Journal
INTERNATIONAL JOURNAL OF FORECASTING
Volume 27, Issue 2, Pages 224-237Publisher
ELSEVIER
DOI: 10.1016/j.ijforecast.2010.01.012
Keywords
Combining forecasts; Factor analysis; PLS; Principal components; SIR; Survey of Professional Forecasters
Categories
Ask authors/readers for more resources
This paper considers several methods of producing a single forecast from several individual ones. We compare standard but hard to beat combination schemes (such as the average of forecasts at each period, or consensus forecast and OLS-based combination schemes) with more sophisticated alternatives that involve dimension reduction techniques. Specifically, we consider principal components, dynamic factor models, partial least squares and sliced inverse regression. Our source of forecasts is the Survey of Professional Forecasters, which provides forecasts for the main US macroeconomic aggregates. The forecasting results show that partial least squares, principal component regression and factor analysis have similar performances (better than the usual benchmark models), but sliced inverse regression shows an extreme behavior (performs either very well or very poorly). (C) 2010 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available