Methods of structural inference are applied to the linear regression model in which the errors follow an autoregressive process. A marginal likelihood function is derived for the autoregressive parameters while structural distributions are obtained for the regression parameters. The marginal likelihood function, in the case of a Markov error process, is shown to be related under certain conditions to the Durbin-Watsonstatistic. This method of inference is illustrated by a simulated example.