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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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Stability and Change in Individual Determinants of Migration: Evidence from 1985-1990 and 1995 to 2000
November 2006
Working Paper Number:
CES-06-27
In this paper, we compare the reliability of migration estimates from two rather different macroeconomic periods in recent U.S. history. One of these periods, 1985-1990 coincides with the culmination of a vast industrial restructuring which saw a significant decline in manufacturing employment. The other period, 1995-2000, encompasses a time of robust economic growth and tight labor markets driven by productivity gains associated with new technologies. Our interest here is in the stability of common individual-level predictors of migration in these rather disparate macroeconomic contexts. Using confidential internal versions of the 1990 and 2000 Census long-form data, we estimate logistic models of the likelihood that individuals will migrate. The geographic detail in the internal Census data permits us to measure migration in ways that are not possible with public-domain Census data on persons. We develop migration definitions that distinguish between local residential mobility likely associated with life course transitions from migration out of the labor market area that may be driven more by employment and other socioeconomic considerations. Using logistic modeling, we find that the same individual attributes predict migration reasonably well during both periods. We also compute some illustrative probabilities of migration that show temporal stability in migration predictors could be lessened by certain changes in population composition.
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What Has Been Capitalized into Property Values: Human Capital, Social Capital, or Cultural Capital?
October 2005
Working Paper Number:
CES-05-25
Urban amenities can be capitalized into land values or property values. However, little attention has been paid to the capitalization of social amenities. This paper classifies three types of social-interaction-based social amenities: human capital, social capital, and cultural capital at residential neighborhood levels. We use the restricted version of the 1990 Massachusetts Census data and estimate hedonic housing models with social amenities. The findings are as follows: (1) Human capital has significant positive effects on property values. This tests the Lucas conjecture. (2) Different types of social capital have different effects on property values: an increase in the percentage of new residents has significant positive effects on property values, probably due to the strength of weak ties. However, an increase in the percentage of single-parent households has negative effects on property values. An increase in the home ownership rate has positive effects at large geographic levels. (3) Cultural capital effects vary from high to low geographic levels, the effects of English proficiency and racial homogeneity are positive at and beyond the tract level, but insignificant at the block level. This may imply that cultural capital is more important in social interactions at large geographic scale.
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Place 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.
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Poverty Estimates for Places in the United States
September 2005
Working Paper Number:
CES-05-12
This paper first describes some historical poverty trends, overall and for demographic groups and broad locations within the U.S. from an ongoing household survey, and then presents some specific information on poverty for localities by size, from the most recent decennial census (2000). Rural poverty exceeded urban poverty in 1969 and 1979, but urban poverty in 1999 was higher than rural poverty. Non-metropolitan area poverty exceeded metropolitan area poverty in each of the four censuses, but within each of those areas, rural poverty is now less than urban poverty. Within metropolitan areas, poverty is highest for those in central cities. For urbanized areas (50,000 or more population), the poverty rate is lower as the area gets larger, with the exception of the very largest-sized areas. This higher poverty for the largest places is accounted for entirely by the higher poverty rate for the central city or cities in those urban agglomerations, as the poverty rates for the parts of the urbanized areas not in the central place continue to fall as the area itself gets larger. Some of the critical relationships affecting the poverty rate of places appear to be the location of certain types of people - female householders, non-citizens, people of color, and college graduates.
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Is the Melting Pot Still Hot? Explaining the Resurgence of Immigrant Segregation
August 2004
Working Paper Number:
CES-04-10
This paper uses decennial Census data to examine trends in immigrant segregation in the United States between 1910 and 2000. Immigrant segregation declined in the first half of the century, but has been rising steadily over the past three decades. Analysis of restricted access 1990 Census microdata suggests that this rise would be even more striking if the native-born children of immigrants could be consistently excluded from the analysis. We analyze panel and cross-sectional variation in immigrant segregation, as well as housing price patterns across metropolitan areas, to test four hypotheses of immigrant segregation. Immigration itself has surged in recent decades, but the tendency for newly arrived immigrants to be younger and of lower socioeconomic status explains very little of the recent rise in immigrant segregation. We also find no evidence of increased nativism in the housing market. Evidence instead points to changes in urban form, particularly the tendency for ethnic enclaves to form as suburbanizing households leave older neighborhoods, as a central explanation for the new immigrant segregation.
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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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Pollution Abatement Expenditure by U.S. Manufacturing Plants: Do Community Characteristics Matter?
November 2003
Working Paper Number:
CES-03-18
A number of previous studies have demonstrated the impact of community characteristics on environmental outcomes such as local pollution levels and the siting of noxious facilities. If certain groups are indeed exposed to higher levels of air pollution, it may be due to a greater concentration of air polluters in those communities and/or facilities in those areas investing less in air pollution abatement. This paper examines the latter, using establishment-level data on manufacturing plants from the U.S. Census Bureau'''s Pollution Abatement Costs and Expenditures (PACE) survey. The empirical formulation herein allows plant-level air pollution abatement operating costs to depend on an array of community characteristics common to this literature. After controlling for establishment characteristics and federal, state, and local regulation, some of these local factors are found to have had an additional effect on air pollution abatement expenditures. In particular, populations with higher homeownership rates and higher per capita income enjoyed greater pollution abatement activity from their nearby plants. Meanwhile, establishments in communities where manufacturing accounted for a greater share of local employment had less pollution abatement spending, suggesting a local constituency that is more resistant to additional regulation. Political ideology is also found to play a role, with plants in areas with larger concentrations of Democrats having more expenditure on air pollution abatement, all else being equal. There is little evidence that race and ethnicity matter when it comes to the pollution abatement behavior of the most pollution-intensive facilities. The findings of this paper support those of a number of recent studies.
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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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What 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.
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