Nelson and Plosser Revisited: Evidence from Fractional ARIMA Models
In this study fractionally integrated ARIMA (ARFIMA) models are estimated using an extended version of Nelson and Plosser’s data set. The analysis employs’s maximum likelihood procedure. Such a parametric approach requires the model to be correctly specified in order for the estimates to be consistent. A model-selection procedure based on diagnostic tests on the residuals, together with several likelihood criteria, is adopted to determine the correct specification for each series. The results suggest that all series, except unemployment and bond yields, are integrated of order greater than one. Thus, the standard approach of taking first differences may result in stationary series with long memory behavior.
Copyright: © 2005 Guglielmo Maria Caporale and Luis A. Gil-Alana. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Non stationarity
- long memory
- ARFIMA models