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Estimating and Predicting Household Expenditures and Income Distributions

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Author Info

  • Jing Dai

    ()
    (Universität Kassel)

  • Stefan Sperlich

    ()
    (Université de Genève)

  • Walter Zucchini

    ()
    (Georg-August Universität Göttingen)

Abstract

A reliable prediction of unconditional welfare distributions, like income or consumption, is essential for welfare analysis, and in particular for inequality, poverty or development studies. Where observations of expenditures or income are missing, the mean prediction based on available covariates is not just a poor estimator of the unconditional distribution; it fails to predict the required information about tails and quantiles. A new estimation method is introduced which can be combined with any mean prediction model. It is used to calculate the income distribution of a survey based on subsample information, to estimate the unconditional income distribution for the non-responding households, and to predict the household expenditures of a future panel wave. It allows for imputing welfare distributions for a census from a survey or for synthetic populations under specific scenarios. Further inference is straight-forward, including prediction of Lorenz curves, indexes like the Gini, or distribution quantiles, including confidence intervals.

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File URL: http://www.uni-marburg.de/fb02/makro/forschung/magkspapers/47-2011_dai.pdf
File Function: First version, 2011
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Bibliographic Info

Paper provided by Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung) in its series MAGKS Papers on Economics with number 201147.

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Length: 26 pages
Date of creation: 2011
Date of revision:
Publication status: Forthcoming in
Handle: RePEc:mar:magkse:201147

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Related research

Keywords: household expenditures; income distribution; poverty mapping; project evaluation; data matching;

References

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Cited by:
  1. Lucia Rizzica, . "When the Cat\'s Away... The Effects of Spousal Migration on Investments on Children," Development Working Papers 361, Centro Studi Luca d\'Agliano, University of Milano.

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