Abstract
Summary Based on a relative entropy approach, this paper proposes a method to estimate or update transition matrices using just cross-sectional observations at two points in time. The method is then applied to explain the development of the US income distribution. Starting from three hypothesized transition matrices and a transition matrix estimated from the PSID data, we show how these matrices must be adjusted in the light of the cross-sectional information. Finally, we explore the consequences of these updated transition matrices for the future development of the US income distribution.
Highlights
Changes in the distribution of income in the US and elsewhere have kindled a lively debate on possible explanations
We show how a transition matrix estimated from the Panel Study of Income Dynamics (PSID) database must be adjusted in the light of the cross-section information contained in the very representative Burkhauser et al (1999) sample
In order to gain information on the unobserved process of income dynamics from cross-section data, our approach needs the following two ingredients: Income distributions observed at two points in time
Summary
Changes in the distribution of income in the US and elsewhere have kindled a lively debate on possible explanations. We will adjust a theory based hypothesis of income dynamics in the light of cross-section information stated as income distributions observed at two points in time. Our method is used to enhance the quality of regularly derived transition matrices by incorporating information from cross-section databases, which usually cover a larger sample and contain more information than panel data. In this case, our approach leads to a statistical test which can be used to draw inferences concerning the initial hypothesis. We discuss the properties of the adjusted transition matrices and their implications for the future development of the income distribution
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