This paper examines the empirical relationship between the probability a plant closes and the compensation paid to the employees in the plant. The paper uses data on over 6500 manufacturing plants from the LRD to estimate the market hedonic wage locus and the probability of plant failure. The empirical results reported in this paper indicate that the probability of plant failure is systematically related to the plant's market share, age, recent growth, and variable cost to revenue ratio. The market hedonic wage regression indicates that workers employed by multi-plant firms earn a positive compensating wage differential for the risk of plant closing but workers employed in single-plant firms do not. Additionally, the paper provides evidence on the general pattern of wage variation across heterogeneous employers. Establishment wage rates are significantly affected by plant size, age, geographic location, industry, capital intensity, and value added per worker.
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Interfirm Segregation and the Black/White Wage Gap
August 1996
Working Paper Number:
CES-96-06
This paper studies interfirm racial segregation in two newly developed firm-level databases. Within the representative MSA, we find that the interfirm distribution of black and white workers is close to what would be implied by the random assignment of workers to firms. However, we also find that black workers are systematically clustered in "black" employers where managers, owners, and customers are also black. These facts may be reconciled by the facts that a) there are not enough black employers to generate much segregation and that b) perhaps other difficult-to-identify forces serve to systematically integrate black and white workers. Finally, we find that the black/white wage gap is entirely a within-firm phenomenon, as blacks do not work in firms that pay low wages on average.
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Labor Productivity: Structural Change and Cyclical Dynamics
May 1998
Working Paper Number:
CES-98-07
A longstanding issue in empirical economics is the behavior of average labor productivity over the business cycle. This paper provides new insights into the cyclicality of aggregate productivity at the plant level as well as the role of reallocation across plants over the cycle. We find that plant-level productivity is even more procyclical than aggregate productivity because short-run reallocation yields a countercyclical contribution to labor productivity. At the plant level we find the cyclicality of productivity varies systematically with long-run employment growth. Over the course of the cycle, plants that are long-run downsizers exhibit significantly greater procyclicality of productivity than long-run upsizers. When we control for the direction of a cyclical shock, we find that the fall in productivity from an adverse magnitude than the fall in productivity from an equivalent adverse cyclical shock for long-run upsizers. We argue that these findings raise questions about one of the most popular explanations or procyclical productivity: changing factor utilization over the cycle.
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Granular Income Inequality and Mobility using IDDA: Exploring Patterns across Race and Ethnicity
November 2023
Working Paper Number:
CES-23-55
Shifting earnings inequality among U.S. workers over the last five decades has been widely stud ied, but understanding how these shifts evolve across smaller groups has been difficult. Publicly available data sources typically only ensure representative data at high levels of aggregation, so they obscure many details of earnings distributions for smaller populations. We define and construct a set of granular statistics describing income distributions, income mobility and con ditional income growth for a large number of subnational groups in the U.S. for a two-decade period (1998-2019). In this paper, we use the resulting data to explore the evolution of income inequality and mobility for detailed groups defined by race and ethnicity. We find that patterns identified from the universe of tax filers and W-2 recipients that we observe differ in important ways from those that one might identify in public sources. The full set of statistics that we construct is available publicly as the Income Distributions and Dynamics in America, or IDDA, data set.
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When Do Firms Shift Production Across States to Avoid Environmental Regulation?
December 2001
Working Paper Number:
CES-01-18
This paper examines whether a firm's allocation of production across its plants responds to the environmental regulation faced by those plants, as measured by differences in stringency across states. We also test whether sensitivity to regulation differs based on differences across firms in compliance behavior and/or differences across states in industry importance and concentration. We use Census data for the paper and oil industries to measure the share of each state in each firm's production during the 1967-1992 period. We use several measures of state environmental stringency and test for interactions between regulatory stringency and three factors: the firm's overall compliance rate, a Herfindahl index of industry concentration in the state, and the industry's share in the state economy. We find significant results for the paper industry: firms allocate smaller production shares to states with stricter regulations. This impact is concentrated among firms with low compliance rates, suggesting that low compliance rates are due to high compliance costs, not low compliance benefits. The interactions between stringency and industry characteristics are less often significant, but suggest that the paper industry is more affected by regulation where it is larger or more concentrated. Our results are weaker for the oil industry, reflecting either less opportunity to shift production across states or a greater impact of environmental regulation on paper mills.
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Alternative Measures of Income Poverty and the Anti-Poverty Effects of Taxes and Transfers
June 2005
Working Paper Number:
CES-05-08
The Census Bureau prepared a number of alternative income-based measures of poverty to illustrate the distributional impacts of several alternatives to the official measure. The paper examines five income variants for two different units of analysis (families and households) for two different assumptions about inflation (the historical Consumer Price Index and a 'Research Series' alternative that uses current methods) for two different sets of thresholds (official and a formula-based alternative base on three parameters). The poverty rate effects are analyzed for the total population, the distributional effects are analyzed using poverty shares, and the anti-poverty effects of taxes and transfers are analyzed using a percentage reduction in poverty rates. Suggestions for future research are included.
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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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Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net
October 2015
Working Paper Number:
CES-15-35
We examine the consequences of underreporting of transfer programs in household survey data for several prototypical analyses of low-income populations. We focus on the Current Population Survey (CPS), the source of official poverty and inequality statistics, but provide evidence that our qualitative conclusions are likely to apply to other surveys. We link administrative data for food stamps, TANF, General Assistance, and subsidized housing from New York State to the CPS at the individual level. Program receipt in the CPS is missed for over one-third of housing assistance recipients, 40 percent of food stamp recipients and 60 percent of TANF and General Assistance recipients. Dollars of benefits are also undercounted for reporting recipients, particularly for TANF, General Assistance and housing assistance. We find that the survey data sharply understate the income of poor households, as conjectured in past work by one of the authors. Underreporting in the survey data also greatly understates the effects of anti-poverty programs and changes our understanding of program targeting, often making it seem that welfare programs are less targeted to both the very poorest and middle income households than they are. Using the combined data rather than survey data alone, the poverty reducing effect of all programs together is nearly doubled while the effect of housing assistance is tripled. We also re-examine the coverage of the safety net, specifically the share of people without work or program receipt. Using the administrative measures of program receipt rather than the survey ones often reduces the share of single mothers falling through the safety net by one-half or more.
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Examining Multi-Level Correlates of Suicide by Merging NVDRS and ACS Data
January 2017
Working Paper Number:
CES-17-25
This paper describes a novel database and an associated suicide event prediction model that surmount longstanding barriers in suicide risk factor research. The database comingles person-level records from the National Violent Death Reporting System (NVDRS) and the American Community Survey (ACS) to establish a case-control study sample that includes all identified suicide cases, while faithfully reflecting general population sociodemographics, in sixteen USA states during the years 2005 2011. It supports a statistical model of individual suicide risk that accommodates person-level factors and the moderation of these factors by their community rates. Named the United States Multi-Level Suicide Data Set (US-MSDS), the database was developed outside the RDC laboratory using publicly available ACS microdata, and reconstructed inside the laboratory using restricted access ACS microdata. Analyses of the latter version yielded findings that largely amplified but also extended those obtained from analyses of the former. This experience shows that the analytic precision achievable using restricted access ACS data can play an important role in conducting social research, although it also indicates that publicly available ACS data have considerable value in conducting preliminary analyses and preparing to use an RDC laboratory. The database development strategy may interest scientists investigating sociodemographic risk factors for other types of low-frequency mortality.
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Capturing More Than Poverty: School Free and Reduced-Price Lunch Data and Household Income
December 2017
Working Paper Number:
carra-2017-09
Educational researchers often use National School Lunch Program (NSLP) data as a proxy for student poverty. Under NSLP policy, students whose household income is less than 130 percent of the poverty line qualify for free lunch and students whose household income is between 130 percent and 185 percent of the poverty line qualify for reduced-price lunch. Linking school administrative records for all 8th graders in a California public school district to household-level IRS income tax data, we examine how well NSLP data capture student disadvantage. We find both that there is substantial disadvantage in household income not captured by NSLP category data, and that NSLP categories capture disadvantage on test scores above and beyond household income.
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Estimating Trends in U.S. Income Inequality Using the Current Population Survey: The Importance of Controlling for Censoring
August 2008
Working Paper Number:
CES-08-25
Using internal and public use March Current Population Survey (CPS) data, we analyze trends in US income inequality (1975'2004). We find that the upward trend in income inequality prior to 1993 significantly slowed thereafter once we control for top coding in the public use data and censoring in the internal data. Because both series do not capture trends at the very top of the income distribution, we use a multiple imputation approach in which values for censored observations are imputed using draws from a Generalized Beta distribution of the Second Kind (GB2) fitted to internal data. Doing so, we find income inequality trends similar to those derived from unadjusted internal data. Our trend results are generally robust to the choice of inequality index, whether Gini coefficient or other commonly-used indices. When we compare our best estimates of the income shares held by the richest tenth with those reported by Piketty and Saez (2003), our trends fairly closely match their trends, except for the top 1 percent of the distribution. Thus, we argue that if United States income inequality has been substantially increasing since 1993, such increases are confined to this very high income group.
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