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Using Implied Probabilities to Improve Estimation with Unconditional Moment Restrictions

  • Alain Guay
  • Florian Pelgrin
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    In this paper, we investigate the information content of implied probabilities (Back and Brown, 1993) to improve estimation in unconditional moment conditions models. We propose and evaluate two 3-step euclidian empirical likelihood estimators and their bias-correction versions for weakly dependent data. The first one is the time series extension of the 3S-EEL proposed by Antoine, Bonnal and Renault (2007).The second one is new and uses in contrast only an estimator of the weighting matrix at an efficient 2-step GMM estimator, while leaving unrestricted the Jacobian matrix. Both estimators use implied probabilities to achieve higher-order improvements relative to the traditional GMM estimator. A Monte-Carlo study reveals that the finite and large sample properties of the (bias-corrected) 3-step estimators compare very favorably to the existing approaches: the 2-step GMM and the continuous updating estimator. As an application, we re-assess the empirical evidence regarding the New Keynesian Phillips curve in the US.

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    Paper provided by CIRPEE in its series Cahiers de recherche with number 0747.

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    Date of creation: 2007
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    Handle: RePEc:lvl:lacicr:0747
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    1. Rudd, Jeremy & Whelan, Karl, 2005. "New tests of the new-Keynesian Phillips curve," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1167-1181, September.
    2. Donald W.K. Andrews, 1988. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Cowles Foundation Discussion Papers 877R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1989.
    3. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-80, July.
    4. Guido W Imbens, Phillip Johnson & Richard H Spady, . "Information theoretic approaches to inference in moment condition model," Economics Papers W12., Economics Group, Nuffield College, University of Oxford.
    5. James M. Nason & Gregor W. Smith, 2005. "Identifying the New Keynesian Phillips curve," Working Paper 2005-01, Federal Reserve Bank of Atlanta.
    6. Galí, Jordi & Gertler, Mark & López-Salido, J David, 2001. "European Inflation Dynamics," CEPR Discussion Papers 2684, C.E.P.R. Discussion Papers.
    7. Patrik Guggenberger & Jinyong Hahn, 2005. "Finite Sample Properties of the Two-Step Empirical Likelihood Estimator," Econometric Reviews, Taylor & Francis Journals, vol. 24(3), pages 247-263.
    8. West, Kenneth D., 1997. "Another heteroskedasticity- and autocorrelation-consistent covariance matrix estimator," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 171-191.
    9. Jondeau, E. & Le Bihan, H., 2003. "ML vs GMM Estimates of Hybrid Macroeconomic Models (With an Application to the New Phillips Curve)," Working papers 103, Banque de France.
    10. Patrik Guggenberger & Richard Smith, 2005. "Generalized empirical likelihood tests in time series models with potential identification failure," CeMMAP working papers CWP01/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Stanislav Anatolyev, 2005. "GMM, GEL, Serial Correlation, and Asymptotic Bias," Econometrica, Econometric Society, vol. 73(3), pages 983-1002, 05.
    12. Susanne M. Schennach, 2007. "Point estimation with exponentially tilted empirical likelihood," Papers 0708.1874, arXiv.org.
    13. Hélène Bonnal & Éric Renault, 2004. "On the Efficient Use of the Informational Content of Estimating Equations: Implied Probabilities and Euclidean Empirical Likelihood," CIRANO Working Papers 2004s-18, CIRANO.
    14. Smith, Richard J., 2007. "Efficient information theoretic inference for conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 138(2), pages 430-460, June.
    15. Alastair R. Hall, 2000. "Covariance Matrix Estimation and the Power of the Overidentifying Restrictions Test," Econometrica, Econometric Society, vol. 68(6), pages 1517-1528, November.
    16. Imbens, G.W. & Johnson, P. & Spady, R.H., 1995. "Information Theoretic Approaches to Inference in Movement Condition Models," Economics Papers 99, Economics Group, Nuffield College, University of Oxford.
    17. Kenneth D. West & Whitney K. Newey, 1995. "Automatic Lag Selection in Covariance Matrix Estimation," NBER Technical Working Papers 0144, National Bureau of Economic Research, Inc.
    18. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    19. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
    20. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
    21. Robert E. Cumby & John Huizinga, 1990. "Testing The Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions," NBER Technical Working Papers 0092, National Bureau of Economic Research, Inc.
    22. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
    23. Joaquim J.S. Ramalho & Richard J. Smith, 2005. "Goodness of Fit Tests for Moment Condition Models," Economics Working Papers 5_2005, University of Évora, Department of Economics (Portugal).
    24. Lindé, Jesper, 2001. "Estimating New-Keynesian Phillips Curves: A Full Information Maximum Likelihood Approach," Working Paper Series 129, Sveriges Riksbank (Central Bank of Sweden), revised 30 Apr 2001.
    25. Ma, Adrian, 2002. "GMM estimation of the new Phillips curve," Economics Letters, Elsevier, vol. 76(3), pages 411-417, August.
    26. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, 01.
    27. Lynda Khalaf & Maral Kichian, 2004. "Estimating New Keynesian Phillips Curves Using Exact Methods," Working Papers 04-11, Bank of Canada.
    28. Kurmann, Andre, 2005. "Quantifying the uncertainty about the fit of a new Keynesian pricing model," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1119-1134, September.
    29. Buiter, Willem H & Jewitt, Ian, 1981. "Staggered Wage Setting with Real Wage Relativities: Variations on a Theme of Taylor," The Manchester School of Economic & Social Studies, University of Manchester, vol. 49(3), pages 211-28, September.
    30. Yuichi Kitamura & Michael Stutzer, 1997. "An Information-Theoretic Alternative to Generalized Method of Moments Estimation," Econometrica, Econometric Society, vol. 65(4), pages 861-874, July.
    31. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
    32. Bryan W. Brown & Whitney K. Newey, 1998. "Efficient Semiparametric Estimation of Expectations," Econometrica, Econometric Society, vol. 66(2), pages 453-464, March.
    33. Frank Kleibergen, 2002. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Econometrica, Econometric Society, vol. 70(5), pages 1781-1803, September.
    34. Back, Kerry & Brown, David P, 1993. "Implied Probabilities in GMM Estimators," Econometrica, Econometric Society, vol. 61(4), pages 971-75, July.
    35. Robinson, Peter M, 1988. "The Stochastic Difference between Econometric Statistics," Econometrica, Econometric Society, vol. 56(3), pages 531-48, May.
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