eCite Digital Repository
Forecast combinations under structural break uncertainty
Citation
Tian, J and Anderson, HM, Forecast combinations under structural break uncertainty, International Journal of Forecasting, 30, (1) pp. 161-175. ISSN 0169-2070 (2014) [Refereed Article]
Copyright Statement
Copyright 2014 Elsevier
DOI: doi:10.1016/j.ijforecast.2013.06.003
Abstract
This paper proposes two new weighting schemes that average forecasts based on different
estimation windows in order to account for possible structural change. The first scheme
weights the forecasts according to the values of reversed ordered CUSUM (ROC) test
statistics, while the second weighting method simply assigns heavier weights to forecasts
that use more recent information. Simulation results show that, when structural breaks
are present, forecasts based on the first weighting scheme outperform those based on
a procedure that simply uses ROC tests to choose and forecast from a single postbreak
estimation window. Combination forecasts based on our second weighting scheme
outperform equally weighted combination forecasts. An empirical application based on a
NAIRU Phillips curve model for the G7 countries illustrates these findings, and also shows
that combination forecasts can outperform the random walk forecasting model.
Item Details
Item Type: | Refereed Article |
---|---|
Keywords: | Bias–variance trade-offs, Choice of estimation windows, Inflation forecasts, Parameter shifts, Reversed order CUSUM tests, Weighted forecats |
Research Division: | Economics |
Research Group: | Econometrics |
Research Field: | Economic models and forecasting |
Objective Division: | Economic Framework |
Objective Group: | Macroeconomics |
Objective Field: | Monetary policy |
UTAS Author: | Tian, J (Dr Jing Tian) |
ID Code: | 92792 |
Year Published: | 2014 |
Web of Science® Times Cited: | 18 |
Deposited By: | TSBE |
Deposited On: | 2014-06-27 |
Last Modified: | 2018-03-07 |
Downloads: | 0 |
Repository Staff Only: item control page