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Employment that is not covered by state unemployment
January 2002
Working Paper Number:
tp-2002-16
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Design Comparison of LODES and ACS Commuting Data Products
October 2014
Working Paper Number:
CES-14-38
The Census Bureau produces two complementary data products, the American Community Survey (ACS) commuting and workplace data and the Longitudinal Employer-Household Dynamics (LEHD) Origin-Destination Employment Statistics (LODES), which can be used to answer questions about spatial, economic, and demographic questions relating to workplaces and home-to-work flows. The products are complementary in the sense that they measure similar activities but each has important unique characteristics that provide information that the other measure cannot. As a result of questions from data users, the Census Bureau has created this document to highlight the major design differences between these two data products. This report guides users on the relative advantages of each data product for various analyses and helps explain differences that may arise when using the products.2,3
As an overview, these two data products are sourced from different inputs, cover different populations and time periods, are subject to different sets of edits and imputations, are released under different confidentiality protection mechanisms, and are tabulated at different geographic and characteristic levels. As a general rule, the two data products should not be expected to match exactly for arbitrary queries and may differ substantially for some queries.
Within this document, we compare the two data products by the design elements that were deemed most likely to contribute to differences in tabulated data. These elements are: Collection, Coverage, Geographic and Longitudinal Scope, Job Definition and Reference Period, Job and Worker Characteristics, Location Definitions (Workplace and Residence), Completeness of Geographic Information and Edits/Imputations, Geographic Tabulation Levels, Control Totals, Confidentiality Protection and Suppression, and Related
Public-Use Data Products.
An in-depth data analysis'in aggregate or with the microdata'between the two data products will be the subject of a future technical report. The Census Bureau has begun a pilot project to integrate ACS microdata with LEHD administrative data to develop an enhanced frame of employment status, place of work, and commuting. The Census Bureau will publish quality metrics for person match rates, residence and workplace match rates, and commute distance comparisons.
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The Closure Effect: Evidence from Workers Compensation Litigation
January 2010
Working Paper Number:
CES-10-01
Consideration of the "best interests" of Workers Compensation (WC) claimants often involves the assumption that those who receive benefits in a "lump-sum" behave "too myopically" with respect to labor supply. However, many attorneys argue that lump-sum settlements induce a beneficial "sense of closure." In this paper, I provide an empirical context for these ideas using a unique set of linked administrative databases owned by the State of California. Upon receipt of a court-approved lump-sum settlement, WC claimants immediately increase labor supply. No such change is found for claimants who receive a court-approved settlement in which the insurer provides benefits over time, suggesting that the method of litigation settlement is a determinant of labor supply.
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NOISE INFUSION AS A CONFIDENTIALITY PROTECTION MEASURE FOR GRAPH-BASED STATISTICS
September 2014
Working Paper Number:
CES-14-30
We use the bipartite graph representation of longitudinally linked em-ployer-employee data, and the associated projections onto the employer and em-ployee nodes, respectively, to characterize the set of potential statistical summar-ies that the trusted custodian might produce. We consider noise infusion as the primary confidentiality protection method. We show that a relatively straightfor-ward extension of the dynamic noise-infusion method used in the U.S. Census Bureau's Quarterly Workforce Indicators can be adapted to provide the same confidentiality guarantees for the graph-based statistics: all inputs have been modified by a minimum percentage deviation (i.e., no actual respondent data are used) and, as the number of entities contributing to a particular statistic increases, the accuracy of that statistic approaches the unprotected value. Our method also ensures that the protected statistics will be identical in all releases based on the same inputs.
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Describing the Form 5500-Business Register Match
January 2003
Working Paper Number:
tp-2003-05
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A Guide to the MEPS-IC Government List Sample Microdata
September 2011
Working Paper Number:
CES-11-27
The Medical Expenditure Panel Survey-Insurance Component (MEPS-IC) is conducted to provide nationally representative estimates on employer sponsored health insurance. MEPSIC data are collected from private sector employers, as well as state and local governments. While similar information is gathered from these two sectors, differences in the survey process exist. The goal of this paper is to provide details on the public sector including types of state and local government employers, sample design, general information on the data collected in the MEPS-IC, and additional sources of information.
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The Effect of Wage Insurance on Labor Supply: A Test for Income Effects
October 2009
Working Paper Number:
CES-09-37
Studies of moral hazard in wage insurance programs such as Unemployment Insurance (UI) or Workers Compensation (WC) have demonstrated that higher benefits discourage work, emphasizing the price distortion inherent in benefit provision. Utilizing administrative data linking WC claim records to wage records from a UI payroll tax database, I find that the effect of WC benefits on the duration of benefit receipt cannot fully account for the effect of these benefits on post-injury unemployment. This indicates that a significant fraction of the effect of WC benefits on employment is due to an income effect rather than a price distortion.
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Contributions to Health Insurance Premiums: When Does the Employer Pay 100 Percent?
December 2005
Working Paper Number:
CES-05-27
We identify the characteristics of establishments that paid 100 percent of health insurance premiums and the policies they offered from 1997-2001, despite increased premium costs. Analyzing data from the MEPS-IC, we see little change in the percent of establishments that paid the full cost of premiums for employees. Most of these establishments were young, small, singleunits, with a relatively high paid workforce. Plans that were fully paid generally required referrals to see specialists, did not cover pre-existing conditions or outpatient prescriptions, and had the highest out-of-pocket expense limits. These plans also were more likely than plans not fully paid by employers to have had a fee-for-service or exclusive provider arrangement, had the highest premiums, and were less likely to be self-insured.
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Exploring Differences in Employment between Household and Establishment Data
April 2009
Working Paper Number:
CES-09-09
Using a large data set that links individual Current Population Survey (CPS) records to employer-reported administrative data, we document substantial discrepancies in basic measures of employment status that persist even after controlling for known definitional differences between the two data sources. We hypothesize that reporting discrepancies should be most prevalent for marginal workers and marginal jobs, and find systematic associations between the incidence of reporting discrepancies and observable person and job characteristics that are consistent with this hypothesis. The paper discusses the implications of the reported findings for both micro and macro labor market analysis
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The Promise and Potential of Linked Employer-Employee Data for Entrepreneurship Research
September 2015
Working Paper Number:
CES-15-29
In this paper, we highlight the potential for linked employer-employee data to be used in entrepreneurship research, describing new data on business start-ups, their founders and early employees, and providing examples of how they can be used in entrepreneurship research. Linked employer-employee data provides a unique perspective on new business creation by combining information on the business, workforce, and individual. By combining data on both workers and firms, linked data can investigate many questions that owner-level or firm-level data cannot easily answer alone - such as composition of the workforce at start-ups and their role in explaining business dynamics, the flow of workers across new and established firms, and the employment paths of the business owners themselves.
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