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Using data on student outcomes and school choice lotteries from a low-income urban school district, we examine how school choice can affect student outcomes through increased motivation and personal effort as well as through improved school and peer inputs. First we use unique daily data on individual-level student absences and suspensions to show that lottery winners have significantly lower truancies after they learn about lottery outcomes but before they enroll in their new schools. The effects are largest for male students entering high school, whose truancy rates decline by 21% in the months after winning the lottery. We then examine the impact attending a chosen school has on student test score outcomes. We find substantial test score gains from attending a charter school and some evidence that choosing and attending a high value-added magnet school improves test scores as well. Our results contribute to current evidence that school choice programs can effectively raise test scores of participants. Our findings suggest that this may occur both through an immediate effect on student behavior and through the benefit of attending a higher-performing school.
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We establish the presence of a gender gap in mathematics across many low- and middle-income countries using detailed, comparable test score data. Examining micro level data on school performance linked to household demographics we note that first, the gender gap appears to increase with age. Indeed, the gap nearly doubles when comparing 4th grade and 8th grade test scores. Second, we test whether commonly proposed explanations such as parental background and investments, unobserved ability, and classroom environment (including teacher gender) explain a substantial portion of the gap. While none of these explanations help in substantially explaining the gender gap we observe, we show that boys and girls differ significantly in perceptions about their own ability in math, conditional on math test scores. Girls are much more likely to state that they dislike math, or find math difficult compared to boys. We highlight differences in self-assessed ability as areas for future research that might lead to a better understanding of the gender gap in math.
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We use administrative data from Chile from 1985 through 2011 to estimate the returns to postsecondary admission as a function of field of study, course requirements, selectivity, and student socioeconomic status. Our data link high school and college records to labor market earnings from federal tax forms. We exploit hundreds of regression discontinuities from the centralized, score-based admissions system to estimate the causal impacts of interest. Returns are positive and significant only among more-selective degrees. Returns are highly heterogeneous by field of study, with large returns in health, law and social science, as well as selective technology and business degrees. We find small to negative returns in arts, humanities and education degrees. We do not find evidence that vocational curriculum focus increases returns for less selective degrees. We do not find differential outcomes for students coming from low- versus high-socioeconomic backgrounds admitted to selective degrees.
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This paper examines the impact of fetal exposure to air pollution on 4th grade test scores in Santiago, Chile. We rely on comparisons across siblings which address concerns about locational sorting and all other time-invariant family characteristics that can lead to endogenous exposure to poor environmental quality. We also exploit data on air quality alerts to help address concerns related to short-run time-varying avoidance behavior, which has been shown to be important in a number of other contexts. We find a strong negative effect from fetal exposure to carbon monoxide (CO) on math and language skills measured in 4th grade. These effects are economically significant and our back of the envelope calculations suggest that the 50% reduction in CO in Santiago between 1990 and 2005 increased lifetime earnings by approximately 100 million USD per birth cohort.
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We test the impact of information about institution- and major-specific labor market outcomes on college enrollment decisions using a randomized controlled trial administered within the online Chilean federal student loan application process. Using linked secondary and post-secondary education records and tax returns for fourteen cohorts of Chilean high school graduates, we created measures of past-cohort earnings for nearly all institution and major combinations in the Chilean higher education system. Applicants were asked a series of survey questions about their enrollment plans and their beliefs about earnings and cost outcomes. Following the survey questions, randomly selected applicants were given information on earnings and costs for past students at their planned enrollment choices, as well as access to a searchable database that allowed them to compare earnings and costs across degrees. Students have unbiased but highly variable beliefs about costs, and upward-biased beliefs about earnings outcomes. Poorer students have less accurate information and choose lower-earning degrees conditional on baseline ability and demographics. While treatment has no effect on whether students enroll in postsecondary education, it does cause low-SES students to enroll in degrees where earnings net of costs were higher for past enrollees. Though effect sizes are small, they substantially exceed the cost of implementing the disclosure policy.
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This paper exploits a large-scale natural experiment to study the equilibrium effects of information restrictions in credit markets. In 2012, Chilean credit bureaus were forced to stop reporting defaults for 2.8 million individuals (21% of the adult population). We show that the effects of information deletion on aggregate borrowing and total surplus are theoretically ambiguous and depend on the pre-deletion demand and cost curves for defaulters and non-defaulters. Using panel data on the universe of bank borrowers in Chile combined with the deleted registry information, we implement machine learning techniques to measure changes in lenders' cost predictions following deletion. Deletion reduces (raises) predicted costs the most for poorer defaulters (non-defaulters) with limited borrowing histories. Using a difference-in-differences design, we find that individuals exposed to increases in predicted costs reduce borrowing by 6.4%, while those exposed to decreases raise borrowing by 11.8% following the deletion, for a 3.5% aggregate drop in borrowing. Using the difference-in-difference estimates as inputs into the theoretical framework, we find evidence that deletion reduced aggregate welfare under a variety of assumptions about lenders' pricing strategies.
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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.
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We use large-scale surveys of Chilean college applicants and college students to explore the way students form beliefs about earnings and cost outcomes at different institutions and majors and how these beliefs relate to degree choice and persistence. Linking our survey records to administrative education and earnings data, we compare earnings and cost expectations to observed values for past students and follow survey participants forward to see how beliefs relate to matriculation and dropout outcomes. We find that students have correctly centered but noisy cost expectations, and appear to systematically overestimate earnings outcomes for past graduates. Students who overestimate costs are less likely to matriculate in any degree program and in their stated first-choice program, and are more likely to drop out. Students who overestimate earnings matriculate at similar rates to other students, but choose degree programs where past students have been less likely to graduate, have earned less early in their careers, and have been more likely to default on student loans. Consistent with an informal model of enrollment choice, students with a stated preference for labor market-related degree characteristics are less likely to overestimate earnings outcomes and choose degrees where past students have gone on to earn more, while the opposite is true for students with a stated preference for enjoyment of the curriculum.
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We establish the presence of a gender gap in mathematics across many low- and middle-income countries using detailed, comparable test score data. Examining micro level data on school performance linked to household demographics we note that first, the gender gap appears to increase with age. Indeed, the gap nearly doubles when comparing 4th grade and 8th grade test scores. Second, we test whether commonly proposed explanations such as parental background and investments, unobserved ability, and classroom environment (including teacher gender) explain a substantial portion of the gap. While none of these explanations help in substantially explaining the gender gap we observe, we show that boys and girls differ significantly in perceptions about their own ability in math, conditional on math test scores. Girls are much more likely to state that they dislike math, or find math difficult compared to boys. We highlight differences in self-assessed ability as areas for future research that might lead to a better understanding of the gender gap in math.
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