This paper studies how increasing teacher compensation at hard-to-staﬀ schools can reduce structural inequality in the access to high-quality teachers. We ﬁrst document dramatic inequities in schooling inputs and teacher quality to which students have access in the context of a large and diverse developing country: Peru. We then leverage a change in teacher compensation to show causal evidence that increasing salaries at less desirable public schools attracts better quality applicants and improves subsequent student test scores. We ﬁnally estimate a model of teacher preferences over local community amenities, school characteristics and wages using detailed job posting and application data from the country-wide centralized teacher assignment system. The ﬁtted model is able to replicate the main features in the data, including the sorting patterns of teachers around the policy change in teacher wages. Model estimates indicate that while current pay bonuses in less desirable regions are helpful, the current policy is woefully insufficient to compensate teachers for the lack of school and community amenities, especially in school vacancies that are distant to the teachers’ home town or the location of their current job. Counterfactual experiments taking into account equilibrium sorting show that budget-neutral changes in the current wage schedule can achieve a remarkably more equitable distribution of teacher quality across regions.
In markets with private options, the optimal level of public provision may require balancing a tradeoff between reducing private options’ market power with the possibility of crowding out potentially high-quality products. These considerations are particularly relevant in many developing countries’ education systems where state capacity is increasing but low levels of past public provision mean many private schools already exist. We study the equilibrium effects of public provision in the context of a large expansion of public schools in the Dominican Republic. Over a five-year period, the government aimed to increase the number of public school classrooms by 78%. Using an event study framework, we estimate the effect of a new public school on neighborhood outcomes and competing private schools, where we instrument for how quickly the public school construction project finished with the characteristics of the contractor randomly assigned to build the project. We find that a new public school increased public sector enrollment significantly. As public enrollment increased, a large number of private schools closed while the surviving schools lowered prices and increased school quality. To study how the level of public provision affects the overall level of quality in the market, we specify and estimate an empirical model of demand (students choosing schools) and supply (schools choosing whether to enter, stay open and what price to charge). We use the model estimates to calculate the level of public provision that maximizes learning. Due to equilibrium competitive effects, we find that the optimal level is non-monotonic in the quality of the increased public schooling.
In many settings, market designers must contend with the presence of firms who participate in the broader game surrounding a market but do not participate in the portion under the designer’s control. In this paper, we study the empirical relevance of the configuration of on- and off-platform options in the context of a centralized college-major choice system. We quantify significant negative externalities generated by off-platform options and measure the aftermarket frictions that contribute to generating them in practice. Our empirical application uses administrative data from the centralized assignment system for higher education in Chile and leverages a recent policy change that increased the number of on-platform slots by approximately 40%. We first present a policy analysis which shows that expanding the centralized platform leads students to start college sooner and raises the share of students who graduate within six years. We develop an empirical model of college applications, aftermarket waitlists, and matriculation choices. We estimate the model using students’ ranked-ordered applications, on- and off-platform enrollment, and on-time graduation outcomes. We use the estimated model to quantify welfare impacts, decompose different mechanisms and to con-duct counterfactual exercises. We find that when more programs are available on the centralized platform, welfare increases substantially. These externalities are driven by students who receive and decline on-platform offers, and are amplified by substantial frictions in waitlists. Our results indicate that expanding the scope of a higher education platform can have real impacts on welfare and human capital. Importantly, the effects are larger for students from lower SES backgrounds, suggesting the design of platforms can have effects on both efficiency and equity.
This paper introduces a simple school choice model in which all students have the same ordinal preferences over schools but only some have access to an outside option. Our model predicts that, under a manipulable school choice mechanism, students with the outside option are more likely to apply to popular schools. We show that while students with the outside option beneﬁt from manipulable systems, students without the outside option may experience either welfare gains or welfare losses. We evaluate the positive predictions of the model using a diﬀerence-in-diﬀerences design that leverages a change from the Boston mechanism to a deferred acceptance mechanism in the New Haven, Connecticut school district. Consistent with the theoretical predictions, students with an outside option are more likely to list popular, highly-rated schools under the manipulable mechanism, but this gap disappears after the switch to the deferred acceptance mechanism.
This paper studies how welfare outcomes in centralized school choice depend on the assignment mechanism when participants are not fully informed. Using a survey of school choice
participants in a strategic setting, we show that beliefs about admissions chances differ from
rational expectations values and predict choice behavior. To quantify the welfare costs of belief
errors, we estimate a model of school choice that incorporates subjective beliefs. We evaluate
the equilibrium effects of switching to a strategy-proof deferred acceptance algorithm, and of
improving households' belief accuracy. Allowing for belief errors reverses the welfare comparison
to favor the deferred acceptance algorithm.
This paper studies the potential small and large scale effects of a policy designed to produce more in-formed consumers in the market for primary education. We develop and test a personalized information provision intervention that targets families of public Pre-K students entering elementary schools in Chile. Using a randomized control trial, we find that the intervention shifts parents’ choices toward schools with higher average test scores, higher value added, higher prices, and schools that tend to be further from their homes. Tracking students with administrative data, we find that student academic achievement on test scores was approximately 0.2 standard deviations higher among treated families five years after the intervention. To quantitatively gauge how average treatment effects might vary in a scaled up version of this policy, we embed the randomized control trial within a structural model of school choice and competition where price and quality are chosen endogenously and schools face capacity constraints. We use the estimated model of demand and supply to simulate policy effects under different assumptions about equilibrium constraints. In counterfactual simulations, we find that capacity constraints play an important role mitigating the policy effect but in several scenarios, the supply-side response increases quality, which contributes to an overall positive average treatment effect. Finally, we show how the estimated model can inform the design of a large scale experiment such that reduced form estimates can capture equilibrium effects and spillovers.
While it is a widely held belief that family and social networks can inﬂuence important life decisions, identifying causal effects is notoriously difficult. This paper presents causal evidence from three countries at different stages of economic development that the educational trajectories of older siblings can signiﬁcantly inﬂuence the college and major choice of younger siblings. We exploit institutional features of centralized college assignment systems in Chile, Croatia, and Sweden to generate quasi-random variation in the educational paths taken by older siblings. Using a regression discontinuity design, we show that younger siblings in each country are signiﬁcantly more likely to apply and enroll in the same college and major that their older sibling was assigned to. These results persist for siblings far apart in age who are unlikely to attend higher education at the same time. We propose three broad classes of mechanisms that can explain why the trajectory of an older sibling can causally affect the college and major choice of a younger sibling. We ﬁnd that spillovers are stronger when older siblings enroll and are successful in majors that on average have higher scoring peers, lower dropout rates and higher earnings from graduates. The evidence presented shows that the decisions, and even random luck, of your close family members and peer network, can have signiﬁcant effects on important life decisions such as the choice of specialization in higher education. The results also suggest that college access programs such as aﬃrmative action, may have important spillover effects through family and social networks.
We study the efficiency of a centralized college admissions platform that operates jointly with a decentralized “off-platform” aftermarket. We exploit a policy change in 2012 in which a significant number of off-platform higher education options joined a centralized assignment system for higher-education programs in Chile. We show evidence that this policy change had impacts on real outcomes finding that the share of students declining their placed spot de-creased by 8% and dropout rates at the end of the first year of college dropped by 2 percentage points (a 16% drop) following this event. To quantify the welfare impacts of the aftermarket on the efficiency of the match, we develop and estimate an empirical model of college applications, aftermarket waitlists and matriculation choices, using individual-level administrative data from Chile on almost half a million applications, including test scores and enrollment decisions at all on- and off-platform higher education options. According to model estimates, welfare increases substantially, students begin their studies sooner, and fewer students drop out by the end of the first year of study when top off-platform programs join the platform. These benefits are greater for less advantaged students and for women. Counterfactual analysis suggests that more desirable options generate larger negative externalities when not on the platform. These externalities are mostly driven by students admitted on on-platform options that decline their spots to pursue off-platform programs; and are amplified by frictions in waitlists that yield socially inefficient allocations. Our results indicate that platform design can have real impact on outcomes of interest. Specifically, our findings suggest policymakers need to consider the implications of off platform options and their characteristics when designing regulation surrounding centralized assignment systems.
This paper studies screening and recruiting policies that use pre-college academic achievement to restrict or incentivize entry to teacher-colleges. Using historical records of college entrance exam scores since 1967 and linking them to administrative data on the population of teachers in Chile, the paper first documents a robust positive and concave relationship between pre-college academic achievement and several short and long run measures of teacher productivity. We then evaluate the effectiveness of two policies that used pre-college achievement to recruit or screen out students entering teacher-colleges. Using a regression discontinuity design based on the government’s recruitment efforts, we evaluate the effective-ness of targeted scholarships at shifting career choices of high achieving students at the individual level as well as the effect on the overall stock of teachers predicted effectiveness. We then evaluate the effects of a recent screening policy that forces teacher colleges to exclude below-average students. We quantify the policies effectiveness by retroactively simulating the policy rule and evaluate its success at screening out low performing teachers and mistakenly high performing teachers. We compare this benchmark policy rule to a series of potential data-driven policy rules and we find that even simple screening policies can identify a significant portion of ex-post low performing teachers. In both policies studied, screening low performing students is more effective than targeting recruitment efforts to only very high achieving students. Taken together, these findings suggest that the combination of better administrative data and flexible prediction methods can be used to implement practical screening and recruiting policies in some contexts and allow for better targeting of investments in future teachers.
While it is widely believed that family and social networks can inﬂuence important life decisions, identifying causal effects is notoriously difficult. This paper presents causal evidence from three countries that the educational trajectories of older siblings can signiﬁcantly inﬂuence the college and major choice of younger siblings. We exploit institutional features of centralized college assignment systems in Chile, Croatia, and Sweden to generate quasi-random variation in the educational paths taken by older siblings. Using a regression discontinuity design, we show that younger siblings in each country are signiﬁcantly more likely to apply and enroll in the same college and major that their older sibling was assigned to. These results persist for siblings far apart in age who are unlikely to attend higher education at the same time. We propose three broad classes of mechanisms that can explain why the trajectory of an older sibling can causally aﬀect the college and major choice of a younger sibling. We ﬁnd that spillovers are stronger when older siblings enroll and are successful in majors that, on average, have higher scoring peers, lower dropout rates and higher earnings from graduates. The evidence presented shows that the decisions, and even random luck, of your close family members and peer network, can have signiﬁcant effects on important life decisions such as the choice of specialization in higher education. The results also suggest that college access programs such as affirmative action, may have important spillover effects through family and social networks.