Modelling income processes with lots of heterogeneity

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 l...

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Main Authors: Browning, M, Ejrnaes, M, Alvarez, J
Format: Working paper
Published: University of Oxford 2006
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author Browning, M
Ejrnaes, M
Alvarez, J
author_facet Browning, M
Ejrnaes, M
Alvarez, J
author_sort Browning, M
collection OXFORD
description 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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spelling oxford-uuid:5d676440-ff42-4f7b-bb45-a317089ea2552022-03-26T17:34:14ZModelling income processes with lots of heterogeneityWorking paperhttp://purl.org/coar/resource_type/c_8042uuid:5d676440-ff42-4f7b-bb45-a317089ea255Symplectic ElementsBulk import via SwordUniversity of Oxford2006Browning, MEjrnaes, MAlvarez, JAll 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.
spellingShingle Browning, M
Ejrnaes, M
Alvarez, J
Modelling income processes with lots of heterogeneity
title Modelling income processes with lots of heterogeneity
title_full Modelling income processes with lots of heterogeneity
title_fullStr Modelling income processes with lots of heterogeneity
title_full_unstemmed Modelling income processes with lots of heterogeneity
title_short Modelling income processes with lots of heterogeneity
title_sort modelling income processes with lots of heterogeneity
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AT alvarezj modellingincomeprocesseswithlotsofheterogeneity