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Modelling income processes with lots of heterogeneity

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  • Martin Browning
  • Mette Ejrnaes

Abstract

All empirical models of earnings processes in the literature assume a good deal of homogeneity. In contrast to this we model earnings processes allowing for lots of heterogeneity between agents. We also introduce an extension to the linear ARMA model that allows that the initial convergence to the long run may be different from that implied by the conventional ARMA model. This is particularly important for unit root tests which are actually tests of a composite of two independent hypotheses. We fit our models to a variety of statistics including most of those considered by previous investigators. We use a sample drawn from the PSID, and focus on white males with a high school degree. Despite this observable homogeneity we find much greater latent heterogeneity than previous investigators. We show that allowance for heterogeneity makes substantial differences to estimates of model parameters and to outcomes of interest. Additionally we find strong evidence against the hypothesis that any worker has a unit root.

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Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 285.

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Date of creation: 01 Oct 2006
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Handle: RePEc:oxf:wpaper:285

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Keywords: Earnings; Heterogeneity; ARMA; Initial Conditions; Unit Root Tests;

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