The widely used Cochrane-Orcutt and Hildreth-Lu procedures for estimating the parameters of a linear regression model with first-order serial correlation typically ignore the first observation. An alternative maximum likelihood procedure is recommended in this paper. This procedure is preferable to conventional ones on theoretical grounds, and sampling experiments suggest that it may yield substantially better estimates in some circumstances.