We develop an easy-to-implement method for forecasting a stationary auto-regressive fractionally integrated moving average (ARFIMA) process subject to structural breaks with unknown break dates. We show that an ARFIMA process subject to a mean shift and a change in the long memory parameter can...

This paper proposes an easy-to-implement approach to forecasting the multivariate long memory process on same realization and further examines its usefulness on forecasting multivariate volatility series. This procedure bases on the extension of the analysis of Lewis and Reinsel (1985) to the...

The collection in Volume 43 Part A of Advances in Econometrics serves as a tribute to Professor M. Hashem Pesaran. Hashem is one of the most innovative, influential, and productive econometricians of his generation, with over 200 papers published in leading scientific journals to his credit...

We explore the usefulness of combining opinion surveys with time-series data to forecast Japanese economy. We demonstrate that the businessmen's judgemental variables might summarize contemporaneous information beyond that of actual series. The combined models do yield substantially more...

This research demonstrates the success of the new CDAR-family global market integration indices in the prediction of equity returns, which have not been thoroughly investigated in the past. We comprehensively investigate the predictive ability of the new CDAR-family indices by means of commonly...