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A Dynamic Tobit Model for the Open Market Desk's Daily Reaction Function

Author

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  • George Monokroussos

    (Economics University at Albany, SUNY)

Abstract

A dynamic Tobit model with Time-varying parameters is proposed for the daily reaction function of the Open Market Desk of the US Federal Reserve. Such a model offers a more realistic depiction of the Desk's behavior than those of past contributions in the literature as it allows for both possible dynamics in the Desk's daily operations and for day-to-day time varying responses of the Desk to changing conditions in the reserves markets and in the short-term interest rates. Ensuing computational complications are overcome by employing Markov Chain Monte Carlo techniques for the estimation of the model. The results reveal a rich pattern of dynamic behavior by the Open Market Desk both inside the maintenance period and across maintenance periods and point towards a Desk which is highly adaptable to evolving conditions both in the economy in general and in the market for reserves in particular

Suggested Citation

  • 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.
    • Handle: RePEc:sce:scecfa:390
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    File URL: http://repec.org/sce2006/up.679.1141143200.pdf
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    References listed on IDEAS

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    1. Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649, Elsevier.
    2. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    3. George Monokroussos, 2013. "A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 71-105, June.
    4. Feinman, Joshua N, 1993. "Estimating the Open Market Desk's Daily Reaction Function," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 25(2), pages 231-247, May.
    5. Hamilton, James D, 1996. "The Daily Market for Federal Funds," Journal of Political Economy, University of Chicago Press, vol. 104(1), pages 26-56, February.
    6. Michael J. Dueker, 1999. "Measuring monetary policy inertia in target Fed funds rate changes," Review, Federal Reserve Bank of St. Louis, vol. 81(Sep), pages 3-10.
    7. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    8. Orphanides, Athanasios, 2004. "Monetary Policy Rules, Macroeconomic Stability, and Inflation: A View from the Trenches," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(2), pages 151-175, April.
    9. Lee, Lung-fei, 1999. "Estimation of dynamic and ARCH Tobit models," Journal of Econometrics, Elsevier, vol. 92(2), pages 355-390, October.
    10. George Monokroussos, 2011. "Dynamic Limited Dependent Variable Modeling and U.S. Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(2‐3), pages 519-534, March.
    11. 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.
    12. 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.
    13. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
    14. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
    15. Dueker, Michael, 1999. "Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs-Sampling Approach to the Bank Prime Rate," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 466-472, October.
    16. Michael Dueker & Katrin Wesche, 2003. "European Business Cycles: New Indices and Their Synchronicity," Economic Inquiry, Western Economic Association International, vol. 41(1), pages 116-131, January.
    17. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
    18. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
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    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates

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