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

A-Tier
Journal: Journal of Econometrics
Year: 2010
Volume: 156
Issue: 2
Pages: 239-259

Score contribution per author:

4.022 = (α=2.01 / 1 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:eee:econom:v:156:y:2010:i:2:p:239-259
Journal Field
Econometrics
Author Count
1
Added to Database
2026-01-25