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A comment on fitting Pareto tails to complex survey data

Rafael Wildauer () and Jakob Kapeller ()

No PKWP2001, Working Papers from Post Keynesian Economics Society (PKES)

Abstract: Taking survey data on household wealth as our major example, this short paper discusses some of the issues applied researchers are facing when fitting (type I) Pareto distributions to complex survey data. The major contribution of this paper is twofold: First, we propose a new and intuitive way of deriving Gabaix and Ibragimov’s (2011) bias correction for Pareto tail estimations from which the generalization to complex survey data follows naturally. Second, we summarise how Kolmogorov-Smirnof and Cramer-von-Mises goodness of fit tests can be generalized to complex survey data. Taken together we think the paper provides a concise and useful presentation of the fundamentals of Pareto tail fitting with complex survey data.

Keywords: Pareto distribution; complex survey data; wealth distribution (search for similar items in EconPapers)
JEL-codes: C46 C83 D31 (search for similar items in EconPapers)
Pages: 9
Date: 2020-01
New Economics Papers: this item is included in nep-ecm and nep-rmg
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http://www.postkeynesian.net/downloads/working-papers/PKWP2001.pdf First version, 2020 (application/pdf)

Related works:
Working Paper: A Comment on Fitting Pareto Tails to Complex Survey Data (2019) Downloads
Working Paper: A Comment on Fitting Pareto Tails to Complex Survey Data (2019) Downloads
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