Abstract
Seemingly absent from the arsenal of currently available
"nearly efficient" testing procedures for the unit root hypothesis, i.e. tests
whose local asymptotic power functions are indistinguishable from the Gaussian
power envelope, is a test admitting a (quasi-)likelihood ratio interpretation. We
show that the likelihood ratio unit root test derived in a Gaussian AR(1) model
with standard normal innovations is nearly efficient in that model. Moreover,
these desirable properties carry over to more complicated models allowing for
serially correlated and/or non-Gaussian innovations.
"nearly efficient" testing procedures for the unit root hypothesis, i.e. tests
whose local asymptotic power functions are indistinguishable from the Gaussian
power envelope, is a test admitting a (quasi-)likelihood ratio interpretation. We
show that the likelihood ratio unit root test derived in a Gaussian AR(1) model
with standard normal innovations is nearly efficient in that model. Moreover,
these desirable properties carry over to more complicated models allowing for
serially correlated and/or non-Gaussian innovations.
| Originalsprog | Engelsk |
|---|---|
| Udgivelsessted | Aarhus |
| Udgiver | Institut for Økonomi, Aarhus Universitet |
| Antal sider | 16 |
| Status | Udgivet - 2009 |