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What Do Survey Data Tell Us about U.S. Businesses?

Author

Listed:
  • Anmol Bhandari

    (University of Minnesota)

  • Ellen McGrattan

    (University of Minnesota)

  • Kurt Gerrard See

    (University of Minnesota)

  • Serdar Birinci

    (University of Minnesota)

Abstract

This paper examines the reliability of widely used surveys on U.S. businesses. We compare survey responses of business owners with administrative data and document large inconsistencies in business incomes, receipts, and the number of owners. We document problems due to nonrepresentative samples and mea- surement errors. Nonrepresentativeness is reflected in undersampling of owners with low incomes. Measurement errors arise because respondents do not re- fer to relevant documents and possibly because of framing issues. We discuss implications for statistics of interest, such as business valuations and returns. We conclude that predictions based on current survey data should be treated with caution.

Suggested Citation

  • Anmol Bhandari & Ellen McGrattan & Kurt Gerrard See & Serdar Birinci, 2019. "What Do Survey Data Tell Us about U.S. Businesses?," 2019 Meeting Papers 53, Society for Economic Dynamics.
  • Handle: RePEc:red:sed019:53
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    Cited by:

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    2. Uribe-Terán, Carlos, 2021. "Higher taxes at the top? The role of tax avoidance," Journal of Economic Dynamics and Control, Elsevier, vol. 129(C).
    3. Anmol Bhandari & Serdar Birinci & Ellen R. McGrattan & Kurt See, 2020. "What Do Survey Data Tell Us about US Businesses?," American Economic Review: Insights, American Economic Association, vol. 2(4), pages 443-458, December.
    4. Matthew Smith & Owen Zidar & Eric Zwick, 2020. "Top Wealth in America: New Estimates and Implications for Taxing the Rich," Working Papers 264, Princeton University, Department of Economics, Center for Economic Policy Studies..
    5. Burkhard Heer & Mark Trede, 2020. "Age-Specific Entrepreneurship and PAYG Public Pensions in Germany," CQE Working Papers 9120, Center for Quantitative Economics (CQE), University of Muenster.
    6. Catherine, Sylvain, 2022. "Keeping options open: What motivates entrepreneurs?," Journal of Financial Economics, Elsevier, vol. 144(1), pages 1-21.
    7. Madeira, Carlos & Margaretic, Paula, 2022. "The impact of financial literacy on the quality of self-reported financial information," Journal of Behavioral and Experimental Finance, Elsevier, vol. 34(C).
    8. Corina Boar & Virgiliu Midrigan, 2020. "Efficient Redistribution," NBER Working Papers 27622, National Bureau of Economic Research, Inc.

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    More about this item

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis

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