TY - JOUR
T1 - Empirical Bayes Methods for Dynamic Factor Models
AU - Koopman, S.J.
AU - Mesters, G.
PY - 2017/7
Y1 - 2017/7
N2 - 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.
AB - 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.
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U2 - 10.1162/REST_a_00614
DO - 10.1162/REST_a_00614
M3 - Article
SN - 0034-6535
VL - 99
SP - 486
EP - 498
JO - Review of Economics and Statistics
JF - Review of Economics and Statistics
IS - 3
ER -