Identification-Robust Minimum Distance Estimation of the New Keynesian Phillips Curve
AbstractLimited-information identification-robust methods on the indexation and price rigidity parameters of the new Keynesian Phillips curve yield very wide confidence intervals. Full-information methods impose more restrictions on the reduced-form dynamics, and thus make more efficient use of the information in the data. We propose identification-robust minimum distance methods for exploiting these additional restrictions and show that they yield considerably smaller confidence intervals for the coefficients of the model compared to their limited-information GMM counterparts. In contrast to previous studies that used GMM, we find evidence of partial but not full indexation, and we obtain sharper inference on the degree of price stickiness.
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Bibliographic InfoPaper provided by Tulane University, Department of Economics in its series Working Papers with number 0904.
Length: 20 pages
Date of creation: Feb 2009
Date of revision:
weak identification; minimum distance; GMM; Phillips curve;
Other versions of this item:
- Leandro M. Magnusson & Sophocles Mavroeidis, 2010. "Identification-Robust Minimum Distance Estimation of the New Keynesian Phillips Curve," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(2-3), pages 465-481, 03.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-02-22 (All new papers)
- NEP-CBA-2009-02-22 (Central Banking)
- NEP-ECM-2009-02-22 (Econometrics)
- NEP-MAC-2009-02-22 (Macroeconomics)
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- Hyeongwoo Kim & Masao Ogaki, 2011.
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