Local GMM estimation of time series models with conditional moment restrictions

Nikolay Gospodinov, Taisuke Otsu

研究成果: Article査読

10 被引用数 (Scopus)

抄録

This paper investigates statistical properties of the local generalized method of moments (LGMM) estimator for some time series models defined by conditional moment restrictions. First, we consider Markov processes with possible conditional heteroskedasticity of unknown forms and establish the consistency, asymptotic normality, and semi-parametric efficiency of the LGMM estimator. Second, we undertake a higher-order asymptotic expansion and demonstrate that the LGMM estimator possesses some appealing bias reduction properties for positively autocorrelated processes. Our analysis of the asymptotic expansion of the LGMM estimator reveals an interesting contrast with the OLS estimator that helps to shed light on the nature of the bias correction performed by the LGMM estimator. The practical importance of these findings is evaluated in terms of a bond and option pricing exercise based on a diffusion model for spot interest rate.

本文言語English
ページ(範囲)476-490
ページ数15
ジャーナルJournal of Econometrics
170
2
DOI
出版ステータスPublished - 2012 10
外部発表はい

ASJC Scopus subject areas

  • 経済学、計量経済学

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