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Is the Consumer Expenditure Survey Representative by Income?

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Listed:
  • John Sabelhaus
  • David Johnson
  • Stephen Ash
  • David Swanson
  • Thesia Garner
  • John Greenlees
  • Steve Henderson

Abstract

Aggregate under-reporting of household spending in the Consumer Expenditure Survey (CE) can result from two fundamental types of measurement errors: higher-income households (who presumably spend more than average) are under-represented in the CE estimation sample, or there is systematic under-reporting of spending by at least some CE survey respondents. Using a new data set linking CE units to zip-code level average Adjusted Gross Income (AGI), we show that the very highest-income households are less likely to respond to the survey when they are sampled, but unit non-response rates are not associated with income over most of the income distribution. Although increasing representation at the high end of the income distribution could in principle significantly raise aggregate CE spending, the low reported average propensity to spend for higher-income respondent households could account for at least as much of the aggregate shortfall in total spending.

Suggested Citation

  • John Sabelhaus & David Johnson & Stephen Ash & David Swanson & Thesia Garner & John Greenlees & Steve Henderson, 2013. "Is the Consumer Expenditure Survey Representative by Income?," NBER Working Papers 19589, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:19589
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    3. Asger Lau Andersen & Amalie Sofie Jensen & Niels Johannesen & Claus Thustrup Kreiner & Søren Leth-Petersen & Adam Sheridan, 2023. "How Do Households Respond to Job Loss? Lessons from Multiple High-Frequency Datasets," American Economic Journal: Applied Economics, American Economic Association, vol. 15(4), pages 1-29, October.
    4. Martin Lettau & Sydney C. Ludvigson & Sai Ma, 2019. "Capital Share Risk in U.S. Asset Pricing," Journal of Finance, American Finance Association, vol. 74(4), pages 1753-1792, August.
    5. Bart H. H. Golsteyn & Stefa Hirsch, 2019. "Are estimates of intergenerational mobility biased by non-response? Evidence from the Netherlands," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 52(1), pages 29-63, January.
    6. Jonathan Fisher & Joseph Marchand, 2014. "Does the retirement consumption puzzle differ across the distribution?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(2), pages 279-296, June.
    7. Crawley, Edmund, 2020. "In search of lost time aggregation," Economics Letters, Elsevier, vol. 189(C).
    8. Sager, Lutz, 2019. "Income inequality and carbon consumption: Evidence from Environmental Engel curves," Energy Economics, Elsevier, vol. 84(S1).
    9. Barry Z. Cynamon & Steven M. Fazzari, 2017. "Household Income, Demand, and Saving: Deriving Macro Data With Micro Data Concepts," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(1), pages 53-69, March.
    10. Garry Barrett & Peter Levell & Kevin Milligan, 2014. "A Comparison of Micro and Macro Expenditure Measures across Countries Using Differing Survey Methods," NBER Chapters, in: Improving the Measurement of Consumer Expenditures, pages 263-286, National Bureau of Economic Research, Inc.
    11. Eika, Lasse & Mogstad, Magne & Vestad, Ola L., 2020. "What can we learn about household consumption expenditure from data on income and assets?," Journal of Public Economics, Elsevier, vol. 189(C).
    12. Jonathan D. Fisher & David S. Johnson & Timothy M. Smeeding & Jeffrey P. Thompson, 2022. "Inequality in 3‐D: Income, Consumption, and Wealth," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(1), pages 16-42, March.
    13. Jonathan Fisher & Joseph Marchand, 2014. "Does the retirement consumption puzzle differ across the distribution?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(2), pages 279-296, June.
    14. Lisa J. Dettling & Sebastian Devlin-Foltz & Jacob Krimmel & Sarah Pack & Jeffrey P. Thompson, 2015. "Comparing Micro and Macro Sources for Household Accounts in the United States: Evidence from the Survey of Consumer Finances," Finance and Economics Discussion Series 2015-86, Board of Governors of the Federal Reserve System (U.S.).
    15. Campos, Rodolfo G. & Reggio, Iliana, 2014. "Measurement error in imputation procedures," Economics Letters, Elsevier, vol. 122(2), pages 197-202.
    16. Starr, Jared & Nicolson, Craig & Ash, Michael & Markowitz, Ezra M. & Moran, Daniel, 2023. "Assessing U.S. consumers' carbon footprints reveals outsized impact of the top 1%," Ecological Economics, Elsevier, vol. 205(C).
    17. Jesse Bricker & Alice Henriques & Jacob Krimmel & John Sabelhaus, 2016. "Measuring Income and Wealth at the Top Using Administrative and Survey Data," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(1 (Spring), pages 261-331.
    18. Edward N. Wolff, 2016. "Deconstructing Household Wealth Trends in the United States, 1983 - 2013," NBER Working Papers 22704, National Bureau of Economic Research, Inc.
    19. Petach, Luke A. & Tavani, Daniele, 2021. "Consumption externalities and growth: Theory and evidence for the United States," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 976-997.

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    More about this item

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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