Empirical Bayes Methods for Dynamic Factor Models

Siem Jan Koopman; Geert Mesters

doi:10.1162/rest_a_00614

Empirical Bayes Methods for Dynamic Factor Models

Siem Jan Koopman¹; Geert Mesters²

¹ VU University Amsterdam, Tinbergen Institute, and CREATES, Aarhus University · ² Universitat Pompeu Fabra, Barcelona GSE and Netherlands Institute for the Study of Crime and Law Enforcement

The Review of Economics and Statistics 2017 open access

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.

DOI: 10.1162/rest_a_00614
Volume: 99 (3)
Pages: 486-498
Language: en
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