期刊名称：Case Studies in Business, Industry and Government Statistics
印刷版ISSN：2152-372X
出版年度：2008
卷号：2
期号：1
页码：21-27
出版社：Bentley University
摘要：When correcting for autocorrelation, most econometrics texts suggest using a quasi-differencing procedure. A number of issues arise. First, it is found that the results from popular two-step procedures may differ dramatically from those obtained from iterative processes. Second, while it is true that most regression packages implement an iterative procedure, the methodology itself is not conveyed in a straightforward manner to students of econometrics. Third, given the various iterative methods in the literature, it is not always clear which method is superior. Fourth, for autocorrelated errors, the importance of the correction factor in simple forecasting is often overlooked. Finally, regression packages report an 2R that is not comparable to that from the Ordinary Least Squares (OLS) estimation. This paper succinctly outlines the procedure for performing iterative procedures, explicitly accounts for autocorrelation among errors when generating forecasts, and identifies the necessary transformations for making proper comparisons relating to2R.
