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.

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