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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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Consequences of the Clean Water Act and the Demand for Water Quality
January 2017
Working Paper Number:
CES-17-07
Since the 1972 U.S. Clean Water Act, government and industry have invested over $1 trillion to abate water pollution, or $100 per person-year. Over half of U.S. stream and river miles, however, still violate pollution standards. We use the most comprehensive set of files ever compiled on water pollution and its determinants, including 50 million pollution readings from 170,000 monitoring sites, to study water pollution's trends, causes, and welfare consequences. We have three main findings. First, water pollution concentrations have fallen substantially since 1972, though were declining at faster rates before then. Second, the Clean Water Act's grants to municipal wastewater treatment plants caused some of these declines. Third, the grants' estimated effects on housing values are generally smaller than the grants' costs.
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Redistribution of Local Labor Market Shocks through Firms' Internal Networks
January 2017
Working Paper Number:
CES-17-03
Local labor market shocks are difficult to insure against. Using confidential micro data from the U.S. Census Bureau's Longitudinal Business Database, we document that firms redistribute the employment impacts of local demand shocks across regions through their internal networks of establishments. During the Great Recession, the massive decline in house prices caused a sharp drop in consumer demand, leading to large employment losses in the non-tradable sector. Consistent with firms smoothing out the impacts of these shocks across regions, we find large elasticities of non-tradable establishment-level employment with respect to house prices in other counties in which the firm has establishments. At the same time, establishments of firms with larger regional networks exhibit lower employment elasticities with respect to local house prices in the establishment's own county. To account for general equilibrium adjustments, we aggregate non-tradable employment at the county level. Similar to what we found at the establishment level, we find that non-tradable county-level employment responds strongly to local demand shocks in other counties linked through firms' internal networks. These results are not driven by direct demand spillovers from nearby counties, common shocks to house prices, or local demand shocks affecting non-tradable employment in distant counties indirectly via the trade channel. Our results suggest that firms play an important role in the extent to which local labor market risks areshared across regions.
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Small Business Growth and Failure during the Great Recession: The Role of House Prices, Race & Gender
November 2016
Working Paper Number:
carra-2016-08
Using 2002-2011 data from the Longitudinal Business Database linked to the 2002 and 2007 Survey of Business Owners, this paper explores whether (through a collateral channel) the rise in home prices over the early 2000's and their subsequent fall associated with the Great Recession had differential impacts on business performance across owner race, ethnicity and gender. We find that the employment growth rate of minority-owned firms, particularly black and Hispanic-owned firms, is more sensitive to changes in house prices than is that of their nonminority-owned counterparts.
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Evaluating the Use of Commercial Data to Improve Survey Estimates of Property Taxes
August 2016
Working Paper Number:
carra-2016-06
While commercial data sources offer promise to statistical agencies for use in production of official statistics, challenges can arise as the data are not collected for statistical purposes. This paper evaluates the use of 2008-2010 property tax data from CoreLogic, Inc. (CoreLogic), aggregated from county and township governments from around the country, to improve 2010 American Community Survey (ACS) estimates of property tax amounts for single-family homes. Particularly, the research evaluates the potential to use CoreLogic to reduce respondent burden, to study survey response error and to improve adjustments for survey nonresponse. The research found that the coverage of the CoreLogic data varies between counties as does the correspondence between ACS and CoreLogic property taxes. This geographic variation implies that different approaches toward using CoreLogic are needed in different areas of the country. Further, large differences between CoreLogic and ACS property taxes in certain counties seem to be due to conceptual differences between what is collected in the two data sources. The research examines three counties, Clark County, NV, Philadelphia County, PA and St. Louis County, MO, and compares how estimates would change with different approaches using the CoreLogic data. Mean county property tax estimates are highly sensitive to whether ACS or CoreLogic data are used to construct estimates. Using CoreLogic data in imputation modeling for nonresponse adjustment of ACS estimates modestly improves the predictive power of imputation models, although estimates of county property taxes and property taxes by mortgage status are not very sensitive to the imputation method.
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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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Externalities of Public Housing: The Effect of Public Housing Demolitions on Local Crime
March 2016
Working Paper Number:
CES-16-16
This paper evaluates the potential for negative externalities from public housing by examining crime rates before and after demolition of public housing projects in Chicago between 1995 and 2010. Using data on block-level crimes by type of crime merged to detailed geographic data on individual public housing demolitions, I find evidence that Chicago's public housing imposed significant externalities on the surrounding neighborhood. Using a difference in difference approach comparing neighborhoods around public housing projects to nearby neighborhoods I find that crime decreases by 8.8% after a demolition. This decrease is concentrated in violent crime. I use an event study to show that the decrease occurs at the approximate date of the eviction of the residents and persists for at least 5 years after the demolition. Neighborhoods with large demolitions and demolitions of public housing that had been poorly maintained display the largest crime decreases.
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