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Nonemployer Statistics by Demographics (NES-D): Exploring Longitudinal Consistency and Sub-national Estimates

Author

Listed:
  • Adela Luque
  • Michaela Dillon
  • Julia Manzella
  • James Noon
  • Kevin Rinz
  • Victoria Udalova

Abstract

Until recently, the quinquennial Survey of Business Owners (SBO) was the only source of information for U.S. employer and nonemployer businesses by owner demographic characteristics such as race, ethnicity, sex and veteran status. Now, however, the Nonemployer Statistics by Demographics series (NES-D) will replace the SBO�s nonemployer component with reliable, and more frequent (annual) business demographic estimates with no additional respondent burden, and at lower imputation rates and costs. NES-D is not a survey; rather, it exploits existing administrative and census records to assign demographic characteristics to the universe of approximately 25 million (as of 2016) nonemployer businesses. Although only in the second year of its research phase, NES-D is rapidly moving towards production, with a planned prototype or experimental version release of 2017 nonemployer data in 2020, followed by annual releases of the series. After the first year of research, we released a working paper (Luque et al., 2019) that assessed the viability of estimating nonemployer demographics exclusively with administrative records (AR) and census data. That paper used one year of data (2015) to produce preliminary tabulations of business counts at the national level. This year we expand that research in multiple ways by: i) examining the longitudinal consistency of administrative and census records coverage, and of our AR-based demographics estimates, ii) evaluating further coverage from additional data sources, iii) exploring estimates at the sub-national level, iv) exploring estimates by industrial sector, v) examining demographics estimates of business receipts as well as of counts, and vi) implementing imputation of missing demographic values. Our current results are consistent with the main findings in Luque et al. (2019), and show that high coverage and demographic assignment rates are not the exception, but the norm. Specifically, we find that AR coverage rates are high and stable over time for each of the three years we examine, 2014-2016. We are able to identify owners for approximately 99 percent of nonemployer businesses (excluding C-corporations), 92 to 93 percent of identified nonemployer owners have no missing demographics, and only about 1 percent are missing three or more demographic characteristics in each of the three years. We also find that our demographics estimates are stable over time, with expected small annual changes that are consistent with underlying population trends in the U.S.. Due to data limitations, these results do not include C-corporations, which represent only 2 percent of nonemployer businesses and 4 percent of receipts. Without added respondent burden and at lower imputation rates and costs, NES-D will provide high-quality business demographics estimates at a higher frequency (annual vs. every 5 years) than the SBO.

Suggested Citation

  • Adela Luque & Michaela Dillon & Julia Manzella & James Noon & Kevin Rinz & Victoria Udalova, 2019. "Nonemployer Statistics by Demographics (NES-D): Exploring Longitudinal Consistency and Sub-national Estimates," Working Papers 19-34, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:wpaper:19-34
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    File URL: https://www2.census.gov/ces/wp/2019/CES-WP-19-34.pdf
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    References listed on IDEAS

    as
    1. Nathan Goldschlag & J. Daniel Kim & Kristin McCue, 2017. "Just Passing Through: Characterizing U.S. Pass-Through Business Owners," Working Papers 17-69, Center for Economic Studies, U.S. Census Bureau.
    2. John Haltiwanger & Ron S. Jarmin & Javier Miranda, 2013. "Who Creates Jobs? Small versus Large versus Young," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 347-361, May.
    3. J. David Brown & Misty L. Heggeness & Suzanne M. Dorinski & Lawrence Warren & Moises Yi, 2018. "Understanding the Quality of Alternative Citizenship Data Sources for the 2020 Census," Working Papers 18-38, Center for Economic Studies, U.S. Census Bureau.
    4. Pierre Azoulay & Benjamin F. Jones & J. Daniel Kim & Javier Miranda, 2020. "Age and High-Growth Entrepreneurship," American Economic Review: Insights, American Economic Association, vol. 2(1), pages 65-82, March.
    5. Adela Luque & Renuka Bhaskar, 2014. "2010 American Community Survey Match Study," CARRA Working Papers 2014-03, Center for Economic Studies, U.S. Census Bureau.
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