Combination forecasts of output growth in a seven-country data set

This paper uses forecast combination methods to forecast output growth in a seven‐country quarterly economic data set covering 1959–1999, with up to 73 predictors per country. Although the forecasts based on individual predictors are unstable over time and across countries, and on average perform wo...

Full description

Saved in:
Bibliographic Details
Published in:Journal of forecasting 2004-09, Vol.23 (6), p.405-430
Main Authors: Stock, James H., Watson, Mark W.
Format: Article
Language:English
Subjects:
Commodities
Consumer Price Index
Cross-national analysis
Data analysis
Datasets
Economic growth
Economic theory
Economics
forecast pooling
Forecasting
Forecasting techniques
Forecasts
GDP
Gross Domestic Product
high-dimensional forecasting
Interest rates
macroeconomic forecasting
Manycountries
Methods
Output
Productivity
Studies
Time series
time-varying parameters
Variables
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper uses forecast combination methods to forecast output growth in a seven‐country quarterly economic data set covering 1959–1999, with up to 73 predictors per country. Although the forecasts based on individual predictors are unstable over time and across countries, and on average perform worse than an autoregressive benchmark, the combination forecasts often improve upon autoregressive forecasts. Despite the unstable performance of the constituent forecasts, the most successful combination forecasts, like the mean, are the least sensitive to the recent performance of the individual forecasts. While consistent with other evidence on the success of simple combination forecasts, this finding is difficult to explain using the theory of combination forecasting in a stationary environment. Copyright © 2004 John Wiley & Sons, Ltd.
ISSN:0277-6693
1099-131X
DOI:10.1002/for.928