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What can we learn about household consumption expenditure from data on income and assets?

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Abstract

A major difficulty faced by researchers who want to study the consumption and savings behavior of households is the lack of reliable panel data on household expenditures. One possibility is to use surveys that follow the same households over time, but such data are rare and they typically have small sample sizes and face significant measurement issues. An alternative approach is to use the accounting identity that total household spending is equal to income plus capital gains minus the change in wealth over the period. The goal of this paper is to examine the advantages and difficulties of using this accounting identity to construct a population panel data with information on household expenditure. To derive such measures of consumption expenditure, we combine several data sources from Norway over the period 1994–2014. This allows us to link tax records on income and wealth to other administrative data with information on financial and real estate transactions. Using this data, we derive household expenditure from the accounting identity, before assessing the sensitivity of this measure of consumption expenditure to the assumptions made and the data used. We then compare our measures of household expenditure to those reported in expenditure surveys and to the aggregates from national accounts. We also illustrate the research opportunities arising from the derived measures of consumption expenditure through two applications: the first is an examination of how relative wage movements among birth cohorts and education groups affected the distribution of household expenditure, while the second is a study of the transmission of income shocks to household consumption.

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  • Lasse Eika & Magne Mogstad & Ola L. Vestad, 2020. "What can we learn about household consumption expenditure from data on income and assets?," Discussion Papers 923, Statistics Norway, Research Department.
  • Handle: RePEc:ssb:dispap:923
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    1. Attanasio, Orazio & Davis, Steven J, 1996. "Relative Wage Movements and the Distribution of Consumption," Journal of Political Economy, University of Chicago Press, vol. 104(6), pages 1227-1262, December.
    2. John Sabelhaus & David Johnson & Stephen Ash & David Swanson & Thesia I. Garner & John Greenlees & Steve Henderson, 2014. "Is the Consumer Expenditure Survey Representative by Income?," NBER Chapters, in: Improving the Measurement of Consumer Expenditures, pages 241-262, National Bureau of Economic Research, Inc.
    3. Martin Browning & S¯ren Leth-Petersen, 2003. "Imputing consumption from income and wealth information," Economic Journal, Royal Economic Society, vol. 113(488), pages 282-301, June.
    4. Christopher D. Carroll & Thomas F. Crossley & John Sabelhaus, 2015. "Improving the Measurement of Consumer Expenditures," NBER Books, National Bureau of Economic Research, Inc, number carr11-1.
    5. Richard Blundell & Luigi Pistaferri & Itay Saporta-Eksten, 2016. "Consumption Inequality and Family Labor Supply," American Economic Review, American Economic Association, vol. 106(2), pages 387-435, February.
    6. Fagereng, Andreas & Halvorsen, Elin, 2017. "Imputing consumption from Norwegian income and wealth registry data," Journal of Economic and Social Measurement, IOS Press, issue 1, pages 67-100.
    7. Richard Blundell & Hamish Low & Ian Preston, 2013. "Decomposing changes in income risk using consumption data," Quantitative Economics, Econometric Society, vol. 4(1), pages 1-37, March.
    8. Martin Browning & Thomas F. Crossley & Joachim Winter, 2014. "The Measurement of Household Consumption Expenditures," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 475-501, August.
    9. Richard Blundell & Ian Preston, 1998. "Consumption Inequality and Income Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(2), pages 603-640.
    10. Richard Blundell & Luigi Pistaferri & Ian Preston, 2008. "Consumption Inequality and Partial Insurance," American Economic Review, American Economic Association, vol. 98(5), pages 1887-1921, December.
    11. Orazio P. Attanasio & Luigi Pistaferri, 2016. "Consumption Inequality," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 3-28, Spring.
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    More about this item

    Keywords

    administrative data; consumption measurement; income; wealth;
    All these keywords.

    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
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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