Forecasting Random Walks Under Drift Instability

43 Pages Posted: 1 May 2008

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

Multiple version iconThere are 2 versions of this paper

Date Written: April 2008

Abstract

This paper considers forecast averaging when the same model is used but estimation is carried out over different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. It is shown that compared to using forecasts based on a single estimation window, averaging over estimation windows leads to a lower bias and to a lower root mean square forecast error for all but the smallest of breaks. Similar results are also obtained when observations are exponentially down-weighted, although in this case the performance of forecasts based on exponential down-weighting critically depends on the choice of the weighting coefficient. The forecasting techniques are applied to monthly inflation series of 21 OECD countries and it is found that average forecasting methods in general perform better than using forecasts based on a single estimation window.

Keywords: forecast combinations, averaging over estimation windows, exponentially down-weighting observations, structural breaks

JEL Classification: C22, C53

Suggested Citation

Pesaran, M. Hashem and Pick, Andreas, Forecasting Random Walks Under Drift Instability (April 2008). CESifo Working Paper Series No. 2293, Available at SSRN: https://ssrn.com/abstract=1126600

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

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
61
Abstract Views
919
rank
248,259
PlumX Metrics