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Assessing DSGE model nonlinearities

Author: S Boragan Aruoba; Luigi Bocola; Frank Schorfheide; National Bureau of Economic Research.
Publisher: Cambridge, Mass. : National Bureau of Economic Research, 2013.
Series: Working paper series (National Bureau of Economic Research), no. 19693.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
We develop a new class of nonlinear time-series models to identify nonlinearities in the data and to evaluate nonlinear DSGE models. U.S. output growth and the federal funds rate display nonlinear conditional mean dynamics, while inflation and nominal wage growth feature conditional heteroskedasticity. We estimate a DSGE model with asymmetric wage/price adjustment costs and use predictive checks to assess its  Read more...
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Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: S Boragan Aruoba; Luigi Bocola; Frank Schorfheide; National Bureau of Economic Research.
OCLC Number: 865476136
Notes: Title from http://www.nber.org/papers/19693 viewed December 16, 2013.
"December 2013."
Includes online appendix (A.15 p.).
Description: 1 online resource (45 pages) : illustrations.
Series Title: Working paper series (National Bureau of Economic Research), no. 19693.
Responsibility: S. Borağan Aruoba, Luigi Bocola, Frank Schorfheide.

Abstract:

We develop a new class of nonlinear time-series models to identify nonlinearities in the data and to evaluate nonlinear DSGE models. U.S. output growth and the federal funds rate display nonlinear conditional mean dynamics, while inflation and nominal wage growth feature conditional heteroskedasticity. We estimate a DSGE model with asymmetric wage/price adjustment costs and use predictive checks to assess its ability to account for nonlinearities. While it is able to match the nonlinear inflation and wage dynamics, thanks to the estimated downward wage/price rigidities, these do not spill over to output growth or the interest rate.

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