 Estimating Continuous-Time Income ModelsChristian Schluter and Mark Trede () No 1811, CQE Working Papers from Center for Quantitative Economics (CQE), University of Muenster Abstract: A fundamental component of inter-temporal consumption-saving and portfolio allocation models is a statistical model of the income process. While income 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 characterized, 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: income processes; integrated non-linearly transformed Ornstein-Uhlenbeck process; temporal aggregation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:cqe:wpaper:1811 Access Statistics for this paper More papers in CQE Working Papers from Center for Quantitative Economics (CQE), University of Muenster Am Stadtgraben 9, 48143 Münster, Germany. Contact information at EDIRC. |
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