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Estimating continuous-time income models

Estimating continuous-time income models
Estimating continuous-time income models
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.
integrated non-linearly transformed ornstein-uhlenbeck process, temporal aggregation
0966-4246
1014
1-40
University of Southampton
Schluter, Christian
ae043254-4cc4-48aa-abad-56a36554de2b
Trede, Mark
7233d600-13a2-4c24-ae9d-16aed9bfca30
Schluter, Christian
ae043254-4cc4-48aa-abad-56a36554de2b
Trede, Mark
7233d600-13a2-4c24-ae9d-16aed9bfca30

Schluter, Christian and Trede, Mark (2010) Estimating continuous-time income models (Discussion Papers in Economics and Econometrics, 1014) University of Southampton

Record type: Monograph (Discussion Paper)

Abstract

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.

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Published date: July 2010
Keywords: integrated non-linearly transformed ornstein-uhlenbeck process, temporal aggregation

Identifiers

Local EPrints ID: 161639
URI: http://eprints.soton.ac.uk/id/eprint/161639
ISSN: 0966-4246
PURE UUID: 5c7cad73-e14f-4487-a1ad-0b6258b03187

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Date deposited: 03 Aug 2010 09:19
Last modified: 14 Mar 2024 02:00

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Contributors

Author: Mark Trede

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