Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1149623 | Journal of Statistical Planning and Inference | 2009 | 15 Pages |
Abstract
In this paper, we propose a new test for coefficient stability of an AR(1) model against the random coefficient autoregressive model of order 1 neither assuming a stationary nor a non-stationary process under the null hypothesis of a constant coefficient. The proposed test is obtained as a modification of the locally best invariant (LBI) test by Lee [(1998). Coefficient constancy test in a random coefficient autoregressive model. J. Statist. Plann. Inference 74, 93-101]. We examine finite sample properties of the proposed test by Monte Carlo experiments comparing with other existing tests, in particular, the LBI test by McCabe and Tremayne [(1995). Testing a time series for difference stationary. Ann. Statist. 23 (3), 1015-1028], which is for the null of a unit root process against the alternative of a stochastic unit root process.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Daisuke Nagakura,