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Estimation in Semiparametric Time Series Regression

  • Jia Chen

    (School of Economics, University of Adelaide)

  • Jiti Gao


    (School of Economics, University of Adelaide)

  • Degui Li

    (School of Economics, University of Adelaide)

In this paper, we consider a semiparametric time series regression model and establish a set of identi cation conditions such that the model under discussion is both identi able 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.

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Paper provided by University of Adelaide, School of Economics in its series School of Economics Working Papers with number 2010-27.

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Length: 18 pages
Date of creation: Oct 2010
Date of revision:
Handle: RePEc:adl:wpaper:2010-27
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