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Tracing the invisible rich: a new approach to modelling Pareto tails in survey data

Tracing the invisible rich: a new approach to modelling Pareto tails in survey data

Wildauer, Rafael ORCID: 0000-0001-6395-6286 and Kapeller, Jakob (2022) Tracing the invisible rich: a new approach to modelling Pareto tails in survey data. Labour Economics, 75:102145. ISSN 0927-5371 (doi:https://doi.org/10.1016/j.labeco.2022.102145)

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Abstract

This paper is concerned with the problem of modelling the tail of the wealth distribution with survey data when the data does not adequately cover the tail of the distribution. In order to deal with the problem post data collection, it is standard practice to either fit a Pareto tail to the data or to combine wealth survey data with observations from rich lists before fitting such a Pareto tail. This paper proposes a novel approach (’rank correction’) to address such cases which does not require additional data-sources. Applying the rank correction approach to wealth survey data (HFCS, SCF, WAS) yields estimates of top wealth shares, which are closely in line with estimates from the World Inequality Database and therefore represent a significant improvement over the raw survey data. While the paper focuses on the distribution of wealth as a case in point the rank correction approach might generally prove useful in contexts, where the tail of a Pareto-distributed variable is not adequately covered by the available data.

Item Type: Article
Uncontrolled Keywords: differential nonresponse, Pareto tail, post data collection, survey data, wealth distribution
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HD Industries. Land use. Labor
Faculty / School / Research Centre / Research Group: Faculty of Business
Faculty of Business > Department of International Business & Economics
Faculty of Business > Institute of Political Economy, Governance, Finance and Accountability (IPEGFA)
Last Modified: 13 May 2022 09:14
URI: http://gala.gre.ac.uk/id/eprint/35166

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