Estimation in Semiparametric Time Series Regression
In this paper, we consider a semiparametric time series regression model and establish a set of identication conditions such that the model under discussion is both identiable 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.
Year of publication: |
2010-10
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Authors: | GAO, Jiti ; Chen, Jia ; Li, Degui |
Institutions: | School of Economics, University of Adelaide |
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