Empirical Bayes Methods for Dynamic Factor Models

Siem Jan Koopman and Geert Mesters

The Review of Economics and Statistics, 2017, vol. 99, issue 3, 486-498

Abstract: We consider the dynamic factor model where the loading matrix, the dynamic factors, and the disturbances are treated as latent stochastic processes. We present empirical Bayes methods that enable the shrinkagebased estimation of the loadings and factors. We investigate the methods in a large Monte Carlo study where we evaluate the finite sample properties of the empirical Bayes methods for quadratic loss functions. Finally, we present and discuss the results of an empirical study concerning the forecasting of U.S. macroeconomic time series using our empirical Bayes methods.

Date: 2017
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Working Paper: Empirical Bayes Methods for Dynamic Factor Models (2014)
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