A Simple Approach to the Parametric Estimation of Potentially Nonstationary Diffusions

Federico M. Bandi and Peter C. B. Phillips ()

No 1522, Cowles Foundation Discussion Papers from Cowles Foundation, Yale University

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; Semimartingale; Stochastic differential equation (search for similar items in EconPapers)
JEL-codes: C14 C22 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: Written
Note: CFP 1205.
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Published in Journal of Econometrics (April 2007), 137(2): 354-395

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Journal Article: A simple approach to the parametric estimation of potentially nonstationary diffusions (2007)
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