Estimating continuous-time income models
Schluter, Christian and Trede, Mark (2010) Estimating continuous-time income models. Discussion Papers in Economics and Econometrics, (1014), 1-40.
While earning processes are commonly unobservable income flows which evolve in continuous time, observable income data are usually discrete, having been aggregated over time. We consider continuous-time earning processes, specifically (non-linearly) transformed Ornstein-Uhlenbeck processes, and the associated integrated, i.e. time aggregated process. Both processes are characterised, and we show that time aggregation alters important statistical properties. The parameters of the earning process are estimable by GMM, and the finite sample properties of the estimator are investigated. Our methods are applied to annual earnings data for the US. It is demonstrated that the model replicates well important features of the earnings distribution.
|Keywords:||integrated non-linearly transformed ornstein-uhlenbeck process, temporal aggregation|
|Subjects:||H Social Sciences > HB Economic Theory
H Social Sciences > HC Economic History and Conditions
H Social Sciences > HG Finance
|Divisions:||University Structure - Pre August 2011 > School of Social Sciences > Economics
|Date Deposited:||03 Aug 2010 09:19|
|Last Modified:||08 Jun 2012 12:55|
|Contributors:||Schluter, Christian (Author)
Trede, Mark (Author)
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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