Hidden Bibliographic Details
| Varying Form of Title: | Data-rich dynamic stochastic general equilibrium and dynamic factor models
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| Other authors / contributors: | IMF Institute, issuing body.
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| ISBN: | 128356565X
9781283565653
9781463916602
1463916604
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| Notes: | At head of title: IMF Institute.
Title from PDF title page (IMF, viewed Jan. 10, 2011).
"September 2011."
Includes bibliographical references (pages 46-49).
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| Summary: | Dynamic factor models and dynamic stochastic general equilibrium (DSGE) models are widely used for empirical research in macroeconomics. The empirical factor literature argues that the co-movement of large panels of macroeconomic and financial data can be captured by relatively few common unobserved factors. Similarly, the dynamics in DSGE models are often governed by a handful of state variables and exogenous processes such as preference and/or technology shocks. Boivin and Giannoni (2006) combine a DSGE and a factor model into a data-rich DSGE model, in which DSGE states are factors and factor dynamics are subject to DSGE model implied restrictions. We compare a data-rich DSGE model with a standard New Keynesian core to an empirical dynamic factor model by estimating both on a rich panel of U.S. macroeconomic and financial data compiled by Stock and Watson (2008). We find that the spaces spanned by the empirical factors and by the data-rich DSGE model states are very close. This proximity allows us to propagate monetary policy and technology innovations in an otherwise non-structural dynamic factor model to obtain predictions for many more series than just a handful of traditional macro variables, including measures of real activity, price indices, labor market indicators, interest rate spreads, money and credit stocks, and exchange rates.
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| Other form: | Print version: Kryshko, Maxym. Data-Rich DSGE and Dynamic Factor Models. Washington : International Monetary Fund, ©2011 9781463903497
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