countries—its lower primary enrollment, particularly among girls and the significant impact of distance to school on enrollment (Andrabi and others 2007, Burde and Linden 2013, Barrera-Osorio and others 2013) are both particular to the region and the country. Nevertheless, it is plausible that the research findings from this context could yield valuable information about schooling across a number of countries.

What can be done to improve schooling in this environment? If poor learning reflects poverty in general, the best solution is to try and make poor people richer, either through growth or redistribution. But if poor learning reflects systematic constraints that prohibit parents and schools from reaching higher levels, alleviating these constraints should lead to better outcomes. In our pragmatic framework, constraints could be identified from observational data and new equilibria could be evaluated after constraints were alleviated. Several features of this line of research are worth emphasizing.

In terms of applying insights from the theory of firms and industrial organization, the presence of private schools in an unregulated setting where prices are set in market equilibrium is critical for our program. These settings allow us to abstract from worrying about multiple objectives that public schools may try to satisfy at the same time. For instance, public schools may locate in very small and poor villages in order to satisfy an _equity_ rationale. Although private school owners may also have a broader societal objective in mind, they also face hard budget constraints and cannot function for long if costs far outstrip revenues. We have showed before that in fact, private schools (a) face little de facto regulation and/or constraints on prices; (b) only a few enjoy revenue sources beyond the fees paid by students and; (c) operate in a fairly competitive setting with average profits similar to the annual wage of a male teacher in the private market. The market structure that has developed in this unregulated setting is one where private schools offer _vertically differentiated_ products at varying prices—although fees are low in general (the average fee is $3 per month in 2011) the same typically have multiple private schools at different quality-price points, with test-scores and infrastructure strongly correlated with prices.

Further, we do not tinker or directly try to affect (or even estimate) the _production function_ for education; our assumption (which could well turn out to be false) is that overall improvements in market functioning will alleviate constraints that schools currently face and by doing so, schools and parents can themselves figure out what will make them better. We measure what happens in the new equilibrium after the constraint is alleviated and try and collect information on a broad variety of outcomes.

Finally, we operate in rural settings with _closed_ markets. That is, in the villages in our studies, children go to the schools in the villages and the vast majority of enrollment in the village schools is from among the children in the village itself.<sup>31</sup> This feature of the environment allows us to manipulate a particular feature of the market and study the equilibrium as a whole. In more complex settings (say, urban

> 31 This reflects the importance of distance as a key factor, both in whether to attend school and the choice of which school to attend. Although the “distance penalty” has been well documented in both observational and experimental studies (Andrabi and others 2007, Burde and Linden 2013, Barrera-Osorio and others 2013) there is less research on understanding precisely what the distance penalty means. Jacoby and Mansuri (2011) provide one attempt to do so and argue that this penalty could reflect the aversion to crossing boundaries across settlements in the same village.

15