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1.5 Million Missing Numbers: Overcoming Employment Suppression in County Business Patterns Data

Author

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  • Andrew M. Isserman

    (Departments of Agricultural and Consumer Economics and Urban and Regional Planning, University of Illinois, Urbana, isserman@uiuc.edu)

  • James Westervelt

    (Engineer Research and Development Center, Army Corps of Engineers, Champaign, IL, james.d.westervelt@ERDC.usace.army.mil)

Abstract

Missing data frustrate research and limit our understanding of regional economies. County Business Patterns annually provides employment data for all U.S. counties and states at the most detailed industrial level, but two out of every three employment statistics are missing. In rural areas, this percentage is higher still. To protect the rights of employers to confidentiality, the U.S. Census Bureau has not disclosed the number of employees in 1.5 million cases in the 2002 data. Instead, it offers a suppression flag that represents an employment range. This article presents a two-stage method for replacing all the flags with employment estimates. Taking advantage of the hierarchical nature of the data both by industry and geography, the first stage identifies the smallest possible range for each suppressed number. Ensuring that employment adds up correctly up and down the industrial and geographical hierarchies, the second stage iteratively adjusts all the estimates until millions of constraints are met. The procedure simultaneously considers all industries in all counties, states, and the nation to produce a complete data set, which is available to the research community on the Internet.

Suggested Citation

  • Andrew M. Isserman & James Westervelt, 2006. "1.5 Million Missing Numbers: Overcoming Employment Suppression in County Business Patterns Data," International Regional Science Review, , vol. 29(3), pages 311-335, July.
  • Handle: RePEc:sae:inrsre:v:29:y:2006:i:3:p:311-335
    DOI: 10.1177/0160017606290359
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    5. Brian E. Whitacre & Dylan L. Johnston & David W. Shideler & Notie H. Lansford, 2020. "The influence of oil and natural gas employment on local retail spending: evidence from Oklahoma panel data," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(1), pages 133-157, February.
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    7. Timothy J. Bartik, 2015. "How Effects of Local Labor Demand Shocks Vary with the Initial Local Unemployment Rate," Growth and Change, Wiley Blackwell, vol. 46(4), pages 529-557, December.
    8. Christopher S. Fowler & Rachel Garshick Kleit, 2014. "The Effects of Industrial Clusters on the Poverty Rate," Economic Geography, Clark University, vol. 90(2), pages 129-154, April.
    9. Weber, Jeremy G., 2014. "A decade of natural gas development: The makings of a resource curse?," Resource and Energy Economics, Elsevier, vol. 37(C), pages 168-183.
    10. Partridge, Mark D. & Tsvetkova, Alexandra, 2018. "Local ability to "rewire" and socioeconomic performance: Evidence from US counties before and after the Great Recession," MPRA Paper 89313, University Library of Munich, Germany.
    11. Aliprantis, Dionissi & Fee, Kyle & Schweitzer, Mark E., 2023. "Opioids and the labor market," Labour Economics, Elsevier, vol. 85(C).
    12. Jing Chen, 2017. "Geographical Scale, Industrial Diversity and Regional Economic Stability," Working Papers Working Paper 2017-03, Regional Research Institute, West Virginia University.
    13. Weinstein, Amanda L. & Partridge, Mark D. & Tsvetkova, Alexandra, 2018. "Follow the money: Aggregate, sectoral and spatial effects of an energy boom on local earnings," Resources Policy, Elsevier, vol. 55(C), pages 196-209.
    14. Erik Dietzenbacher & Manfred Lenzen & Bart Los & Dabo Guan & Michael L. Lahr & Ferran Sancho & Sangwon Suh & Cuihong Yang, 2013. "Input--Output Analysis: The Next 25 Years," Economic Systems Research, Taylor & Francis Journals, vol. 25(4), pages 369-389, December.
    15. Timothy J. Bartik & Nathan Sotherland, 2015. "Migration and Housing Price Effects of Place-Based College Scholarships," Upjohn Working Papers 15-245, W.E. Upjohn Institute for Employment Research.
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