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Clark, T.E. and McCracken, M.W., “Improving forecast accuracy by combining recursive and rolling forecasts,” IER, 50, 363-395. 2009.

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Article

Adjusting Band-Regression Estimators for Prediction: Shrinkage and Downweighting

1Department of Statistics and Operations Research, University of Vienna, Vienna, Austria


International Journal of Econometrics and Financial Management. 2015, Vol. 3 No. 3, 121-130
DOI: 10.12691/ijefm-3-3-3
Copyright © 2015 Science and Education Publishing

Cite this paper:
Erhard Reschenhofer, Marek Chudy. Adjusting Band-Regression Estimators for Prediction: Shrinkage and Downweighting. International Journal of Econometrics and Financial Management. 2015; 3(3):121-130. doi: 10.12691/ijefm-3-3-3.

Correspondence to: Erhard  Reschenhofer, Department of Statistics and Operations Research, University of Vienna, Vienna, Austria. Email: erhard.reschenhofer@univie.ac.at

Abstract

This paper proposes further developments of band-regression models for forecasting purposes, namely a simple method for shrinking the parameter estimates as well as a method for the automatic selection of the underlying frequency band. In combination with a method for downweighting older data, the improved band-regression model is used to forecast real GDP growth across nine industrialized economies. The results of this empirical study show that this forecasting approach outperforms conventional forecasting methods. As a secondary finding, the empirical results also raise doubts whether the yield-curve spread is really a valuable leading indicator of GDP growth.

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