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Measuring Total Household Spending in a Monthly Internet Survey: Evidence from the American Life Panel


  • Michael D. Hurd
  • Susann Rohwedder


Beginning in May 2009 we fielded a monthly Internet survey designed to measure total household spending as the aggregate of about 40 spending components. This paper reports on a number of outcomes from 30 waves of data collection. These outcomes include sample attrition, indicators of data quality such as item nonresponse and the variance in total spending, and substantive results such as the trajectory of total spending and the trajectories of some components of spending. We conclude that high-frequency surveying for total spending is feasible and that the resulting data show expected patterns of levels and change.

Suggested Citation

  • Michael D. Hurd & Susann Rohwedder, 2012. "Measuring Total Household Spending in a Monthly Internet Survey: Evidence from the American Life Panel," NBER Working Papers 17974, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:17974
    Note: AG

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    References listed on IDEAS

    1. Matthew Brzozowski & Thomas F. Crossley, 2011. "Viewpoint: Measuring the well-being of the poor with income or consumption: a Canadian perspective," Canadian Journal of Economics, Canadian Economics Association, vol. 44(1), pages 88-106, February.
    2. Michael Hurd & Susann Rohwedder, 2009. "Methodological Innovations in Collecting Spending Data: The HRS Consumption and Activities Mail Survey," Fiscal Studies, Institute for Fiscal Studies, pages 435-459.
    3. Melvin Stephens, 2004. "Job Loss Expectations, Realizations, and Household Consumption Behavior," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 253-269, February.
    4. Gruber, Jonathan, 1997. "The Consumption Smoothing Benefits of Unemployment Insurance," American Economic Review, American Economic Association, vol. 87(1), pages 192-205, March.
    5. Martin Browning & Thomas F. Crossley, 2009. "Shocks, Stocks, and Socks: Smoothing Consumption Over a Temporary Income Loss," Journal of the European Economic Association, MIT Press, vol. 7(6), pages 1169-1192, December.
    6. Michael D. Hurd & Susann Rohwedder, 2013. "Wealth Dynamics and Active Saving at Older Ages," NBER Chapters,in: Improving the Measurement of Consumer Expenditures, pages 388-413 National Bureau of Economic Research, Inc.
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    Cited by:

    1. Francesco D'Acunto & Daniel Hoang & Michael Weber, 2016. "Unconventional Fiscal Policy, Inflation Expectations, and Consumption Expenditure," CESifo Working Paper Series 5793, CESifo Group Munich.
    2. Francesco D’Acunto & Daniel Hoang & Michael Weber, 2017. "The Effect of Unconventional Fiscal Policy on Consumption Expenditure," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 15(1), pages 09-11, April.
    3. Adam Bee & Bruce D. Meyer & James X. Sullivan, 2013. "The Validity of Consumption Data: Are the Consumer Expenditure Interview and Diary Surveys Informative?," NBER Chapters,in: Improving the Measurement of Consumer Expenditures, pages 204-240 National Bureau of Economic Research, Inc.
    4. Jonathan A. Parker & Nicholas S. Souleles & Christopher D. Carroll, 2014. "The Benefits of Panel Data in Consumer Expenditure Surveys," NBER Chapters,in: Improving the Measurement of Consumer Expenditures, pages 75-99 National Bureau of Economic Research, Inc.
    5. Luc Bissonnette & Arthur van Soest, 2015. "The Financial Crisis and Consumers' Income and Pension Expectations," Cahiers de recherche 1502, Chaire de recherche Industrielle Alliance sur les enjeux économiques des changements démographiques.
    6. Federica Teppa, 2014. "Consumption behaviour and financial crisis in the Netherlands," DNB Working Papers 453, Netherlands Central Bank, Research Department.
    7. Michael Weber & Daniel Hoang & Francesco D'Acunto, 2015. "Inflation Expectations and Consumption Expenditure," 2015 Meeting Papers 1266, Society for Economic Dynamics.
    8. Burke, Mary A. & Ozdagli, Ali K., 2013. "Household inflation expectations and consumer spending: evidence from panel data," Working Papers 13-25, Federal Reserve Bank of Boston.

    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • 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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