OUC Economic Research Paper series No.0601
A
modified Box-Cox transformation in the multivariate ARMA model |
| Takahiro
Terasaka1 and Yuzo
Hosoya2 |
1 Department of Economics, Otaru University of Commerce, 2 Department of Economics, Meisei University |
| Abstract |
The
Box-Cox transformation has been used as a simple method of transforming
dependent variable in ordinary-linear regression circumstances for improving
the Gaussian-likelihood fit and making the disturbance terms of a model
reasonably homoscedastic. The paper introduces a new version of the Box-Cox
transformation and investigates how it works in terms of asymptotic performance
and application, focusing in particular on inference on stationary multivariate
ARMA models. The paper proposes a computational estimation procedure which
extends the three-step Hannan and Rissanen method so as to accommodate
the transformation and, for the purpose of parameter testing, the paper
proposes a Monte-Carlo Wald test. The allied algorithm is applied to a
bivariate series of Tokyo stock-price index (Topix) and the call rate. |