thomas Hoffer, and Sally Kilgore (1982). High School Achievement: Public, Catholic and Private Schools Compared. 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