Moment Matching versus Bayesian Estimation: Backward-Looking Behaviour in a New-Keynesian Baseline Model

Stephen Sacht, Reiner Franke and Tae-Seok Jang

VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order from Verein für Socialpolitik / German Economic Association

Abstract: The paper considers an elementary New-Keynesian three equation model and compares its Bayesian estimation to the results from the method of moments (MM), which seeks to match a finite set of the model-generated second moments of in ation, output and the interest rate to their empirical counterparts. It is found that in the Great Ination (GI) period - though not in the Great Moderation (GM) - the two estimations imply a significantly different covariance structure. Regarding the parameters, special emphasis is placed on the degree of backward-looking behaviour in the Phillips curve. While, in line with much of the literature, it plays a minor role in the Bayesian estimations, MM yields values of the price indexation parameter close to or even at its maximal value of unity. For both GI and GM, these results are worth noticing since in (strong or, respectively, weak) contrast to the Bayesian parameters, the covariance matching thus achieved is entirely satisfactory.

JEL-codes: C52 E32 E37 (search for similar items in EconPapers)
Date: 2013
New Economics Papers: this item is included in nep-ecm and nep-mac
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https://www.econstor.eu/bitstream/10419/79694/1/VfS_2013_pid_231.pdf (application/pdf)

Related works:
Journal Article: Moment matching versus Bayesian estimation: Backward-looking behaviour in a New-Keynesian baseline model (2015)
Working Paper: Moment matching versus Bayesian estimation: Backward-looking behaviour in a New-Keynesian baseline model (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:vfsc13:79694

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