6.14 District spending and education outcomes

general, and lewis (2013) has shown that daK does indeed have a strong positive effect on capital spending in the education sector. It is also plausible that daK negatively affects routine spending as districts shift any additional fiscal resources to support daK-financed capital projects. If this is true, then daK’s positive impact on capital spending might be cancelled out by its negative effect on routine spending, thus voiding its net effect on aggregate spending. lewis (2014b) provided some evidence to suggest that the daK may crowd-in additional capital spending at least under certain circumstances, which supports this argument. a final issue of concern regarding daK transfers is that the magnitude of annual allocations is quite volatile across districts, creating challenges in planning and completing capital projects in education and other sectors. This may also help explain the weak effects of daK on spending.

The relationship between district spending and education outcomes is examined next. figure 6.14 illustrates the association between district total and education spending and education access, as measured by net enrollment rates, and education quality, as proxied by national test scores. The figure shows no clear relationship between district spending and education outcomes.

But simple scatterplots do not account for several important aspects of the relationship between spending and education outcomes. first, they do not accommodate the likelihood that education outcomes in one period depend on outcomes in the previous period. second, they do not account for the possible

FIGURE 6.14

District spending and education outcomes

endogeneity of district spending in determining outcomes. Finally, they do not control for other possible influences on education outcomes.

The regressions represent an attempt to overcome all these problems (World Bank 2021, tables 2.3, 2.4, 2.5, and 2.6). The results suggest that a 1 percent increase in total spending leads to a 0.029 increase in enrollment rates and a 0.062 increase in average test scores. These are modest effects. In addition, the regression results imply that a 1 percentage point increase in the education budget share leads to a 0.10 increase in enrollment rates and a 0.04 increase in average test scores, although these results are not statistically significant at conventional levels.

The lack of impact that education spending has on test scores is perhaps odd. There is some indication, however, that at least some districts do not classify BOS as education spending but rather as administrative expenditure. If so, then the fact that BOS is not included in the calculation of education spending in many districts might dilute the estimated effectiveness of education expenditures on test scores. On the other hand, it may simply be that increased education spending does not have any impact on the quality of education as measured by test scores. Kurniawati et al. (2018), for example, argue that education sector investments have not led to any substantive improvements in education quality in Indonesia.

One way to illustrate the impact of district expenditures on education outcomes after accounting for the influence of outcomes in the previous period, spending endogeneity, and covariate effects is to create scatter plots that show the relationship between district expenditures and predicted education outcomes from the estimated regression equation. As figure 6.15 shows, the relationship between spending and predicted outcomes is now positive.

In sum, intergovernmental transfers determine district spending to a large extent, and district spending positively influences local education outcomes on average, at least to a limited extent. These relationships suggest that the inequitable distribution of transfers and spending in Indonesia may lead to inequitable educational opportunities and outcomes. As a result, some districts receive considerably more funds than others and therefore spend significantly more as well and vice versa. The districts that receive lower transfers are relatively disadvantaged because they have fewer opportunities to improve their performance, which is reflected in their outcomes.

The inequity in education outcomes is illustrated in figure 6.16, which shows the frequency distribution of district enrollment and test scores in 2016. In that year, enrollment rates varied from about 10 percent to 85 percent, and district test scores ranged from about 40 to 80 (out of 100). District education outcomes in Indonesia are indeed unequal, and this chapter argues that these unequal outcomes are to some extent a function of the unequal distribution of transfers.

Overall, the analysis raises at least two additional questions. First, why does local government spending have such a muted impact on various education outcomes? Second, what other policies or factors might positively or negatively influence such outcomes?

Research indicates a number of elements that mitigate the positive effects of local spending on school enrollment and test scores in Indonesia. Suryadarma et al. (2006) demonstrate that teacher absenteeism has a strong negative effect on student achievement in test scores. Suryadarma (2012) shows that district corruption constrains the positive impact of spending on school enrollment. Lewis (2017b) finds that the spending of local governments that manage their