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Measuring Household Spending and Payment Habits: The Role of "Typical" and "Specific" Time Frames in Survey Questions

In: Improving the Measurement of Consumer Expenditures

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  • Marco Angrisani
  • Arie Kapteyn
  • Scott Schuh

Abstract

We designed and fielded an experimental module in the American Life Panel (ALP) where we ask individuals to report the number of their purchases and the amount paid by debit cards, cash, credit cards, and personal checks. The design of the experiment features several stages of randomization. First, three different groups of sample participants are randomly assigned to an entry month (July, August, or September, 2011) and are to be interviewed four times during a year, once every quarter. Second, for each method of payment a sequence of questions elicits spending behavior during a day, week, month, and year. At the time of the first interview, this sequence is randomly assigned to refer to ?specific? time spans or to ?typical? time spans. In all subsequent interviews, a ?specific? sequence becomes a ?typical? sequence and vice versa. In this paper, we analyze the data from the first wave of the survey. We show that the type? specific or typical? and length of recall periods greatly influence household reporting behavior.
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Suggested Citation

  • Marco Angrisani & Arie Kapteyn & Scott Schuh, 2014. "Measuring Household Spending and Payment Habits: The Role of "Typical" and "Specific" Time Frames in Survey Questions," NBER Chapters, in: Improving the Measurement of Consumer Expenditures, pages 414-440, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberch:12672
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    References listed on IDEAS

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    1. Jean-Marc Robin, 1993. "Econometric Analysis of the Short-run Fluctuations of Households' Purchases," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(4), pages 923-934.
    2. Kevin Foster & Erik Meijer & Scott Schuh & Mike Zabek, 2011. "The 2009 survey of consumer payment choice," Public Policy Discussion Paper 11-1, Federal Reserve Bank of Boston.
    3. Chesher, Andrew & Irish, Margaret, 1987. "Residual analysis in the grouped and censored normal linear model," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 33-61.
    4. Margaret Grosh & Paul Glewwe, 2000. "Designing Household Survey Questionnaires for Developing Countries," World Bank Publications - Books, The World Bank Group, number 25338, December.
    5. Deaton, Angus & Irish, Margaret, 1984. "Statistical models for zero expenditures in household budgets," Journal of Public Economics, Elsevier, vol. 23(1-2), pages 59-80.
    6. Schuh, Scott & Stavins, Joanna, 2010. "Why are (some) consumers (finally) writing fewer checks? The role of payment characteristics," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1745-1758, August.
    7. Angus Deaton & Valerie Kozel, 2005. "Data and Dogma: The Great Indian Poverty Debate," The World Bank Research Observer, World Bank, vol. 20(2), pages 177-199.
    8. Jean-Marc Robin, 1993. "Econometric Analysis of the Short-Run Fluctuations of Households' Purchases," Post-Print hal-03587668, HAL.
    9. John C. Ham & Xianghong Li & Lara D. Shore-Sheppard, 2016. "The Employment Dynamics of Disadvantaged Women: Evidence from the SIPP," Journal of Labor Economics, University of Chicago Press, vol. 34(4), pages 899-944.
    10. Blundell, Richard & Meghir, Costas, 1987. "Bivariate alternatives to the Tobit model," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 179-200.
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    Cited by:

    1. Marcin Hitczenko, 2013. "Optimal recall period length in consumer payment surveys," Working Papers 13-16, Federal Reserve Bank of Boston.
    2. Marco Angrisani & Kevin Foster & Marcin Hitczenko, 2013. "The 2010 Survey of Consumer Payment Choice: technical appendix," Research Data Report 13-3, Federal Reserve Bank of Boston.
    3. Fiedler, John L. & Mwangi, Dena M., 2016. "Improving household consumption and expenditure surveys’ food consumption metrics: Developing a strategic approach to the unfinished agenda:," IFPRI discussion papers 1570, International Food Policy Research Institute (IFPRI).
    4. Marco Angrisani & Kevin Foster & Marcin Hitczenko, 2015. "The 2013 Survey of Consumer Payment Choice: technical appendix," Research Data Report 15-5, Federal Reserve Bank of Boston.
    5. Marco Angrisani & Kevin Foster & Marcin Hitczenko, 2014. "The 2011 and 2012 Surveys of Consumer Payment Choice: technical appendix," Research Data Report 14-2, Federal Reserve Bank of Boston.
    6. Pannuzi Nicoletta & Grassi Donatella & Masi Alessandra & Lemmi Achille & Regoli Andrea, 2020. "Investigating the Effects of the Household Budget Survey Redesign on Consumption and Inequality Estimates: the Italian Experience," Journal of Official Statistics, Sciendo, vol. 36(2), pages 411-434, June.
    7. Marcin Hitczenko, 2021. "Improved Estimation of Poisson Rate Distributions through a Multi-Mode Survey Design," FRB Atlanta Working Paper 2021-10, Federal Reserve Bank of Atlanta.
    8. Scott Schuh, 2017. "Measuring consumer expenditures with payment diaries," Working Papers 17-2, Federal Reserve Bank of Boston.
    9. Claire Greene & Scott Schuh & Joanna Stavins, 2018. "The 2012 diary of consumer payment choice," Research Data Report 18-1, Federal Reserve Bank of Boston.

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