How Useful is Bagging in Forecasting Economic Time Series? A Case Study of Us CPI Inflation

37 Pages Posted: 30 Dec 2005

See all articles by Atsushi Inoue

Atsushi Inoue

Southern Methodist University

Lutz Kilian

Federal Reserve Banks - Federal Reserve Bank of Dallas; Centre for Economic Policy Research (CEPR)

Date Written: October 2005

Abstract

This paper explores the usefulness of bagging methods in forecasting economic time series from linear multiple regression models. We focus on the widely studied question of whether the inclusion of indicators of real economic activity lowers the prediction mean-squared error of forecast models of US consumer price inflation. We study bagging methods for linear regression models with correlated regressors and for factor models. We compare the accuracy of simulated out-of-sample forecasts of inflation based on these bagging methods to that of alternative forecast methods, including factor model forecasts, shrinkage estimator forecasts, combination forecasts and Bayesian model averaging. We find that bagging methods in this application are almost as accurate or more accurate than the best alternatives. Our empirical analysis demonstrates that large reductions in the prediction mean squared error are possible relative to existing methods, a result that is also suggested by the asymptotic analysis of some stylized linear multiple regression examples.

Keywords: Bootstrap aggregation, Bayesian model averaging, forecast combination, factor models, shrinkage estimation, forecast model selection, pre-testing

JEL Classification: C22, C52, C53

Suggested Citation

Inoue, Atsushi and Kilian, Lutz, How Useful is Bagging in Forecasting Economic Time Series? A Case Study of Us CPI Inflation (October 2005). CEPR Discussion Paper No. 5304, Available at SSRN: https://ssrn.com/abstract=872856

Atsushi Inoue

Southern Methodist University ( email )

Dallas, TX 75275
United States

Lutz Kilian (Contact Author)

Federal Reserve Banks - Federal Reserve Bank of Dallas ( email )

2200 North Pearl Street
PO Box 655906
Dallas, TX 75265-5906
United States

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom