metadata: authors: 0: author: Noss,Andrew J.
docna: 0: docna: Education and adjustment : a review of the literature
docty: Policy Research Working Paper
subtopic: Public Sector Economics,Primary Education,Tertiary Education,Educational Sciences,Educational Institutions & Facilities,Effective Schools and Teachers,Public Financial Management,Public Finance Decentralization and
            Poverty Reduction
teratopic: Education
abstracts: cdata!: Many recent studies evaluate the effects
            of adjustment on economic growth and on the poor, but few
            assess the specific impacts of adjustment on the education
            sector.  The author assesses what is known about how
            adjustment affects education.  He concludes that reliable
            evidence is limited.  Most critics of adjustment programs
            say little about education directly and do not distinguish
            the effects of adjustment measures from the effects of
            internal recession, fiscal constraints, or structural
            problems.  Early adjustment programs ignored education
            issues - but adjustment lasted longer than expected, so the
            Bank has broadened its approach to protect education from
            the negative effects of adjustment.  Relevant data are
            scarce and of poor quality. The most common indicators -
            aggregate financing and enrollment indicators - are
            difficult to interpret.  Moreover, analyses may compare
            indicators between two before-and-after points but say
            nothing about how or why indicators change.  The effects of
            changes in financing on coverage, quality, and equity of
            education are by no means obvious.  Education has a long
            gestation period, so the impacts of adjustment may not yet
            be evident.  Country studies are probably the best framework
            for analyzing the adjustment process.  The database of key
            education indicators must be improved.
repnme: repnme: Education and adjustment : a review of the literature
display_title: Education and adjustment : a review
            of the literature
listing_relative_url: /research/1991/06/699952/education-adjustment-review-literature
topicv3: Teachers Management m1326119 1523,Primary Education m1326139 480,Public Finance Management m1326316 716,Tertiary Education m1326349 482,Education m1327048 470
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Education
origu: Policy, Research & Ect Affairs
no_of_pages: 79
author_keys: 0: author_key: 872419
model_extractions: <!-- Start of picture text --> Policy, Research, and External Affaire<br><!-- End of picture text --> <!-- Start of picture text --> Edualon and Employment<br>WPS 701<br><!-- End of picture text --> This paper -a product of the Education and Employment Division, Population and Human<sup>Resources</sup> - Department is part of a larger effort in PRE to understand the education sector in the broader<sup>context</sup> of Bank operations, particularly adjustment programs. It is the second<sup>step in a research agenda that</sup> includes analysis of how the education sector should be treated in public expenditure reviews<sup>in the context</sup> of adjustment (see WPS 510) and of how adjustment-related operations<sup>affect the education sector. Copies</sup> are available free from the World Bank, 1818 H Street NW, Washington DC 20433.<sup>Please contact Cynthia</sup> Cristobal, room S6-035, extension 33640 (68 pages with figures and tables).

Many recent stuties evaluate the effects of adjustment on ecoinomic growth and on the poor, but few assess the specific impacts of adjustment on the education sector. Noss assesses what is known about how adjustment (particularly World Bank adjustment lending) affects education.

He concludes that reliable evidence about the effect of adjustnent policies on education is limnited.

Most critics of adjustment programs say little about education directly and do not distinguish the effects of adjustment measures from the effects of international recession, fiscal constraints, or structural problems. Early adjustment programs ignored education issues but adjustment lasted longer than expected, so the Bank has broadened its approach to protect education from the negative effects of adjustment.

Relevant data are scarce and of poor quality. The most common indicators aggregate financing and enrollment indicators - are difficult to interpret. Moreover, analyses may compare indicators between two before-and-after points but say nothing about how or why indicators change.

The effects of changes in financing on coverage, quality, and equity of education are by no means obvious. Education has a long gestation period, so the impacts of adjustment may not yet be evident. Country studies are probably the best framework for analyzing the adjustment process. The database of kev education indicators must be improved.

The PRE Working Paper Series disseminates the findings of work under way in the Bank's<sup>Policy, Research, and External</sup> AffairsComplex. Anobjectiveoftheseries is to getthese fmdings outquickly, even if presentations<sup>arc Icss than fullypolished.</sup> The findings, interpretations, and conclusions in these papers do not necessarily represent<sup>official Bank policy.</sup> Produced by the PRE Dissemination Center
# **TABLE OF CONTENTS**

|Execu|tive Sum|mary<br>**..........**|i|
|---|---|---|---|
|I.|Intro<br>|duction<br>............................<br>**..........**<br>|**.**<br>. 1<br>|
||**A.**|Description<br>.............................|I|
||B.<br>|Effects of adjustmtnt on education .......................<br>|2|
||C|Changes in World Bank operations .......................|6|
|H.|The|Evidence: Methodology and Data Limitations ......|..........<br>12|
||<br>A.<br>|<br>Methodology ....................................<br>|12<br>|
||B.|Data ....................................|15|
|III.|The|Evidence: Major Issues ................................|20|
||<br>**A.**<br>|<br>Capacity ..................<br>.................<br>|20|
||B.|Coverage ....................................|25|
||C.|<br>Quaity<br>...................................<br>|27|
||D.|Equity<br>.<br>.<br>...................|...........<br>30|
||E.|<br>What evidence is missing? .<br>..............|.............<br>31|
|IV.|Conc|lusions................<br>...........|........32|
||A.<br>|Dynamics of adjustmentpolicies ..........<br>........<br>|......<br>32<br>|
||**B.**|Data colect-on efforts ...............................|33|
||C.|Questions for further research .........................|34|
|||**ANNEXES**||
|**1.**|Coun|try Studies ...............<br>..................|36|
|||<br>Chile<br>..<br>...............................|36|
|||Costa Rica ..................................|37|
|||Ghana ...............<br>..................|39|
|||Malawi ...............<br>..................<br>|41<br><br>|
|||Morocco............................|.....<br>43|
|||Philippines|44|
|||.................................<br>South Korea .................................|46|
|||Turkey<br>.................................<br>|48|
|||Zambia<br>.........................|49|
|2.|Worl|d Bank Adjustment Operations by Country .......<br>..|.........<br>51|
|3.<br>|<br>Coun<br>|<br>try Typology of Fiscal Duress ...........................<br>|56<br>|
|4.|Coun|try Typology of Adjustment ......<br>............|..........<br>58|

Bibliography .61
# **TABLES**

|11.1:|Methodologies to analyze the impacts of adjustment on education .....|<br>13|
|---|---|---|
|In1.1:|Deta presentation in the literature ............................|21|
|111.2:|Total long-term debt ...............<br>.......................|23|
|I1I.3:|Education financing ...............<br>.......................|23|
|1m.4:<br>|<br>Government expenditure cuts in education, 1979-83 .....<br>..........|<br>25|
|m.5:|Real public education spending per capita ......................|27|

# **BOXES**

|I.1:|SALs that address education ..........<br>.......................|8|
|---|---|---|
|I.2:|Sector adjustment lending in Ghana and Mali ....................|9|
|I.3:|SILs and SECILs ......|11|
|11.1:|Isolating the effects of adjustment ......................<br>.......|......<br>15|
|11.2:|Data quality ............................................|16|
|111.1:|"Before" and "after" World Bank-supported adjustment:||
||No clear trends ..........................|22|
|III.2:|The debt service squeeze in Tanzania .........................|24|
|HU1.3:|<br>Education spending and enrollment rate time trends:||
||Costa Rica and Ghana .26||
|111.4:|Per student expenditures: Intrasectoral trends||
||in Costa Rica and Ghana .........................|28|
|1II.5:|Teacher salaries .........................|29|
|111.6:|Education equity--rural versus urban .........................|30|

Reviewers Birger Fredriksen (PHREE), Luis Riveros (CECMG), Antoine Schwartz (PHREE), Gail Stevenson (PHREE), Jacques van der Gaag (PHRWH), and Adriaan Verspoor (PHREE) made helpful comments on earlier drafts.
# ACRONYMS

|EIAL<br>|Early Intensive Adjustment Lending Country<br>|
|---|---|
|EMENA|Europe, Middle East and North Africa region<br>|
|GDP<br>|Gross Domestic Product<br>|
|GNP<br>|Gross National Product<br>|
|IAL|Intensive Adjustment Lending Country<br>|
|IDS<br>|Institute for Development Studies (Sussex)<br>|
|ILO|International Labour Office<br>|
|IMF|International Monetary Fund|
|LAC|Latin America and Caribbean region|
|LSMS|Living Standards Measurement Surveys<br>|
|NAL|No Adjustment Lending Country|
|OAL|Other Adjustment Lending Country<br>|
|PE|Primary Enrollment Rate<br>|
|PER|Public Expenditure Review|
|PFP|Policy Framework Paper<br>|
|PPP|Purchasing Power Parity|
|PRM<br>|Public Resource Mobilization<br>|
|SAC|Structural Adjustment Credit|
|SAL<br>|Structural Adjustment Loan<br>|
|SDA|Social Dimensions of Adjustment<br>|
|SECAL|Sector Adjustment Ioan|
|SECIL|Sector Investment Loan|
|SIL|Specific Investment Loan<br>|
|SRA|Sector Resource Allocation|
|SRM|Sector Resource Mobilization|
|UNDP|United Nations Development Programme|
|UNESCO|<br>United Nations Educational, Scientific, and Cultural Organization|
|WDR|World Development Report|
# EXECUTIVE SUMMARY

i. This pap reviews the literatuire (World Bank and external sources) in order to assess what is known about the effects of adjustment on education, with particular emphas,s on World Bank adjustment lending. Facing external shocks and serious balance of payments disequilibria, countries have several choices: to postpone the need for adjustment by borrowing more abroad, to increase domestic controls and the inward orientation of the economy, or to undertake a program of managed adjustment (usually with IMF or World Bank assistance). World Bank adjustment lending supports several types of policies that directly or indirectly influence education: trade policies (exchange rate flexibility, trade liberalization), fiscal policies (tax and price reforms), and public sector management policies (reductions in expenditures, civil service reform). In the short term, these policies affect both education supply and demand. Long-term effects depend on whether adjustment successfully renews economic growth, and whether any short-term damages are reversible. Adjust. **.it** measures affect education through changes in the macro (budget containment, cost recovery) and micro (household incomes and prices) levels of the economy. The impacts of adjustment on education are determined by corditions L the sector before adjustment, as well as the naure and implementation of the adjustment program.

ii. Adjustment programs have incited strong debate since iheir inception, with the debate focusing on IMF and World Bank adjustment lending. However, most critics of adjustment programs say little about education directly, and do not distinguish the effects of international recession, fiscal constraints, or structural problems from the effects of adjustment measures. The Bank initially emphasized that macroeconomic adjustment policies were short-term and therefore were not the appropriate instrument for promoting long-term social development. Early adjustment programs ignored education issues, seeking to rapidly redress economic distortions. But the adjustment process lasted much er than expected, and Bank and external researchers found evidence of significant shon .m costs in the social sectors. As a result, the Bank has broadened its approach to adjustment in order to better protect education from direct and indirect negative impacts of adjustment. SAL conditionality tatgeting education increased, and the Bank also developed new instruments for policy lending to the sector: education SECALs, hybrid loans combining investment and adjustment components, traditional investment loans that specifically support sector adjustment programs, and sector investment loans.

iii. Analyzing how adjustment affects education is more important than simply determining adjustment's "guilt" or "innocence." In order to design and implement appropriate intorventions, lenders, borrowers, and policymakers need to know how macroeconomic and sector adjustment, both as on-going processes and as deliberate responses to discrete c6rcumstances, affect one another. It is particularly important to determine the likely effects of policy reforms on sector financing, and in turn, the effect of changes in financing on coverage, quality, and equity. The literature frequently suggests that declining trends during the "adjustment" period (post-1980) imply causality, and offer hypotheses about how macroeconomic or sector adjustment policies translate into sector effects. However, concrete evidence that explains the process of sector adjustment to sector or macroeconomic reforms and that supports general statements is lacking.

i
> **is.** Although adjustment has certain direct and indirect implications for education, many of the eui rent trends have their roots in preadjustment mismanagement or economic recession. A ijustment is an essential and continuous process for every country that wishes its economy to grow. Countries must continuously adapt to changing international conditions. Many countries that do not adjust quickly enough face serious difficulties, including unsustainable fiscal deficits and debt burdens. Nonadjustment results in distortior- and inefficiency at the macro and sector levels that are exacerbated over time, and is likl.y to have serious detrimental effects on education.

V. In order to understand the process through which adjustment affects education, a comparative dynamics approach is required, i.e., o;ne that incorporates the dynamics of the effects of change internal to the system on outcomes. An ideal methodology would determine how specific adiustment measures affect education supply and demand, d- in turn how the interactions between supply and demand factors translate into sector outcomes. Even when correlation is evident, analysts must delve deeper to determine what happened, why did it happen, was the outcome intended, and is the direction of change positive or negative. In addition, it is necessary to estimate likely education outcomes in the absence of adjustment programs, in order to establish causal links between indicators and adjustment programs.

vi. Evaluation studies have not rigorously followed this approach. Available data and models limit analysis to a comparative statics approach. First, the data describing the evolution of the education sector during adjustment are scarce and of poor quality. The most common indicators are aggregate financing and enrollment indicators that are difficult to interpret. Second, whether they compare figures from "before" and "after"' adjustment or establish typologies of "adjuaing" versus "nonadjusting' countries, analyses compare indicators between two static points, but say nothing about how or why the indicators changed. In particular, the effects of changes in financing on coverage, quality, and equity are by no means obvious. Because education has a long gestation period, the impacts of adjustment may not yet be evident. Long-term effects may differ in magnitude and direction from short-term effects. Finally, it is virtually impossible to isolate the effects of adjustment from those of other simultaneous influences on the sector. Given the complexity of adjustment, combined with data constraints, it may be impossible to develop a general methodology to analyze how adjustment programs affect education. In the absence of any crosscountry comparative dynamics models for adjustment and the education sector, country studies that crosstabulate a variety of indicators provide some insight into the dynamics of adjustment and education.

vii. In the literature that compares the situation in "adjusting" and "nonadjusting" countrios, th-e principal conclusion is that public education expenditures and gross primary enrollment rates are negatively associated with World Bank adjustment lending. The longterm implications for national development are serious. Education financing deteriorated in adjusting countries because recession reduced all public expenditures, debt service obligations grew, or civil service wages changed and reduced education's budget share relative to less labor-intensive public seczors. However, the question of what would happen in the absence of adjustment lending remains. Education expenditures may decline even ii
more and long-term effects may be even more serious if macroeconomic ar-d sector distortions persist.

viii. In general, seetor financing data only describe central government spending (neglecting local government or private resources). The coexistence of adjustment programs and decl-ning enrollment rates does not nece-sarily imply causality, nor are<sup>the means</sup> through which adjustment policies translate int enrollment changes apparent. Country studies suggest that public education financing .; not immediately and directly associated with enrollment rates. Coverage of quality indicators is inconsistent, incomplete, and inconclusive regarding the impacts of adjustment programs on edusition quality. Available evidence must be interpreted carefully, as the links between adjustment policies and quality indicators are difficult to ascertain. Nor does the literature analyze equity indicators<sup>in a</sup> systematic manner. The most widely-cited equity indicator is the female (versus male<sup>or</sup> total) primary enrollment rate. Adjustment appears not to have influenced equity: female enrollment rates continued to approach male enrollment rates during the adjustment period. Quantitative evidence in the form of comparisons between rural and urban areas or nousehold income levels is scarce.

ix. The difficulties in separating the costs of adju.:tment from the costs of external shocks, poor policies, or nonadjustment, imply a continuing need for careful monitoring and analysis. To analyze the process through which adjustment affects the educatior. sector, time series data are necessary for a number of years before, during, and after (if possible) adjustment. Data collection and monitoring efforts must focus systematically on a wide range of indicators that measure aspects of education supply and demand. Expendture data should measure more than the absolute and relative allocation. of public resources to the sector, for example private, community, and local or regional government financing. Sector resources should be categorized by function (capital versus recurrent), by purpose (salaries, supplies, maintenance), and by level of education. Data on income distribution, the potential returns to education, as well as the opportunity and private costs of education are necessary to understand education demand.)" Collecting this information is a massive undertaking, and may only be feasible in country studies.

X. In conclusion, reliable evidence on the effect of adjustment policies on the education sector is limited. There appears to be a causal link between adjustment and education, but the nature of the link varies widely and is 1 -lv understood. For example, evidence of reductions in public expenditures during adjusuiiient is pervasive, but there is considerable uncertainty regarding the effects of declining public financing on education. Explanatory models are poorly specified, and they rely on a weak database. As a result, it is difficult to determine causality, i.e., to isolate the specific effects of adjustment policies. Furthermore, the implications of changes in financing for education quality and equity are l/Addition information is useful in evaluating changes in quality and equity, for example: changes in health and nutrition that affect children's learning ability; intake, repeater, and dropout rates, as well as student performance on standard exams: enrollment<sup>rates</sup> broken down by region, gender, and income level.

iii
unclear. Given country-specific initial conditions, shock., and adjustment packages, country studies are the most effective framework for analyzing the adjustment ptocess.

xi. Further research and analysis that focuies on process monitori.ig is critical. For example, the database can be improved by monitoring key education indicators duning the adjustment process- Research should seek to complement existing comparative statics assessments with analyse3 of the dynamics of sector adjustment. Particular questions for further research that have important implications for the design and implementation of adjustment programs are given below. But even in the absence of precise answers, evidence suggests probable links between adjustment measures and the education sector. Progress is evident in the design of World Bank adjustment lending, but much more needs to be done to address education sector issues.

* How do macroeconomic policies, particularly changes in public expenditure levels, affect the supply of education? How do changes in supply in turn affect coverage, quality, and equity in the education sector?

* How is contraction in the education sector managed--what are the dynamics cf budget cuts among different subsectors of education? What political forces promote or impede adjustments? If resource transfers from higher to primary education are widely recommended, why are they not implemented? How, if at all, can adjustment lending affect institutional bottlenecks?

Is education protected or vulnerable relative to other sectors during periods ,, fiscal retrenchment, increasing debt, or civil service reform? Does education vulnerability vary by region or income level? If differences exist, can they be explained by differences in the adjustment process between country groups? What types of policies or conditions enable a country to protect education (i.e., deliver a reasonable level of service), and specifically basic education?

_e '0To_ what extent have local government, community, private, or household resources replaced declining government resources? How do decentralization and cost recovery in turn affect coverage, quality, and equity?

**_o_** How and why has demand for education changed during adjustment? How do changes in incomes (the household's or individual's ability to invest in human capital), the opportunity cost of attending school, private returns to investing in education, or health and nutrition affect coverage, quality, and equity?

iv
# **I.** INTRODUCTION

1.01 Although many studies evaluate the effects of adjustment on economic growth and on the poor, few assess the specific impacts of adjustment progr-ms en the education sector. This paper reviews the lterature on this topic (World Bank dnd external sources) in order to assess what is known about the effects of adjustment on education, with particular emphasis on World Bank adjustment lending. Section I provides a brief description and history of adjustment lending, and analyzes how adjustment policies affect the education sector. It concludes witn a description of changes in ad astment lending and presents several types of loans that address education issues. Section II describes the types of data and methodologies used to assess the impact of adjustment on education. The section also points out difficulties in interpretii-,i available data. Section III analyzes major factors (capacity, coverage, quality, and equity) that affect education supply and demand, and suggests additional data and analyses that are required to design and implement effective adjustment interventions from the education sector perspective. Finally, Section IV broadly summarizes how the sector manages the adjustment process. It concludes with a number of questions for further research that have important implications for designing and implementing adjustment programs.

# A. Description

1.02 Many developing countries faced serious balance of payments problems during the late 1970s and early 1980s. The problems stemmed from factors such as the sharp deterioration in the terms of trade for oil-importing countries and from the legacy of weaknesses in domestic policies and institutions (for example, overvalued exchange rates and bloated civil services). Faced with adverse external shocks, a country can respond in several ways. One is to postpone the need ) adjust by borrowing more abroad--an alternative seldom open to countries already heavily indebted in the 1980s. Another is to increase domestic controls and the inward orientation of the economy--an alternative likely to be costly in terms of efficiency and growth. Finally, a country can undertake a program of managed adjustment, usujally with IMF and World Bank assistance. Adjustment broadly includes managed reductions in public expenditures as well as changes in relative prices. Adjustment measures are designed to make the economy more efficient, more flexible, and better able, o use resources and thereby to engineer sustainable long-term growth.

1.03 The World Bank's first structural adjustment loans (SALs) were extended in 1980. Adjustment loans differ fror:- traditional investment loans in that they provide quickdisbursing budgetary support disbuirsed in tranches against successful implementation of a set of agreed-upon policy actions. World Bank adjustment policies are distinct from the IMFs stabilization policies. Stabilization is short-.erm, demand-oriented, and focused on the macroeconomic and financial sides of the economy. Adjustment is aimed at the medium-term (3-5 years), supply-side, microeconomic as well as macroeconomic, and real sides of the economy. The two interventions are coordinated in thb n11diirm term since the IMF and the World Bank agree with the country on priorities '% it joint policy framew3rk

1
paper (PFP) bevfore engaging in any stabilization or adjutstment lending.21 Lending conditionality must then coincide with the PFP. In practice, almost all adjustment loans have been contingent upon having an IMF stabilization agreement under way or already in place (Stevenson, 1988).

1.04 After growing rapidly in the first half of **the** 1980s, adjustment lending leveled off in 1986-88, when it averaged $4.5 billion a year or 24 percent of Bank Group leniding. The scope of adjustment lending widened with the introduction of sectoral adj'tstment loans (SECALs) and, to a smaller degree, quick-disbursing components of hybrid investment and adjustment loans. SECALs increased from 15 percent ($15 niillion) of World Bank adjustment lending commitments in 1980 to 64 percent ($2,535 million) in 1990. Seventy countries had received over 200 adjustment loans by the end of FY90. Sixteen countries had five or more SALs or SECALs, 23 countries three or four adjustment loans, and 31 one or two (see annex 2). Adjustment lending rec-ipients are equally divided between lowincome and middle-income countries, with Sub-Saharan Africa accounting for most of the former and the highly-indebted countries for most of the latter. **!a** 1989, regional shares of total adjustment lending commitments were similar to those in recent years: 44 percent LAC, 20 percent Africa, 19 percent Asia, and 17 percent EMENA.

1.05 The World Bank's &djustment lending supports several types of policies. Trade **-** policies emphasize exchange rate flexibility, export expansion, -d impurt liberalization. Fiscal policies include tax reforms and the removal of price distortions that adversely affect productivity. Public sector management policies seek to improve management capabilities and the efficiency of government cApenditures. The World Bank and the borrower agree on a number of "conditionalities" that are to be met prior to or during the course of loan disbursement. Conditionality initially applied to macroeconomic policy elements, but during the 1980s widened to include conditions relating to sectoral, institutional and micro levels (Havnevik, 1987). Conditionality in several policy areas has important implications for the education sector. Public recurrent and capital expenditures conditionality addresses the size and composition of the public investment program, as well as the recurrent expenditure allocation, in order to reduce the government buidget deficit and rationalize the public expenditure program. Wages and employment conditionaliti focuses on civil service retrenchment and is often implemented through a wage bill or hiring freeze. Subsidies conditionality reduces or removes government subsidies in order to correct price distortions, improve economic efficiency, and improve the equity and efficiency of subsidy programs through better targeting. Social policies conditionalit protects vulnerable groups from the impacts of adjustment, especially during the transition period (Kakwani, et.al., 1990).

# B. Effects of adiustment on education

1.06 Adjustment programs have incited strong debate since their inception. The debate focuses on IMF and World Bank I- ling, although a number of countries undertook adjustment programs without assistance **th** xm these two institutions, and other bilateral and

l/However, in the short term IMF and Bank programs may have significantly different objectives: for example, recent Bank programs emphasize social nets and target groups.

2
multilateral donors coflnanced adjustment programs. The effects of adjustment on education depend on the external environment as we: as on conditions within the country and within the sector before the adjustment period. Sahn (1989) suggests that the variability in performance and outcomes observed in adjusting countries largely reflects: 1) external and domestic circumstances that precipitated the nend for such change (inefficient domestic policies, external shocks, the debt crisis), and under which reform programs are applied; 2) the character of the policy package (macro versus sector-specific measures); 3) the degree and pace of implementation; and 4) the choice of the year as the starting point for "adjustment."

1.07 Mosz critics argue that adjustment negatively affects incomes and living conditons of the poor. Evidence to support these arguments is not conclusive. Although critics say little about education directly, their arguments do apply indirectly to education: deteriorating incomes and living conditions may reduce demand for education, while improved education may help improve incomes and living conditions. One arpument is that adjustment programs stem from a strictly economic outlook that considers recurrent expenditures on education to be the same as any other recurrent spending. Thus educat is simply one more source of public spending that aggravates budgetary disequilibriun However, human capital theory views recurrent education spending as a productivity-raising investment in human resources. Therefore, changes in recurrent spending that alter the output and quality of education affect the productivity of human resources, and in turn affect siational income and growth over the long term. Adjustment policies that reduce education spending may reduce investment in human capital if spending does not become more efficient, and may have long-term costs that outweigh short-term cost savings. In fact, many Bank-funded adjustment program explicitly protect real education expenditures, particularly at the primary level, and focus or, ways to increase the efficiency of resource Use in the sector.

1.08 Another important argument is that in practice policy changes under adjustment are guided by political rather than efficiency considerations. This argument addresse- the implementation rather than the design ef adjustment programs. Nevertheless, chargLs in program design may alleviate some implementation obstacles. Serageldin (1989) asserts that a common tendency is to cut back on social spending at basic levels (primary education) in favor of areas where political constituencies are more powerful (universities) Experton (1988) concurs tnat goverrments find it easier to avoid irncreasing access to primary education than to impose structural reforms to reduce demand for higher education.Z' The result is that resources increasingly favor higher levels of education, particularly at the expense of rural and marginalized populations, the ones least likely to react negatively to these austerity measures. Furthermore, Gallagher (1990) states that for political reasons, direct hardships to employees and immediate costs to society or

}/For example, in response to nationwide student unrest in 1987-88 among secondary and university students, the Senegalese government proposed substantial increases for higher education in the 1988/89 budget, contrary to the adjustment program's targets for containing expenditures in higher eduication in order to finance expansion rf primary education (Fredriksen, 1990a).

3
policymakers are avoided. Amadeo and Camargo (1989) also argue that tight budgets result in spending cuts to those items easiest to cut (supplies, infrastructure) rather than those making the most sense from an efficiency viewpoint (salaries, jobs). Contractionary budgets therefore tend to be accompanied by lower allocative efficiency although the goal is to inr"v efficiency.

1.09 Although adjustment policies do have certain direct and indirect implications for education, current trends often have their roots in pre-adjustment mismanagement or economic recession. Most critics of adjustment programs do not distinguish the effects of international recession, tiscal constraints, or structural protlems from the effects of programs or policies designed to offset them. Some recognize that recession and the debt crisis produced severe fiscal imbalances that require adjustment of some form (Knight, 1989), but others imply that conntries would make no policy changes to improve the situation in the absence of Bank lending, although policies are often unsustainable (Michalopoulos, 1987). Adjustment is an essential and continuous process for every country that wis.hes its economy to grow. Countries must continuously adapt to changing international economic conditions, particularly external shocks such as increases in the price of oil, world recession, and changing terms of trade. Many countries that do not adjust quickly enough face serious difficulties, including unsustainable fiscal and trade deficits, large debts, unrealistic exchange rates, inappropriate tax and price structures, and inefficient public sector management. Nonadjustment results in distortions and inefficiency at the macroeconomic and sector levels that are exacerbated while resources decline and economic growth stagnates, and is likely to have serious detrimental effects on education.

1.10 4djustment measures (undertaken with or without World Bank assistance) affect education through changes at the macro and micro levels of the economy. Adjustment at the macro level often implies a combination of budget containment measures for the public education system, limited access to postprimary public education, and higher user fees for education services at the secondary and tertiary levels. At the micro level, changes in household incomes and prices (user fees, reduced student subsidies) directly influence the demand for education by altering the opportunity cost of attending school (UNDP, 1989). Household incomes also affect health and nutrition status, and thus indirectly influence attendance aml learning ability. Finally, adjustment affects education through changes in markets and infrastructure (resulting from currency devaluation, fiscal and monetary restraint, and price liberalization) that affect the supply of education services and the opportunity cost of attending school (World Bank, 1990b). More specifically, adjustment policy effects on education supply and demand are described below.

1.11 Education Supply: The most obvious impacts of adjustment policies on education are short-term changes in public expenditures. Education supply need not decline if private resources replace public resources. But in most countries, education is primarily funded by the public sector. Because SALs focus on correcting imbalances in the economy and laying the foundations for growth rather than on equity, the particular forms taken by cuts in subsidies, real wages, and real education expenditures have high social costs, at least until the economy begins to grow (Cornia, et.al., 1987). Griffin and Knight (1989) argue that in many Third World countries human development programs are "savagely" cut, and long-term prospects for development diminish while inequality and poverty increase. The

4
most sophisticated analysis available (Kakwani, Makonnen and van der Gaag, 1990) associates adjustment lending with doclining trends in public education financing and gross primary enrollment rates. Lower public education expenditures may result in lower quality and quantity of education services, fewer amenities (school lunches), or higher user fees. Furthermore, any change in civil service wages or employment has particularly strong effects on the labor-intensive education sector. Lower wages may reduce the short-term efforts of teachers, if not cause an exodus of experienced teachers (UNDP, 1989). Even if adjustment policies do not cause deteriorations in soJal conditions directly, they are criticized for not reversing declining trends.

1.12 On the other hand, Kakwani, et.al. (1990) suggest that the need to cut expenditures provides an opportunity to increase efficiency and equity i.a the use of resources. Serageldin (1989) notes that the Bank increasingly supports specific measures to protect vulnerable groups, for example by shielding public expenditures on key education and basic welfare services, by reviewing the composition of education expenditures and reorienting government spending in the sector, and through compensatory actions and transitional arrangements. Berg (1989) emphasizes that measures to reduce secondary and higher education's budget share; over time release resources that can be reallocated to primary education. Costs can be reduced by improving the efficiency ane cost-effectiveness of all public expenditures. The Bank hopes that by giving the social impacts of adjustment programs earlier and more serious attention, the adverse impacts of adjustment can be reduced (Ribe, et.al., 1990). For example, education expenditures can target those most in need, while the burden is placed on the relatively wealthy who have access to private education facilities and are able to pay higher fees (Demery and Addison, 1987). The need to restructure the public budget under adjustment is an opportunity for governments to evaluate social programs. If these measures are effective, the quantity and quality of educLtion services could improve during the adjustment period, even when sector resources decline. Guaranteeing access to education services protects the human capital of the poor, but will often require additional public resources. The Bank (1989e) explicitly recommends that governments in Africa commit additional resources to the social sectors, with an overall objective of 8-10 percent of GDP to be spent on human resource development.

1.13 Education Demand: The major demand effect is likely to be short-term reductions in income that lower demand for schooling. Declining household incomes, higher unemployment levels, and changes in relative prices raise the opportunity cost of time spent in school, relative to time spent in economic or household activities. Demand for education also decline if poor health and nutrition reduce attendance and the capacity to gain from education. Finally, demand responds to changes in supply such as lower quality and higher user fees.

1.14 Demand effects of adjustment policies are also positive. If children have less attractive labor market options, the opportunity cost of attending school declines. Demand also increases in response to more attractive labor market options: adjustment in the long term increases the expected private rate of return to education in response to expected improvements in the long-term prospects of the economy if the adjustment program is successful (UNDP, 1989). Overall impacts on demand vary by level of education because of differences in social and private rates of return to education investment. The social rate

_5_
of return from primary education, and the private rate of return from tertiary education, are relatively high. Therefore, reductions in public education expenditures will affect subsectors differently, depending on how the cuts are implemented. Cuts at the primary level tend to reduce demand, whereas cuts at the tertiary level are more likely to induce private expenditures, and demand is less likely to decline. For this reason, many adjustment programs include reallocations from tertiary to primary education.

1.15 Sbortterm- versus Long-term Effects: Bank analysts continue to argue that some short-term social costs are inevitable when an economy has to adjust to adverse external shocks or to the effects of previous policy mismanagement. Even a well-designed adjustment program harms some groups, while the majority benefit, since adjustment usually involves changing relative prices and reducing government expenditures. But Nicholas (1988) proposes that the transitional costs of orderly adjustment are smaller, particularly under recent adjustment programs that include conditions for maintaining social sector expenditures, and the long-term benefits larger, than with ad hoc adjustment.

1.16 The long-term effects depend very much on whether the adjustment policy is successful (economic growth resumes, employment increases, and wages rise). If it is, then as compared with the situation that would have prevailed without the adjustment program, the private returns to education and the supply of resources for education will probably be greater. However, the opportunity cost of time spent in education rather than in productive activities is also likely to be greater. Generally the former effect is expected to dominate, though it is far from obvious that it will in all cases (UNDP, 1989). According to Turok (1989), "education is a slow process requiring sustained effort which cannot be made up for by crash-courses when funds once more become available." Likewise, Simai (1986) warns that unavoidable cuts in social expenditures should be made with extreme caution and with a long-term policy view, since losses in these areas cannot be easily recouped and longterm damages, even of shorter-term measures, may be excessively high. Disinvestment in human capital threatens the country's future development potential.

# C. Changes in World Bank adjustment operations

1.17 The Bank initially emphasized that macroeconomic adjustment policies were not the appropriate instrument for supporting long-term social development. However, the adjustment process lasted much longer than expected, and Bank and external researchers found evidence of significant short-term costs in the social sectors. As a result of external analysis, experience with adjustment lending, and changing government and World Bank objectives, adjustment loans at the end of the 1980s differed significantly from those in the early 1980s. The Bank traditionally focused on the investment budget and paid less attention to budget posts primarily financed through the recurrent budget (such as education). The first SALs did not consider the social impact, and the Bank disassociated economic adjustment policies from the social sectors. However, adjustment is taking longer in most countries than was originally expected. Two Bank reports on adjustment lending (1990a, 1988e) concluded that because domestic inefficiencies proved to be more intractable than previously thought and external uncertainties continued, the focus of adjustment lending should shift from short-term crisis management and stabilization to more fundamental issues of long-term growth, development, and poverty reduction (Ribe and

6
Carvalho, 1990b). Furthermore, the Bank recognizes that adjustment programs impose transitional costs: output, employment and consumption are depressed as in a recession; the structure of incentives is changed to stimulate a reallocation of resources between sectors and activities; and productive resources do not move effortlessly and instantaneously among alternative uses in response to changes in relative prices.

1.18 The Bank approach to adjustment evolved and gradually measures were incorporated in adjustment programs to protect the social sectors including education from the direct and indirect negative impacts of adjustment measures. The lending focus shifted from macroeconomic (SALs) to sector (SECALs) adjustment. Less comprehensive SECALs were often politically more acceptable and also more feasible, given the limited implementation capacity in many countries. The sector approacii was also more appealing because reforms of sectoral institutions and policies often had the potential both to address macroeconomic problems and to increase efficiency at the sectoral level. The following quotes illustrate how the focus of adjustment lending changed:

1986: SALs are not intended, nor are they the appropriate instrument, to address poverty, basic needs and social issues directly. It is virtually impossible to alleviate poverty and deficiencies in social services in a severely distorted economy in a crisis situation. SALs therefore seek to redress these distortions, and the poor will benefit in the medium-term to long-term (World Bank, 1986d).

1990: Adjustment programs should provide measures to reduce the potential short-run burden on the poor of external shocks or adjustment policies. Social sector adjustment loans (SECALs) should complement adjustment policy reforms by supporting measures to achieve fundamental social objectives, such as improving education for the poor. This type of lending should be an integral part of overall adjustment programs (World Bank, 1990a).

Both types of adjustment loans increasingly supported greater efficiency and equity in social expenditures, particularly in the education sector (Nicholas, 1988). Recent Bank adjustment operations include more detailed analyses of the anticipated social impacts of adjustment programs and more measures to alleviate the short-run costs (such as reallocations of social expenditures toward services used by disadvantaged groups).

1.19 The Bank's first attempts to address education in adjustment programs were introduced several years after Bank-assisted adjustment had begun, in the form of education SECALs. Most recently, the Bank began to address the sector in SAL conditionality, or in investment projects designed and implemented at the same time as the overall adjustment program. Concern for the education sector has shifted to much earlier in the adjustment process, and a pattern of increasing attention over time to education sector concerns is evident. Not only did SAL conditionality targeting education increase after 1986, but the World Bank also developed new instruments for policy lending to the sector: education SECALs, hybrid loans combining investment and adjustment components, specific investment loans with a significant policy component, and social development funds.

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1.20 Structural adjustment operations: Ribe and Carvalho (1990b) review 30 SALs (approved between July, 1986 and December, 1988) and conclude that more recent SALs include a greater number of interventions to address the social impacts of adjustment. SAL conditionality specifically referring to education and the social sectors greatly increased in recent years (box 1.1).y

# BOX **1.1:** SALs that **addrduc?tiQi**

Recent SALs include social expenditure reforms that protect the poor against short-term social costs or that enhance the long-term impact of the adjustment program on the poor. In particular: SALs seek to maintain or increase reai expenditures on basic education in a period of overall reduction in public expenditures. Mauritania's SAL I (1987) gave priority in allocating bud'etary resources to education, albeit under the strict constraint of balanced budgets.

- SALs redirect social sector expenditures to the poor through better resource targeting toward or within primary educaton. Niger's SAL I (1986) channeled public savings from reduced transfers and subsidies and higher user charges for tertiary education to. primary schooling.

- SALs improve the efficiency of public social expenditures. Sao Tom6 and Principe's SAL 1 (1987) proposed to improve public expenditure efficiency in education by assuring adequate budgetary aocations and by redesigning programs and delivery systems to maximize the impact of such programs.

Sourc: Ribe and Carvalho (1990b).

lExamples are SALs in Benin (1989), Cameroon (1989), C6te d'Ivoire (1982, 1984), Gabon (1988), Ghana (1987, 1989), Guinea (1988), Malawi (1981, 1984), Mauritania (1987), Mozambique (1989), Niger (1986), Senegal (1986, 1987, 1990), Togo (1988), and Zaire (1987).

8
BOX [2: Sector adjlulstme Iend' in ' " , ' i XH~IiAN Ghana's First Education Sector AdJustment Cdit (1987) supported tie government's education reform program to reverse the decid-long deterioration in educational infrastructure and to use recurrent expenditures more efficiently The program is being continued under the Second Educatidn Sector Adjustment Credit (1990). The reform supports the following measures:

* Duration of schooling: Shorten pre-university sehooling from 17 to- 12 years, and increase the length of the school day and the shool year.

* Curriculum: Manufacture a limited number of basic textbooks locally, many of them in local languages, and introduce a simplified syllabus for junior secondary schools. Levy fees for textbooks in secondary and tertiary education.

* Teacher training: In response to a growing shortage of qualified teachers, shorten the teacher training course for new teachers by a year to three years.

* Budget: Audit the Ministry of Education staff,. aboish all posts "filled" by non-existen **t** eachers, and reduce non-teaching staff. HalveAtie room and board'. subsidy for secondary and tertiary institutions, replacing subsidies with scholarships or loans for the most needy students.

MALI: Mali's Education Sector Consolidation Projedt (989) combines a s adjustment program with an investment element that fociuses on primary education and the management of sector resources.

The sector adjustment program establishes the policy and institutional -framework for improving, at all levels of the system:: a:) equt, tyacsd .b) performance and relevance, and c) the cost-effective.management of human, financial and physical resources. For example, student o nto econfdary and higher education are controlled in line with projected budgetary resources and trends in labor market demand. The adjustment program also supports revision of textbooks and teacher training policies, mobilize rate resources, ad restructures the budget in favor of primay education and materials.

Within this framework, the investment element supports the core investments of a long-term development program. It inreases enrollments through a school construction, rehabilitation, and repair program. Additional investment focuses on revising teacher training and primary education curricula, as well as on providing textbooks, pedagogic materials, and in-service training.

Sources: Nicholas (1988), World Bank (1989b).

... ...

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1.21 Serjme et: SECALs (box 1.2) are typically extended to countries facing acute macroeconomic difficulties as well as severe distortions in the allocation and use of education resources. The sector adjustment program normally comprises: a) reforms to promote more efficient allocation and use of sector resources; b) targets for the share of the government's budget allocation to the sector, to specific subsectors, or to particular types of expenditures; and c) a mediun.i-term investment program for the sector (Fredriksen, 1990b). The first Education SECAL was to Morocco in 1986, followed by others in Ghana (1987, 1990), Guinea (1990), and Nigeria (1990). The World Bank's first and only "hybrid" education sector investment and adjustment loan in Mali (1989) combines the adjustment features of a SECAL with the investment features of an investment loan. The hybrid loan is used where preventing the deterioration of already low education quality and coverage is urgent, requiring both broad reforms as in SECALs and investment to support the implementation of the reforms (Fredriksen, 1990b).

1.22 Investment projects concurrent with adjustment operations (box 1.3): The bulk of Bank involvement with education sector adjustment continues to be through traditional project lending. Specific investment loans (SILs) finance investments (specific works, goods, and services) designed to create new education and training capacity and to improve the quality and efficiency of existing programs by strengthening the sector's planning and management capacity. SILs gradually evolved from an almost exclusive focus on the economic and technical viability of the investment itself to include policy reforms considered essential to ensure its overall sustainability.4 / Sector investment loans (SECILs) also support policy and institutional change objectives, but differ from traditional SILs in that SECILs transfer responsibility for detailed project design, appraisal and supervision (especially of physical investments) from the Bank to the borrower. SECILs also focus more on policy and institutional objectives, and typically finance a share of the country's sectoral investment program (Fredriksen, 1990b).

i"Examples of recent SILs (FY1990) that incorporate strong adjustment measures are Bangladesh (General Education), China (Vocational and Technical Education), Malawi (Second Education Credit), and Tanzania (Education Planning and Rehabilitation).

0/SECILs for FY1990 were Egypt (Engineering and Technical Education), Pakistan (Sind Primary Education Development), Turkey (National Education Development), and Korea (Universities Science and Technology Research).

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# **BOX L3: Ss** and **SECls**

SEOAL SII The principal objective of the Sdn6gal Primaty Education Development Project (1987) was to assist the government in accelerating the qualitative and quantitative development of primary education, within the framework of its adjustment program. The adjustment measures promoted through the project are In most respects as comprehensive as those promoted through recent SECALs or hybrids. The project combines an investment component (that addresses textbooks provision, planming and research capabilities, construction), with a policy component. The policy component has two types of measures: To increase primary school enrollments by reducing unit costs through more efficient use of teachers and facilities: double-shift and multigrade teaching, higher student/teacher ratios, increase the ratio of "instituteurs" to "instituteurs-adjoints."

* To contain spending in post-primary education: reduce scholarships and indirect subsidies, establish cost recovety, and limit budget growth.

MALAWI SEC:L, Malawi's First Education Sector Credit (1987) financed a three-year time slice of the government's 1985-1995 education investment program. Responsibility for project design and implementation was transferred to the government because the latter had demonstrated, in the course of five preceding education projects, adequate appraisal and implementation capability. The government prepared a series of policy actions that the program supported:

- To improve education equity by increasing primary education's share of education resources.

* To improve education efficiency, i.e., improved student flows especially at the primary level). Specific measures targeted curriculum reform, teacher training, lower student/teacher ratios, and sufficient supply of materials.

- To contain the growth of public expenditures on education by reducing unit costs and increasing cost recovery measures at postprimary levels.

- To improve access to primary (self-help primary school construction program), secondary (shift system and more day schools), and vocational education (better utilization of existing facilities).

# Qrces: Fredriksen (1990a), World Bank (1987c).

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# H. **TIHE** EVIDENCE: METHODOLOGY AND DATA LIMITATIONS

2.01 In order to understand the process through which adjustment measures affect education, a comparative dynamics approach (i.e., one that incorporates the dynamics of the effects of change internal to the system v., outcomes) is required.V An ideal methodology would need to identify exactly what adjustment is: what are the specific measures and how do they, independently from other simultaneous influences on the sector, translate into effects measurable by education indicators (i.e., establish causality).V Analysts must determine how adjustment programs affect the factors governing education supply and demand, and in turn how the interactions between supply and demand factors translate into sector outcomes. In addition, it would be essential to estimate likely education outcomes in the absence of adjustment programs, in order to establish causal links between indicators and adjustment programs. However, given the complexity of adjustment, combined with data constraints, it may be impossible to develop a general methodology to analyze how adjustment programs affect education. A recent UNDP report concludes that "problems of data and methodology have thus far been so severe as to preclude any systematic evaluation of the social impacts of adjustment programs" (Chapelier and Tabatabai, 1989).

2.02 Existing data and models limit analysis to a comparative statics approach. First, the data describing the evolution of the e6acation sector during adjustment are scarce and of poor quality. Second, wh ether they compare figures from "before" and "after" adjustment or establish typologies of "adjusting" versus "nonadjusting" countries, analyses compare indicators between two points in time, but say nothing about how or why the indicators changed. In the absence of crosscountry comparative dynamics models for adjustment and the education sector, country studies that crosstabulate a variety of indicators provide some insight into the dynamics of adjustment and education.

## x MethodoloQ

2.03 Most analysis in the literature is superficial and based only on trends in education indicators during the period after 1980--the "adjustment" period-or on anecdotal evidence. Adjustment policies are cited as one of the factors that influence trends, along with the global economic crisis, the debt burden, political strife, environmental degradation, and population growth (Colclough and Lewin, 1990; Lewin and Berstecher, 1989). Anecdotal evidence (Cornia, et.al. [1987] report that positive macroeconomic trends belie visible deterioration in social infrastructure) is not quantified, and therefore does not permit crosscountry comparisons or generalizations.

L/The methodological difficulty is that of understanding how the macroeconomic environment affects the sector: what happens within the sector? Aggregate data provide few answers. One must study the micro level of schools, households, and individuals.

Z/For example, a country study could follow a group of people from the preadjustment period through to the postadjustment period, and compare their education outcomes to those of a counterfactual group that did not go through adjustment.

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# Table II.1: Methodologies to analWze the impacts of adjustment on education

|Methodology|Nu<br>Source<br>Cou|mber oEc<br>ntries|onmic<br>Indico|Education<br>Indicators|Conclusion|
|---|---|---|---|---|---|
|Before and after<br>adjustment|Sahn|16|Public budget (real<br>and % of GDP)|Education spenading (real<br>and share of discretionary<br>public budget)|No clear impacts<br>of adjustment|
|Fiscal duress|Gallagher|35|GDP growth|Education spending (share<br>of total and discretionary<br>public budgets)<br>Gross enrollment rates<br>(primary and secondary)|No clear impacts<br>of adjustment|
|Adjusting versus<br>Nonadjusting<br>Countries|Kakwani,<br>Makonnen,<br>Van der Gaag|86<br>|Public budget (total<br>and discretionary<br>as % of GDP)<br>Per capita private<br>consumption|Education spending (share<br>of total and discretionary<br>public budgets, GDP)<br>Per capita spending<br>Primary enrollment rates<br>(gross and net)<br>Growth of primary school teac<br>Student/teacher ratios|Intense adjusment<br>related to declines<br>in all education<br>indicators<br>hers|
|Adjusting versus<br>Nonadjusting<br>Countries|World Bank<br>(1990a)|78|GDP growth<br>Public debt<br>Public deficit<br>Savings, investment<br>rates<br>Per capita private<br>consumption|Education spending (%<br>of discretionary<br>public budget and GDP)<br>Per capita expenditures<br>(annual change)<br>Gross primary enrollment rate|Intense adjustment<br>related to declines<br>in all education<br>indicators|
2.04 Four sources evaluate how adjustment affected certain education indicators in the short term by establishing counterfactuals in order to compare (for a single group of countries) actual performance before adjustment with actual performance during adjustment, or alternatively (for two distinct country groups) actual performance observed during an adjustment program with actual performance in the absence of such a program. Table 11.1 presents the respective methodologies, showing that in several instances this analysis is quite simple and arbitrary.

2.05 Sahn (1989) compares education indicators for countries "before" and "after" World Bank-supported adjustment (see box 111.1). This methodology implies that any changes between the two periods are the result of adjustment lending, whereas any number of other factors could be responsible. In addition, Sahn does not compare countries that received adjustment loans to countries that did not. Gallagher (1990) compares "fiscally duressed" countriesW to nonadjusting countries (arnex 5) in order to determine how both groups managed the education sector. Neither Sahn nor Gallagher find any strong evidence that adjustment has affected public education financing and enrollment rates, either positively or negatively (chapter III).

2.06 The most sophisticated methodology is presented by Kakwani, Makonnen and van der Gaag (1990), who define five categories of adjusting and nonadjusting countries (annex 4). However, the results may be biased because of data paucity, resulting in some categnries for specific indicators containing as few as two countries. A later report (World Bank, 1990a) consolidates the country categories into three: early intensely adjusting (EIAL), other adjusting (OAL), and nonadjusting (NAL). Both reports associate adjustment lending with declining trends in public education financing, per capita expenditures, and gross primary enrollment rates.

2.07 Methodologies that compare adjustinp to nonadjusting countries facilitate crosscountry comparisons of changes in the education sector where countries faced broadly siniiar conditions such as recession or World Bank adjustment lending. However, isolating the effects of adjustment measures from those of other influences remains difficult (box 11.1). The differentiation between adjusting and nonadjusting countries may not be valid. Presumably the countries that adjusted were those that needed to do so, and therefore faced different economic conditions (internal and external) from those that did not need to adjust. For example, a high proportion of nonadjusting countries were middle-income countries. Furthermore, the World Bank methodology described above addresses only Bank-assisted adjustment, although some "nonadjusting" countries undertook major adjustment programs without Bank assistance (for example, Benin, Cameroon, and Sri Lanka).

V/Countries that were forced to adjust during the 1980s by sustaining reductions in real government expenditures and government expenditures as a share of GDP, with or without World Bank assistance.

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# **BOX** . Is o ,lating L th f., of ji t.1lint . .

Although the "before" and "after" periods can be tailored to the timing of adjustment in each country, change in a performance indicator in the program countries is attributed exclusively to program effects. However, during the 1980s the nonprogram determinants of performance varied widely over time and between countries. Thus the situation prevailing before the program is not a good predictor of what would have happened in the absence of a program.

The control-grcnp approach examines changes in nonadjusting countries to estimate what would have happened in adjusting countries in the absence of programs. Hlowever, it assumes that all countries face the same external enviromnent, and ignores the effects of preprogram and other country-specific characteristics on performance. The results may be biased if the external environment of program countries differs systematically from that of nonprogram countries. Finally, the approach requires a uniform definition of the period before and after adjustment, since the same period must apply to all countries.

The modified control-group approach adopted by the World Bank (1990a) minimizes the sample-selection bias and takes account of the changing external environment of each country. This approach recognizes the nonrandom selection of structural adjustment program countries, identifies the specific differences between adjusting and nonadjusting countries in the preprogram period, and then controls for these differences in comparing subsequent performance. To correct for the self-selection bias, the approach calculates the probability that a country will undertake: an adjustment progr based on lagged values of performance indicators (including external shocks, fiscal deficit, and dummy variables for concurrent IMP programs, world regions, and high debt), world nonprogram variables, and individual country characteristics.

Source: World Bank (1990a).

## B.Data

2.08 Data Qualitv: Crosscountry comparisons between literature sources are difficult because sources do not use the same indicators or the same time period, and it is often difficult to determine which figures are more likely to be correct (box II.2). At times, differences result from discrepancies in definitions: for example, education spending as a percentage of GNP refers alternatively to public and private spending, to public spending, or to central government spending. Sources that provide average data for five-year intervals ignore annual changes in the intervening years that can be significant. Other sources ignore long-term trends dating back to the 1970s. Finally, the age-specific population data used **to** derive gross enrollment rates are based on data for fertility and infant mortality from the last reliable census and extrapolations using a presumed population distribution (Berstecher and Carr-Hill, 1990).

15
Compiling the data for two indicators in Zambia reveals discrepanclec * between sources. For example, Source 1 indicates that education's share of the public budget increased after 1980, whereas Source 2 suggests that education's share declined through 1983. Source 3 shows a serious decline in enrollment rates in 1980, whereas Source 4 describes only a marginal decline in 1981. Variation between the sources for a single yenr is eight percentage points. Discrepancies may result from differences in definitions or in methods of extrapolation. Conclusions in different sources may therefore contradict one another, and it is difficult to judge which data are more likely to be correct.

Education shar-e of total goverment budget .(% 1975 1977 1979 1980 1981 1982 1983 1984 1985 Source 1 11.5 13.8 12.1 8.9 11.0 13.0 15.2 Source 2 17 (75-77) 14.2 (78-80) 13.8 (81-83) 142 (84-85)

# Gross pnmary enrollment rat _L_

1970 1975 1980 1981 1982 1983 1984 1985 1986 Source 3 90 97 90 93 .9699 97 Source 4 98 97 98 101 103 Sources: 1. Auerhan, et.al. (1985); 2. Colclough and Lewin (1990); 3. World Bank (1987a); and 4. World Bank (1988e). ._________________.. .

2.09 Data Availability: An important obstacle to assessing the effects of adjustment policies on the educatio:l sector is the lack of disaggregate data. The literature on education and adjustment (both aggregate analyses and country studies) most frequently provides data on public education financing levels and enrollment rates. Data on quality and equity indicators are much more scarce, and information on factors that influence the demand for education is virtually nonexistent, 2.10 Pata Aggregation: Many sources compare indicators for country groups to show crosscountry trends, but data coverage is inconsistent. First, the selection of indicators varies among reports. Second, the time period for which data are provided vary: some reports give annual figures, others give averages for periods of between two and ten years, still others average figures for "before" and "after" adjustment. Third, reports group countries alternatively by region (World Bank regions or geographic), by income level, or by differentiating "adjusting" from "non-adjusting" countries. Colclough and Lewin (1990) provide education sector statistics and trends for the 35 countries with gross primary 16
enrollment ratios of less than 90 percent ii 1985. This group is selected because "these are the countries whose populations are the most disadvantaged, in terms of the goals of Education For All." Seldom do two reports provide figures for the same indicator, the same year, and the same group of countries. Often the selection is restricted by data availability.

2.11 Time-Lags: Adjustment policies are relatively new (the first SAL was in 1980, the first Education SECAL in 1986). Education has a long gestation period, and the time lag before the impacts of adjustment-instigated changes become evident may be significant. In many cases the impacts of adjustment are still working their way through the education cycle. Many adverse effcts of adjustment are said to be temporary results of transition, and the long-term effects are expccted to be positive. Time lags are also evident in data collection eftorts: UNESCO data (the principal source for .:rosscountry comparisons) are currently available only through 1987, and even these figures are incomplete for specific countries or years. Only 45 of the 70 adjustment borrowers (annex 1) received Sias or SECALs before 1987. UNESCO data thus do not provide any evidence on the education sector during adjustment for over one-third of all adjusting countries. Many of the other countries had not completed the adjustment process by 1987, and analysis of the available data can therefore only be incomplete.

2.12 Causality: The literature makes few attempts to establish causality between adjustment policies and changes in the education sector. Did the decline in public spending result from externally-induced recession and structural problems, poor management, or adjustment policies designed to offset economic difficulties? What is the counterfactual, i.e., were conditions better or worse than if the World Bank had not supported implementation of the adjustment process? Sahn (1989) states that adjustment lending often occurs in the face of severe economic crises that would precipitate radical changes in public spending even without the typical SAL conditionality. According to Chapelier and Tabatabai (1989), many countries that needed economic stabilization and adjustment (particularly those in sub-Saharan Africa) had already been through a protracted period of mounting economic stress, during which social services deteriorated, before they undertook adjustment programs. Most sources do not separate the impacts of deteriorating economic conditions (recession, inflation, and the debt crisis) from those of changes in macroeconomic policies to address these problems.

2.13 Another variable influencing the education sector, independent of adjustment policies, is govemment commitment. Griffin and Knight (1989) argue that given the need for adjustment, it was easier and more expedient to reduce expenditures on human development than on other central government budget items. Governments' willingness to allocate resources to education changed during the 1980s as a result of increasing unemployment and migration of the educated, qualification escalation unrelated to job skills, and uncertainty about the contribution of education to increased productivity. According to Lewin (1987), changing government commitment and tighter budgets outweighed pressure to increase education investment from growing social demand fueled by population growth, continued manpower shortages, the power of interest groups, and the ideology of free and universal education provision. These statements, however, are not supported with specific evidence.

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2.14 Data Interpretation: The most common education indicators used in the reviewed literature are education spending as a share- of the public budget or of GNP, and the gross enrollment rate. These indicators, by themselves, explain little. Whether or not a decline in education's share of the total public budget reflects specific government priorities depends on a number of factors:

* Debt brden: Few reports assess public education spending as a share of discretionary government spending (excluding interest payments).41 The growing debt burden may reduce all sectors' shares of the budget. For example, Fuller (1989) reports that debt service accounts for 38 percent of government recurrent spending in Malawi.

- Recession: A dec!ine in education's share of GNP may result from a smaller public budget (as a share of GNP).

* Real expenditures: Figures on budget shares indicate priorities within the government budget, but do not reveal how real expenditures changed. If the budget grows, education's budget share could decrease even though real education expenditures increase, and vice versa. An important difficulty in estimating real education expenditures is the lack of a suitable deflator for nominal expenditures. The common practice of using the GDP deflator is highly questionable. For example, if food prices triple while all other prices remain constant, the GDP deflator will falsely suggest that real education expenditures declined. Determining an appropriate deflator is not trivial. Because the largest outlays in education are teachers' salaries, real wages should figure prominently in this deflator. If expenditures decline because teacher salaries are cut, education supply will not change unless teachers quit or teaching quality declines.

a Regional or local government financing; Public eddcation fliancing figures often ignore regional and local contributions. If figures for education financing refer to central government expenditures only, they may provide little information on sector financing. For example, tl.- bulk of education financing in Nigeria comes from local and state governments.

* Private financing: Figures for public education spending ignore the contribution from private sources that is quite significant in some countries (80 percent in Haiti). If private spending increased while public spending declined, total sector resources may have remained constant or even increased.

* Intrasectoral allocations: Figures for total education spending conceal changes in resource allocations by level of education (which subsectors were vulnerable or protected) and by function (recurrent versus capital, salaries versus materials).

6<sup>1</sup> Exceptions are Sahn (1989); Gallagher (1990); Kakwani, Makonnen, and van der Gaag (1990); and World Bank (1990a).

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A declining share to capital spending may have implications for present or future enrollment rates. However, the effects depend on the original spending levels: capital spending may decline because construction tapers off once universal enrollment is attained, or because donors and local communities increasingly bear capital costs. A growing share of the education budget allocated to personnel costs could signal a deteriorating quality of education as materials become scarce while teaching j( is or wages are protected. But it could also indicate that textbook provision is increasingly financed by external sources.

2.15 Real expenditures per student are a function of changes in both the relative or absolute sector resource allocation and enrollments. Per student expenditures could decline although real public expenditures increase, if the number of students increases even more. Changes in real per capita education expenditures are not a reliable indicator of the<sup>impact</sup> of adjustment. If school enrollments grow faster than the total population, the increases in per capita education expenditures observed in several adjusting countries do not preclude declines in per student expenditures.

2.16 The effects of changes in financing on coverage, quality, and equity are not obvious. According to the World Bank (1990d), the effects of a decline in sector spending depend on: 1) the adequacy of the original level of sector spending, 2) the absolute, rather than relative, decline in spending, 3) the ability of the sector to recover expenditure losses in years of increasing government spending, and 4) the relationship of spending to the number of beneficiaries in the system (supply versus demand). Although reductions in public allocations to education may lead to school closure or quality deterioration, Berstecher and Carr-Hill (1990) point out that some governments only reduced available spaces (and expenditures) in response to a decline in the number of students registering. Furthermore, a decrease in real education spending does not necessarily induce sector decline, if wastage declines while equity and efficiency improve.

2.17 Enrollment rates trace changes in sector coverage, but do not indicate whether supply or demand has changed. In Ghana, for example, real education spending increased, but the increase in enrollments did not keep up with population growth, and enrollment rates declined. Finally, changes in compliance with or enforcement of official age limits may change the gross enrollment rate independent of any change in supply<sup>or demand.</sup> While repetition and dropout rates may change in response to changes in quality, these rates are also affected by other factors. For example, in a number of countries repetition rates are largely a function of national regulations, and dropout rates are significantly affected by perceptions of the opportunity costs and benefits of education.

19
# m. **THE** EVIDENCE: MAJOR ISSUES

3.01 This section examines the treatment in the literature of major factors--capacity, coverage, quality, and equity--that relate to education supply and demand. Table III.1 summarizes the ways sources present education lata, the major issues the data cover, and whether sources link trends or outcomes to adjustment measures. On the whole, appropriate methodologies have not been developed to analyze the impacts of adjustment programs on education. Likewise, the data are too crude to permit any meaningful inference regarding causality. Even when correlation is evident, the literature does not delve deeper to determine what happened, why did it happen, was the outcome intended, and is the direction of change positive or negative. Existing methodologies (annexes 3 and 4) associate declines in public education expenditures and gross primary enrollment rates with adjustment programs, but do not examine quality and equity indicators. The impacts of changes in financing and coverage on quality and equity are by no means obvious. Available case studies provide quality and equity indicators from the "adjustment period," but do not analyze how adjustment programs (distinct from recession or external shocks) affect educationY Annex 1 contains nine case studies: each compiles available education sector data for a specific country and examines possible links to adjustment processes. Boxes throughout the chapter illustrate relevant issues and evidence from the case studies.

A.apaiy 3.02 During the 1960s and early 1970s, public education spending (by central and local governments) in virtually all countries rose considerably faster than either government revenue or GNP (Cornia, et.al., 1987). A UNESCO study describes adjustment as an acute phase of a longer crisis, and the expansion of the education system during the last decades as an "education explosion" (Duvieusart, 1990). Was this expansion sustainable? In many cases downward trends in public education financing began in .he late 1970s.

3.03 Sahn (1989) examines public education financing in real terms and as a share of the government budget from before and after the first World Bank adjustment loan (box 111.1). Gallagher (1990) compares average allocations of total and discretionary public budgets to education among fiscally duressed (adjusting) and other (nonadjusting) countries (annex 3). These simple analyses do not find any strong links between adjustment and public education financing. Gallagher concludes that reductions in social spending are associated with the general decline in total government spending that results from slower economic growth. However, two recent World Bank studies (Kakwani, et.al., 1990; and World Bank, 1990a) associate adjustment directly with declining public resources allocated to education: education's share of the public budget and GDP increased in all country groups except intensely adjusting countries after 1980 (annex 4).

/For example, Aedo-Richmond and Noguera (1989); Cornia, et.al. (1987); Fuller (1989); Hinchliffe (1989), Hoppers (1989); and Kydd (1988).

20
# Table M.1: Data presentation in the literature

|Source*|Data presentation|Crosscountr<br>a<br>g|Data linked to|Ed<br>£<br>idiu<br>t<br>iac|ucation is<br>stment<br>iCovera|sues cove<br> <br>e QuahIE|red:<br>Egtiq|
|---|---|---|---|---|---|---|---|
|Colclough and Lewin|a) Time series data<br>b) Case studies|<br>Yes<br>No|No<br>Yes|X<br>X|X<br>X|(X)<br>X|(X)<br>X|
|Comnia, Jolly, Stewart|Case studies|No|Yes|X|X|X|X|
|Gallagher|Adjustment method|ology Yes|Yes|X|X|(X)||
|Kakwani, Makonnen,<br>van der Gaag|Adjustment method|ology Yes|Yes|X|X|(X)||
|Lockheed, Verspoor, etal.|Time series data|Yes|No|X|X|X|(X)|
|Sahn|Adjustment method|ology Yes|Yes|X|X|(X)||
|World Bank (1988c)|Time series data|Yes|No|X|X|(X)|(X)|

(X) indicates that issues are addressed, but to a lesser degree.

'Note: The list is not exhaustive, and covers only the principal sources cited in the text.
# **BOX 111.1:** 'Before" and "after" World Bank-sUrted adjustment: No clear trends

Sahn (1989) compares average public education spending indicators during the three years preceding the first World Bank adjustment loan to those during a sirmilar period after the loan in sixteen African countries. Education's share of public discretionary spending increased in eight of sixteen countries between the two periods, and declined in the other eight. Real education spending did likewise. Sahn finds no conclusive evidence to suggest that countries reduce govermment expenditures, either in real terms or as a share of the government budget, as a consequence of receiving adjustment loans. In countries where government education spending declined during the 1980s, the trend generally predated the beginning of the adjustment process.

However, some of the data raise serious methodological questions, for example the tremendous changes in real education expenditures for Ghana, Nigeria, and Sierra Leone. Because the indices are calculated from expenditures measured in US$, the changes may result primarily from currency devaluation. Devaluation is likely to have little impact on education supply, particularly at the primary level. These figures by themselves explain little.

||Education<br>as % of di<br>governent<br>Before<br>adjustment|expenditure<br>scretionary<br>expenditure<br>After<br>adjustment|Educ<br>expen<br>(1980<br>Before<br>adjustment|ation<br>ditures<br>=100)<br>After<br>adjustment|
|---|---|---|---|---|
|Burkina Faso<br>'|19.4<br>|20.3<br>|115.2<br>|154.6<br>|
|C6te dlvoire<br>|19.4<br>|25.2<br>|116.0<br>|129.5<br>|
|Ghana<br>|16.1<br>|23.8<br>|56.2<br>|110.8<br>|
|Kenya<br>|20.0<br>|22.9<br>|91.1<br>|114.1<br>|
|Madagascar<br>|19.6<br>|18.3<br>|95.9<br>|89.4<br>|
|Malawi<br>|11.5<br>|15.0<br>|102.8<br>|110.3<br>|
|Mauritius<br>|19.3<br>|19.2<br>|104.4<br>|98.4<br>|
|Niger<br>|14.3<br>|12.7<br>|63.1<br>|58.2<br>|
|Nigeria<br>|8.6<br>|10.4<br>|140.0<br>|92.2<br>|
|Senegal<br>|24.6<br>|20.2<br>|100.0<br>|102.3<br>|
|Sierra Leone<br>|17.2<br>|11.1<br>|115.4<br>|57.8<br>|
|Tanzania<br>|13.9<br>|13.6<br>|99.9<br>|91.5<br>|
|Togo<br>|22.4<br>|15.3<br>|124.5<br>|99.5<br>|
|Uganda<br>|12.7<br>|15.0<br>|144.0<br>|151.1<br>|
|Zambia<br>|16.5<br>|13.8<br>|109.5<br>|93.0<br>|
|Zimbabwe|23.4|23.5|154.3|165.2|

22
Table III.2: Total long-term debt _(%_ of GNP)

||1980*<br>|1985<br>|1988<br>|
|---|---|---|---|
|Intensely adjusting countries (IAL)|35.1|82.4|82.9|
|<br>Other adjusting countries (OAL)|32.1|_51.5_|70.6|
|Nonadjusting countries (NAL)|27.1|57.6|53.1|

'1980 figures refer to public long-tern! debt only.

Source: World Development Reports (1982, 1987, 1990).

Table III.3: Education financing (%o of discretionaxy public expenditures)

||Countries|1975|1980|1986|
|---|---|---|---|---|
|EIAL|10|16.9|17.6|16.2|
|OAL|_5_||11.7|12.7|
|NAL|_5_|8.7|10.9|12.9|

Source: World Bank, 1990a.

3.04 Why did education's share of the budget decline in adiusting countries? One explanation is that debt service payments crowded out other public spending. Countries that adopted adjustment programs (IAL and OAL countries) already faced higher debt burdens in 1980 than did nonadjusting countries (table I.2). Since over 90 percent of long-term debt is public in all developing country groups,y nonconcessionl adjustment borrowing increased the debt burden and contributed to a resource transfer toward debt payments and away from other publicly financed sectors. The debt burden increased during the 1980s for all country groups, but the increase was more rapid for adjusting countries, particularly for intensely adjusting countries. At the same time, GDP growth (and government revenues) stagnated or declined in many countries. Table 111.3 suggests that governments "protected" education during the early 1980s--education's share of the discretionary public budget (i.e., excluding debt service payments) increased slightly. However, in intensely adjusting (EIAL) countries, the growing debt burden after 1980 outweighed attempts to shelter the education budget. Box 111.2 describes the case of Tanzania, an intensely adjusting country. Finally, currency devaluations may induce shifts in the allocation of public resources towards sectors that are more import- or foreign exchange-intensive (including debt service) than education.

3.05 A second explanation for education's declining public budget share is that a change in relative prices in turn alters relative resource allocations, independent of any concrete reallocative decisions. For example, because education is a relatively laborintensive sector, any across-the-board civil service wage cut will, ceteris paribus, reduce education's share of the public budget relative to less labor-intensive public sectors (Schwartz and Stevenson, 1990).

2/Calculated from World Debt Tables.

23
# OX M1.2: Tbe debt **serice squeeze** in Tanzania

Tanzania (an intensely adjusting country) reduce;d the public budget allocation to education and to other public sectors between 1984 and 1988, while increasing the debt service allocation continuously to over one third of the public budget. Wher.ever the budget expanded, debt service constituted most of the increase. In real terms, education expenditures decreased, other public expenditures increased slightly, but debt service more than doubled. Betveen 1986 and 1987, although education's share of the total public budget fell from 16 to 14 percent, its share of the discretionary public budget (excluding debt service) rose from 21 to 24 percent. The debt burden crowded out education expenditures and overwhelmed the government's efforts to favor education in the budget allocation process, and real education expenditures declined.

# Index of real public expenditures by sector (No of public budget)

||1984|1985|1986|1987|<br>1988|
|---|---|---|---|---|---|
|Debt Service<br>|100 (189o)<br>|114 (20%)<br>|126 (24%)<br>|176 (28%o<br>|)256(34%o)<br>|
|Education<br>|100 (16%)<br>|92_(14%)_<br>|96 (16%)<br>|95 (14%)<br>|98 (12%o)<br>|
|Other<br>|1UO (66%)<br>|102 (66%o|) 87 (60%)|99 (58%)|111_(54%o)_|
|Total|100|103|95|112|135|

Sourc: Berstecher and Carr-Hill (1990).

3.06 Figures that describe changes in education's share of the public budget or GNP alone do not indicate whether education was protected or vulnerable relative to other sectors in the allocation of public resources. Comparing intersectoral allocations over time reveals government priorities during periods of recession and adjustment. One method is to calculate the coefficient of vulnerability (Hicks and Kubish, 1984): the ratio of the percentage change in education spending to the percentage change in total public spending during the adjustment period, defined only for countries where government spending fell. The coefficient is greater than one if the sector was vulnerable, less than one if the sector was protected, and negative if the sector was highly protected. For example, the coefficient for Guinea during the adjustment period 1986-89 is 0.64. Although real education spending fell by 25 percent over the period, education was "protected" relative to the rest of the government budget, which fell by almost 40 percent in real terms. In Malawi, the coefficient of vulnerability is 5.5, indicating a high degree of vulnerability (all government spending fell 3.2 percent in real terms over the adjustment period 1982-88, but education spending fell by 17.4 percent).

3.07 Cornia, et.al. (1987) compare government expenditure cuts across regions from 1979-83 (table HI1.4). They define the education sector as: "vulnerable" if expenditure cuts in education exceed aggregate percentage cuts; "protected" if expenditures in education 24
are cut by a smaller percentage than the aggregate spending; and "highly protected" if real education expenditures increase while aggregate government expenditures decline.

# Table 111.4: Government expenditure cuts in education. 1979-1983 (, of cases b region)

|Region<br>No. of countries|All<br>(57)|Africa<br>(16)|Asia<br>(8)|EMENA<br>(13)|LAC<br>(20)|
|---|---|---|---|---|---|
|Vulnerable|45|38|25|38|65|
|Protected|22|24|50|27|_5_|
|Highly Protected|33|38|25|35|30|
|Total|100|100|100|100|100|

Source: Cornia, et.al. (1987).

3.08 Because the data predate all but the earliest adjustment loans, they reflect government priorities in making budget cuts during economic recession rather than during adjustment. Most countries (67 percent) reduced education spending during the recession period from 1979-1983. In 22 percent, the education reduction was less in percentage terms than the aggregate reduction. However, in 45 percent, education was vulnerable (Cornia, et.al., 1987). Did these patterns persist during the adjustment period? Why was education particularly vulnerable in LAC, but particularly protected in Asia?V Were there systematic differences in adjustment processes between regions?

B. Coverage 3.09 Several authors link Bank adjustment lending to declining coverage in the short term. Gallagher (1990) argues that "trends in primary school enrollments very much rerlect spending trends, rising in most instances between the mid 1970s to the beginning of the 1980s and slowing or declining since then." However, the evidence he presents is unclear: fiscal duress is negatively with gross primary enrollment rates in Africa and Asia, but not in EMENA or LAC (annex 3). Kakwani, et.al. (1990) find that gross primary enrollment rates increased in all country groups from 1970 to 1985 except among intensely adjusting (IAL) countries. Furthermore, the rate of growth of primary enrollments declined in TAL countries after 1980, although total enrollments continued to increase in all country groups.

i/Asian countries, compared to LAC countries, tend to have smaller debt service obligations, higher economic growth, and smaller shares of the public budget devoted to education.

I/Nonpublic sources of financing tend to constitute a significant proportion of education expenditures in EMENA and LAC (but less so in Africa and Asia), and can compensate for declining public expenditures.

25
# BOX 113:Eductionspenine and enrollMent at tiMe tlands: **Costa Rica and** Ghana

Do public financing of education and enrollment rates follow similar time trends? Data from Costa Rica and Ghana tell different stories. Education's share of the public budget and GDP in Costa Rica declined from 1981 to 1983, increased slowly after 1983, but in 1987 remained below the 1980 level (real expenditures also declined). Public education spending as a share of GDP is also below the 1983 level. Enrollment rates declined between 1980 and 1985, apparently in conjunction with declining public financing.

||1980|1981|1983|1985|1987|1988|
|---|---|---|---|---|---|---|
|% of public budget<br>|14.9|15.1|12.1|12.7|13.7|12.9|
|%of GDP<br>|6.7<br>|5.8<br>|_5.0_|_5.0_|_5.0_|4.8|
|Gross primary enrollment rate<br>|106%<br>|||101%|||
|Gross secondaty enrollment rate|47%|||41%|||

# Source: World Bank (1990d).

In Ghana, trends in financing levels and enrollment rates do not coincide. Ghana suffered a severe recession in the early 1980s, when central government spending on education declined markedly (both real expenditures and central government education spending as a proportion of the public budget and GDP). Enrollment rates at both the primary and secondary levels suffered during the 1980s despite rising central government spending after 1981. The increase in expenditures in 1986 resulted from a wage increase for teachers, which was not intended to expand coverage. The enrollment rate declined because population growth exceeded the rate of expansion of the school system.

||1975 1980|1981 1982|1984 1985|1987|1988|
|---|---|---|---|---|---|
|% of public budget<br>|20.6 22.0<br>|17.1 18.7<br>|20.2 18.0<br> <br>|23.9<br>|25.7|
|% of GDP<br>|4.5 2.4<br>|1.8 2.1<br>|2.0<br>2.4<br>|3.3<br>|3.5<br>|
|Real expenditures<br>(index)<br>|174.5 100.0|73.6 78.0|78.3 98.8|147.7|167.0|
|Enrollment rates:<br>Gross primary<br>|71% 80%<br>|77%<br>|76% 72%<br>|71%<br>||
|Gross secondary|37% 41%|38%|41% 39%|40%||
|S=cg:World Bank<br>....<br>**.**<br>.... .|(1990c).|||||

3.10 The coexistence of adjustment programs and declining enrollment rates does not imply causality, nor are the means through which adjustment policies translate into changes 26
in sector coverage apparent. Country studies (box 111.3 and annex 1) suggest that public education financing is not immediately and directly associated with enrollment rates in all cases. Gross enrollment rates declined in Korea despite increasing public education expenditures, and increased in Ghana and Zambia even though public spending declined. Enrollment rates may more accurately reflect changes in demand for education resulting from deteriorating economic conditions and declining household incomes. For example, families may withdraw their children from school in order to reduce education spending, and to have the children contribute to household income (Fuller, 1989). Declining enrollment rates may result from deteriorating labor market conditions during recession and adjustment, as a response to lower perceived private returns to education investment. In order to assess the impact of adjustment measures on education coverage, it is essential to examine the supply and demand factors that caused changes in enrollment rates.

# C. Quality

3.11 A complete analysis of changes in the quality of education requires information for a variety of indicators: per student expenditures (recurrent, and on materials), sector budget shares (recurrent versus capital spending, salaries versus materials), and internal efficiency (repeater and dropout rates, test scores). Coverage of these indicators in the literature is inconsistent, incomplete, and inconclusive regarding the impacts of adjustment programs on education quality. Available evidence must be interpreted with care, as the links between adjustment policies and quality indicators are difficult to ascertain.

# Tab!e 111.5: Real public education spending per capita (% annual change)

||Countries|1970-80|1981-84|1985-87|
|---|---|---|---|---|
|EIAL|<br>10|10.8|1.1|0.8|
|OAL|5||0.5|_5.5_|
|NAL|3|6.7|0.3|9.7|

# Source: World Bank (1990a).

3.12 Per capita and per student spending: Insofar as adjustment measures contributed to lower public education expenditures while enrollments increased, adjustment produced declines in real public expenditures per student. For example, average per capita education expenditures increased in all country groups except intensely adjusting countries after 1980 (annex 4). Table 111.5 indicates that although annual growth in real government education spending per capita was extremely slow for all country groups from 1981 to 1984, the growth rate accelerated during the 1985-87 period for all except intensely adjusting (EIAL) countries. However, lower per student expenditures may not reduce the quality of education if compensating measures increase efficiency in resource use. At the same time, increasing expenditures per student do not necessarily indicate a positive impact on the sector. In Ghana (box I11.4), the increase in per primary student expenditures from 1983 to 1988 would have been small or even negative if enrollment rates (box 111.3) had not fallen. Another influence on education quality which is receiving increasing attention in the literature, but little quantification, is nonsalary expenditures per student, i.e., expenditures on materials and supplies.

27
# **BOX m4:** Per student =nditures: Intrasectoral trends in Costa Rica and Ghana

In Costa Rica, public per student expenditures dropped drastically between 1980 and 1982. Although they rose gradually after 1982, in 1986 they remained below 1980 levels. Furthermore, the breakdown by level of education _shows_ that the tertiary level did not suffer as much as the primary level: per student spending declined less, and rose faster. Although primary and secondary spending were reduced by the same proportion through 1982, per student secondary spending increased more rapidly after 1982.

|Costa Rica|1980|1981|1982|1983|1984|1985|1986|
|---|---|---|---|---|---|---|---|
|Primary and Preschool|100|71|48|53|58|59|65|
|General Secondary|100|70|47|_55_|62|67|74|
|<br>Vocational Secondary<br>|100<br>|70<br>|46<br>|54<br>|60<br>|68|77<br>|
|Tertiary|100|86|61|65|76|77|90|

## Soure: World Bank (1989c).

Real public expenditures per student also declined at all levels in Ghana from 1970 to 1980, but declines were greater for secondary and tertiary education. Primary education was relatively protected. Severe declines date from well before the first World Bank adjustment loan in 1983. In fac, per student expenditures (particularly primary) have improved since 1983, partly as a result of enrollments growing less rapidly than the school-age population.

|Ghbana*|1970|1975|1980|1983|1985|1988|
|---|---|---|---|---|---|---|
|Primary|161|100|51|39|61|98|
|<br>Secondary|76|100|50|30|44|58|
|<br>Tertiary||100|33|17|52|61|

Source: World Bank (1988c). 'Because of the difficulties in combining figures from different sources, these figures are not exact and are intended only to indicate likely trends.

3.13 Capital versus recurrent spending: Whether or not capital and recurrent spending levels are adequate is determined in part by how well existing facilities serve the current population and meet future needs. Gallagher (1990) finds that the share of investment in total education spending declined between the mid-1970s and the mid-1980s in 19 of 25 developing countries. However, donors played an increasing role in financing capital investments in Africa, and capital spending in countries such as Botswana and Thailand declined after universal primary education was achieved (when budgetary needs were limited to construction and equipment necessary to keep pace with population growth).

28
# **BOX m115:** Teacher saladris

Many African countries faced severe economic recessions beginning in 1980. In most cases, real average teacher salaries declined after 1980. However, Malawi and Zambia protected teacher salaries relative to manufacturing worker salaries (Malawi only after 1983), thus encouraging teachers to stay in the sector. But in Kenya and Zimbabwe, teacher salaries declined relative to wages in the manufacturing sector. Such changes in relative wages could induce qualified teachers to seek employment in other sectors, with negative impacts on the quality of education. The literature does not analyze the impacts of changes in relative wages on teacher employment patterns.

## Index of real aveage teacher salaries

||1980|1981|1982|1983|1984|1985|
|---|---|---|---|---|---|---|
|Kenya|100|98|84|73|68|71|
|Malawi|100|96|99|96|94|96|
|Zambia|100|83|89|113|88||
|Zimbabwe|100|92|89|72|_55_|63|

Ratio of average salaries of primary teachers to manufacturing workers

||1980|1981|1982|1983|1984|- 1985|
|---|---|---|---|---|---|---|
|Kenya<br>|100<br>|99|92|82|77|<br>86|
|Malawi|100|95|73|100|119|145|
|Zambia|100|100|114|158|148||
|Zimbabwe|100|84|78|68|56|61|

SQu=: Zymelman and DeStefano (1989).

3.14 According to Lewin and Berstecher (1989), between 1975-1980 and 1980-1983 the recurrent share of education spending in developing countries increased more often than it decreased. Changes in recurrent spending (teacher salaries) can affect both teacher morale and supply (both the total number and individual qualifications), and in turn influence education quality. Although in many countries the share of the education budget devoted to personnel costs rose, real teacher salaries often declined (box 111.5). Comparing trends in teacher salaries to overall wage trends (declining in real terms in many countries) indicates whether the sector was vulnerable or protected during adjustment. In the long run, if teacher salaries fall belo-w "comparable" wages, the quality of teaching will deteriorate as the best teachers shift to other occupations. Relatively high teacher salaries encourage qualified teachers to stay in the sector. However, in order to pay higher wages the government may reduce spending on other education budget items that affect the quality of education as well: teaching materials, construction, or maintenance.

29
3.15 Other guality indicators: Several other indicators describe changes in education quality. Kakwani, et.al. (1990) use student/teacher ratios as a proxy for education quality, implying that a lower ratio in IAL countries (35 in 1980-85 versus 39 in 1970-75) reflects a positive quality effect from ib.e adjustment process. On the other hand, Lockheed, Verspoor, et.al. (1990) argue that class size reduction in the 25-45 range in fact has little impact on education quality. Declining student/teacher ratios in adjusting countries suggests only that teacher recruitment is much less responsive to macroeconomic shocks (recession or adjustment) than is the demand for education. Internal efficiency indicators such as test scores, repeater rates, dropout rates, completion rates, and years to produce a graduate also reveal quality changes. Two reports provide internal efficiency indicators for a large number of countries (Lockheed, Verspoor, et.al., 1990; World Bank, 1988c), but do not examine the impact of adjustment programs. On average, repeater and completion rates (in primary education) improved slightly for all developing countries.

# BOX 111.6: Education equityrural yersus urban

Morocco offers a unique comparison of primary education indicators between rural and urban areas. Trends during the 1980s were similar for the two sreas, except for the gross enrollment rate: the urban rate declined and the rt. . te increased. By building schools and bouses for teachers in rural areas, L rocro's first Education SECAL (1986) sought to narrow the gap between urban r rural areas, and to improve rural and female enrollment rates. The gap between the two areas remained significant in 1988 according to all three indicators. It may be too soon, after only two years of sector adjustment, for equity improvements to be measurable.

<!-- Start of picture text --> 1980 1988<br>Urban Rural Urban Rural<br>Student/teacher ratio 40 33 30 22<br>Gross enrollment rate (t) 124 49 96 52<br>Girls as % of enrollments 45 24 46 29<br>Sowrc: World Bank (1989a).<br><!-- End of picture text -->

## EquiE y

3.16 Adjustment programs that alter education financing also affect equity. For example, changes in the intrasectoral allocation of public resources by level affect education supply and demand, particularly with respect to the poor who benefit the most from basic education. The literature provides only country-specific evidence (annex 1). Costa Rica cut per student expenditures in primary education more than in secondary or tertiary education. Ghana protected per student primary spending, although enrollment growth did not keep pace with population growth (box 111.4). Several sources mention that the effects of decreasing public financing may be offset by increasing contributions from user fees and 30
private sources. On the other hand, Gallagher (1990) argues that when national economic growth slows, the private sector, communities, and individuals also have fewer resources, and that user fees may reduce the demand for education if people cannot afford to pay. Public subsidies to private education decline in declining budgets, further hampering nongovernment provision of education.

3.17 Breaking down enrollment rates by gender, region, or income level indicates the equity impacts of adjustment measures. The most widely-cited equity indicator is the female (versus male or total) primary enrollment rate. Adjustment appears not to have influenced equity: female enrollment rates continued to approach male enrollment rates during the adjustment period (annex 1). Although the literature emphasizes that adjustment disproportionately affected the poor, comparisons between rural and urban areas (box II1.6) or household income levels are scarce.

E. What evidence is missing?

3.18 Data for education during adjustment are scarce and inconclusive. Although public education financing and gross enrollment rates declined in intensely adjusting countries, the overall impacts of these trends on the sector, and particularly on quality and equity, cannot be determined because of data and methodology' aitations. Sources focus on macro (public financing levels) and micro (per student expenditures) effects of adjustment policies on the supply of education. At the macro level, the supply of education in most countries is determined by the level of public funding. But sector financing data often describe only central government spending, and neglect local government or private resources. The impacts of changes in education resources on quality and equity are not obvious. They depend on the level of inefficiency in the system (a major focus of sector reform efforts), and on intrasectoral allocations to recurrent versus capital budgets, by function, and by level of education. Sources rarely break down sector financing figures according to these categories.

3.19 General conclusions about macro (income distribution) or micro (household earnings, costs and expectations) effects on the demand for education are unsubstantiated statements. Sources seldom include indicators for factors (other than public education expenditures) that influence the demand for education, for example income distribution, real and opportunity costs of education, and potential returns from education. They also provide little information regarding indirect impacts of adjustment measures on children's learning ability through changes in health and nutrition. Much of the relevant information must be obtained through household surveys.

3.20 Although education quality and equity data are extensive in particular country studies (boxes 111.4-111.6), for most countries the evidence is scarce and not linked e;-plicitly to adjustment measures. Internal efficiency indicators (repeater rates, dropout rates, and test scores) provide information on changes in education quality, but are not used extensively in the adjustment literature. In addition, few sources examine equity indicators to address the impacts of adjustment measures by region, income level, and gender.

31
# IV. CONCLUSIONS

4.01 How did the education sector adjust during the 1980s, in response to econornic shocks and macroeconomic measures? Did education suffer? Did education suffer more than other sectors? The problem is mor, important than simply deternining adjustment's "guilt" or "innocence." In order to design and implement appropriate interventions, donors, borrowers, and policyymakers need to know how macroeconomic and sector adjustment, both as on-going processes and as deliberate responses to discrete circumstances, affect one another. It is particularly important to determine the likely effects of policy reforms on sector financing, and in turn the effect of changes in financing on output, quality, and equity. General trends of declining education spending and enrollment rates since the early 1980s or even before are apparent, particularly in Africa but also in LAC. The literature suggests that declining trends during the "adjustment" period (post-1980) imply causality, and hypothesize about how macroeconomic or sector adjustment policies translate into sector effects. However, concrete evidence that explains how the process of sector adjustment is linked to sector or macroeconomic reforms and that provides specific evidence supporting general statements is lacking.

# A. Dynamics of adjustment policies

4.02 Public budget retrenchment during periods of recession, fiscal austerity, and managed adjustment is the principal form of sector adjustment described in the literature. Real education spending and education's share of the public budget declined in several countries, particularly where the debt burden grew. But education spending was seldom cut more than other public sector budgets (excluding defense). The most disturbing evidence is that public education spending and primary enrollment rates declined on average in intensely adjusting countries after 1980, while rising in all other country groups (Kakwani, et.al., 1990). But even these trends are not a priori bad and need to be investigated in more depth: to what extent were declining resources allocated more efficiently, and did internal efficiency improve to offset declining gross enrollment rates? It is important to note that declines in financing in most cases date from well before the beginning of World Bank-assisted adjustment. In a few cases adjustment coincides with rising public education resources.

4.03 One commonly-r%commended setof adjustment measures seeks to promote more effective resource allocation and utilization in the education sector, for example by reallocating resources from higher to primary education. Even if total resources decline, budget rationalization (determining core investment priorities, defining a standard budget process, eliminating ghost teachers) can mitigate the impact of a decline in overall resources by increasing the efficiency of resourc use in order to improve sector performance and output.

4.01 Another set of measures aims at cost recovery, particularly in secondary and tertiary education. By introducing or increasing user fees, reducing student subsidies, and increasing community participation in school construction and maintenance, total education spending can increase or remain constant even though public spending declines, with no 32
negative impacts on the quality of education. However, cost recovery schemes have administrative and equity implications: user fees may reduce attendance by the poor unless effective targeted scholarship programs compensate poorer students. Incomplete or inequitable fee collection only exacerbates existing underfinancing and inequity. Berstecher (1988) suggests that declining financial capacity of families to demand and pay for services during austerity and recession limits the efficiency of cost recovery ineasures. Little is known about the impact of cost recovery measures on education supply and demand.

4.05 Finally, privatization can mobilize nongovernment resources for education to compensate for declining public resources. Chile pursued this course with some success: private enrollments rose although only in subsidized private schools. Similar to cost recovery measures, privatization may reduce enrollments among poorer students who cannot afford to pay for education services, unless private schools supplement (rather than replace) public schools.

# B. Data collection effQrts

4.06 The difficulties of separating the costs of adjustment from the costs of external shocks, poor policies, or not adjusting, imply a continuing need for careful monitoring and analysis. To analyze the process through which adjustment affects the education sector, time series data are necessary for a number of years before, during, and after (if possible) adjustment. Data collection and monitoring efforts must focus systematically on a few key indicators that measure aspects of education supply and demand. Expenditure data should measure more than the absolute and relative allocation of public resources to the sector, for example private, community, and local or regional government financing. Sector resources should be categorized by function (capital versus recurrent), by purpose (salaries, supplies, maintenance), and by level of education. Data on income distribution, the potential returns to education, and the opportunity and private costs of education are necessary to understand education demand." 4.07 Existing case studies use several of these indicators, but never in a complete or systematic fashion. Collecting the above information is a massive undertaking, and may only be feasible in a few selected country studies. In the absence of comparative dynamics models, crosstabulations of indicators for a given country show how indicators are interrelated, and thus help explain how the sector has adjusted. Given country-specific initial conditions, shocks, and adjustment packages, country studies are the most effective framework for analyzing the adjustment pro.css.

4.08 Several research programs have begun data collecdion efforts that focus on indicators relevant to the dynamics of the adjustment process in particular countries. The Living Standard Measurement Surveys (LSMS) collect data on household income and L<sup>1</sup> Additional information is useful in evaluating changes in quality and equity, for example: changes in health and nutrition that affect children's learning ability; intake, repeater, and dropout rates, as well as student performance on standard exams; enrollment rates broken down by region, gender, and income level.

33
behavior. Surveys assess trends in economic and social status in order to identify links between adjustment policies and changes in socioeconomi **c** onditions of particular groups (Serageldin, 1989). Changes in socioeconomic conditions in turn affect the macro and micro demand for education. Household and village surveys also collect information on educational attainment, schooling expenses, and school character and location. The Social Dimensions of Adjustment (SDA) Program is undertaking similar household and community surveys in a number of African countries. The SDA program was launched in 1987 as a joint venture between the UNDP Regional Programme for Africa, the African Development Bank, and the World Bank.

# C Ouestions for further research

4.09 In conclusion, reliable evidence on the effect of adjustment policies on the education sector is limited. There appears to be a causal link between adjustment and education, but the nature of the link varies widely and is poorly understood. For example, evidence of reductions in public expenditures during adjustment is pervasive, but there is considerable uncertainty regarding the effects of declining public financing on education. Explanatory models are poorly specified, and they rely on a weak database. As a result, it is difficult to determine causality, i.e., to isolate the specific effects of adjustment policies. Furthermore, the implications of changes in financing for education quality and equity are unclear.

4.10 Further research and arialysis that focuses on process monitoring is critical. For example, the database can be improved by monitoring key education indicators during the adjustment process. Research should seek to complement existing comparative statics assessments with analyses of the dynamics of sector adjustment. Particular questions for further research that have important implications for the design and implementation of adjustment programs are given below. But even in the absence of precise answers, evidence suggests probable links between adjustment measures and the education sector. Progress is evident in the design of World Bank adjustment lending, but muc'- more needs to be done to address education sector issujes.

* How do macroeconomic policies, particularly changes in public expenditure levels, affect the supply of education? How do changes in supply in turn affect coverage, quality, and equity in the education sector?

* How is contraction in the education sector managed-what are the dynamics of budget cuts among different subsectors of education? What political forces promote or impede adjustments? If resource transfers from higher to primary education are widely recommended, why are they not implemented? How, if at all, can adjustment lending affect institutional bottlenecks?

* Is education protected or vulnerable relative to other sectors during periods of fiscal retrenchment, increasing debt, or civil service reform? Does education vulnerability vary by region or income level? If differences exist, can they be explained by differences in the adjustment process between country groups?

34
What types of policies or conditions enable a country to protect education (i.e., deliver a reasonable level Qf scrvi,ce), and specifically basic education?

To what extent have local government, community, private, or household resources replaced declining government resources? How do decentralization and cost recovery in turn affect coverage, quality, and equity?

How and why has demand for education changed during adjustment? How do changes in incomes (the household's or individual's ability to invest in human capital), the opportunity cost of attending school, private returns to investing in education, or health and nutrition affect coverage, quality, and equity?

_35_
# ANNEX 1: CASE **STUDIES**

5.01 The nine case studies include the countries from each World Bank region (Africa, Asia, EMENA, LAC) for which data coverage is most complete: Chile, Costa Rica, Ghana, Korea, Malawi, Morocco, Philippines, Turkey, and Zambia. Each case study compiles available education sector data for a specific country and examines possible links to adjustment programs. A table summarizes available evidence on education indicators for each country from all sources. Because sources often disagree over exact figures, but rarely over general trends, the tables are intended to indicate only likely trends.

# CHILE

5.02 Chile introduced major education reforms during the early 1980s, concurrent with other reforms to increase privatization and reduce the role of state, but did not receive any Bank adjustment loans until 1986. Severe economic dislocations began in the early 1970s, accompanied by socio-political conflicts. Chile's response to the 1975 world recession and terms of trade problems was to increase foreign borrowing. Chile received World Bank SALs in 1986, 1987, and 1988. SAL conditionality focused on reducing tariffs and ending wage indexation (that is, controlling the growth of civil service salaries). Unfortunately, little data is available for the period after World Bank-assisted adjustment began.

5.03 Chile is often cited as an example of a country that protected the poor without utudermining the adjustment process, particularly with respect to child nutrition (Nicholas, 1988). This protection did not extend to the education sector. After 1974, Chile reduced the share of government resources devoted to education, although public spending was simultaneously redirected from universities to the pre-school, primary and intermediate levels. The increase in per student expenditures after 1980 was aided by declining primary enrollment rates.

5.04 Increasing resources to primary education may be responsible for improving repeater rates at this level. However, primary enrollment rates worsened as a result of deterioration in economic and nutritional status at the household level. Families could not afford materials, and the school feeding program was reduced in 1975-76. Education coupons replaced state-sponsored education. But in times of recession, poorer households cashed in their coupons rather than spend them on schooling (United Nations, 1988), suggesting that the opportunity cost of education rose. Therefore, despite continuing public subsidies, the emphasis on private schools may have been detrimental to school attendance by poorer students.

_5.05_ Beginning in 1980 schools were transferred to municipalities. They continued to receive government subsidies, although subsidies were difficult to maintain during the austerity period from 1982 to 1986. Quality declined in municipality-operated private schools because teacher salaries were lower and resources were limited, especially in lowincome communities. Test scores declined during the 1980s in all subjects. The allocation of state subsidies encouraged private schools to be more concerned with pupil numbers than 36
with standards. Social class background increasingly determined education and career opportunities through the segmented educational system (Aedo-Richmond and Noguera, 1989).

# Chile: education indiaors

||1975|1980|1981|1982|1983|1984|1985|1986|1987 1988|
|---|---|---|---|---|---|---|---|---|---|
|Finance:||||||||||
|%of public budget<br>||8.2<br>|9.1<br>|9.6<br>|8.4<br>|7.5<br>|5.4<br>|7.5<br>||
|%of GDP<br>||3.1<br>|3.4<br>|4.2<br>|3.6<br>|3.4|_2.5_|3.3|3.1|
|real expenditures (index)|95|108|120|127|111|||||
|Intrasectoral finance:||||||||||
|recurrent budget share(%)<br>|94<br>|95|||||99|||
|primary share of budget (%)|35|46|48|51|53|||51||
|<br>higher share of budget (%)||34||||||3||
|Oulput (enrollment rates--%):<br>||||||||||
|gross primary<br>|106|105|102|100|99|96|95|||
|net primary||90|||||89|||
|gross secondary||53|||||69|||
|Ouality:||||||||||
|per student spending (index)<br>|48|100|||||115|||
|test scores: math (index)||||||100|||94|
|test scores: Spanish (index)||||||100|||90|
|<br>primary repeaters(%)|||17|||15||||
|<br>primary dropouts(%)|6|_5_|9|3|_5_|_5_||||
|FSuity:||||||||||
|% primary students female|49|49|||||49|||

5.06 Chile undertook major education sector reforms without sector adjustment loan assistance from the World Bank. Data indicate that enrollment rates declined while the quality of education itself deteriorated. The data cover only the period preceding World Bank SALs, and therefore any trends are the result of economic conditions and government policies rather than effects of controlled adjustment. The effects of adjustment lending on the education sector cannot yet be assessed.

## **COSTA RICA**

5.07 Costa Rica adopted a Bank-assisted adjustment program (beginning in 1983) that did not explicitly target education but ntrertheless included conditionality with direct implications for sector employment and wages. The country underwent a public sector37
led expansion in the 1970s, but deficits were only sustainable as long as foreign financing was forthcomning. In the early 1980s international conditions deteriorated, foreign financing dried up, and Costa Rica suffered its worst recession in 30 years. In 1982 GDP fell by over 7 percent, and the annual rate of inflation was 90 percert. Costa Rica received an exports development SECAL in 1983, followed by SALs in 1985 and 1989. SAL conditionality included a freeze on public sector employment, controls on the growth of civil service salaries, and strict budget control allocation by the Ministry of Finance.

# Costa Rica: educaton indicators

<!-- Start of picture text --> 1975 1980 1981 1982 1983 1984 1985 1986 1987 1988<br>Finance:<br>% of public budget 14.9 15.1 13.5 12.1 12.2 12.7 12.8 13.7 12.9<br>% of GDP 6.7 5.8 4.8 5.0 5.0 5.0 5.1 5.0 4.8<br>real expenditures (index) 69 100 59<br>Intrasectoral finance:<br>capital budget share (%) 28 13 10 9 8<br>primary share of budget (%) 37 33 37<br>higher share of budget (%) 34 40<br>Qutput (enrollment rates--%):<br>gross primary 106 106 101 104 100<br>net primary 89 84<br>gross secondary 47 41<br>gross tertiary 21 23 25<br>Ouality:<br>per student spending (index)<br>primary 100 71 48 53 58 59 65<br>secondary 100 70 47 55 62 67 74<br>higher 100 86 61 65 76 77 90<br>primary repeaters (%) 7 8 11<br>primary promotions (%) 89 90 84 86 86<br>secondary promotions (%) 67 66 54 57 54<br>Equit:<br>% primary students female 49 48 48<br><!-- End of picture text --> 5.08 The greatest declines in public education spending occurred during the recession and austerity period of the early 1980s. Costa Rica protected primary education's share of the budget during the recession and austerity period of the 1980s, but did not reallocate resources from higher education. Government efforts were not sufficient as real education spending levels (total and per student) declined tremendously. The primary enrollment rate 38
did not change much, but deteriorating education quality and equity may have serious implications for Costa Rica's education system over the long term. The literature does not assess the effects of adjustment on the education sector, despite relatively good data that are as recent as 1988 and that include quality and equity indicators. The 1985 SAL did not explicitly target education and apparently did not influence deteriorating trends.

5.09 Education spending as a percentage of total government spending and GDP declined from 1980 to 1986. Real public education expenditures were lower in 1985 than in 1975. However, the coefficient of vulnerability for education (the ratio of the change in public education spending to the change in total public spending) between 1980 and 1985 of 0.75 suggests that education was protected relative to total government spending during a period of declining public expenditures (World Bank, 1990d).

5.10 Because real education spending fell while enrollments rose (by less than one percent annually from 1980 to 1985), real per student education expenditures declined by one-third from 1980 to 1986. The greatest declines were from 1979-1982, but expenditures in 1986 had not yet recovered their 1980 levels. Within the recurrent budget, teaching materials received less than 0.5 percent of the budget. Repeater and promotion rates worsened after 1980, and the difference between the number of years to produce a primary graduate and the number of years in the system increased from 1.2 in 1980 to 1.8 in 1985. Deterioration continued throughout the decade, although not as rapidly after 1985. Primary education's share of the public education budget increased after 1980 but remained far below the 1970 level of 51 percent.

# GHANA

5.11 Economic mismanagement and adverse external developments (deteriorating terms of trade) during the early 1980s together were responsible for declines in production in all sectors of the economy, especially exports and food. In 1982 and 1983, prolonged drought, the sudden influx of one million Ghanaians from Nigeria, and the falling price of cocoa aggravated a critical shortage of foreign exchange, high inflation, and an increasingly overvalued exchange rate. Real GNP and GNP per capita were lower in 1984 than in 1974, reaching their lowest point in 1982.

5.12 In addition to a macroeconomic adjustment program, Ghana simul aneously undertook education sector adjustment with Bank assistance. The government introduced an adjustment program in 1983 with World Bank and IMF support. IMF stand-by agreements coincided with the first World Bank adjustment operations (import and export development SECALs in 1983, 1984, and 1985). SECAL conditionality included a 60 percent increase in civil service salaries. Other World Bank adjustment loans followed annually through 1990 (SALs in 1987, 1989, 1990). SAL conditionality emphasized civil service reform (retrenchment and wage controls--arresting the SECAL policy of wage increases) and budget rationalization, including a review of non-wage recurrent expenditures and the development of budget guidelines for recurrent expenditure allocations in education. Reforms also emphasized the rehabilitation of physical and social infrastructures. Ghana is the archetypal education sector adjustment case, with two 39
education SECALs (1987 and 1990) totalling $84.5 million. The first education SECAL supported major restructuring of the education system, a reorientation of expenditures to primary education, teacher training, retrenchment of nonteaching staff, a freeze on teaching posts, and reduced subsidies. The second reinforces these reforms and extends them to the secondary level.

# Ghana: educatQn indicatrs

||197|5 1980|1981|1982|1983|1984|198|5 198|6 1987 1988|
|---|---|---|---|---|---|---|---|---|---|
|Einance:<br>||||||||||
|% of public budget<br>|18.7<br>|17.2<br>|13.4<br>|20.2<br>|18.7<br>|19.1<br>|18.0<br>|23.9<br>|23.9 25.7<br>|
|% of GDP<br>|6.0<br>|3.1<br>|1.8<br>|2.1|1.0|1.0|2.6|3.3|3.3 3.5|
|real expenditures (index)|175|100|74|78||78|99|143|148 167|
|Intrasectoral finance:<br>||||||||||
|recurrent budget share_(%)_<br>|78<br>|56|||||97|||
|salary budget share (%)<br>|57<br>|||||54||74||
|primary share of budget (%)|25|29|||||27|||
|QuiMt(enrollment rates--%):<br>||||||||||
|gross primary<br>|71<br>|80<br>|77|77|78|76|76|72|71|
|net primary<br>|59|64|||||59|||
|gross secondary|37|41||38|38|41|40|39|40|
|Quality:<br>||||||||||
|per student spending (index)<br>grade 4 completion_(%)_|259<br>82|100<br>85|86|83|76|75|84|98||
|% primary students female|43|44|||||43|||

5.13 Gross primary enrollment rates declined from 1983 to 1987 because total enrollments grew at only one-third the rate of growth of the school-age population (Colclough and Lewin, 1990). The literature does not explain why total enrollment growth faltered. Perhaps enrollment rate declines are a lagged response to declining public education spending. Because declining student/teacher ratios result in part from enrollment rate declines, the former do not necessarily represent quality improvements.

5.14 Public spending per student during the 1980s remained less than half the 1975 level. From 1980 to 1985, recurrent spending per primary teacher decreased approximately 15 percent. 4,000 trained teachers left the sector between 1977 and 1981 because of inadequate salaries (Cornia, et.al., 1987). The share of the education budget allocated to teacher salaries declined from 1975 to 1984, before increasing abruptly in 1986 following a salary raise.

40
5.15 Education financing began to deteriorate in the 1970s, and trends continued under adjustment. In addition, output, quality, and equity indicators declined after 1980. The literature cites "macro policy changes" as one of several factors responsible for deterioration in the sector during the early 1980s. Sahn's 'before" and "after" comparison implies that adjustment raised education expenditures significantly: education's share of discretionary spending increased from 16.1 percent 'before" adjustment (1981-83) to 23.8 percent "after" adjustment (1986-87), and real education spending doubled. However, real public education spending more than halved between 1975 and 1984, ana had not returned to 1975 levels by 1988. Colclough and Lewin k1990) describe effects of the 1987 Education SECAL including increases in enrollments and materials expenditures, decreases in subsidies, and the elimination of unnecessary non-teaching staff positions.

5.16 Adjustment policies may have contributed to improvements after 1985 in teacher salaries, education's share of the government budget (discretionary and total), and real education spending. However, real spending levels remain below 1975 pre-crisis levels. Furthermore, the literature does not examine how adjustment policies translated into sector quality, efficiency, or equity improvements, nor why certain indicators (particularly enrollment rates) continued to decline. The most recent data (1988) do not include figures for education quality, internal efficiency, or equity.

# MALAWI

5.17 Malawi was an early adjustment borrower, and the adjustment program addressed education sector concerns through SAL conditionality. Serious economic difficulties began in the 1980s following several external shocks: deteriorating terms of trade from 1977-1980, disruption of transportation routes by the war in Mozambique, and drought in 1980/81. Debt service increased by 7.3 percent annually after 1980, while GDP and GDP per capita declined in 1980 and 1981 and increased only slowly after 1981. Malawi received its first SAL in 1981. Additional Bank loans followed almost annually from 1983 to 1990. Adjustment in Malawi was therefore protracted over an entire decade, contrary to the intentions of early adjustment lending, but representative of programs in many other countries. SALs focused on budget rationalization and restructuring, and included conditionality to increase development expenditures on education (SAL 1), and to ensure adequate budget outlays for education and improve efficiency in the fee collection system (SAL 2).

5.18 In accordance with SAL I conditionality, education's share of the public budget increased in 1981 and 1982. The subsequent decline may indicate that the increase was not sustainable (economically and/or politically). Following the first SAL, the declining trend in primary education's share of the sector budget was reversed, but higher education's share continued to grow at a faster pace. Meanwhile the growth of enrollments declined and enrollment rates stagnated during the 1980s, perhaps because rural families drew on children's labor to backstop the erosion of subsistence and surplus production. Initial evidence indicates that a decline in family production or cash income often places significant pressure on even young children, which may in turn lower school attendance and actual achievement (Roe and Johnson, 1989).

41
5.19 Sahn (1989) associates initial s,. or financing improvements with adjustment: education's share of the total government *,udget increased (from 11.5 percent to 15.0 percent) as did real education spending (from and index of 103 to 110) between the period before structural adjustment (up through 1980) and the period after (1981-84). However, they fell to 10.6 percent and 105 respectively in 1986-87. The rapid growth of enrollments between 1965 and 1980 slowed after 1980. Absolute primary enrollments actually dropped by 35,000 children (4 percent) between 1981 and 1983, corresponding closely to a period of drought and falling agricultural output.

Malawi: education indicator5

||1975|1980|1981|1982|1983|1984|1985|1986|1987 1988|
|---|---|---|---|---|---|---|---|---|---|
|Finance:||||||||||
|% of public budget<br>|9.4<br>|9.0<br>|11.1<br>|14.3<br>|13.4<br>|12.3<br>|11.0<br>|10.8<br>|10.0 10.4<br>|
|% of GDP<br>|2.5|3.1|3.9|4.1|3.9|3.4|3.5|3.6|3.1|
|real expenditures (index)|63|100||107|||101||_105_|
|Intrasectoral finance:<br>||||||||||
|recurrent budget share(%)<br>|92<br>|76|||||72|||
|primary share of budget (%)|45|39|||||41|||
|<br>higher share of budget (%)|||||24|||34||
|**QjjRut**(enrollment rates--%):||||||||||
|gross primary<br>|_56_<br>|60<br>|65|62|60|60|62|_65_|66|
|net primary|36|40||||43|44|48|49|
|gross secondary||3|4|4|4|4|4|4|4|
|Ouality:||||||||||
|per student spending (index)|111|100|||||104|||
|teacher salaries (index)||100|96|99|96|94|96|||
|primary repeaters (%)|17|17|15|14|16|16|18|21||
|<br>grade 4 completion (%)|67|59|60|53|52|47|53|68|64|
|primary male enrollment(t)<br>||72||73|69|69|70|73|73|
|primary female enrollment (%|)|48||52|50|51|53|57|59|

5.20 Sources disagree on public per student expenditure trends after 1980. Fuller (1989) describes declines at all levels between 1980 and 1987 (in 1980 US$): by over onehalf in primary education, and by three-fourths in secondary and tertiary education. At the same time, Lockheed, Verspoor, et.al. (1990) describe a slight increase from 1980 to 1985 at the primary level (1985 US$). Public recurrent expenditure per primary teacher also declined ten percent from 1980 to 1988 (Lewin and Berstecher, 1989). The ratio of teacher salaries to manufacturing worker salaries declined through 1982 (from 0.91 in 1980 to 0.67), 42
but rose to 1.32 in 1985 (Zymelman and DeStefano, 1989). Improvements in the ratio of teacher salaries to manufacturing worker salaries suggest that education was protected relative to other public sectors during the adjustment period.

5.21 Changes in internal efficiency are ambiguous. The repeater rate in primary schools worsened, and the average length of study to produce a primary graduate increased from 5.7 years in 1980 to 6 in 1985 (Lewin and Berstecher, 1989). The difference between the number of years to produce a graduate and the number of years in the imary school system declined from 8 in 1980 to 7.2 in 1985, but the proportion of students progressing from the final grade of primary to the first grade of secondary general education declined from 15 percent in 1970 to 7 percent in 1983. Although university tuition increased incrementally, tertiary education's share of public education spending increased to over onethird in 1986 (Samoff, 1990b).

# MOROCCO

5.22 Morocco addressed the need for adjustment through Bank-assisted sector adjustment programs, including the education sector. Unlike Ghana, Morocco's education SECAL did not follow a SAL. Following the second oil shock, Morocco's terms of trade deteriorated, while budget allocations to national defense increased. GDP growth slowed to under 4 percent per year between 1977-80, and debt service increased from 11 percent of exports in 1977 to 33 percent in 1981. Controlled adjustment began with IMF assistance in 1980. The Bank's involvement focused on SECAILs (each year from 1984 to 1988, and 1990), and the first SAL was not until 1989. The World Bank's first-ever Education SECAL (1986) focused on expanding primary and lower secondary education by reorienting expenditures to these levels, while limiting the growth of upper secondary and university enrollments. In addition, the loan provided materials, supported quality improvements, reduced fellowships, and limited recruitment and salaries.

5.23 Between 1980 and 1988, the public budget as a proportion of GNP (net of the growing deficit) declined slightly while education's share of the budget increased slightly. The growth of total enrollments at the primary level slowed dramatically from seven percent between 1975-80 to only one percent from 1980-85. Recurrent expenditures per teacher declined three percent per year between 1980 and 1985 (Colclough and Lewin, 1990). The limited evidence on efficiency indicators shows improvement in primary education: the primary school final exam pass rate improved from 34 percent in 1980 to 61 percent in 1988, while repeater and dropout rates declined. However, improvement dates from before the 1986 Education SECAL.

5.24 Primary education's budget share did not change during the 1980s while tertiary education's share increased. The data do encompass the first years of the Education SECAL, and suggest that SECAL conditionality was not initially effective in reorienting budget allocations to primary education. A strong gender bias persists in enrollments at both primary and tertiary levels, and progress in increasing the proportion of females continues to be slow in the 1980s, especially at the primary level. Females comprised less than 40 percent of primary and tertiary enrollments in 1988. Box IV.10 provides a 43
comparison, unique in the literature, of primary education indicators for urban versus rural areas. Trends are similar in both areas, but the gap between urban and rural is significant and did not diminish during the 1980s, except for the gross enrollment rate.

# Morocco educiatin indicato-rs

||1975|1980|1981|1982|1983|1984|1985 1986|1987 1988|
|---|---|---|---|---|---|---|---|---|
|% of public budget<br> <br>|12.0<br>|18.3<br>|||||18.4|19.2|
|% of GDP<br>|_5.1_|6.4|||||||
|real expenditures (index)|61|100|||||||
|Intrasecto l finance:<br>|||||||||
|recurrent budget share(%)<br>|86<br>|81|||||||
|primary share of budget (%)<br>|37<br>|34|||||34|34|
|higher share of budget(%)|14|17|||||18|20|
|Qutput:|||||||||
|gross primary enrollment (%)<br>|62<br>|77<br>|79|85|86|80|81||
|net primary enrollment(t)|48|64|||||64||
|**Quality:**<br>|||||||||
|per student spending (index)<br>primary repeaters(%)<br>|80<br>28|100<br>30|||||20||
|primary dropouts(%)|||||||11|10|
|% primary students female<br>|36<br>|37<br>|||||38|38|
|% tertiary students female|20|25|||||34|34|

## PHILIPPINES

5.25 Adjustment in the Philippines was supported by several Bank loans, but none of these loans explicitly targeted education. The government nevertheless protected the education sector. Longstanding structural problems worsened following external shocks (the world recession of the early 1980s, and deteriorating terms of trade between 1979-83) and inadequate adjustment policies. As a result, the Philippines faced a severe foreign exchange crisis in 1984 and 1985. Per capita GNP in 1985 was below its 1975 level. Controlled adjustment with World Bank assistance began in 1981 with the first SAL Additional adjustment loans included SALs in 1983 and 1987, as well as SECALs in 1985, 1988, 1989, and 1990. Bank conditionality emphasized privatization, trade liberalization, and the need to sustain operating and maintenance expenditure levels. Data coverage for the Philippines is excellent.

44
5.26 Despite public resource constraints during the recession of the early 1980s, education's share of the public budget remained constant (except in 1984), and its share of GDP increased after 1984. Although education's share of the budget and GNP increased, real education expenditures in 1985 were three-fourths their 1980 levels. Declining real education spending after 1980 may have contributed to a lower primary enrollment rate. The growth of enrollments slowed at all levels after 1980, although total enrollments continued to increase.

# _MPsipies:_ eductn indcato

||197|5 198|0 198|1 198|2 198|3 198|4 1985|1986 1987 1988|
|---|---|---|---|---|---|---|---|---|
|Einance:|||||||||
|% of public budget|13.8|11.1|10.9|11.5|10.7|8.4|11.5|11.6|
|% of GNP||1.7|1.8|1.9|1.7|1.5|1.8|2.2 2.5 2.8|
|real expenditures (index)|87|100|||||75||
|Intrasectoral finance:|||||||||
|recurrent budget share(%)|82|96|||||93||
|<br>salary budget share (%)|87||||||62|59|
|<br>materials budget share(%)|0.3||||||0.9|0.6|
|<br>primary share of budget (%)|82|61|||||64||
|Qutput (enrollment rates--%):|||||||||
|gross primary|107|113|111|109|109|107|94|9)|
|<br>netprimary|94|94|93|92|88|88|90|89|
|<br>gross secondary|54|65|64|66|67|68|65|65|
|<br>gross tertiary|18|26|27|29|32|34|38||
|Ouality:|||||||||
|per student expenditures (ind<br>|ex)<br>||||||||
|primary|95|100|||||63|83|
|<br>secondary|44|100|||||41|66|
|<br>tertiary|<br>28|<br>100|||||45||
|<br>achievement test scores (inde|x)||||||||
|primary|85|||||||100|
|<br>secondary||||100||104|108||
|<br>primary repeaters(t)||2.4||2.1|2.3|2.3|1.8||
|<br>primary dropouts(t)||||2.9|2.8|2.7|2.0||
|<br>primary completion(%)||||67|67|65|63||
|liquity:<br>|||||||||

- % primary students female 51 49 49

5.27 Budget allocations to capital investment and materials expenditures increased slightly during the adjustment period. The recurrent share of the public education budget declined after 1980, but remained above its 1975 level. Perhaps as a result of increased 45
materials spending, the student/textbook ratio in primary schools improved dramatically from 10/1 in 1979 to 2/1 in 1987. Student scores on primary and secondary school achievement tests also improved. Real recurrent spending per primary teacher declined 45 percent between 1980 and 1985 (Lewin and Berstecher, 1989). Although teacher salaries declined from 1982 to 1985, rural teacher salaries were protected relative to average rural wages (Cornia, et.al., 1987). In addition, the ratio of annual teacher salaries to GNP per capita increased from 1.5 in 1983 to 2.2 in 1988 in public primary schools, and from 1.7 to 2.4 in public secondary schools.

5.28 Internal efficiency indicators are ambiguous: repeater and dropout rates improved while completion rates deteriorated during the 1980s. Equity in the education sector did not deteriorate under adjustment. Primary education's share of the total recurrent budget increased from 1980 to 1985, although its share again remained far below the 1975 level. Female gross primnary enrollment rates exceeded 100 percent throughout the adjustment period.

5.29 As a result of rising enrollments and declining real expenditures on education, per student expenditures declined at all levels between 1980 and 1983: by one-third for primary students, and by over one-half for secondary and tertiary students. Primary education was protected relative to other levels during the first adjustment years. However, the decline in real education spending (total and per student) may have negative longterm impacts on quality and equity, although the evidence is ambiguous.

# SOUTH **KOREA**

5.30 Like the Philippines, South Korea undertook macroeconomic adjustment with Bank assistance, and protected education even though lending did not explicitly target the sector. South Korea faced deteriorating economic conditions during the 1980 world-wide recession. Export growth stagnated with inflationary pressures from the second oil crisis and political instability. Unfavorable weather in 1980 caused a 22 percent decline in agricultural output. Real GNP declined 5.2 percent, the first decline in 20 years. Per capita real income also declined 10 percent from 1979-81. The government launched a comprehensive economic reform package focusing on stabilization, liberalization, and adjustment beginning in 1979. South Korea received World Bank SALs in 1982 and 1984, and an industry finance SECAL in 1985. SAL conditionality focused on rationalizing imports and exports, and real wage grovwh.

5.31 The South Korean structural adjustment program was an early one and therefore lacked any explicit consideration of the short-term effects of adjustment on vulnerable groups. The government's program nevertheless included measures to insulate the poor from adjustment, for example by increasing spending on education. "Korea's adjustment and its accompanying social programs to protect the poor are widely regarded as models for other countries" (Stevenson, 1988).

5.32 However, as in Ghana, enrollment rates declined despite increasing public spending. Was protection insufficient? Should spending have increased even more? Or 46
do enrollment rates depend on factors other than public spending levels? For example, do changes in family incomes have a greater influence than perceived education quality on demand for education? The evidence that increases in public education spending do not automatically raise enrollment rates may have important implications for education policy in other countries.

5.33 Educat.in spending increased its share of GNP significantly between 1980 and 1988. This growth resulted from increasing public spending as a share of GNP combined with an increase in education's share of the public budget. Real education expenditures more than quadrupled between 1975 and 1985. However, primary enrollment rates dropped from 1980 to 1985, even though a pre-existing program of tuition exemption for poor children expanded during the 1979-81 recession. Total primary enrollments declined three percent between 1980-85. Increasing public spending and declining enrollments caused public education spending per primary student to nearly double between 1980 and 1985.

# South Korea: education indicators

||197|5 1980|1981|1982 1983|1984|1985 1986 1987 1988|
|---|---|---|---|---|---|---|
|Finance:<br>|||||||
|% of public budget<br>|12.9|14.6|14.4|17.0 17.9|16.8|16.9|
|% of GDP<br>|2.2|3.7||||4.8|
|real expenditures (index)|41|100||||186|
|Inraectoral finance:<br>|||||||
|recurrent budget share(%)|74|84||||80|
|primary share of budget (%)|62|50||||47|
|3utput (enrollment rates--%):<br>gross primary<br>|107|109|107|109 103|99|96|
|net primary|100|||||94|
|Ouality:|||||||
|per student spending (index)<br>primary repeaters (%)|46<br>0|100<br>0||||192<br>0|
|Equity:|||||||
|% primary students female|48|49||||49|

5.34 The share of recurrent spending in the total budget declined slightly from 1980 to 1985, suggesting that, unlike the pattern found in many countries, investment in education was not neglected during the adjustment period. Female primary enrollment rates exceeded total enrollment rates. One cause for concern is the declining share of sector spending allocated to primary education.

47
## TURKEY

5.35 Similar to the previous two cases, the adjustment program in Turkey did not explicitly address education, despite massive borrowing from the World Bank throughout the decade. However, Turkey was less successful at protecting education than were the Philippines and South Korea. A growing external debt burden abruptly halted growth in mid-1977, with a sharp deterioration in creditworthiness, severe shortages of imports, disruptions in industrial production and a consequent rise in urban unemployment. GNP, which was growing at an annual rate of 4 percent in 1977, declined in 1979. Inflation increased from 24 percent 1977 to 64 percent 1979. Turkey received five SALs between 1980 and 1984 totalling over $1.5 billion, as well as four SECALs from 1985 to 1988 totalling $1.4 billion. SAL conditionality emphasized increasing efficiency, reducing the role of the public sector in the economy, rationalizing investment, and promoting exports.

# Turkey education **indicator**

||1975|1980 1981|1982|1983|1984|1985|1986 1987 1988|
|---|---|---|---|---|---|---|---|
|Finance:<br> <br>||||||||
|% of public budget<br> <br>% of GDP<br>|23.1|14.2<br>2.8<br>||||23|11.9|
|real expenditures (index)||100||||106||
|Intrasectoral finance:<br>||||||||
|recurrent budget share(%)<br>primary share of budget(%)||84<br>44||||83<br>46||
|Output (enrollment rates--%):<br>gross primary<br>|108<br>|96 100<br>||111|113|113||
|net primary|72|65||||75||
|Ouality:<br>|<br>|||||||
|per student spending (index)<br>|<br>|100||||94||
|secondary placement exam<br>pass rate (%)|||22|35|28|28||
|Equity:<br>% primary students female|45|45||||47||

5.36 Data on Turkey's education sector is scarce, and the most recent (for only one indicator) is from 1986. Education suffered the greatest setbacks (declines in education's share of the government budget and the primary enrollment rate) during economic shocks in the late 1970s, rather than during the Bank-assisted adjustment process after 1980. During the adjustment period enrollment rates recovered, but education's share of government spending remained below the 1975 level. Despite declining sector financing, 48
the growth of total primary enrollments accelerated from 0.7 percent per year from 197580 to 3.2 percent per year from 1980-85 (Colclough and Lewin, 1990).

5.37 The literature provides little information on the quality and efficiency of education during the adjustment period. Because spending declined while enrollments increased, public education spending per primary student declined. Real recurrent spending per primary teacher increased by about 5 percent between 1980 and 1985 (Lewin and Berstecher, 1989). Despite declining public expenditures, the proportion of secondary graduates successful at placement exams improved between 1982 and 1985. Female primary enrollment rates paralleled total enrollment rates, declining from 97 percent in 1975 to 90 percent in 1980, but rising to 110 percent in 1985. The proportion of female students in primary enrollments increased slightly during the adjustment period.

# ZAMBIA

5.38 The Bank assisted adjustment in Zambia through sector adjustment programs and recovery credits, none of which targeted education explicitly. Copper prices collapsed in the mid-1970s, an,. terms of trade deteriorated. The currency became increasingly overvalued, and the network of controls on imports, foreign exchange and credit allocation became increasingly complex. Despite a declining revenue base, the government tried to maintain government services and employment, resulting in a growing budget deficit that attained 18 percent of GDP in 1980-82. Controlled adjustment began around 1982. Zambia received World Bank adjustment loans beginning in 1984: SECALs in 1984, 1985, and 1986 followed by recovery credits in 1986 and 1990. Conditionality focused on promoting exports (SECALs), as well as restructuring public expenditures, strengthening government capacity for economic management, and wage restraint (SALs).

5.39 Trends of fewer real resources to education and a higher share to wages began before adjustment. Increased spending levels around 1982 were only a brief interruption of declining trends. Unlike in Ghana and Malawi, education's share of the discretionary public budget and real education expenditures both declined from the period before to the period after adjustment. Colclough and L2win (1990) state that adjustment failed to increase the orientation of social spending to primary services delivery. Primary and tertiary education's shares of recurrent spending in fact did not change from 1980 to 1983.

5.40 Enrollment rates fell before, and rose after, 1980. The growth of total primary enrollments increased from 3.6 percent per year between 1975-80 to 5.3 percent in the 198085 period (UNDP 1990b). Given rising enrollments while sector resources declined, a decline in per student expenditures was inevitable: at the primary level they fell by onethird from 1975 to 1985, with the bulk of the decline before 1980. However, the evidence on quality and equity is scarce and contradictory. Most declines occurred between 1975 and 1980, and evidence suggests stagnation after 1980. The elimination of private enrollments between 1975 and 1980 (declining from 24 to 1 percent of primary enrollments) may have serious implications for education quality. Although it promoted greater equity between wealthy and poor students, it increased the burden on public resources at a time when the latter were shrinking and enrollments were rising. However, the difference between the 49
# number of years to produce a graduate and the number of years in the primary system improved, from 1.4 in 1975 to 0.7 in 1985. e -

# Zambia: education indicators

||1975|1980|1981|1982|1983|1984|1985|1986|1987 1988|
|---|---|---|---|---|---|---|---|---|---|
|Einance:<br>||||||||||
|% of public budget<br>|13.9<br>|11.4<br>|11.9<br>|15.1<br>|14.5<br>|16.0<br>|12.3<br>||8.3<br>|
|%of GDP<br>|5.9<br>|4.2<br>|4.3<br>|_5.9_<br>|4.7<br>|4.7<br>|4.3<br>|3.5<br>|2.9<br>|
|real expenditures (index)|139|100|110|145|112|112|104|86|73|
|Intrasectoral finance:<br>||||||||||
|recurrent budget share_(t)_<br>budget share to salaries_(%)_<br>|77<br>|95<br>||||94||||
|primary<br>|77<br>|88<br>|91<br>|89<br>|91<br>|||||
|secondary<br>|14|30|34|38|42|||||
|budget shares by level (%)<br>||||||||||
|primary<br>|45<br>|45<br>|43<br>|45<br>|47<br>|||||
|secondary<br>|22<br>|22<br>|20<br>|20<br>|20<br>|||||
|higher|8|11|14|14|11|||||
|Qutput (enrollment rate--%):<br>||||||||||
|gross primary<br>|97|90<br>|||93<br>|96<br>|99|97||
|net primary<br>||77<br>|||80<br>|81<br>||||
|gross secondary|15|16||17|17|17|17|||
|ouality:<br>||||||||||
|per student spending (index)<br>|143|100<br>|||||96|||
|teacher salaries (index)<br>||100<br>|83<br>|89<br>|113<br>|88<br>||||
|pnrimary repeaters_(%)_<br>|2.1<br>|1.9<br>|_1.5_<br>|1.3|_1.5_|1.8||2.1<br>||
|grade 4 completion_(t)_|96|99|100|||||100||
|Equity:<br>||||||||||
|primary enrollment rates_(%)_<br> <br>||||||||||
|male<br> <br>|105<br>|98<br>|||100<br>|103<br>|106<br>|102||
|female<br>|88<br>|82<br>|||87|89|93<br>|92||
|% primary students female|45|47|||||47|||

5.41 Within the recurrent budget, salaries were given increasing priority at the primary and secondary levels. Nevertheless, real recurrent spending per primary teacher declined by 12 percent from 1980 to 1984 (Lewin and Berstecher, 1989). Teacher salaries during the early years of adjustment were protected relative to those gf manufacturing workers: the ratio of teacher salaries to manufacturing worker salaries increased from 1.05 in 1980 to 1.56 in 1984. However, real teacher salaries in 1984 were below 1980 levels (Zymelman and DeStefano, 1989).

_50_
**ANNMC** 2: WORID BANK ADJUSIMENIT **OPERXAONS** BY COUNMRY

Counttvang Algeria Angola Aspntina Bangladesh Benin Bolivia Brazil Burkina Faso Burundi cameron Central African Rep.

Chad Chile China Colombia Congo Costa Rica Cote d'lvoire fledft Economic reform 1990 Rehabilitation 1990 Agriculture 1986 Trade policy 1 1987 Banking 1988 Trade policy n 1989 Program 1980 Program 1981 Program 1982 Program 1983 Program 1984 Program 1986 Industry 1987 Enefry 1989 Finance 1990 SAL 1 1989 SAL 1 1980 Reconstruction imports 1986 Reconstruction imports U 1987 Financial 1988 Agriculture 1984 Export development 1984 Credit and marketing 1986 Fertilizer 1985 SAC I 1986 SAL n1 1988 Agriculture 1989 coffee 1990 SAL 1 1989 SAL 1 1987 Cotton 1988 SAL 11 1988 Financial rehabilitation 1989 Transport 1989 Social development 1990 SAL ! 1986 SAL II 1987 SAL !!I 1988 Rural sector 1988 Trade policy 1985 Trade and agriculture 1986 Power 1988 SAL 1988 Export development 1983 SAL ! 1985 SAL 11 1989 SAL ! 1982 SAL 11 1984 SAL 111 1986 Agriculture 1990 51
Countt Loan ot credi M Cote dlvoire (continued) Enerq 1990 Water supply/sewerage 1990 Dominica SAC 1 1987 Ecuador Agriculture 1986 Financial 1988 Equatorial Guinea Rehabilitation imports 1986 SAL I 1990 Gabon SAL 1988 Gambia SAL 1987 SAL 11 1989 Ghana Reconstruction imports 1983 Export rehabilitation 1984 Reconstruction imports 1985 Industry 1986 SAL 1 1987 Education 1987 Financial 1988 SAC 11 1989 Education UI 1990 Guatemala Export 1990 Guinea SAC 1 1986 SAL It 1988 Education 1990 Guinea Bissau Rehabilitation imports 1985 SAL I 1987 SAC It 1989 Guyana SAL 1 1980 SAC 11 1990 Haiti Economic recovery 1987 Honduras SAL 1 1989 Hungay Industry 1986 Industry 1988 SAL 1990 Indonesia Trade 1987 Trade policy 11 1988 Private sector development 1989 Jamaica Export development 1980 Export development 11 1981 SAL 1 1982 Export development III 1983 SAL 11 1983 SAL III 198S Public enterprise 1987 Trade and finance 1987 Agriculture 1990 Jordan Trade 1990 Kenya SAC I 1980 SAC 11 1983 Agriculture 1986 Industry operations 1988 Finance 1989 Indonesia Jamaica Jordan Kenya 52
|Qounta|~~~~~~~Loan<br>or cM|Yea|
|---|---|---|
|Laos|SAC|1989|
|Madagar|Industry<br>|1985<br>|
||Agriculture<br>|1986<br>|
||Industry and trade<br>Public setor|1987<br>1988|
|Malawi|SAL 1<br>FertilIzer|1981<br>1983|
||<br>SAL n<br>|1984<br>|
||SAL Hi<br>Id" d d|19S6<br>1988|
||nusty an trae<br>||
||Agriculture|1990|
|Mali|Publicenterprise<br>Human rgMrm|1988<br>1989|
|Mauritania|Public enterprpi<br>|19SS<br>|
||SNIM rehabilitation<br>|1986<br>|
||SAL<br>Agriculture/irrigation|1987<br>1990|
||<br>Public enterprise|1990|
|Mauritius|SAL 1<br>SAL|1981<br>1984|
||n<br>Industry|1987|
|Mexico|Expoft development 1|1983|
||<br>Trade poilcy|1987|
||<br>AIlt|1988|
||grcuure<br>Pertilizer|1988|
||Trade olicn|1998|
||py <br>Finance|1989|
||Industfy restucturing|1989|
||<br>Idt li|1989|
||nusry pocy<br>||
||Public enterprise|1989|
||Deregulation<br>|1990<br>|
||Exports II<br>Special interests|1990<br>1990|
|Morocco|Industry trade policy<br>|19S4<br>|
||AgricultureI<br>Id"t td li|198S<br>1986|
||nury rae pocy||
||_ucatio<br>Public enterprise<br>|1986<br>1987<br>|
||A.griculture11<br>SAL I|1988<br>1989|
||<br>Debt management|1990|
|Mozambique|Rehabilitation<br>|1985<br>|
||Rehabilitation I<br>Rehabilitation III|198S<br>1989|
||<br>Small/medium enterprises|1990|
|Nepal|SAL<br>SAL 11|1987<br>1989|
|Niger|SAC<br>Public enterprise|1986<br>1987|
|Nigeria|Fertilizer imports<br>|1984<br>|
||Trade poicy<br>Trd nd intmnt li|1987<br>1989|
||ae a vese pocy<br>Budgetary finance policy<br>Univrsity deveoment|1990<br>1990|
|Pakistan|Fertilizer Imports<br>SAL I|1981<br>1982|
||<br>Energy|1985|

Morocco Mozambique Nepal Niger Nigeria Pakistan 53
Contr Pakistan (continued) Panama Philippines Rwanda Sao TomE & Principe Senegal Sierra Leone Somalia South Korea Sri Lanka Sudan Tanzania Thaiiand Togo Tunisia Turkey Leon orLQLdit Ye Export development 1986 Agriculture 1989 Energy 11 1989 Finance 1989 Transport/rilways 1990 SAL 1 1984 SAL If 1987 SAL 1 1981 SAL 11 1983 Agriculture 1985 Economic recofvery 1987 Govemment corporations 1988 Finance 1989 Telecommunications 1990 SAL 1 1987 SAC 11 1990 SAL 1 1981 SAC 11 1986 SAL 111 1987 Banking/Finance 1990 SAC IV 1990 Transport 1990 Agriculture 1984 Agriculture 1986 SAL/Agriculture n 1989 SAL 1 1982 SAL n 1984 Industry Finance 1985 Economic recovery 1990 Agriculture rehabilitation 1980 Agiculture rehabilitation 11 1983 Economic recovery 1990 Export rehabilitation 1981 Multisector rehabilitation 1987 Industry and trade 1989 SAL 1 1982 SAL n 1983 SAC I 1983 SAI 11 198S SAL HI 1988 Agriculture 1987 Industry and trade policy 1987 SAL I 1988 Agriculture n 1989 Public enterprise 1990 SAL 1 1980 SAL II 1981 SAL III 1982 SAL IV 1983 SAL V 1984 Agriculture 1985 Finance 1986 Energy 1987 Finance 11 1988 54
|Countr|lmn or cred.||
|---|---|---|
|Uganda|Reconstruction<br>I<br>Reconstruction<br>11<br>Agriculture rehabilitation<br>Reconstruction<br>III<br>Economic<br>recovcqy|1980<br>1982<br>1983<br>1964<br>1988|
|Urguay|Agriculture<br>SAL I<br>SAL n|1985<br>1987<br>1989|
|Venezuela|SAL<br>Trade policy|1989<br>1989|
|Yugoslavia|SAL 1<br>Fertilizer|1983<br>1984|
|Zaire|Industry<br>SAL I|1986<br>1987|
|Zambia|Export rehabilitatlon<br>Agriculture rehabilitation<br>Industry<br>Recovery|1984<br>1985<br>1986<br>1986|
|Zimbabwe|Manufacturing<br>exports|1983|

Sourc World Bank Adjustmeit Operations Data.

_55_
# ANNEX 3: COUNTRY TYPOLOGY OF FISCAL DURESS

The following countries are categorized as experiencing "fiscal duress during the 1980s if they met two of three criteria: sustained improvement in fiscal balance, sustained reductions in the share of government spending in GDP, and sustained reductions in real government spending.

Edii,.tion spending I (% of govermment lbdget)

||Total b<br>1975 -79|udget<br>1980-85|Disri<br> <br>1975-|onary<br>79|budget<br>1980-85|
|---|---|---|---|---|---|
|Africa|15.3|15.3|16.1||16.9|
|Africa duressed|13.9|15.2|14.6||17.1|
|Asia|12.4|12.4|13.6||14.2|
|Asia duressed|17.6|16.7|18.8||18.6|
|EMENA|11.6|11.7|12.1||13.4|
|EMENA duressed|14.2|13.7|15.9||17.3|
|LAC|16.6|14.5|17.4||15.7|
|LAC duressed|18.2|16.1|18.6||16.4|
|P<br>|Gross enro<br>rimary scho<br>|llment rates<br>gls<br>|(%)<br>Seg.<br>|Qnd= s<br>|chools<br>|
|1975-77|1980-82|1984-85|1975-77|1980-8|2 1984-8.|
|Africa<br>61|71|71|13|16|18|
|Africa duressed<br>60|71|67|9|14|12|
|Asia<br>_55_|66|68|33|34|36|
|Asia duressed<br>56|57|52|44|47|49|
|EMENA<br>69|77|77|33|42|49|
|EMENA duressed<br>86|99|102|30|38|44|
|LAC<br>100|103|104|39|46|50|
|LAC duressed<br>104|109|110|40|48|53|

56
||initi<br>|al adusiment period|At|
|---|---|---|---|
|Africa|<br>Benin|<br>1984|X|
||Central African Republic<br>|1983-84|X|
||Congo<br>|1983|X|
||C6te d'Ivoire<br>|1983<br>|X|
||Liberia<br>|1983||
||Madagascar<br>|1983|X|
||Malawi|1982|X|
||Mauritania|1984-86|X|
||Niger<br>|1982-84|X|
||Senegal|1983-85|X|
||Sierra Leone<br>|1980-82|X|
||Somalia|1980|X|
||Tanzania<br>|1980-83|X|
||Togo<br>|1980-82|X|
||Uganda|1985|X|
|LAC|Bahamas|1980-84||
||Chile<br>|1983-85|X|
||Colombia<br>|1983-85|X|
||Ecuador<br>|1983-85|X|
||El Salvador|1981-83||
||Jamaica<br>|1981|X|
||Mexico<br>|1983|X|
||Nicaragua|1984||
||Peru|1982||
||Uruguay<br>|1983-85|X|
||Venezuela|1982-83||
|EMENA|Iran|throughout||
||Jordan|1981||
||Morocco|1982-83|X|
||Tunisia|1985-86|X|
||United Arab Emirates|1983||
|AliA|Fiji|1982-83||
||Papua New Guinea|1982||
||Sri Lanka|1981-83||
||Thailand|1986|X|

Source: Gallagher (1990).

57
# ANNEX 4: COUNdTPRY TYPOLOGY OF ADJUSTMENr

- AL countri (intensely adjusting) have received three or more SALs, or two completed SALs, by 1989, with lending starting in or before 1985 (25 cases).

- Pre-196 countries have received less than three SALs but were included in the program befoi-e 1985 (11 cases).

_Post-1985_ countries received adjustment loans between 1986-1988 (19 cases).

- NAL+ countnies had an increase in average annual per capita GDP growth during the period 1980-87 (17 cases). These countries do not need IMF/World Bank types of adjustment measures, unless the policies they pursue are unsustainable.

- NAL- countries had a decrease in average annual per capita GDP growth during the period 1980-87 (14 cases). These are potential candidates for World Bank adjustment lending, and are proba)ly the closest to the counterfactual nonadjusting countries.

# Public education financing **(%** of total public expenditures)

||Countries<br>|1975<br>|1980<br>|1986|
|---|---|---|---|---|
|IAL<br>|11<br>|14.8<br>|14.8<br>|12.0|
|Pre-1986<br>|2<br>|16.2<br>|15.5<br>|19.0|
|Post-1985<br>|3<br>|9.7<br>|6.7<br>|8.1|
|NAL|12|9.9|10.0|12.1|

# Public education financing (% of GDP)

||Countries<br>|1975|1980|1986|
|---|---|---|---|---|
|IAL<br>|11<br>|3.3|_3.5_|2.9|
|Pre-1986<br>|2|3.0|4.0|4.6|
|Post-1985<br>|3<br>|---|6.7|8.1|
|NAL|12|9.9|10.0|12.1|

# Gross primarv enrollment rates (t)

||Countries<br>|1970<br>|1975|1980|1985|
|---|---|---|---|---|---|
|LAL<br>|25<br>|77.4|83.2|94.2|90.1|
|Pre-1986<br>|9|67.3|70.8|75.5|84.0|
|Post-1985<br>|18<br>|52.4<br>|65.5|68.4|73.7|
|NAL (Total)<br>|33<br>|73.5|80.3|86.0|91.1|
|NAL+<br>|18<br>|76.9|82.4|89.9|98.3|
|NAL-|15|69.4|77.7|81.3|82.6|

58
Per capita educatiQn expenditures (19-80 PP-P dollars)

||Countries<br>|1980|1986|
|---|---|---|---|
|IAL<br>|11<br>|81.2|73.2|
|Pre-1986<br>|2<br>|29.7|40.1|
|Post-1985<br>|3<br>|27.4|39.9|
|NAL|12|48.7|90.8|

# IAL

Low-income Ghana Middle-income Bolivia Kenya Brazil Madagascar Chile Malawi Colombia Mauritania Costa Rica Nigeria Cote d'Ivoire Pakistan Jamaica Tanzania Mauritius Togo Mexico Zambia Morocco Phi!ppines Senegal South Korea Thailand T'urkey Pre-1986 Countries Low-income Burkina Faso Middle-income Guinea Bissau Guyana Sierra Leone Sudan Uganda Ecuador Panama Uruguay Yugoslavia Zimbabwe 59
|Low-income|Bangladesh<br>Middle-income<br>Burundi<br>Central African Rep.<br>Chiad<br>China<br>Congo<br>Gambia<br>Guinea<br>Indonesia<br>Mali<br>Nepal<br>Niger<br>Somalia<br>Zaire|Argentina<br>Gabon<br>Honduras<br>Hungary<br>Tunisia|
|---|---|---|
|KAL± Countries|||
|Low-income|Benin<br>Middle-income<br>Myanmar<br>India<br>Rwanda<br>Sri Lanka|Botswana<br>Cameroon<br>Dominican Republic<br>Egypt<br>Jordan<br>Malaysia<br>Oman<br>Para&aay<br>Peru<br>Poland<br>Portugal<br>Yemen Arab Republic|
|_NAT-_Coutri<br>Low-income|Ethiopia<br>Middle-income<br>Haiti<br>Lesotho<br>Liberia<br>Mozambique<br>Yemen PDR|Algeria<br>El Salvador<br>Guatemala<br>Nicaragua<br>Papua NP-w Guinea<br>Syria<br>Trinidad & Tobago<br>Venezuela|

Sarce: Kakwani Makonnen and van der Gaag (1990).

60
# BIBLTOGRAPHY

- AEDO-RICHMOND, Ruth and Ines NOGUERA. "Recession and Educational Policy in Chile in the 1980s." IDS Bulletin, Vol. 20, No. 1. January 1989. pp. 24-30.

- AINSWORTH, Martha and Juan MUNOZ. The C6te d'Ivoire Living Standard Survey. LSMS Working Paper No. 26. 1986.

- AMADEO, Edward J., Jose Marcio CAMARGO, and Ciludio de Moura CASTRO. 'The Political Economy of Budget Cuts: A Suggested Scheme of Analysis." ILO, Training Policies Department. September, 1990.

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68
# PRE Working Paper Series

||io|Authbgt||Contact<br>for paper|
|---|---|---|---|---|
|WPS675|Are Buybacks Back? Menu-Driven<br>Debt-Reduction Schemes with<br>Heterogenous Creditors|Ishac Diwan<br>Mark M. Spiegel|May 1991|S. King-Watson<br>33730|
|WPS676|Higher Education in the Republic<br>of Yemen: The University of Sana'a|Viswanathan Selvaratnam<br>Omporn L. Regel|May 1991|C. Cristobal<br>33640|
|WPS677|On Economic Transformation in East<br>Central Europe: A Historical and<br>International Perspective|- Andres Solimano|May 1991|E. Khine<br>39361|
|WPS678|Economic Growth: A Review of the<br>Theoretical and Empirical Literature|David Renelt|May 1991|R. Luz<br>34303|
|WPS679|Poverty Alleviation in Mexico|Santiago Levy|May 1991|M. Stroude<br>38831|
|WPS680|On Hunger and Public Action|Martin Ravallion|May 1991|C. Spooner<br>30464|
|WPS681|Political-Economy Arguments for<br>UniformTariff|Arvind Panagariya<br>Dani Rodrik|May 1991|K. Cabana<br>37947|
|WPS682|Intertemporal Substitution, Risk<br>Aversion, and Private Savings in<br>Mexico|Patricio Arrau<br>Sweder van Wijnbergen|May 1991|S. King-Watson<br>31047|
|WPS683|Vocational Schooling, Occupational<br>Matching, and Labor Market Earnings<br>in Israel|Shoshana Neuman<br>Adrian Ziderman|May 1991|C. Cristobal<br>33640|
|WPS684|The Value of Intra-household Survey<br>Data for Age-based Nutritional<br>Targeting|Lawrence Haddad<br>Ravi Kanbur|May 1991|J. Sweeney<br>31021|
|WPS685|Children and Intra-household<br>Inequality: A Theoretical Analysis|Ravi Kanbur|May 1991|J. Sweeney<br>31021|
|WPS686|Lending for Learning: Twenty Years<br>of World Bank Support for Basic<br>Education|Adriaan Verspoor|May 1991|C. Cristobal<br>33640|
|WPS687|Brazilian Frozen Concentrated<br>Orange Juice: The Folly of Unfair<br>Trade Cases|Carlos Alberto Primo Braga<br>Simao Davi Silber|May 1991|N. Artis<br>37947|
|WPS688|Macroeconomics of Public Sector<br>Deficits: The Case of Zimbabwe|Felipe Morande<br>Klaus Schmidt-Hebbel|May 1991|S. Jonnakuty<br>39074|
PRE Working Paper Series

||_Av_hfor|torF|Contact|
|---|---|---|---|
|WPS689 Do Tax Policies Stimulate Investme<br>in Physical and Research<br>and<br>Development<br>Capital?|nt Anwar Shah<br>John Baffes|May 1991|A. Bhalla<br>37699|
|WPS690 The Terms-of-Trade<br>Effects from the<br>Elimination<br>of State Trading in Sovie<br>Hungarian Trade|Gabor Oblath<br>t- David Tarr|May 1991|J. Smith<br>37350|
|WPS691 Can Debt-Reduction<br>Policies Restor<br>Investment<br>and Economic<br>Growth<br>in Highly Indebted<br>Countries? A<br>Macroeconomic<br>Framework<br>Applied<br>to Argentina|e Jacques Morisset|May 1991|S. King-Watson<br>31047|
|WPS692 Health Financing in the Poor<br>Countries: Cost Recovery<br>or Cost<br>Reduction?|J. Brunet-Jailly|May 1991|0. Nadora<br>31091|
|WPS693 Report on Adjustment<br>LendingII:<br>Lessons for Eastern Europe|Vittorio Corbo|May 1991|A. Oropesa<br>39075|
|WPS694 Labor Markets in an Era of<br>Adjustment: An Overview|Susan Horton<br>Ravi Kanbur<br>Dipak Mazumdar|May 1991|M. Schreier<br>36432|
|WPS695 Long Term Prospects<br>in Eastern<br>Europe: The Role of Extemal Financ<br>in an Era of Change|Ishac Diwan<br>e Fernando<br>Saldanha|June 1991|S. King-Watson<br>33730|
|WPS696 Macroeconomics<br>of Public Sector<br>Deficits: The Case of Chile|Jorge Marshall<br>Klaus Schmidt-Hebbe|June 1991<br>l|S. Jonnakuty<br>39074|
|WPS697 Volatility Reversal from Interest<br>Rates to the Real Exchange<br>Rate:<br>Financial Liberalization<br>in Chile,<br>1975-82|Paul D. McNelis<br>Klaus Schmidt-Hebbe|June 1991<br>l|S. Jonnakuty<br>39074|
|WPS698 Tax Policy Options to Promote<br>Private Capital Formation<br>in Pakistan|Andrew Feltenstein<br>Anwar Shah|June 1991|A. Bhalla<br>37699|
|WPS699 Regulation<br>and Deregulatio**n**<br>i<br>Industrial Countries: Some Lessons<br>for LDCs|Ralph Bradburd<br>David R. Ross|June 1991|E. Madrona<br>37496|
|WPS700 Trade Liberalization<br>and the<br>Transition to a Market Economy|Oleh Havrylyshyn<br>David Tarr|June 1991|N. Castillo<br>37961|
|WPS701 Education<br>and Adjustment:<br>A Review<br>of the Literature|Andrew Noss|June 1991|C. Cristobal<br>33640|