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Are New Keynesian Phillips Curves Identified ?

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  • Maral Kichian
  • Jean-Marie Dufour
  • Lynda Khalaf

Abstract

In this paper we use optimal-instrument and new finite-sample methods to test the empirical relevance of the New Keynesian Phillips curve (NKPC) equation. Unlike generalized method of moments-based methods, these generalized Anderson-Rubin tests are immune to the presence of weak instruments, and allow, by construction, to assess the identification status of a model. Our results are illustrated using the Gali-Gertler (1999) NKPC specifications and data, as well as a survey-based inflation expectation series from the Philadelphia Fed. Our test rejects the reported Gali-Gertler estimates, conditional on their choice of instruments. Nevertheless, and in contrast to Ma (2002), we do obtain relatively informative confidence sets. This provides support for NKPC equations and illustrates the usefulness of using exact procedures and optimal instruments in IV-based estimations. In particular, our results reveal that firms fix prices in a predominantly backward-looking manner, but that they adjust prices every quarter or so. Furthermore, the outcomes indicate that it is difficult to pin-point the extent of the importance of marginal costs for the inflation process.

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Bibliographic Info

Paper provided by Econometric Society in its series Econometric Society 2004 North American Summer Meetings with number 424.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:nasm04:424

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Keywords: NKPC; Anderson-Rubin Test; Weak Instruments; Optimal instruments;

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References

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  1. DUFOUR, Jean-Marie & KHALAF, Lynda, 2000. "Simulation-Based Finite and Large Sample Tests in Multivariate Regressions," Cahiers de recherche, Universite de Montreal, Departement de sciences economiques 2000-10, Universite de Montreal, Departement de sciences economiques.
  2. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, Econometric Society, vol. 65(3), pages 557-586, May.
  3. Kleibergen, F.R. & Zivot, E., 1998. "Bayesian and classical approaches to instrumental variable regression," Econometric Institute Research Papers EI 9835, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  4. Jeff Fuhrer & George Moore, 1993. "Inflation persistence," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 93-17, Board of Governors of the Federal Reserve System (U.S.).
  5. Ma, Adrian, 2002. "GMM estimation of the new Phillips curve," Economics Letters, Elsevier, Elsevier, vol. 76(3), pages 411-417, August.
  6. Jordi Gali & Mark Gertler, 2000. "Inflation Dynamics: A Structural Econometric Analysis," NBER Working Papers 7551, National Bureau of Economic Research, Inc.
  7. Zivot, E & Startz, R & Nelson, C-R, 1997. "Valid Confidence Intervals and Inference in the Presence of Weak Instruments," Working Papers, University of Washington, Department of Economics 97-17, University of Washington, Department of Economics.
  8. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(4), pages 518-29, October.
  9. Marcelo J. Moreira, 2003. "A General Theory of Hypothesis Testing in the Simultaneous Equations Model," Harvard Institute of Economic Research Working Papers, Harvard - Institute of Economic Research 1992, Harvard - Institute of Economic Research.
  10. Jordi Galí & Mark Gertler & J. David López-Salido, 2000. "European Inflation Dynamics," Banco de Espa�a Working Papers 0020, Banco de Espa�a.
  11. Lynda Khalaf & Jean-Marie Dufour, 2004. "Simulation-Based Finite-Sample Inference in Simultaneous Equations," Econometric Society 2004 North American Summer Meetings, Econometric Society 239, Econometric Society.
  12. DUFOUR, Jean-Marie & TAAMOUTI, Mohamed, 2003. "Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments," Cahiers de recherche, Universite de Montreal, Departement de sciences economiques 2003-10, Universite de Montreal, Departement de sciences economiques.
  13. Jiahui Wang & Eric Zivot, 1998. "Inference on Structural Parameters in Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, Econometric Society, vol. 66(6), pages 1389-1404, November.
  14. DUFOUR, Jean-Marie, 2003. "Identification, Weak Instruments and Statistical Inference in Econometrics," Cahiers de recherche, Centre interuniversitaire de recherche en économie quantitative, CIREQ 10-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  15. Dufour, Jean-Marie & Jasiak, Joann, 2001. "Finite Sample Limited Information Inference Methods for Structural Equations and Models with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(3), pages 815-43, August.
  16. Jean-Marie Dufour, 2003. "Identification, Weak Instruments and Statistical Inference in Econometrics," CIRANO Working Papers, CIRANO 2003s-49, CIRANO.
  17. Jeffrey C. Fuhrer, 1995. "The [un]importance of forward-looking behavior in price specifications," Working Papers, Federal Reserve Bank of Boston 95-6, Federal Reserve Bank of Boston.
  18. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, Econometric Society, vol. 65(6), pages 1365-1388, November.
  19. Frank Kleibergen, 2000. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Tinbergen Institute Discussion Papers 00-055/4, Tinbergen Institute.
  20. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, Econometric Society, vol. 68(5), pages 1055-1096, September.
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Cited by:
  1. Sandeep Mazumder, 2008. "The New Keynesian Phillips Curve and the Cyclicality of Marginal Cost," Economics Working Paper Archive, The Johns Hopkins University,Department of Economics 545, The Johns Hopkins University,Department of Economics.
  2. Sophocles Mavroeidis, 2006. "Testing the New Keynesian Phillips Curve Without Assuming Identification," Working Papers 2006-13, Brown University, Department of Economics.

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