When the error terms are autocorrelated, the conventional t-tests for individual regression coefficients mislead us to over-rejection of the null hypothesis. We examine, by Monte Carlo experiments, the small sample properties of the unrestricted estimator ofρand of the estimator ofρrestricted by the null hypothesis. We compare the small sample properties of the Wald, likelihood ratio and Lagrange multiplier test statistics for individual regression coefficients. It is shown that when the null hypothesis is true, the unrestricted estimator ofρis biased. It is also shown that the Lagrange multiplier test using the maximum likelihood estimator ofρperforms better than the Wald and likelihood ratio tests.