Diffusion Indexes

67 Pages Posted: 8 Aug 2000  

James H. Stock

Harvard University - Department of Economics; National Bureau of Economic Research (NBER); Harvard University - Harvard Kennedy School (HKS)

Mark W. Watson

Princeton University - Woodrow Wilson School of Public and International Affairs; National Bureau of Economic Research (NBER)

Date Written: August 1998

Abstract

This paper considers forecasting a single time series using more predictors than there are time series observations. The approach is to construct a relatively few indexes, akin to diffusion indexes, which are weighted averages of the predictors, using an approximate dynamic factor model. Estimation is discussed for balanced and unbalanced panels. The estimated dynamic factors are (uniformly) consistent, even in the presence of time varying parameters and/or data contamination, and forecasts based on the estimated factors are efficient. In an application to forecasting U.S. inflation and industrial production using 224 monthly time series, these forecasts outperform various state-of-the-art benchmark models.

Suggested Citation

Stock, James H. and Watson, Mark W., Diffusion Indexes (August 1998). NBER Working Paper No. w6702. Available at SSRN: https://ssrn.com/abstract=226366

James H. Stock (Contact Author)

Harvard University - Department of Economics ( email )

Littauer Center
Cambridge, MA 02138
United States
617-496-0502 (Phone)
617-496-5960 (Fax)

National Bureau of Economic Research (NBER)

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Harvard University - Harvard Kennedy School (HKS) ( email )

79 John F. Kennedy Street
Cambridge, MA 02138
United States

Mark W. Watson

Princeton University - Woodrow Wilson School of Public and International Affairs ( email )

Princeton University
Princeton, NJ 08544-1021
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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