Estimation in Semiparametric Time Series Models

17 Pages Posted: 18 Sep 2010

See all articles by Jiti Gao

Jiti Gao

Monash University - Department of Econometrics & Business Statistics

Jia Chen

University of Adelaide - School of Economics

Degui Li

University of Adelaide - School of Economics

Date Written: September 15, 2010

Abstract

In this paper, we consider a semiparametric time series regression model and establish a set of identification conditions such that the model under discussion is both identifiable and estimable. We then discuss how to estimate a sequence of local alternative functions nonparametrically when the null hypothesis does not hold. An asymptotic theory is established in each case. An empirical application is also included.

Keywords: Asymptotic consistency, deterministic trend, model identifiability, time series

JEL Classification: C14, C32

Suggested Citation

Gao, Jiti and Chen, Jia and Li, Degui, Estimation in Semiparametric Time Series Models (September 15, 2010). Available at SSRN: https://ssrn.com/abstract=1677748 or http://dx.doi.org/10.2139/ssrn.1677748

Jiti Gao (Contact Author)

Monash University - Department of Econometrics & Business Statistics ( email )

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HOME PAGE: http://www.jitigao.com

Jia Chen

University of Adelaide - School of Economics ( email )

No 233 North Terrace, School of Commerce
Adelaide SA, SA 5005
Australia

Degui Li

University of Adelaide - School of Economics ( email )

No 233 North Terrace, School of Commerce
Adelaide, South Australia 5005
Australia

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