Publication Type
Journal Article
Version
publishedVersion
Publication Date
4-2007
Abstract
A simple and robust approach is proposed for the parametric estimation of scalar homogeneous stochastic differential equations. We specify a parametric class of diffusions and estimate the parameters of interest by minimizing criteria based on the integrated squared difference between kernel estimates of the drift and diffusion functions and their parametric counterparts. The procedure does not require simulations or approximations to the true transition density and has the simplicity of standard nonlinear least-squares methods in discrete time. A complete asymptotic theory for the parametric estimates is developed. The limit theory relies on infill and long span asymptotics and is robust to deviations from stationarity, requiring only recurrence.
Keywords
Diffusion, Drift, Local time, Parametric estimation, Stochastic differential equation
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Econometrics
Volume
137
Issue
2
First Page
354
Last Page
395
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2005.06.033,
Publisher
Elsevier
Citation
BANDI, Federico and PHILLIPS, Peter C. B..
A Simple Approach to the Parametric Estimation of Potentially Nonstationary Diffusions. (2007). Journal of Econometrics. 137, (2), 354-395.
Available at: https://ink.library.smu.edu.sg/soe_research/281
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1016/j.jeconom.2005.06.033