[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/ssb/dispap/923.html
   My bibliography  Save this paper

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

Author

Listed:
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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: https://www.ssb.no/en/forskning/discussion-papers/_attachment/414305
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Orazio P. Attanasio & Luigi Pistaferri, 2016. "Consumption Inequality," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 3-28, Spring.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Crawley, Edmund & Theloudis, Alexandros, 2024. "Income Shocks and their Transmission into Consumption," Discussion Paper 2024-012, Tilburg University, Center for Economic Research.
    2. Theloudis, Alexandros, 2021. "Consumption inequality across heterogeneous families," European Economic Review, Elsevier, vol. 136(C).
    3. Landais, Camille & Kolsrud, Jonas & Spinnewijn, Johannes, 2017. "Studying Consumption Patterns using Registry Data: Lessons From Swedish Administrative Data," CEPR Discussion Papers 12402, C.E.P.R. Discussion Papers.
    4. Orazio Attanasio & Corina Mommaerts & Costas Meghir, 2015. "Insurance in Extended Family Networks," Cowles Foundation Discussion Papers 1996, Cowles Foundation for Research in Economics, Yale University.
    5. Neil Amin‐Smith & Orazio P. Attanasio, 2020. "Consumption and Wage Inequality in the US: The Dynamics of the Last Three Decades," Fiscal Studies, John Wiley & Sons, vol. 41(1), pages 7-38, March.
    6. Jeanne Commault, 2016. "How Does Nondurable Consumption Respond To Transitory Income Shocks? Reconciling Natural Experiments and Structural Estimations," Working Papers hal-01328904, HAL.
    7. Robin Jessen & Johannes König, 2023. "Hours risk and wage risk: repercussions over the life cycle," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(4), pages 956-996, October.
    8. Kolsrud, Jonas & Landais, Camille & Spinnewijn, Johannes, 2020. "The value of registry data for consumption analysis: An application to health shocks," Journal of Public Economics, Elsevier, vol. 189(C).
    9. José Casado, 2011. "From income to consumption: measuring households partial insurance," Empirical Economics, Springer, vol. 40(2), pages 471-495, April.
    10. Kohei Kubota, 2021. "Partial insurance in Japan," The Japanese Economic Review, Springer, vol. 72(2), pages 299-328, April.
    11. Etheridge, Ben, 2015. "A test of the household income process using consumption and wealth data," European Economic Review, Elsevier, vol. 78(C), pages 129-157.
    12. Andreas Fagereng & Martin B. Holm & Gisle J. Natvik, 2021. "MPC Heterogeneity and Household Balance Sheets," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(4), pages 1-54, October.
    13. Campanale, Claudio & Sartarelli, Marcello, 2024. "Life-cycle wealth accumulation and consumption insurance," Journal of Macroeconomics, Elsevier, vol. 79(C).
    14. De Giorgi, Giacomo & Gambetti, Luca & Naguib, Costanza, 2020. "Life-Cycle Inequality: Blacks And Whites Differentials In Life Expectancy, Savings, Income, And Consumption," CEPR Discussion Papers 15182, C.E.P.R. Discussion Papers.
    15. David Autor & Andreas Kostøl & Magne Mogstad & Bradley Setzler, 2019. "Disability Benefits, Consumption Insurance, and Household Labor Supply," American Economic Review, American Economic Association, vol. 109(7), pages 2613-2654, July.
    16. Claudio Campanale, 2020. "Consumption insurance and education: A puzzle?," Working papers 069, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    17. Giacomo De Giorgi & Luca Gambetti & Costanza Naguib, 2023. "Life-Cycle Inequality: the Black and White Differential," Diskussionsschriften dp2301, Universitaet Bern, Departement Volkswirtschaft.
    18. Pierfederico Asdrubali & Simone Tedeschi & Luigi Ventura, 2020. "Household risk‐sharing channels," Quantitative Economics, Econometric Society, vol. 11(3), pages 1109-1142, July.
    19. Zhao, Da & Wu, Tianhao & He, Qiwei, 2017. "Consumption inequality and its evolution in urban China," China Economic Review, Elsevier, vol. 46(C), pages 208-228.
    20. Jessen, Robin & König, Johannes, 2018. "Hours risk, wage risk, and life-cycle labor supply," Ruhr Economic Papers 771, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ssb:dispap:923. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: L Maasø (email available below). General contact details of provider: https://edirc.repec.org/data/ssbgvno.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.