This paper examines the effect of property rights on economic development within local labor markets, including how property rights change the equilibrium response to place-based policies. It does so in the context of federally recognized American Indian reservations, where a fraction of the land is held in trust by the US federal government and associated with restrictions on transactions. I find that incomplete property rights on reservations are responsible for lower wages and higher levels of unemployment. The direction of these findings is robust to an instrumental variables approach to dealing with the endogeneity of property rights. Next I shed light on the extent to which place-based policies can improve economic outcomes on reservations. I use a spatial equilibrium framework to study the incidence of casino adoption, a place-based policy unique to reservations. The key insight from the model is that incomplete property rights impose frictions in the housing market that lower the migration response to casino adoption, improving the likelihood that the local population benefits. Consistent with the model's predictions, I find that casino adoption raises average wages and that the wage effect is greater on reservations with more land in trust. My estimates suggest that wage increases correspond to welfare improvements. This paper provides insights into how place-based policies and property rights jointly shape economic outcomes through changes in the labor market, the housing market, and the mobility of workers.
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Earnings Through the Stages: Using Tax Data to Test for Sources of Error in CPS ASEC Earnings and Inequality Measures
September 2024
Working Paper Number:
CES-24-52
In this paper, I explore the impact of generalized coverage error, item non-response bias, and measurement error on measures of earnings and earnings inequality in the CPS ASEC. I match addresses selected for the CPS ASEC to administrative data from 1040 tax returns. I then compare earnings statistics in the tax data for wage and salary earnings in samples corresponding to seven stages of the CPS ASEC survey production process. I also compare the statistics using the actual survey responses. The statistics I examine include mean earnings, the Gini coefficient, percentile earnings shares, and shares of the survey weight for a range of percentiles. I examine how the accuracy of the statistics calculated using the survey data is affected by including imputed responses for both those who did not respond to the full CPS ASEC and those who did not respond to the earnings question. I find that generalized coverage error and item nonresponse bias are dominated by measurement error, and that an important aspect of measurement error is households reporting no wage and salary earnings in the CPS ASEC when there are such earnings in the tax data. I find that the CPS ASEC sample misses earnings at the high end of the distribution from the initial selection stage and that the final survey weights exacerbate this.
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The Racial and Ethnic Composition of Local Government Employees in Large Metro Areas, 1960-2010
August 2013
Working Paper Number:
CES-13-38
This study uses census microdata from 1960 to 2010 to look at how the racial and ethnic composition of local government employees has reflected the diversity of the general population in the 100 largest metro areas over the last half century. Historically, one route to upward social mobility has been employment in local government. This study uses microdata that predates key immigration and civil rights legislation of the 1960s through to the present to examine changes in the racial and ethnic composition of local government employees and in the general population. For this study, local government employees have been divided into high- and low-wage occupations. These data indicate that local workforces have grown more diverse over time, though representation across different racial and ethnic groups and geographic areas is uneven. African-Americans were underrepresented in high-wage local government employment and overrepresented in low-wage jobs in the early years of this study, particularly in the South, but have since become proportionally represented in high-wage jobs on a national level. In contrast, the most recent data indicate that Hispanic and other races are underrepresented in this employment group, particularly in the West. Though the numbers of Hispanic and Asian high-wage local government employees are increasing, it appears that it will take several years for those groups to achieve proportional representation throughout the United States.
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"It's Not You, It's Me": Breakup In U.S.-China Trade Relationships
February 2014
Working Paper Number:
CES-14-08
This paper uses confidential U.S. Customs data on U.S. importers and their Chinese exporters toinvestigate the frictions from changing exporting partners. High costs from switching partners can affect the efficiency of buyer-supplier matches by impeding the movement of importers from high to lower cost exporters. I test the significance of this channel using U.S. import data, which identifies firms on both sides (U.S. and foreign) of an international trade relationship, the location of the foreign supplier, and values and quantities for the universe of U.S. import transactions. Using transactions with China from 2003-2008, I find evidence suggesting that barriers to switching exporters are considerable: 45% of arm's-length importers maintain their partner from one year to the next, and one-third of all switching importers remain in the same city as their original partner. In addition, importers paying the highest prices are the most likely to change their exporting partner. Guided by these empirical regularities, I propose and structurally estimate a dynamic discrete choice model of exporter choice, embedded in a heterogeneous firm model of international trade. In the model, importing firms choose a future partner using information for each choice, but are subject to partner and location-specific costs if they decide to switch their current partner. Structural estimates of switching costs are large, and heterogeneous across industries. For the random sample of 50 industries I use, halving switching costs shrinks the fraction of importers remaining with their partner from 57% to 18%, and this improvement in match efficiency leads to a 12.5% decrease in the U.S.-China Import Price Index.
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Receipt of Public and Private Food Assistance Across the Rural-Urban Continuum Before and During the COVID-19 Pandemic: Analysis of Current Population Survey Data
August 2025
Working Paper Number:
CES-25-51
Background: The nutrition safety net in the United States is critical to supporting food security among households in need. Food assistance in the United States includes both government-funded food programs and private community-based providers who distribute food to in need households. The COVID-19 pandemic impacted experiences of food security and use of private and public food assistance resources. However, this may have differed for households residing in urban versus rural areas. We explored receipt of Supplemental Nutrition Assistance Program (SNAP) benefits or food from community-based emergency food providers across a detailed measure of the rural-urban continuum before and during the COVID-19 pandemic.
Methods: We linked restricted use Current Population Survey Food Security Supplement data to census-tract level United States Department of Agriculture Rural-Urban Commuting Area codes to estimate prevalence of self-reported SNAP participation and receipt of emergency food support across temporal (2015-2019 versus 2020-2021) and socio-spatial (urban, large rural city/town, small rural town, or isolated rural town/area) dimensions. We report prevalences as point estimates with 95% confidence intervals, all weighted for national representation.
Results:
The weighted prevalence of self-reported SNAP participation was 8.9% (8.7-9.2%) in 2015-2019 and 9.1% (8.5-9.5%) in 2020-2021 in urban areas, 11.4% (10.8-12.2%) in 2015-2019 and 11.6% (10.5-12.9%) in 2020-2021 in large rural towns/cities, 13.4% (12.3-14.6%) in 2015-2019 and 12.3% (10.5-14.5%) in 2020-2021 in small rural towns, and 9.7% (8.6-10.9%) in 2015-2019 and 10.9% (8.8-13.4% )in 2020-2021 isolated rural towns. The weighted prevalence of self-reported receipt of emergency food was 4.9% (4.8-5.1%) in 2015-2019 and 6.2% (5.8-6.5%) in 2020-2021 in urban areas, 6.8% (6.2-7.4%) in 2015-2019 and 7.6% (6.6-8.6%) in 2020-2021 in large rural towns/cities, 8.1% (7.3-9.1%) in 2015-2019 and 7.1% (5.7-8.8%) in 2020-2021 in small rural towns, and 6.8% (5.9-7.7%) in 2015-2019 and 8.5% (6.7-10.6%) in 2020-2021 isolated rural towns.
Conclusion: Households in rural communities use public and private food assistance at higher rates than urban areas, but there is variation across communities depending on the level of rurality.
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Testing the Advantages of Using Product Level Data to Create Linkages Across Industrial Coding Systems
October 1993
Working Paper Number:
CES-93-14
After the major revision of the U.S. Standard Industrial Classification system (SIC) in the 1987, the problem arose of how to evaluate industrial performance over time. The revision resulted in the creation of new industries, the combination of old industries, and the remixing of other industries to better reflect the present U.S. economy. A method had to be developed to make the old and new sets of industries comparable over time. Ryten (1991) argues for performing the conversion at the "most micro level," the product level. Linking industries should be accomplished by reclassifying product data of each establishment to a standard system, reassigning the primary activity of the establishment, reaggregating the data to the industry level, and then making the desired statistical comparison (Ryten, 1991). This paper discusses linking the data at the very micro, product level, and at the more macro, industry level. The results suggest that with complete product information the product level conversion is preferable for most industries in manufacturing because it recognizes that establishments may switch their primary industry because of the conversion. For some industries, especially those having no substantial changes in SIC codes over time, the conversion at the industry level is fairly accurate. A small group of industries lacks complete product information in 1982 to link the 1982 product codes to the 1987 codes. This results in having to rely on the industry concordance to create a time series of statistics.
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The Transformation of Self Employment
February 2022
Working Paper Number:
CES-22-03
Over the past half-century, while self-employment has consistently accounted for around one in ten of the United States workforce, its composition has changed. Since 1970, industries with high startup capital requirements have declined from 53% of self-employment to 23%. This same time period also witnessed declines in 'hometown' local entrepreneurship and the probability of the self-employed being among top earners. Using 2016 data, we show that high startup capital requirements are linked with lower profitability at small scales. The transition away from high startup capital industries appears most closely linked to changes in small business production functions and less due to advantageous reallocation to other opportunities, growth in returns-to-scale among large businesses, or a worsening of financing conditions and debt levels.
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An Alternative Theory of the Plant Size Distribution with an Application to Trade
May 2010
Working Paper Number:
CES-10-10
There is wide variation in the sizes of manufacturing plants, even within the most narrowly defined industry classifications used by statistical agencies. Standard theories attribute all such size differences to productivity differences. This paper develops an alternative theory in which industries are made up of large plants producing standardized goods and small plants making custom or specialty goods. It uses confidential Census data to estimate the parameters of the model, including estimates of plant counts in the standardized and specialty segments by industry. The estimated model fits the data relatively well compared with estimates based on standard approaches. In particular, the predictions of the model for the impacts of a surge in imports from China are consistent with what happened to U.S. manufacturing industries that experienced such a surge over the period 1997'2007. Large-scale standardized plants were decimated, while small-scale specialty plants were relatively less impacted.
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Whose Neighborhood Now? Gentrification and Community Life in Low-Income Urban Neighborhoods
June 2024
Working Paper Number:
CES-24-29
Gentrification is a process of urban change that has wide-ranging social and political impacts, but previous studies provide divergent findings. Does gentrification leave residents feeling alienated, or does it bolster neighborhood social satisfaction? Politically, does urban change mobilize residents, or leave them disengaged? I assess a national, cross-sectional sample of about 17,500 respondents in lower-income urban neighborhoods, and use a structural equation modeling approach to model six latent variables pertaining to local social environment and political participation. Amongst the full sample, gentrification has a positive association with all six factors. However, this relationship depends upon respondents' level of income, length of residency, and racial identity. White residents and those with shorter length of residency report higher levels of social cohesion as gentrification increases, but there is no such association amongst racial minority groups and longer-term residents. This finding aligns with a perspective on gentrification as a racialized process, and demonstrates that gentrification-related amenities primarily serve the interests of white residents and newcomers. All groups, however, are more likely to participate in neighborhood politics as gentrification increases, drawing attention to the agency of local residents as they attempt to influence processes of urban change.
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The Worker-Establishment Characteristics Database
June 1995
Working Paper Number:
CES-95-10
A data set combining information on the characteristics of both workers and their employers has long been a grail for labor economists. The reason for this interest is that while a number of theoretical models in labor economics stress the importance of employer-employee matching in determining labor market outcomes, almost all empirical work relies on either worker surveys with little information about employers or establishment surveys with little information about workers. The Worker-Establishment Characteristic Database (WECD) represents just such an employer-employee-matched database. Containing 199,557 manufacturing workers matched to 16,144 manufacturing establishments, the WECD is the largest worker-firm matched data set available for the U.S. This paper describes how this data set was constructed and assesses the usefulness of these data for economic research. In addition, I discuss some of the issues that can be addressed using employer-employee-matched data and plans for creating future versions of the WECD.
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EXPANDING THE ROLE OF SYNTHETIC DATA AT THE U.S. CENSUS BUREAU
February 2014
Working Paper Number:
CES-14-10
National Statistical offices (NSOs) create official statistics from data collected from survey respondents, government administrative records and other sources. The raw source data is usually considered to be confidential. In the case of the U.S. Census Bureau, confidentiality of survey and administrative records microdata is mandated by statute, and this mandate to protect confidentiality is often at odds with the needs of users to extract as much information from the data as possible. Traditional disclosure protection techniques result in official data products that do not fully utilize the information content of the underlying microdata. Typically, these products take the form of simple aggregate tabulations. In a few cases anonymized public- use micro samples are made available, but these face a growing risk of re-identification by the increasing amounts of information about individuals and firms available in the public domain. One approach for overcoming these risks is to release products based on synthetic data where values are simulated from statistical models designed to mimic the (joint) distributions of the underlying microdata. We discuss re- cent Census Bureau work to develop and deploy such products. We discuss the benefits and challenges involved with extending the scope of synthetic data products in official statistics.
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