Pseudo-maximum likelihood estimation in two classes of semiparametric diffusion models

Dennis Kristensen

Journal of Econometrics, 2010, vol. 156, issue 2, 239-259

Abstract: Two classes of semiparametric diffusion models are considered, where either the drift or the diffusion term is parameterized, while the other term is left unspecified. We propose a pseudo-maximum likelihood estimator (PMLE) of the parametric component that maximizes the likelihood with a preliminary estimator of the unspecified term plugged in. It is demonstrated how models and estimators can be used in a two-step specification testing strategy of semiparametric and fully parametric models, and shown that approximate/simulated versions of the PMLE inherit the properties of the actual but infeasible estimator. A simulation study investigates the finite sample performance of the PMLE.

Keywords: Diffusion; process; Kernel; estimation; Pseudo-likelihood; Semiparametric; Testing (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (19)

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Working Paper: Pseudo-Maximum Likelihood Estimation in Two Classes of Semiparametric Diffusion Models (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:156:y:2010:i:2:p:239-259

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