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Confronting Model Misspecification in Macroeconomics / Daniel F. Waggoner, Tao Zha.

NBER Working papers Available online

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Format:
Book
Author/Creator:
Waggoner, Daniel F.
Contributor:
National Bureau of Economic Research.
Zha, Tao.
Series:
Working Paper Series (National Bureau of Economic Research) no. w17791.
NBER working paper series no. w17791
Language:
English
Physical Description:
1 online resource: illustrations (black and white);
Place of Publication:
Cambridge, Mass. National Bureau of Economic Research 2012.
Summary:
We estimate a Markov-switching mixture of two familiar macroeconomic models: a richly parameterized DSGE model and a corresponding BVAR model. We show that the Markov-switching mixture model dominates both individual models and improves the fit considerably. Our estimation indicates that the DSGE model plays an important role only in the late 1970s and the early 1980s. We show how to use the mixture model as a data filter for estimation of the DSGE model when the BVAR model is not identified. Moreover, we show how to compute the impulse responses to the same type of shock shared by the DSGE and BVAR models when the shock is identified in the BVAR model. Our exercises demonstrate the importance of integrating model uncertainty and parameter uncertainty to address potential model misspecification in macroeconomics.
Notes:
Print version record
January 2012.

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