Structural Dynamic Factor Analysis Using Prior Information From Macroeconomic Theory

Gregor Bäurle
Authors registered in the RePEc Author Service: Gregor Bäurle ()

Journal of Business & Economic Statistics, 2013, vol. 31, issue 2, 136-150

Abstract: Dynamic factor models are becoming increasingly popular in empirical macroeconomics due to their ability to cope with large datasets. Dynamic stochastic general equilibrium (DSGE) models, on the other hand, are suitable for the analysis of policy interventions from a methodical point of view. In this article, we provide a Bayesian method to combine the statistically rich specification of the former with the conceptual advantages of the latter by using information from a DSGE model to form a prior belief about parameters in the dynamic factor model. Because the method establishes a connection between observed data and economic theory and at the same time incorporates information from a large dataset, our setting is useful to study the effects of policy interventions on a large number of observed variables. An application of the method to U.S. data shows that a moderate weight of the DSGE prior is optimal and that the model performs well in terms of forecasting. We then analyze the impact of monetary shocks on both the factors and selected series using a DSGE-based identification of these shocks. Supplementary materials for this article are available online.

Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/07350015.2012.747839 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlbes:v:31:y:2013:i:2:p:136-150

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UBES20

DOI: 10.1080/07350015.2012.747839

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan

More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().