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A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series

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Listed author(s):
  • George Monokroussos

Abstract

Estimating Limited Dependent Variable Time Series models through standard extremum methods can be a daunting computational task because of the need for integration of high order multiple integrals and/or numerical optimization of difficult objective functions. This paper proposes a classical Markov Chain Monte Carlo (MCMC) estimation technique with data augmentation that overcomes both of these problems. The asymptotic properties of the proposed estimator are established. Furthermore, a practical and flexible algorithmic framework for this class of models is proposed and is illustrated using simulated data, thus also offering some insight into the small-sample biases of such estimators. Finally, the versatility of the proposed framework is illustrated with an application of a dynamic tobit model for the Open Market Desk's Daily Reaction Function.

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File URL: http://www.albany.edu/economics/research/workingp/2009/mcmcldv.pdf
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Paper provided by University at Albany, SUNY, Department of Economics in its series Discussion Papers with number 09-07.

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Date of creation: 2009
Handle: RePEc:nya:albaec:09-07
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Department of Economics, BA 110 University at Albany State University of New York Albany, NY 12222 U.S.A.

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Fax: (518) 442-4736

Order Information: Postal: Department of Economics, BA 110 University at Albany State University of New York Albany, NY 12222 U.S.A.
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Find related papers by JEL classification:
  • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
  • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
  • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
  • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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  1. George Monokroussos, 2011. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43, pages 519-534, 03.
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  4. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
  5. Robert Jong & Ana María Herrera, 2011. "Dynamic Censored Regression and the Open Market Desk Reaction Function," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 228-237, April.
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  17. Pesaran, M Hashem & Samiei, Hossein, 1992. "An Analysis of the Determination of Deutsche Mark/French Franc Exchange Rate in a Discrete-Time Target-Zone Model," Economic Journal, Royal Economic Society, vol. 102(411), pages 388-401, March.
  18. Eichengreen, Barry & Watson, Mark W & Grossman, Richard S, 1985. "Bank Rate Policy under the Interwar Gold Standard: A Dynamic Probit Model," Economic Journal, Royal Economic Society, vol. 95(379), pages 725-745, September.
  19. Geweke, John & Keane, Michael, 2001. "Computationally intensive methods for integration in econometrics," Handbook of Econometrics,in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 56, pages 3463-3568 Elsevier.
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  22. Demiralp, Selva & Farley, Dennis, 2005. "Declining required reserves, funds rate volatility, and open market operations," Journal of Banking & Finance, Elsevier, vol. 29(5), pages 1131-1152, May.
  23. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
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Cited by:

  1. George Monokroussos, 2011. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43, pages 519-534, 03.
  2. George Monokroussos, 2006. "A Dynamic Tobit Model for the Open Market Desk's Daily Reaction Function," Computing in Economics and Finance 2006 390, Society for Computational Economics.

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