The Weight of the Rich: Improving Surveys Using Tax Data

Thomas Blanchet (1, 2, 3) , Ignacio Flores (3) , Marc Morgan (1, 3)

1 PSE - Paris School of Economics
2 PJSE - Paris Jourdan Sciences Economiques
3 WIL - World Inequality Lab

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.

Keywords: Income inequality; Top incomes; Inequality; Survey Representativeness; Tax Data; Reweighting; Calibration

Domains: Humanities and Social Sciences; Economics and Finance

Thomas Blanchet, Ignacio Flores, Marc Morgan. The Weight of the Rich: Improving Surveys Using Tax Data. 2018. ⟨hal-02878315⟩