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Recalculating... : How Uncertainty in Local Labor Market Definitions Affects Empirical Findings
January 2017
Working Paper Number:
CES-17-49R
This paper evaluates the use of commuting zones as a local labor market definition. We revisit Tolbert and Sizer (1996) and demonstrate the sensitivity of definitions to two features of the methodology: a cluster dissimilarity cutoff, or the count of clusters, and uncertainty in the input data. We show how these features impact empirical estimates using a standard application of commuting zones and an example from related literature. We conclude with advice to researchers on how to demonstrate the robustness of empirical findings to uncertainty in the definition of commuting zones
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Two Perspectives on Commuting: A Comparison of Home to Work Flows Across Job-Linked Survey and Administrative Files
January 2017
Working Paper Number:
CES-17-34
Commuting flows and workplace employment data have a wide constituency of users including urban and regional planners, social science and transportation researchers, and businesses. The U.S. Census Bureau releases two, national data products that give the magnitude and characteristics of home to work flows. The American Community Survey (ACS) tabulates households' responses on employment, workplace, and commuting behavior. The Longitudinal Employer-Household Dynamics (LEHD) program tabulates administrative records on jobs in the LEHD Origin-Destination Employment Statistics (LODES). Design differences across the datasets lead to divergence in a comparable statistic: county-to-county aggregate commute flows. To understand differences in the public use data, this study compares ACS and LEHD source files, using identifying information and probabilistic matching to join person and job records. In our assessment, we compare commuting statistics for job frames linked on person, employment status, employer, and workplace and we identify person and job characteristics as well as design features of the data frames that explain aggregate differences. We find a lower rate of within-county commuting and farther commutes in LODES. We attribute these greater distances to differences in workplace reporting and to uncertainty of establishment assignments in LEHD for workers at multi-unit employers. Minor contributing factors include differences in residence location and ACS workplace edits. The results of this analysis and the data infrastructure developed will support further work to understand and enhance commuting statistics in both datasets.
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Has Falling Crime Invited Gentrification?
January 2017
Working Paper Number:
CES-17-27
Over the past two decades, crime has fallen dramatically in cities in the United States. We explore whether, in the face of falling central city crime rates, households with more resources and options were more likely to move into central cities overall and more particularly into low income and/or majority minority central city neighborhoods. We use confidential, geocoded versions of the 1990 and 2000 Decennial Census and the 2010, 2011, and 2012 American Community Survey to track moves to different neighborhoods in 244 Core Based Statistical Areas (CBSAs) and their largest central cities. Our dataset includes over four million household moves across the three time periods. We focus on three household types typically considered gentrifiers: high-income, college-educated, and white households. We find that declines in city crime are associated with increases in the probability that highincome and college-educated households choose to move into central city neighborhoods, including low-income and majority minority central city neighborhoods. Moreover, we find little evidence that households with lower incomes and without college degrees are more likely to move to cities when violent crime falls. These results hold during the 1990s as well as the 2000s and for the 100 largest metropolitan areas, where crime declines were greatest. There is weaker evidence that white households are disproportionately drawn to cities as crime falls in the 100 largest metropolitan areas from 2000 to 2010.
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Local Labor Demand and Program Participation Dynamics
November 2016
Working Paper Number:
carra-2016-10
Estimates the effect of fluctuations in local labor conditions on the likelihood that existing participants are able to transition out of the Supplemental Nutrition Assistance Program (SNAP). Our primary data are SNAP administrative records from New York (2007-2012) linked to the 2010 Census at the person-level. We further augment these data by linking to industry-specific labor market indicators at the county-level. We find that local labor markets matter for the length of time individuals spend on SNAP, but there is substantial heterogeneity in estimated effects across local industries. While employment growth in industries with small shares of SNAP participants has no impact on SNAP exits, growth in local industries with creases the likelihood that recipients exit the program. We also observe corresponding increases in entries when these industries experience localized contractions. Notably, estimated industry effects vary across race groups and parental status, with Black Alone non-Hispanic, Hispanic, and mothers benefiting the least from improvements in local labor market conditions.
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The Effect of Low-Income Housing on Neighborhood Mobility:
Evidence from Linked Micro-Data
May 2016
Working Paper Number:
carra-2016-02
While subsidized low-income housing construction provides affordable living conditions for poor households, many observers worry that building low-income housing in poor communities induces individuals to move to poor neighborhoods. We examine this issue using detailed, nationally representative microdata constructed from linked decennial censuses. Our analysis exploits exogenous variation in low-income housing supply induced by program eligibility rules for Low-Income Housing Tax Credits to estimate the effect of subsidized housing on neighborhood mobility patterns. The results indicate little evidence to suggest a causal effect of additional low-income housing construction on the characteristics of neighborhoods to which households move. This result is true for households across the income distribution, and supports the hypothesis that subsidized housing provides affordable living conditions without encouraging households to move to less-affluent neighborhoods than they would have otherwise.
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Black Pioneers, Intermetropolitan Movers, and Housing Desegregation
March 2016
Working Paper Number:
CES-16-23
In this project, we examine the mobility choices of black households between 1960 and 2000. We use household-level Decennial Census data geocoded down to the census tract level. Our results indicate that, for black households, one's status as an intermetropolitan migrant ' especially from an urban area outside the South ' is a powerful predictor of pioneering into a white neighborhood. Moreover, and perhaps even more importantly, the ratio of these intermetropolitan black arrivals to the incumbent metropolitan black population is a powerful predictor of whether a metropolitan area experiences substantial declines in housing segregation.
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Structural versus Ethnic Dimensions of Housing Segregation
March 2016
Working Paper Number:
CES-16-22
Racial residential segregation is still very high in many American cities. Some portion of segregation is attributable to socioeconomic differences across racial lines; some portion is caused by purely racial factors, such as preferences about the racial composition of one's neighborhood or discrimination in the housing market. Social scientists have had great difficulty disaggregating segregation into a portion that can be explained by interracial differences in socioeconomic characteristics (what we call structural factors) versus a portion attributable to racial and ethnic factors. What would such a measure look like? In this paper, we draw on a new source of data to develop an innovative structural segregation measure that shows the amount of segregation that would remain if we could assign households to housing units based only on non-racial socioeconomic characteristics. This inquiry provides vital building blocks for the broader enterprise of understanding and remedying housing segregation.
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Changes in Neighborhood Inequality, 2000-2010
March 2016
Working Paper Number:
CES-16-18
Recent work has suggested that higher income inequality may be a desirable attribute of a neighborhood in that it represents diversity, even though high (and rising) inequality appears to be detrimental to the nation as a whole. The research reported here has determined the key characteristics of a census tract that are associated with the level of inequality in 2000 or 2010, and those associated with changes in income inequality between 2000 and 2010. For the change, the strongest influence is a negative effect for the level of income inequality in 2000; that is, higher income inequality in 2000 leads to a decline over the decade, ceteris paribus. Neighborhoods with higher proportions or levels of the following population and housing characteristics tend to have both higher income inequality and a larger increase in income inequality between 2000 and 2010: individuals in poverty, those with a bachelor's degree, older individuals, householders living alone, and median rent, and lower median housing value and household income. Among these, perhaps the most important determinant is the percent in poverty in 2000. Furthermore, as the baseline level of demographic and economic diversity increases, the better the baseline and change characteristics explain the change in the Gini index from 2000 to 2010.
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Urban-Suburban Migration in the United States, 1955-2000
February 2016
Working Paper Number:
CES-16-08
This study uses census microdata from 1960 to 2010 to look at the rates of suburbanization in the 100 largest metro areas. Looking at the racial and ethnic composition of the population, and then further breaking down these groups by income, it's clear that more affluent people were more likely to move to the suburbs. Also, the White non-Hispanic population has long been the most suburbanized group. A majority of the White population lived in suburbs by 1960 in the 100 largest metro areas, while most of the Black non-Hispanic population lived in urban core areas as late as 2000. The Hispanic and Asian populations went from majority urban to majority suburban during this period.
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The Impact of Immigration on the Labor Market Outcomes of Native Workers: Evidence using Longitudinal Data from the LEHD
January 2016
Working Paper Number:
CES-16-56
Empirical estimates of the effect of immigration on native workers that rely on spatial comparisons have generally found small effects, but have been subject to the criticism that out-migration by native workers dampens the observed effect by spreading it over a larger area. In contrast, studies that rely on variation in immigration across industries, occupations, or education-based skill-levels often report large negative effects, but rely primarily on repeated cross-sectional data sets which also cannot account for the adjustment of native workers over time. In this paper, we use a newly available data set, the Longitudinal Employer Household Data (LEHD), which provides quarterly earnings records, geographic location, and firm and industry identifiers for 97% of all privately employed workers in 29 states. We use this data to analyze the impact of immigration on earnings changes and the mobility response of native workers. Overall, we find that although immigration has a negative effect on the earnings and employment of native workers, and positive effects on their firm, industry, and cross-state mobility, the overall size of the effects is small.
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