This paper contributes to the growing literature that identifies and measures the impact of social context on individual economic behavior. We develop a model of housing demand with neighborhood e'ects and neighborhood choice. Modelling neighborhood choice is of fundamental importance in estimating and understanding endogenous and exogenous neighborhood effects. That is, to obtain unbiased estimates of neighborhood effects, it is necessary to control for non-random sorting into neighborhoods. Estimation of the model exploits a unique data set of household data that has been augmented with contextual information at two di'erent levels ('scales') of aggregation. One is at the neighborhood cluster level, of about ten neighbors, with the data coming from a special sample of the American Housing Survey. A second level is the census tract to which these dwelling units belong. Tract-level data are available in the Summary Tape Files of the decennial Census data. We merge these two data sets by gaining access to confidential data of the U.S. Bureau of the Census. We overcome some limitations of these data by implementing some significant methodological advances in estimating discrete choice models. Our results for the neighborhood choice model indicate that individuals prefer to live near others like themselves. This can perpetuate income inequality since those with the best opportunities at economic success will cluster together. The results for the housing demand equation are similar to those in our earlier work [Ioannides and Zabel (2000] where we find evidence of significant endogenous and contextual neighborhood effects.
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Location, Location, Location: The 3L Approach to House Price Determination
May 2004
Working Paper Number:
CES-04-06
The immobility of houses means that their location affects their values. This explains the common belief that three things determine the price of a house: location, location, and location. We use this notion to develop the 3L Approach to house price determination. That is, prices are determined by the Metropolitan Statistical Area (MSA), town, and street where the house is located. This study creates a unique data set based on data from the American Housing Survey (AHS) consisting of small 'clusters' of housing units with information on their housing characteristics and resident characteristics that is merged with census tract-level attributes. We use this data to verify the 3L Approach: we find that all three levels of location are significant when estimating the house price hedonic equation. This indicates that individuals care about their local neighborhood, i.e. the general upkeep of their street and possibly their neighbors' characteristics (cluster variables), a broader area such as the school district and/or the town (tract variables) that account for school quality and crime rates, and the particular amenities found in their MSA.
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Estimation and Inference in Regression Discontinuity Designs with Clustered Sampling
August 2015
Working Paper Number:
carra-2015-06
Regression Discontinuity (RD) designs have become popular in empirical studies due to their attractive properties for estimating causal effects under transparent assumptions. Nonetheless, most popular procedures assume i.i.d. data, which is not reasonable in many common applications. To relax this assumption, we derive the properties of traditional non-parametric estimators in a setting that incorporates potential clustering at the level of the running variable, and propose an accompanying optimal-MSE bandwidth selection rule. Simulation results demonstrate that falsely assuming data are i.i.d. when selecting the bandwidth may lead to the choice of bandwidths that are too small relative to the optimal-MSE bandwidth. Last, we apply our procedure using person-level microdata that exhibits clustering at the census tract level to analyze the impact of the Low-Income Housing Tax Credit program on neighborhood characteristics and low-income housing supply.
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Networking Off Madison Avenue
October 2005
Working Paper Number:
CES-05-15
This paper examines the effect on productivity of having more near advertising agency neighbors and hence better opportunities for meetings and exchange within Manhattan. We will show that there is extremely rapid spatial decay in the benefits of having more near neighbors even in the close quarters of southern Manhattan, a finding that is new to the empirical literature and indicates our understanding of scale externalities is still very limited. The finding indicates that having a high density of commercial establishments is important in enhancing local productivity, an issue in Lucas and Rossi-Hansberg (2002), where within business district spatial decay of spillovers plays a key role. We will argue also that in Manhattan advertising agencies trade-off the higher rent costs of being in bigger clusters nearer 'centers of action', against the lower rent costs of operating on the 'fringes' away from high concentrations of other agencies. Introducing the idea of trade-offs immediately suggests heterogeneity is involved. We will show that higher quality agencies are the ones willing to pay more rent to locate in greater size clusters, specifically because they benefit more from networking. While all this is an exploration of neighborhood and networking externalities, the findings relate to the economic anatomy of large metro areas like New Yorkthe nature of their buzz.
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FALLING HOUSE PRICES AND LABOR MOBILITY: EVIDENCE FROM MATCHED EMPLOYER-EMPLOYEE DATA
August 2013
Working Paper Number:
CES-13-43
This study uses worker-level employment data from the U.S. Census Bureau to test whether falling home prices affect a worker's propensity to take a job in a different metropolitan area from where he is currently located. Using a sample of workers from the American Community Survey, I employ a within-MSA-time estimation that compares homeowners to renters in their propensities to relocate for jobs according to data from the Longitudinal Employer Household Dynamics database. This strategy allows me to disentangle the influence of house prices from that of other time-varying, location-specific shocks. Estimates show that homeowners who have experienced declines in the nominal value of their home are approximately 20% less likely to take a new job in a location outside of the metropolitan area that they currently live and work in, relative to an equivalent renter. This evidence is consistent with the hypothesis that housing lock-in has contributed to the decreased labor mobility of homeowners during the recent housing bust.
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Quality Sorting and Networking: Evidence from the Advertising Agency Industry
October 2005
Working Paper Number:
CES-05-16
This paper provides a model of knowledge sharing and networking among single unit advertising agencies and investigates the implications of this model in the presence of heterogeneity in agencies' quality. In a stylized screening model, we show that, under a modest set of assumptions, the separation outcome is a Pareto-undominated Nash equilibrium. That is, high quality agencies locate themselves in a high wage and rent area to sift out low quality agencies and guarantee their network quality. We identify a necessary condition for the separating equilibrium to exist and to reject the pooling equilibrium even in the presence of agglomeration economies from networking. We derive the maximum profit of an agency and show the condition has a directly testable implication in the empirical specification of the agency's profit function. We use a sample of movers'existing agencies that relocate among urban areas'in order to extract a predetermined measure of their quality prior to relocation. We estimate the parameters of the profit function, using the Census confidential establishment-level data, and show that the necessary condition for separation is met and that there is strong separation and sorting on quality among agencies in their location decisions.
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A 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.
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UNEMPLOYMENT DURATION AND GEOGRAPHIC MOBILITY: DO MOVERS FARE BETTER THAN STAYERS?
October 2014
Working Paper Number:
CES-14-41
This study uses a sample of unemployed workers constructed from the American
Community Survey and the LEHD database, to compare the unemployment durations of those who find subsequent employment by relocating to a metropolitan area outside of their originally observed residence, versus those who find employment in their original location. Results from a hazard analysis confirm the importance of many of the determinants of migration posited in the literature, such as age, education, and local labor market conditions. While simple averages and OLS estimates indicate that migrating for a new job reduces the probability of re-employment within a given time frame and lengthens the spell of unemployment in the aggregate, after controlling for selection into migration using an IV approach based on local house price changes, the results suggest that out-migrating for employment actually has a large and significant beneficial effect of shortening the time to re-employment. This implies that those who migrate for jobs in the data may be particularly disadvantaged in their ability to find employment and thus have a strong short-term incentive to relocate.
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An 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.
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Bright Minds, Big Rent: Gentrification and the Rising Returns to Skill
January 2016
Working Paper Number:
CES-16-36R
In 1980, Census data indicate, housing prices in large US cities rose with distance from the city center. By 2010, the relationship had reversed. We propose that this development can be traced to high-income households working longer hours. With little non-market time, proximity to work takes on added salience, leading high-income households to forgo suburban amenities and extending the gentrification trend beyond its 1970s niche status. In a tract-level data set covering the 27 largest US cities, years 1980-2010, we find support for our hypothesis. Using a Bartik-type demand shifter for skilled labor we find that full-time skilled workers favor centrality and the rising share in the population can account for the observed price changes in favor of the city center.
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Identifying 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.
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