demonstrate that this effect is causal. To disentangle demand from supply effects (perhaps mothers with secondary education demand more schooling for their children), we further show that wages are _lower_ in villages with girls’ secondary schools, consistent with a shock that shifted the supply, rather than demand curve outwards.

The ability of private schools to locate thus responds critically to the availability of skilled labor in the market. But the story does not stop there. In recent work, we compute the productivity of teachers using longitudinal data over four years in private schools (Bau and Das, 2014b). We demonstrate a strong correlation in teachers’ wages and teacher value-added in private schools and show that this correlation arises because better teachers move to schools that pay more—there is no variation in wages by teacher value-added within the same school. Consistent with the idea that the schooling market works by allocating scarce, productive teachers across vertically-differentiated schools, we find that high value-added teachers exit low quality schools faster, as do low value-added teachers in high quality schools. The high turnover and attrition could, in turn, create problems in the labor market as it sharply reduces the incentive for school owners to train teachers. Particularly in low quality schools, owners will realize that more training will make it more likely that they will lose their teachers to higher quality schools. The gains to training will be realized by the schools that the teachers eventually move to rather than the schools that trained them. This in turn suggests experiments where such training is subsidized by the government.

# <u>Section IV.3 Credit Market Failures: Increasing Access to Finance</u>

Our third experiment tackled constraints arising from a lack of financing for private schools. In the literature on small and medium enterprises, lack of credit has been one of the major barriers to expansion and greater profits. But whether credit can improve the ability of private schools to deliver services so far remains untested.

We constructed an experiment that allowed us to look both at credit constraints and the policy effect of alleviating credit in the market for schools (Andrabi and others 2014c). The experiment was as follows. Starting with a set of villages, we divided the sample into three groups. One group of villages was the “control” group where no school received financial grants. In the second group we randomly chose a single school to receive grants. In the third group _every_ private school in the village received grants. The difference between the second and group and the control group is informative of the size of credit constraints (Group 2) and the difference between the third group and the other two provides the policy effect of providing financial assistance to the market. We took a light touch in our financing strategy. Schools were given Rs.50000 (roughly $500) and asked to submit a plan for how they would use the money to improve their schools. We then checked for gross abuse, but overall the schools could do as they wanted with the funds, even if they used it in ways that were outside their original plan document.

One year later we found that schools in the group where only one school had received grants significantly increased enrollment and revenue, although they had spent no more than half the grant on schooling improvements. In contrast, in the third group, schools had spent _all_ the money on schooling improvements, but each had seen smaller enrollment increases. Critically, it was only in this group that 18