Are Error-Correction Models Superior?
Author InfoMichael F. Bleaney Abstract The out-of-sample forecasting performance of error-correction models of exchange rates is tested on recent monthly data and on annual data from 1900 to 1995. The results for the monthly data set strongly favor the naive model, even when the series are pooled. In the annual data, the best model is usually a regression model of some form, but there is no evidence that a researcher can pick a regression model that outpredicts a naive model more often than not, either by choosing at random or by selecting the model that best fits past data. Download InfoTo download: If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
