Papers written by Author(s): 'Patrick Bayer'
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Viewing papers 1 through 5 of 5
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Working PaperA Unified Framework for Measuring Preferences for Schools and Neighborhoods
October 2007
Working Paper Number:
CES-07-27
This paper develops a comprehensive framework for estimating household preferences for school and neighborhood attributes in the presence of sorting. It embeds a boundary discontinuity design in a heterogeneous model of residential choice to address the endogeneity of school and neighborhood attributes. The model is estimated using restricted-access Census data from a large metropolitan area, yielding a number of new results. First, households are willing to pay less than one percent more in house prices ' substantially lower than previous estimates ' when the average performance of the local school increases by five percent. Second, much of the apparent willingness to pay for more educated and wealthier neighbors is explained by the correlation of these sociodemographic measures with unobserved neighborhood quality. Third, neighborhood race is not capitalized directly into housing prices; instead, the negative correlation of neighborhood race and housing prices is due entirely to the fact that blacks live in unobservably lower quality neighborhoods. Finally, there is considerable heterogeneity in preferences for schools and neighbors: in particular, we find that households prefer to selfsegregate on the basis of both race and education.View Full Paper PDF
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Working PaperIdentifying Individual and Group Effects in the Presence of Sorting: A Neighborhood Effects Application
January 2007
Working Paper Number:
CES-07-03
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 the canonical vertical sorting model of Epple and Platt (1998), that there is 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 converts 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.View Full Paper PDF
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Working PaperPlace of Work and Place of Residence: Informal Hiring Networks and Labor Market Outcomes
October 2005
Working Paper Number:
CES-05-23
We use a novel dataset and research design to empirically detect the effect of social interactions among neighbors on labor market outcomes. Specifically, using Census data that characterize residential and employment locations down to the city block, we examine whether individuals residing in the same block are more likely to work together than those in nearby blocks. We find evidence of significant social interactions operating at the block level: residing on the same versus nearby blocks increases the probability of working together by over 33 percent. The results also indicate that this referral effect is stronger when individuals are similar in sociodemographic characteristics (e.g., both have children of similar ages) and when at least one individual is well attached to the labor market. These findings are robust across various specifications intended to address concerns related to sorting and reverse causation. Further, having determined the characteristics of a pair of individuals that lead to an especially strong referral effect, we provide evidence that the increased availability of neighborhood referrals has a significant impact on a wide range of labor market outcomes including employment and wages.View Full Paper PDF
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Working PaperAn Equilibrium Model of Sorting in an Urban Housing Market: A Study of the Causes and Consequences of Residential Segregation
January 2003
Working Paper Number:
CES-03-01
This paper presents a new equilibrium framework for analyzing economic and policy questions related to the sorting of households within a large metropolitan area. At its heart is a model describing the residential location choices of households that makes explicit the way that individual decisions aggregate to form a housing market equilibrium. The model incorporates choice-specific unobservables, and in the presence of these, a general strategy is provided for identifying household preferences over choice characteristics, including those that depend on household sorting such as neighborhood racial composition. We estimate the model using restricted access Census data that characterize the precise residential and employment locations of a quarter of a million households in the San Francisco Bay Area, yielding accurate measures of references for a wide variety of housing and neighborhood attributes across different types of household. The main economic analysis of the paper uses these estimates in combination with the equilibrium model to explore the causes and consequences of racial segregation in the housing market. Our results indicate that, given the preference structure of households in the Bay Area, the elimination of racial differences in income and wealth would significantly increase the residential segregation of each major racial group. Given the relatively small fractions of Asian, Black, and Hispanic households in the Bay Area (each ~10%), the elimination of racial differences in income/wealth (or, education or employment geography) spreads households in these racial groups much more evenly across the income distribution, allowing more racial sorting to occur at all points in the distribution ' e.g., leading to the formation of wealthy, segregated Black and Hispanic neighborhoods. The partial equilibrium predictions of the model, which do not account for the fact that neighborhood sociodemographic compositions and prices adjust as part of moving to a new equilibrium, lead to the opposite conclusion, emphasizing the value of the general equilibrium approach developed in the paper. Our analysis also provides evidence sorting on the basis of race itself (whether driven by preferences directly or discrimination) leads to large reductions in the consumption of public safety and school quality by all Black and Hispanic households, and large reductions in the housing consumption of upper-income Black and Hispanic households.View Full Paper PDF
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Working PaperWhat Drives Racial Segregation? New Evidence Using Census Microdata
October 2002
Working Paper Number:
CES-02-26
Residential segregation on the basis of race is widespread and has important welfare consequences. This paper sheds new light on the forces that drive observed segregation patterns. Making use of restricted micro-Census data from the San Francisco Bay Area and a new measurement framework, it assesses the extent to which the correlation of race with other household characteristics, such as income, education and immigration status, can explain a significant portion of observed racial segregation. In contrast to the findings of the previous literature, which has been hampered by serious data limitations, our analysis indicates that individual household characteristics can explain a considerable fraction of segregation by race. Taken together, we find that the correlation of race with other household attributes can explain almost 95 percent of segregation for Hispanic households, over 50 percent for Asian households, and approximately 30 percent for White and Black households. Our analysis also indicates that different factors drive the segregation of different races. Language explains a substantial proportion - more than 30 percent - of Asian and Hispanic segregation, education explains a further 20 percent of Hispanic segregation, while income is the most important non-race household characteristic for Black households, explaining around 10 percent of Black segregation.View Full Paper PDF
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