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Imputing total expenditures from a non-exhaustive list of items: An empirical assessment using the SAVE data set

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  • Lothar Essig

    (Munich Center for the Economics of Aging (MEA))

Abstract

General purpose surveys typically refrain from using an exhaustive list of consumption expenditure items since the gain of more precise data on consumption is usually more than offset by the large increase in interview time and respondent effort which reduces re-sponse willingness. An alternative is to ask respondents a non-exhaustive list of consumption expenditure items and use those items to impute total consumption by the use of an external data source. This paper uses the SAVE (internal) and EVS (external) data sets to apply such a procedure.

Suggested Citation

  • Lothar Essig, 2005. "Imputing total expenditures from a non-exhaustive list of items: An empirical assessment using the SAVE data set," MEA discussion paper series 05081, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    • Handle: RePEc:mea:meawpa:05081
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    References listed on IDEAS

    as
    1. Erich Battistin & Raffaele Miniaci & Guglielmo Weber, 2003. "What Do We Learn from Recall Consumption Data?," Journal of Human Resources, University of Wisconsin Press, vol. 38(2).
    2. Joachim Winter, 2004. "Response bias in survey-based measures of household consumption," Economics Bulletin, AccessEcon, vol. 3(9), pages 1-12.
    3. 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.
    4. Michael D. Hurd & Daniel McFadden & Harish Chand & Li Gan & Angela Menill & Michael Roberts, 1998. "Consumption and Savings Balances of the Elderly: Experimental Evidence on Survey Response Bias," NBER Chapters, in: Frontiers in the Economics of Aging, pages 353-392, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Essig, Lothar, 2004. "Precautionary saving and old-age provisions: Do subjective saving motives measures work?," Sonderforschungsbereich 504 Publications 05-22, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    2. Lothar Essig, 2005. "Precautionary saving and old-age provisions: Do subjective saving motive measures work?," MEA discussion paper series 05084, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    3. Lothar Essig, 2005. "Measures for savings and saving rates in the German SAVE data set," MEA discussion paper series 05086, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.

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    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
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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