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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
JEL classification: C46 C83 D31