(ii) Results: We start by examining whether districts that received the most FONCODES expenditure for school improvements achieved the largest gains in school attendance.<sup>4</sup> Although the LSMS surveys can be used to construct measures of district-level attendance, district-level measures based on larger numbers of children from more districts can also be obtained from the 1993 census and the 1996 INEI survey. While we do not have household-level census data, we do have information on district-level attendance rates for children aged 6 to I 15 Figure 6.1 shows the relationship between school attendance rates and a modified version of the FONCODES index. We modify the FONCODES index so that we exclude one variablethe fraction of children aged 6-11 who are not attending school.<sup>6</sup> Keeping this variable in the FONCODES index would have produced a purely mechanical negative relationship between the index and school attendance in 1993. Each line in Figure 6.1 corresponds to a nonparametric regression of the attendance rate on the index in each of the two years, 1993 and 1996. Figure 6.1 shows that the relationship between attendance rates and the FONCODES index ilas changed during the period. There is an obvious negative relationship between school attendance and high levels of unmet basic needs in 1993, but this is no longer apparent in 1996. In other words, worse-off districts had large gains in school attendance, but better-off districts did not. Figure 6.2 graphs the _change_ in the school attendance rate and the per capita FONCODES expenditures on education-both as a function of the FONCODES index. This figure shows that the worse-off districts which experienced greater gains in school attendance also received more funding for school improvements. The degree of co-movement between attendance gains and school funding is striking. It is possible that the relative gains of children in poorer districts were due to some (unobserved) factor which is coincidentally associated with FONCODES expenditures. But the data are also consistent with a causal relationship between expenditures and attendance gains.

14 Throughout section 6, we consider only FONCODES expenditures on the construction and renovation of classrooms (see Table 1.1). Specifications based on total education expenditures do not fit the data quite as well, suggesting that the construction of sports facilities and the provision of educational material by FONCODES did not have a discernible impact on educational outcomes.

15 The 1993 census and the 1996 INEI surveys both ask about whether children in the household were attending school ("asistiendo al colegio"), which is slightly different from the LSMS question of whether children were attending school "or studying something" ("asistiendo al colegio o estudiando algo"). One consequence of this difference in the questionnaires is that school attendance rates from the LSMS are somewhat higher than for the other data sources. Note also that attendance rates are unlikely to be equal to enrollment rates, as some children may be enrolled but not attending school.

16 Our procedure is to construct, for each district, what the FONCODES index would have been had the district-level school attendance rate been equal to the average over all districts. Essentially, this means that the modified index is based only on the seven non-attendance components of the original.

17 One puzzling feature of Figures 6.1 and 6.2 is that attendance rates appear to have _declined_ for children in well-off districts between the earlier and later years. However, this decline may be at least partly a feature of the timing of the surveys. In Peru, the school year runs from April to December. The 1993 census data was collected in June, relatively early in the school year. The 1996 INEI was collected in November. Attrition of attendance over the course of the school year could account for the lower mean 16