Abstract
In this paper we consider general first order autoregression, including the stationary, the explosive and the unstable cases. It is well-known in the literature that the usual bootstrap method for the least squares parameter estimator is asymptotically consistent for the stationary and the explosive cases, but does not work in the unstable case, where the parameter value is equal to +1 and or −1. We propose a modified bootstrap method, which turns out to be asymptotically consistent in all possible situations. Furthermore, we derive tests for stationarity and nonstationarity for first order autoregressions. The bootstrap method is used to obtain critical values. Some simulation results are also enclosed.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.