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Introducing the Medical Expenditure Panel Survey-Insurance Component with Administrative Records (MEPS-ICAR): Description, Data Construction Methodology, and Quality Assessment
August 2022
Working Paper Number:
CES-22-29
This report introduces a new dataset, the Medical Expenditure Panel Survey-Insurance Component with Administrative Records (MEPS-ICAR), consisting of MEPS-IC survey data on establishments and their health insurance benefits packages linked to Decennial Census data and administrative tax records on MEPS-IC establishments' workforces. These data include new measures of the characteristics of MEPS-IC establishments' parent firms, employee turnover, the full distribution of MEPS-IC workers' personal and family incomes, the geographic locations where those workers live, and improved workforce demographic detail. Next, this report details the methods used for producing the MEPS-ICAR. Broadly, the linking process begins by matching establishments' parent firms to their workforces using identifiers appearing in tax records. The linking process concludes by matching establishments to their own workforces by identifying the subset of their parent firm's workforce that best matches the expected size, total payroll, and residential geographic distribution of the establishment's workforce. Finally, this report presents statistics characterizing the match rate and the MEPS-ICAR data itself. Key results include that match rates are consistently high (exceeding 90%) across nearly all data subgroups and that the matched data exhibit a reasonable distribution of employment, payroll, and worker commute distances relative to expectations and external benchmarks. Notably, employment measures derived from tax records, but not used in the match itself, correspond with high fidelity to the employment levels that establishments report in the MEPS-IC. Cumulatively, the construction of the MEPS-ICAR significantly expands the capabilities of the MEPS-IC and presents many opportunities for analysts.
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The impact of manufacturing credentials on earnings and the probability of employment
May 2022
Working Paper Number:
CES-22-15
This paper examines the labor market returns to earning industry-certified credentials in the manufacturing sector. Specifically, we are interested in estimating the impact of a manufacturing credential on wages, probability of employment, and probability of employment specifically in the manufacturing sector post credential attainment. We link students who earned manufacturing credentials to their enrollment and completion records, and then further link them to their IRS tax records for earnings and employment (Form W2 and 1040) and to the American Community Survey and decennial census for demographic information. We present earnings trajectories for workers with credentials by type of credential, industry of employment, age, race and ethnicity, gender, and state. To obtain a more causal estimate of the impact of a credential on earnings, we implement a coarsened exact matching strategy to compare outcomes between otherwise similar people with and without a manufacturing credential. We find that the attainment of a manufacturing industry credential is associated with higher earnings and a higher likelihood of labor market participation when we compare attainers to a group of non-attainers who are otherwise similar.
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Occupational Classifications: A Machine Learning Approach
August 2018
Working Paper Number:
CES-18-37
Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job titles and occupations, millions of dollars could be saved in labor costs, data processing could be sped up, data could become more consistent, and it might be possible to generate, without a lag, current information about the changing occupational composition of the labor market. This paper examines the potential to assign occupations to job titles contained in administrative data using automated, machine-learning approaches. We use a new extraordinarily rich and detailed set of data on transactional HR records of large firms (universities) in a relatively narrowly defined industry (public institutions of higher education) to identify the potential for machine-learning approaches to classify occupations.
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The Distributional Effects of Minimum Wages: Evidence from Linked Survey and Administrative Data
March 2018
Working Paper Number:
carra-2018-02
States and localities are increasingly experimenting with higher minimum wages in response to rising income inequality and stagnant economic mobility, but commonly used public datasets offer limited opportunities to evaluate the extent to which such changes affect earnings growth. We use administrative earnings data from the Social Security Administration linked to the Current Population Survey to overcome important limitations of public data and estimate effects of the minimum wage on growth incidence curves and income mobility profiles, providing insight into how cross-sectional effects of the minimum wage on earnings persist over time. Under both approaches, we find that raising the minimum wage increases earnings growth at the bottom of the distribution, and those effects persist and indeed grow in magnitude over several years. This finding is robust to a variety of specifications, including alternatives commonly used in the literature on employment effects of the minimum wage. Instrumental variables and subsample analyses indicate that geographic mobility likely contributes to the effects we identify. Extrapolating from our estimates suggests that a minimum wage increase comparable in magnitude to the increase experienced in Seattle between 2013 and 2016 would have blunted some, but not nearly all, of the worst income losses suffered at the bottom of the income distribution during the Great Recession.
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Labor Market Effects of the Affordable Care Act: Evidence from a Tax Notch
July 2017
Working Paper Number:
carra-2017-07
States that declined to raise their Medicaid income eligibility cutoffs to 138 percent of the federal poverty level (FPL) under the Affordable Care Act (ACA) created a "coverage gap'' between their existing, often much lower Medicaid eligibility cutoffs and the FPL, the lowest level of income at which the ACA provides refundable, advanceable "premium tax credits'' to subsidize the purchase of private insurance. Lacking access to any form of subsidized health insurance, residents of those states with income in that range face a strong incentive, in the form of a large, discrete increase in post-tax income (i.e. an upward notch) at the FPL, to increase their earnings and obtain the premium tax credit. We investigate the extent to which they respond to that incentive. Using the universe of tax returns, we document excess mass, or bunching, in the income distribution surrounding this notch. Consistent with Saez (2010), we find that bunching occurs only among filers with self-employment income. Specifically, filers without children and married filers with three or fewer children exhibit significant bunching. Analysis of tax data linked to labor supply measures from the American Community Survey, however, suggests that this bunching likely reflects a change in reported income rather than a change in true labor supply. We find no evidence that wage and salary workers adjust their labor supply in response to increased availability of directly purchased health insurance.
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Who Files for Personal Bankruptcy in the United States?
January 2017
Working Paper Number:
CES-17-54
Who files for bankruptcy in the United States is not well understood. Previous research relied on small samples from national surveys or a small number of states from administrative records. I use over 10 million administrative bankruptcy records linked to the 2000 Decennial Census and the 2001-2009 American Community Surveys to understand who files for personal bankruptcy. Bankruptcy filers are middle income, more likely to be divorced, more likely to be black, more likely to have terminal high school degree or some college, and more likely to be middle-aged. Bankruptcy filers are more likely to be employed than the U.S. as a whole, and they are more likely to be employed 50-52 weeks. The bankruptcy population is aging faster than the U.S. population as a whole. Lastly, using the pseudo-panels I study what happens in the years around bankruptcy. Individuals are likely to get divorced in the years before bankruptcy and then remarry. Income falls before bankruptcy and then rises after bankruptcy.
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Differences in Self-employment Duration by Year of Entry & Pre-entry
November 2016
Working Paper Number:
carra-2016-09
Self-employment is associated with entrepreneurship and a motivation to pursue an opportunity. Previous research indicates that people also become self-employed because of limited opportunities in the wage sector. Using a unique set of data that links the American Community Survey to Form 1040 and W-2 records, this paper extends the existing literature by examining self-employment duration for five consecutive entry cohorts, including two cohorts who entered self-employment during the Great Recession. Severely limited labor market opportunities may have driven many in the recession cohorts to enter self-employment, while those entering self-employment during the boom may have been pursuing opportunities under favorable market conditions. To more explicitly test the concept of "necessity" versus "opportunity" self-employment, we also examine the pre-entry wage labor attachment of entrants. Specifically, we ask whether an association exists between wage labor attachment and the duration of self-employment. We also explore whether the demographic/socio-economic characteristics and self-employment exit behavior of the cohorts are different, and if so, how. We find evidence consistent with the existence of "necessity" vs. "opportunity" self-employment types.
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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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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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Revisiting the Effects of Unemployment Insurance Extensions on Unemployment: A Measurement Error-Corrected Regression Discontinuity Approach
March 2016
Working Paper Number:
carra-2016-01
The extension of Unemployment Insurance (UI) benefits was a key policy response to the Great Recession. However, these benefit extensions may have had detrimental labor market effects. While evidence on the individual labor supply response indicates small effects on unemployment, recent work by Hagedorn et al. (2015) uses a county border pair identification strategy to find that the total effects inclusive of effects on labor demand are substantially larger. By focusing on variation within border county pairs, this identification strategy requires counties in the pairs to be similar in terms of unobservable factors. We explore this assumption using an alternative regression discontinuity approach that controls for changes in unobservables by distance to the border. To do so, we must account for measurement error induced by using county-level aggregates. These new results provide no evidence of a large change in unemployment induced by differences in UI generosity across state boundaries. Further analysis suggests that individuals respond to UI benefit differences across boundaries by targeting job search in high-benefit states, thereby raising concerns of treatment spillovers in this setting. Taken together, these two results suggest that the effect of UI benefit extensions on unemployment remains an open question.
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