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What do we learn from recall consumption data?

Author

Listed:
  • Erich Battistin

    (Institute for Fiscal Studies, London)

  • Raffaele Miniaci

    (Department of Economics, Padua University)

  • Guglielmo Weber

    (Department of Economics, Padua University)

Abstract

In this paper we use two complementary Italian data sources (the 1995 Istat and Bank of Italy household surveys) to generate household-specific non-durable expenditure in the Bank of Italy sample that contains relatively high-quality income data. We show that food expenditure data are of comparable quality and informational content across the two surveys, once heaping, rounding and time averaging are properly accounted for. We therefore depart from standard practice and rely on the estimation of an inverse Engel curve on Istat data to impute non-durable expenditure to Bank of Italy observations, and show how these estimates can be used to analyse consumption age profiles conditional on demographics. Our key result is that predictions based on a standard set of demographic and socioeconomic indicators are quite different from predictions that also condition on simulated food consumption, in the sense that their age profile is less in line with the implications of the standard consumer intertemporal optimization problem.

Suggested Citation

  • Erich Battistin & Raffaele Miniaci & Guglielmo Weber, 2003. "What do we learn from recall consumption data?," Temi di discussione (Economic working papers) 466, Bank of Italy, Economic Research and International Relations Area.
  • Handle: RePEc:bdi:wptemi:td_466_03
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    References listed on IDEAS

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    More about this item

    Keywords

    recall errors; heaping and rounding; multiple imputations and consumption;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • 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
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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