Parents gauge school quality in part by the level of student achievement and a school's racial and socioeconomic mix. The importance of school characteristics in the housing market can be seen in the jump in house prices at school district boundaries where peer characteristics change. The question of whether schools with more attractive peers are really better in a value-added sense remains open, however. This paper uses a fuzzy regression-discontinuity design to evaluate the causal effects of peer characteristics. Our design exploits admissions cutoffs at Boston and New York City's heavily over-subscribed exam schools. Successful applicants near admissions cutoffs for the least selective of these schools move from schools with scores near the bottom of the state SAT score distribution to schools with scores near the median. Successful applicants near admissions cutoffs for the most selective of these schools move from above-average schools to schools with students whose scores fall in the extreme upper tail. Exam school students can also expect to study with fewer nonwhite classmates than unsuccessful applicants. Our estimates suggest that the marked changes in peer characteristics at exam school admissions cutoffs have little causal effect on test scores or college quality.

Buying or selling a residential property is one of the most important financial decisions for a large majority of households in the United States. In 2007, 68 percent of households owned their own home, more than a third of national wealth was held in residential real estate, and there were 6.4 million sales of existing homes according to estimates from the Department of Housing and Urban Development.

Abstract We use admissions lotteries to estimate the effects of large-scale public preschool in Boston on college-going, college preparation, standardized test scores, and behavioral outcomes. Preschool enrollment boosts college attendance as well as SAT test taking and high school graduation. Preschool also decreases high school disciplinary measures including juvenile incarceration, but has no detectable effect on state achievement test scores. An analysis of subgroups shows that effects on college enrollment, SAT-taking, and disciplinary outcomes are larger for boys than for girls. Our findings illustrate possibilities for large-scale modern, public preschool and highlight the importance of measuring long-term and non–test score outcomes in evaluating the effectiveness of education programs.

Abstract We introduce two empirical strategies harnessing the randomness in school assignment mechanisms to measure school value-added. The first estimator controls for the probability of school assignment, treating take-up as ignorable. We test this assumption using randomness in assignments. The second approach uses assignments as instrumental variables (IVs) for low-dimensional models of value-added and forms empirical Bayes posteriors from these IV estimates. Both strategies solve the underidentification challenge arising from school undersubscription. Models controlling for assignment risk and lagged achievement in Denver and New York City yield reliable value-added estimates. Estimates from models with lower-quality achievement controls are improved by IV.

This paper describes the market for borrowing corporate bonds using a comprehensive data set from a major lender. The cost of borrowing corporate bonds is comparable to the cost of borrowing stock, between 10 and 20 basis points, and both have fallen over time. Factors that influence borrowing costs are loan size, percentage of inventory lent, rating, and borrower identity. There is no evidence that bond short sellers have private information. Bonds with Credit Default Swaps (CDS) contracts are more actively lent than those without. Finally, the 2007 Credit Crunch does not affect average borrowing costs or loan volume, but does increase borrowing cost variance.

We develop over-identification tests that use admissions lotteries to assess the predictive value of regression-based value-added models (VAMs). These tests have degrees of freedom equal to the number of quasi-experiments available to estimate school effects. By contrast, previously implemented VAM validation strategies look at a single restriction only, sometimes said to measure forecast bias. Tests of forecast bias may be misleading when the test statistic is constructed from many lotteries or quasi-experiments, some of which have weak first stage effects on school attendance. The theory developed here is applied to data from the Charlotte-Mecklenberg School district analyzed by Deming (2014).

School choice systems aspire to delink residential location and school assignments by allowing children to apply to schools outside of their neighborhood. However, choice programs also affect incentives to live in certain neighborhoods, and this feedback may undermine the goals of choice. We investigate this possibility by developing a model of public school and residential choice. School choice narrows the range between the highest and lowest quality schools compared to neighborhood assignment rules, and these changes in school quality are capitalized into equilibrium housing prices. This compressed distribution generates an ends-against-the-middle trade-off with school choice compared to neighborhood assignment. Paradoxically, even when choice results in improvement in the lowest-performing schools, the lowest type residents need not benefit. (JEL H75, I21, I28, R23, R31)

Several K-12 and university systems have adopted race-neutral affirmative action in place of race-based alternatives. This paper explores whether these plans are effective substitutes for racial quotas in Chicago Public Schools (CPS), which now employs a race-neutral, place-based affirmative action system at its selective exam high schools. The CPS plan is ineffective compared to plans that explicitly consider race: about three-quarters of the reduction in average entrance scores at the top schools could have been avoided with the same level of racial diversity. Moreover, the CPS plan is less effective at adding low-income students than was the previous system of racial quotas. We develop a theoretical framework that motivates quantifying the inefficiency of race-neutral policies based on the distortion in student preparedness they create for a given level of diversity and use it to evaluate several alternatives. The CPS plan can be improved in several ways, but no race-neutral policy restores minority representation to prior levels without substantially greater distortions, implying significant efficiency costs from prohibitions on the explicit use of race. (JEL H75, I21, I28, J15)

In Fall 2009, Chicago authorities abandoned a school assignment mechanism midstream, citing concerns about its vulnerability to manipulation. Nonetheless, they asked thousands of applicants to re-rank schools in a new mechanism that is also manipulable. This paper introduces a method to compare mechanisms by their vulnerability to manipulation. Our methodology formalizes how the old mechanism is at least as manipulable as any other plausible mechanism, including the new one. A number of similar transitions took place in England after the widely popular Boston mechanism was ruled illegal in 2007. Our approach provides support for these and other recent policy changes. (JEL C78, D82, H75, I21, I28)