A comparative study of finite sample properties of band spectrum regression estimators

Monte Carlo methods are used to compared the small sample properties of several approaches to seasonal adjustment when the objective is to estimate regression coefficients. The methods compared are band spectrum regression, the dummy variable method and the moving average method. The results seem to indicate that band spectrum regression will have superior small sample properties compared with the dummy variable method, which again seemto be preferable to ordinary least squares and to the moving average method.