Semiparametric Estimation and Inference for Trending I(D) and Related Processes
27 Pages Posted: 14 Jan 2012
Date Written: March 12, 2007
This paper deals with estimation and hypothesis testing in models allowing for trending processes that are possibly nonstationary, nonlinear, and non-Gaussian. Using semi-parametric estimators, we obtain asymptotic confidence intervals for the trend and memory parameters, and we develop joint hypothesis testing for these. The confidence intervals are applicable for a wide class of processes, exhibit good coverage accuracy, and are easy to implement.
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