Specification and Estimation of Bayesian Dynamic Factor Models: A Monte Carlo Analysis with an Application to Global House Price Comovement

46 Pages Posted: 20 Oct 2015 Last revised: 3 Jan 2019

See all articles by Laura E. Jackson

Laura E. Jackson

Bentley University - Department of Economics

M. Ayhan Kose

World Bank; Brookings Institution; Centre for Economic Policy Research (CEPR); Australian National University (ANU)

Chris Otrok

University of Missouri; Federal Reserve Banks - Federal Reserve Bank of St. Louis

Michael Owyang

Federal Reserve Bank of St. Louis - Research Division

Date Written: 2015-08-26

Abstract

We compare methods to measure comovement in business cycle data using multi-level dynamic factor models. To do so, we employ a Monte Carlo procedure to evaluate model performance for different specifications of factor models across three different estimation procedures. We consider three general factor model specifications used in applied work. The first is a single- factor model, the second a two-level factor model, and the third a three-level factor model. Our estimation procedures are the Bayesian approach of Otrok and Whiteman (1998), the Bayesian state space approach of Kim and Nelson (1998) and a frequentist principal components approach. The latter serves as a benchmark to measure any potential gains from the more computationally intensive Bayesian procedures. We then apply the three methods to a novel new dataset on house prices in advanced and emerging markets from Cesa-Bianchi, Cespedes, and Rebucci (2015) and interpret the empirical results in light of the Monte Carlo results.

Keywords: principal components, Kalman filter, data augmentation, business cycles

JEL Classification: C3

Suggested Citation

Jackson Young, Laura and Kose, M. Ayhan and Otrok, Christopher and Owyang, Michael T., Specification and Estimation of Bayesian Dynamic Factor Models: A Monte Carlo Analysis with an Application to Global House Price Comovement (2015-08-26). FRB St. Louis Working Paper No. 2015-31, Available at SSRN: https://ssrn.com/abstract=2676521

Laura Jackson Young (Contact Author)

Bentley University - Department of Economics ( email )

175 Forest Street
Waltham, MA 02452-4705
United States

M. Ayhan Kose

World Bank ( email )

1818 H Street, NW
Washington, DC 20433
United States

Brookings Institution ( email )

1775 Massachusetts Ave, NW
Washington, DC 20036
United States

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

Australian National University (ANU) ( email )

Canberra, Australian Capital Territory 2601
Australia

Christopher Otrok

University of Missouri ( email )

118 Professional Building
Columbia, MO 65211
United States

Federal Reserve Banks - Federal Reserve Bank of St. Louis ( email )

411 Locust St
Saint Louis, MO 63011
United States

Michael T. Owyang

Federal Reserve Bank of St. Louis - Research Division ( email )

411 Locust St
Saint Louis, MO 63011
United States

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