the test-scores of children improved. Thus, schools are credit constrained (otherwise, mimicking the effect of providing grants in only one school, they could borrow money and expand enrollment at the expense of other schools, earning as our schools did, a positive return on the investment over and above the market rate of interest), but “picking” schools to receive credit does not expand the size of the market in terms of quality. When we do try and “pick” schools, by providing credit to a single school, the school expands capacity _knowing that other schools cannot do so due to the lack of access to credit_ . When we treat every school in an _ex ante_ equal manner it prevents the use of strategies that rely on differential treatment and forces schools to expand the size of the market. In ongoing work, we are now extending these lessons to work with financial service providers and design specific financial products that are better tailored to the investment needs of schools and that can be offered at scale to address the broader credit market failures faced by the sector.

Of course, the lack of access to finance is a problem in public as well as private schools. There is a movement towards financing local bodies and providing them fungible cash to use as they desire in their schools. Between 2003 and 2011, we evaluated precisely such a strategy in the schools in our sample through a government intervention (Andrabi and others 2014d). Specifically, villages were randomly chosen and each public school in such a treatment village received cash from the government to be administered and used by a reformed School Management Committee.

Although the implementation of the program was delayed as is often the case with government programs (it was due to start in 2004, but schools received money only in 2006 and the program started in earnest only in 2007), we were able to track school performance over 7 years with surveys between 2003 and 2007 and then again in 2011 (political events made it difficult to implement field surveys between 2007 and 2011).

When we went back in 2011, we found a fundamentally changed environment in treatment villages. First, the average child in the village—whether in public or private schools—had improved test-scores in English, Mathematics and Urdu. These differences were to the tune of 0.4 standard-deviations in instrumental variables specifications, which is a large increase in the context of educational interventions.<sup>34</sup> We then looked differentially at public and private schools and show that the increases accrued to children in _both types of schools_ . If this was because private schools had to respond to increases in public school quality, we should also find that responses were higher in private schools that were in greater direct competition with their government counterparts. Again, this is precisely what the data show. We look at differential effects for private schools that were initially closer to public schools and those that were farther away and report higher increases for those that were in close proximity. Alleviating financial constraints in public schools increased the quality of public schooling _and_ private schools responded by increasing the quality of their own offerings.<sup>35</sup>

> 34 Since every public school in treated villages was allocated to receive funding, we do not know what would happen if only one public school received funding, which is the exact parallel to our private financing experiment.

> 35 In the case of public schools, this mirrors recent findings from Kenya and India that providing greater incentives to teachers, whether through direct payments conditional on test-score performance or performance-based tenure schemes can increase test-scores. See Muralidharan and Sundararaman (2013) for evidence from and Indian pay-for-performance scheme and Duflo,

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