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The Weight of the Rich: Improving Surveys Using Tax Data

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  • Thomas Blanchet

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - INRA - Institut National de la Recherche Agronomique - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique, WIL - World Inequality Lab)

  • Ignacio Flores

    (WIL - World Inequality Lab)

  • Marc Morgan

    (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, WIL - World Inequality Lab)

Abstract

It is generally accepted that household surveys fail to accurately portray the top tail of the income distribution. Indeed, studies based on tax data challenge the credibility of surveys as a source to study inequality. To date, there is no broad consensus on how to best reconcile these two datasets. This paper presents a novel method that enables a consistent combination of these two sources of data, under the assumption that tax data sets a credible lower bound on the amount of people with given levels of income. The resulting micro-dataset preserves the consistency of other socio-demographic variables at both the individual and aggregate levels. It thus allows researchers to analyze dimensions of social inequality under a more representative distributive framework. Our procedure is illustrated by empirical applications to five countries, covering both developed and less-developed contexts over numerous years.

Suggested Citation

  • Thomas Blanchet & Ignacio Flores & Marc Morgan, 2018. "The Weight of the Rich: Improving Surveys Using Tax Data," World Inequality Lab Working Papers hal-02878315, HAL.
  • Handle: RePEc:hal:wilwps:hal-02878315
    Note: View the original document on HAL open archive server: https://pse.hal.science/hal-02878315
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