Testing AR(1) Against MA(1) Disturbances in the Linear Regression Model: An Alternative Procedure

Abstract

This paper is concerned with the problem of testing the hypothesis that the disturbances of a regression model are generated by a first-order autoregressive process against the alternative assumption that they follow a first-order moving average scheme. The test proposed has the advantages of requiring only ordinary least squares estimation and of being simple to implement. Some Monte Carlo results on the finite sample behaviour of the test are provided.