Estimation in Semiparametric Time Series Regression
نویسندگان
چکیده
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. Jiti Gao is from the School of Economics, The University of Adelaide. Adelaide SA 5005, Australia. Email: [email protected].
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