Patrick Bayer

A Dynamic Model of Demand for Houses and Neighborhoods

This paper develops a dynamic model of neighborhood choice along with a computationally light multi-step estimator. The proposed empirical framework captures observed and unobserved preference heterogeneity across households and locations in a flexible way. The model is estimated using a newly assembled data set that matches demographic information from mortgage applications to the universe of housing transactions in the San Francisco Bay Area from 1994- 2004. The results provide the first estimates of the marginal willingness to pay for several non-marketed amenities – neighborhood air pollution, violent crime and racial composition – in a dynamic framework. Comparing these estimates with those from a static version of the model highlights several important biases that arise when dynamic considerations are ignored.

Tiebout Sorting and Neighborhood Stratification

Tiebout’s classic 1956 paper has strong implications regarding stratification across and within jurisdictions, predicting (in the simplest instance) a hierarchy of internally homogeneous communities, ordered by household income. In practice, urban areas tend to exhibit varying degrees of within-neighborhood mixing, likely attributable to departures from several standard Tiebout assumptions – the fact that households are influenced by more than public goods packages when deciding where to live, the heterogeneous nature of the housing stock, and the role of employment geography, given commuting costs are non-zero. To shed light on the way these factors influence observed residential mixing, this paper quantifies the separate contributions of employment geography and housing preferences in reducing neighborhood stratification. It does so using an equilibrium sorting model, estimated with rich Census micro-data. Simulations based on the model using credibly-identified demand estimates show that counterfactual reductions in commuting costs lead to marked increases in education segregation and, to a lesser degree, increases in income segregation, as households now find it easier to locate in neighborhoods with similar households. In contrast, turning off preferences for housing characteristics actually reduces income segregation, indicating that the nonuniform distribution of housing serves to stratify households based on ability-to-pay. Related, we show that differences in housing also help accentuate differences in the consumption of local amenities.

Identifying Individual and Group Effects in the Presence of Sorting: A Neighborhood Effects Application

Researchers have long recognized that the non-random sorting of individuals into groups generates correlation between individual and group attributes that is likely to bias naive estimates of both individual and group effects. This paper proposes a non-parametric strategy for identifying these effects in a model that allows for both individual and group unobservables, applying this strategy to the estimation of neighborhood effects on labor market outcomes. The first part of this strategy is guided by a robust feature of the equilibrium in vertical sorting models - a monotonic relationship between neighborhood housing prices and neighborhood quality. This implies that under certain conditions a non-parametric function of neighborhood housing prices serves as a suitable control function for the neighborhood unobservable in the labor market outcome regression. This control function transforms the problem to a model with one unobservable so that traditional instrumental variables solutions may be applied. In our application, we instrument for each individual’s observed neighborhood attributes with the average neighborhood attributes of a set of observationally identical individuals. The neighborhood effects model is estimated using confidential microdata from the 1990 Decennial Census for the Boston MSA. The results imply that the direct effects of geographic proximity to jobs, neighborhood poverty rates, and average neighborhood education are substantially larger than the conditional correlations identified using OLS, although the net effect of neighborhood quality on labor market outcomes remains small. These findings are robust across a wide variety of specifications and robustness checks.

The Effectiveness of Juvenile Correctional Facilities: Public versus Private Management

This paper uses data on juvenile offenders released from correctional facilities in Florida to explore the effects of facility management type (private for‐profit, private nonprofit, public state‐operated, and public county‐operated) on recidivism outcomes and costs. The data provide detailed information on individual characteristics, criminal and correctional histories, judge‐assigned restrictiveness levels, and home zip codes—allowing us to control for the nonrandom assignment of individuals to facilities far better than any previous study. Relative to all other management types, for‐profit management leads to a statistically significant increase in recidivism, but relative to nonprofit and state‐operated facilities, for‐profit facilities operate at a lower cost to the government per comparable individual released. Cost‐benefit analysis implies that the short‐run savings offered by for‐profit over nonprofit management are negated in the long run due to increased recidivism rates, even if one measures the benefits of reducing criminal activity as only the avoided costs of additional confinement.

Nonparametric Identification and Estimation in a Roy Model With Common Nonpecuniary Returns

We consider identification and estimation of a Roy model that includes a common nonpecuniary utility component associated with each choice alternative. This augmented Roy model has broader applications to many polychotomous choice problems in addition to occupational sorting. We develop a pair of nonparametric estimators for this model, derive asymptotics, and illustrate small-sample properties with a series of Monte Carlo experiments. We apply one of these models to migration behavior and analyze the effect of Roy sorting on observed returns to college education. Correcting for Roy sorting bias, the returns to a college degree are cut in half. This article has supplementary material online.

Distinguishing Racial Preferences in the Housing Market: Theory and Evidence

Given the extent of residential segregation on the basis of race and ethnicity in U.S. cities, it is unsurprising that a long line of research in social science has attempted to better-understand the causes and consequences of segregation. One prominent branch of that literature has used housing market data on the observed patterns of residential sorting and corresponding housing prices to make inferences about (i) the nature of household preferences for the racial composition of their neighborhoods and (ii) the extent to which segregation is driven by centralized discriminatory forces versus the decentralized location decisions of households, given their preferences (Zabel, this Volume, and Hite, this Volume).1

Choice and Competition in Education Markets

This paper presents a new approach for measuring the effects of competition on school performance. We use an equilibrium sorting model to generate an intuitive measure of the competition each school faces, captured by the slope of the school’s demand curve. We then show that this competition measure is positively related to school performance using rich Census data: a one standard-deviation increase in competitiveness leads to a 0.1 standard-deviation performance improvement, controlling for a host of other factors. This positive performance relationship is consistent with strong supply responsiveness, relevant to the school choice debate.

A Fair and Impartial Jury? The Role of Age in Jury Selection and Trial Outcomes

This paper uses data from over 700 felony trials in Sarasota and Lake Counties in Florida from 2000-2010 to examine the role of age in jury selection and trial outcomes. The results of the analysis imply that prosecutors are more likely to use their peremptory challenges to exclude younger members of the jury pool, while defense attorneys exclude older potential jurors. Having established that age has an important role in jury selection, the paper employs a research design that isolates the effect of the random variation in the age composition of the pool of eligible jurors called for jury duty to examine the causal impact of age on trial outcomes. Consistent with the jury selection patterns, the empirical evidence implies that older jurors are indeed more likely to convict. These results are robust to the inclusion of a broad set of controls for the racial and gender composition of the jury and a series of county, time, and judge fixed effects; almost identical effects are estimated separately for each county. These findings have implications for the role that the institution of peremptory challenges has on a defendant’s right to a fair trial and to an eligible citizen’s rights to serve on a jury.

Speculative Fever: Investor Contagion in the Housing Bubble

Historical anecdotes of new investors being drawn into a booming asset market, only to suffer when the market turns, abound. While the role of investor contagion in asset bubbles has been explored extensively in the theoretical literature, causal empirical evidence on the topic is virtually non-existent. This paper studies the recent boom and bust in the U.S. housing market, establishing that many novice investors entered the market as a direct result of observing investing activity of multiple forms in their own neighborhoods and that these “infected” investors performed poorly relative to other investors along several dimensions.

What Drives Racial and Ethnic Differences in High Cost Mortgages? The Role of High Risk Lenders

This paper examines racial and ethnic differences in high cost mortgage lending in seven diverse metropolitan areas from 2004-2007. Even after controlling for credit score and other key risk factors, African-American and Hispanic home buyers are 105 and 78 percent more likely to have high cost mortgages for home purchases. The increased incidence of high cost mortgages is attributable to both sorting across lenders (60-65 percent) and differential treatment of equally qualified borrowers by lenders (35-40 percent). The vast majority of the racial and ethnic differences across lender can be explained by a single measure of the lender’s foreclosure risk and most of the within-lender differences are concentrated at high-risk lenders. Thus, differential exposure to high-risk lenders combined with the differential treatment by these lenders explains almost all of the racial and ethnic differences in high cost mortgage borrowing.