Large sample properties are studied for a first-order autoregression (AR(1)) with a root greater than unity. It is shown that, contrary to the AR coefficient, the least-squares (LS) estimator of the intercept and its t-statistic are asymptotically normal without requiring the Gaussian error distribution, and hence an invariance principle applies. The coefficient based test and the t test have better power for testing the hypothesis of zero intercept in the explosive process than in the stationary process.
Explosive model, Intercept, Invariance principle, Bubbles
Econometrics | Economics
WANG, Xiaohu and YU, Jun.
Limit Theory for an Explosive Autoregressive Process. (2015). Economic Letters. 126, 176-180. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1619
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.