Optimal Forecasts in the Presence of Structural Breaks

55 Pages Posted: 27 Dec 2011

See all articles by M. Hashem Pesaran

M. Hashem Pesaran

University of Southern California - Department of Economics; University of Cambridge - Trinity College (Cambridge)

Andreas Pick

Erasmus University Rotterdam (EUR) - Department of Econometrics; De Nederlandsche Bank

Mikhail Pranovich

International Monetary Fund (IMF); University of Cambridge; Joint Vienna Insitute

Date Written: December 27, 2011

Abstract

This paper considers the problem of forecasting under continuous and discrete structural breaks and proposes weighting observations to obtain optimal forecasts in the MSFE sense. We derive optimal weights for continuous and discrete break processes. Under continuous breaks, our approach recovers exponential smoothing weights. Under discrete breaks, we provide analytical expressions for the weights in models with a single regressor and asymptotically for larger models. It is shown that in these cases the value of the optimal weight is the same across observations within a given regime and differs only across regimes. In practice, where information on structural breaks is uncertain a forecasting procedure based on robust weights is proposed. Monte Carlo experiments and an empirical application to the predictive power of the yield curve analyze the performance of our approach relative to other forecasting methods.

Keywords: forecasting, structural breaks, optimal weights, robust weights, exponential smoothing

JEL Classification: C22, C53

Suggested Citation

Pesaran, M. Hashem and Pick, Andreas and Pranovich, Mikhail, Optimal Forecasts in the Presence of Structural Breaks (December 27, 2011). De Nederlandsche Bank Working Paper No. 327, Available at SSRN: https://ssrn.com/abstract=1977191 or http://dx.doi.org/10.2139/ssrn.1977191

M. Hashem Pesaran (Contact Author)

University of Southern California - Department of Economics

3620 South Vermont Ave. Kaprielian (KAP) Hall 300
Los Angeles, CA 90089
United States

University of Cambridge - Trinity College (Cambridge) ( email )

United Kingdom

Andreas Pick

Erasmus University Rotterdam (EUR) - Department of Econometrics ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

De Nederlandsche Bank ( email )

PO Box 98
1000 AB Amsterdam
Amsterdam, 1000 AB
Netherlands

Mikhail Pranovich

International Monetary Fund (IMF) ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

University of Cambridge

Trinity Ln
Cambridge, CB2 1TN
United Kingdom

Joint Vienna Insitute

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Wien, A-1090
Austria

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