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. Keywords; integrated non-linearly transformed ornstein-uhlenbeck process, temporal aggregation
|Date of creation:||01 Jul 2010|
|Contact details of provider:|| Postal: Highfield, Southampton SO17 1BJ|
Phone: (+44) 23 80592537
Fax: (+44) 23 80593858
Web page: http://www.economics.soton.ac.uk/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:stn:sotoec:1014. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Thorn)
If references are entirely missing, you can add them using this form.