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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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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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Interactions, Neighborhood Selection, and Housing Demand
August 2002
Working Paper Number:
CES-02-19
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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Leaving Home: Modeling the Effect of Civic and Economic Structure on Individual Migration Patterns
June 2002
Working Paper Number:
CES-02-16
This research analyzes the effect of community structure upon individuals' probabilities of moving between 1985 and 1990. Using the full Census sample long form microdata for 1990, we re-allocate adult persons in 1990 to their 1985 county of residence. Then, using origin county macro-structural variables (derived from the Economic Census microdata) and individual characteristics (from Decennial Census microdata), we develop a two level hierarchical linear model. In level 1, we construct a logistic equation modeling individual probabilities of moving. In level 2, we model the contextual effects of origin community structure on these models. These contextual effects fall into two categories: 1) economic conditions that comprise the usual aggregate 'push' factors and 2) civic community factors that act to retain people in their community. Results specify the relationship between community context and individual migration patterns, and demonstrate effects of local economic structure and local civic structure on these individual probabilities. Most notably, we find that civic attributes of communities are associated with a propensity to stay in place, net of community economic factors and individual characteristics.
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Civic Community in Small-Town America: How Civic Welfare is Influenced by Local Capitalism and Civic Engagement
December 2001
Working Paper Number:
CES-01-19
The aims of this paper are twofold: first, to gain a fuller understanding of factors that foster community cohesion and contribute to the residents' social and economic well-being; and, second, to move beyond previous research that used larger spatial units such as states, counties, or aggregates of counties and to focus instead on American small towns (population 2,500-20,000). The data on small towns are drawn from public-use files and from confidential microdata from various economic censuses. From these sources we construct measures of locally oriented firms, self-employment, business establishments that serve as gathering places, and associations. The local capitalism and civic engagement variables generally perform as hypothesized; in some cases they are related quite strongly to civic welfare outcomes such as income levels, poverty rates, and nonmigration rates. We discuss the advantages and disadvantages of working with place-level data and suggest some strategies for subsequent work on small towns and other incorporated places.
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The Utilization of Different Modes of Residence and Health Services by the Elderly
December 2001
Working Paper Number:
CES-01-14
Demand for health services are examined among Americans ages 65 and older using the Medical Expenditure Panel Survey. Analyses are provided of mode of residence, demand for paid health services in private settings, and the choice of type of nursing home using a common set of explanatory variables. The research shows that age, Medicare coverage, and the use of assistive technology are the strongest predictors of mode of residence. The second analysis shows that total expenditures for paid home health care (HHC) and hospital care do not decrease as expected when the percentage paid by individuals and/or their families increases. Finally, the third analysis suggests that the distribution of nursing home (NH) services is related to ability to pay.
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