LAD estimation with random coefficient autocorrelated errors

摘要

In this paper we compare the performance of LAD and OLS in the linear regression model with errors which are randomly autocorrelated. This model yields thick-tailed error distributions which make profitable to estimate the model by LAD. The LAD estimator for randomly autocorrelated errors is proved to be asymptotically normal. The Monte Carlo results show that LAD improves upon OLS, unless we revert to a constant autocorrelation model, where the two methods are comparable.