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A Comparison Of Person-Reported Industry To Employer-Reported Industry In Survey And Administrative Data

Listed author(s):
  • Emily Isenberg
  • Liana Christin Landivar
  • Esther Mezey

The Census Bureau collects industry information through surveys and administrative data and creates associated public-use statistics. In this paper, we compare person-reported industry in the American Community Survey (ACS) to employer-reported industry from the Quarterly Census of Employment and Wages (QCEW) that is part of the Census Bureau’s Longitudinal Employer-Household Dynamics (LEHD) program. This research provides necessary information on the use of administrative data as a supplement to survey data industry information, and the findings will be useful for anyone using industry information from either source. Our project is part of a larger effort to compare information on jobs from household survey data to employer-reported information. This research is the first to compare ACS job data to firm-based administrative data. We find an overall industry sector match rate of 75 percent, and a 61 percent match rate at the 4-digit Census Industry Code (CIC) level. Industry match rates vary by sector and by whether industry sector is classified using ACS or LEHD industry information. The educational services and health care and social assistance sectors have among the highest match rates. The management of companies and enterprises sector has the lowest match rate, using either ACS-reported or LEHD-reported sector. For individuals with imputed industry data, the industry sector match rate is only 14 percent. Our findings suggest that the industry distribution and the sample in a particular industry sector will differ depending on whether ACS or LEHD data are used.

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Paper provided by Center for Economic Studies, U.S. Census Bureau in its series Working Papers with number 13-47.

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Length: 58 pages
Date of creation: Sep 2013
Handle: RePEc:cen:wpaper:13-47
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  1. Marc Roemer, 2002. "Using Administrative Earnings Records to Assess Wage Data Quality in the March Current Population Survey and the Survey of Income and Program Participation," Longitudinal Employer-Household Dynamics Technical Papers 2002-22, Center for Economic Studies, U.S. Census Bureau.
  2. Katharine G. Abraham & John Haltiwanger & Kristin Sandusky & James R. Spletzer, 2013. "Exploring Differences in Employment between Household and Establishment Data," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 129-172.
  3. Christopher R. Bollinger & Barry T. Hirsch, 2006. "Match Bias from Earnings Imputation in the Current Population Survey: The Case of Imperfect Matching," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 483-520, July.
  4. Christopher R. Bollinger & Barry T. Hirsch, 2013. "Is Earnings Nonresponse Ignorable?," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 407-416, May.
  5. Bound, John & Krueger, Alan B, 1991. "The Extent of Measurement Error in Longitudinal Earnings Data: Do Two Wrongs Make a Right?," Journal of Labor Economics, University of Chicago Press, vol. 9(1), pages 1-24, January.
  6. Bound, John, et al, 1994. "Evidence on the Validity of Cross-Sectional and Longitudinal Labor Market Data," Journal of Labor Economics, University of Chicago Press, vol. 12(3), pages 345-368, July.
  7. Kristin Fairman & Lucia Foster & C.J. Krizan & Ian Rucker, 2008. "An Analysis of Key Differences in Micro Data: Results from the Business List Comparison Project," Working Papers 08-28, Center for Economic Studies, U.S. Census Bureau.
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