funded education projects. Unfortunately, this is not always the case. Consider, for example, households in rural areas who only have children attending primary school. In 4 rural communities in the sample, all such households reported that FONCODES had financed improvements to the local school, and in a further 107 all reported that FONCODES had not financed improvements. In 46 rural communities, however, there was no agreement, with different households providing different responses. These results, and similar ones for the FONCODES school breakfast program, suggest that households in the 1996 INEI survey do not always report program benefits accurately. Measurement error of this sort will bias the estimates of program incidence if it is correlated with income, so that richer (or poorer) households are more (or less) likely to report that they benefited from FONCODES.

A second problem arises if program participation has an impact on per capita income. Ideally, to estimate program incidence, one would rank households by the per capita income they would have had in the absence of the program. But this income is, by definition, unobservable. We believe that in the case at hand the impact of program participation on household income is not a major source of concern because the monetary value to a household of FONCODES investments in education should only be a small fraction of total household income. Throughout the analysis, we simply rank households by their observed per capita income." As before, we present nonparametric regressions for educational infrastructure and school breakfast programs.

Figure 5.7 presents a nonparametric univariate density estimate of the distribution of the log of per capita income. A very small fraction of the population in Peru lives on a (log of) per capita income of less than 6 soles or more than 10 soles per year. The graphs for the nonparametric regressions trim these households at the top and bottom 1% of the income distribution.

Figure 5.8 compares the household-level incidence of FONCODES investments in school infrastructure with those made by INFES, and the Parents' Committees (akin to the PTA's in the United States). Two things are worth noting about the graph. First, it shows that the incidence of investments in educational infrastructure is more pro-poor when these are made by FONCODES than when they are made by the Parents' Committees or INFES. The comparison between FONCODES and INFES is particularly clear. To some extent, no doubt, this reflects the fact that l In theory, participation in an education program could increase or decrease household income in the short run. Benefiting from a free school breakfast program will likely represent an increase in income, but putting children in school may lead to a short-term decrease in income if these children would otherwise have been gainfully employed. Note that a similar problem with an unobservable counter-factual may also arise with our estimates of the incidence of FONCODES-level geographic targeting for 1992 and 1993. This is because the analysis ranks districts by mean district per capita income, but this income could itself have been affected by FONCODES investments made prior to 1993.

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