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Survey Instruments and the Reports of Consumption Expenditures: Evidence from the Consumer Expenditure Surveys

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Abstract

This paper provides evidence on the relevance of the collection mode for the analysis of consumption data for the United States using complementary data sets from the Consumer Expenditure Surveys (CEX). We first show that population figures from consumption reports obtained with diaries markedly differ from those obtained using recall data. We then exploit multiple measurements of food expenditure available in the CEX to identify the effects of the collection mode on important features of the distribution of consumption (not just its mean). Finally, we show how to purge the expenditure measurements from most of the effects of the collection mode and thus obtain an improved measure of consumption that combines information from multiple reports in the CEX. The paper concludes by suggesting some guidelines for empirical research that have important implications for the measurement of inequality and well being.

Suggested Citation

  • Erich Battistin & Mario Padula, 2010. "Survey Instruments and the Reports of Consumption Expenditures: Evidence from the Consumer Expenditure Surveys," CSEF Working Papers 259, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    • Handle: RePEc:sef:csefwp:259
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    Cited by:

    1. Olivier Coibion & Yuriy Gorodnichenko & Dmitri Koustas, 2021. "Consumption Inequality and the Frequency of Purchases," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(4), pages 449-482, October.
    2. Li‐Chun Zhang, 2021. "Proxy expenditure weights for Consumer Price Index: Audit sampling inference for big‐data statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 571-588, April.
    3. Giacomo De Giorgi & Luca Gambetti, 2017. "Business Cycle Fluctuations and the Distribution of Consumption," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 23, pages 19-41, January.
    4. Campos, Rodolfo G. & Reggio, Iliana, 2013. "Measurement error and imputation of consumption in survey data," UC3M Working papers. Economics we1219, Universidad Carlos III de Madrid. Departamento de Economía.
    5. Scrimgeour, Dean & Gorry, James, 2015. "Using Engel Curves to Estimate CPI Bias for the Elderly," Working Papers 2015-03, Department of Economics, Colgate University, revised 08 Jun 2015.
    6. Rodolfo G. Campos & Iliana Reggio & Dionisio Garc𫑐, 2013. "Micro versus macro consumption data: the cyclical properties of the consumer expenditure survey," Applied Economics, Taylor & Francis Journals, vol. 45(26), pages 3778-3785, September.
    7. Li-Chun Zhang, 2019. "Proxy expenditure weights for Consumer Price Index: Audit sampling inference for big data statistics," Papers 1906.11208, arXiv.org.
    8. Marcin Hitczenko, 2013. "Optimal recall period length in consumer payment surveys," Working Papers 13-16, Federal Reserve Bank of Boston.
    9. Giacomo De Giorgi & Luca Gambetti, 2012. "Consumption Heterogenity Over the Business Cycle," UFAE and IAE Working Papers 904.12, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    10. Giacomo De Giorgi & Luca Gambetti, 2012. "The Effects of Government Spending on the Distribution of Consumption," UFAE and IAE Working Papers 905.12, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    11. Olga Gorbachev, 2011. "Did Household Consumption Become More Volatile?," American Economic Review, American Economic Association, vol. 101(5), pages 2248-2270, August.
    12. Thomas F. Crossley & Joachim K. Winter, 2014. "Asking Households about Expenditures: What Have We Learned?," NBER Chapters, in: Improving the Measurement of Consumer Expenditures, pages 23-50, National Bureau of Economic Research, Inc.
    13. Campos, Rodolfo G. & Reggio, Iliana & García-Píriz, Dionisio, 2012. "Micro vs. macro consumption data : the cyclical properties of the consumer expenditure survey," UC3M Working papers. Economics we1220, Universidad Carlos III de Madrid. Departamento de Economía.
    14. Justine Hastings & Jesse M. Shapiro, 2018. "How Are SNAP Benefits Spent? Evidence from a Retail Panel," American Economic Review, American Economic Association, vol. 108(12), pages 3493-3540, December.
    15. Campos, Rodolfo G. & Reggio, Iliana, 2014. "Measurement error in imputation procedures," Economics Letters, Elsevier, vol. 122(2), pages 197-202.

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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