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The Tempered Ordered Probit (TOP) Model with an Application to Monetary Policy

  • Greene, William H.
  • Gillman, Max
  • Harris, Mark N.
  • Spencer, Christopher

We propose a Tempered Ordered Probit (TOP) model. Our contribution lies not only in explicitly accounting for an excessive number of observations in a given choice category - as is the case in the standard literature on inflated models; rather, we introduce a new econometric model which nests the recently developed Middle Inflated Ordered Probit (MIOP) models of Bagozzi and Mukherjee (2012) and Brooks, Harris, and Spencer (2012) as a special case, and further, can be used as a specification test of the MIOP, where the implicit test is described as being one of symmetry versus asymmetry. In our application, which exploits a panel data-set containing the votes of Bank of England Monetary Policy Committee (MPC) members, we show that the TOP model affords the econometrician considerable flexibility with respect to modeling the impact of different forms of uncertainty on interest rate decisions. Our findings, we argue, reveal MPC members. asymmetric attitudes towards uncertainty and the changeability of interest rates.

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File URL: http://hermes-ir.lib.hit-u.ac.jp/rs/bitstream/10086/25891/1/wp2013-4.pdf
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Paper provided by Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University in its series CEI Working Paper Series with number 2013-04.

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Length: 34, 14 p.
Date of creation: Sep 2013
Date of revision:
Handle: RePEc:hit:hitcei:2013-04
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  1. RIBONI, Alessandro & RUGE-MURCIA, Francisco J., 2007. "Preference Heterogeneity in Monetary Policy Committees," Cahiers de recherche 2007-05, Universite de Montreal, Departement de sciences economiques.
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  7. Christopher Martin & Costas Milas, 2005. "Uncertainty and Monetary Policy Rules in the United States," Keele Economics Research Papers KERP 2005/10, Centre for Economic Research, Keele University.
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  11. Gerlach-Kristen, Petra, 2008. "Taking two steps at a time: On the optimal pattern of policy interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 32(2), pages 550-570, February.
  12. RIBONI, Alessandro & RUGE-MURCIA, Francisco J., 2011. "Dissent in Monetary Policy Decisions," Cahiers de recherche 06-2011, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
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  26. Dolado, Juan J & Maria-Dolores, Ramon, 2002. " Evaluating Changes in the Bank of Spain's Interest Rate Target: An Alternative Approach Using Marked Point Processes," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(2), pages 159-82, May.
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  34. Allen, Stuart D & Bray, Jeremy & Seaks, Terry G, 1997. " A Multinomial Logit Analysis of the Influence of Policy Variables and Board Experience on FOMC Voting Behavior," Public Choice, Springer, vol. 92(1-2), pages 27-39, July.
  35. Swanson, Eric T., 2004. "Signal Extraction And Non-Certainty-Equivalence In Optimal Monetary Policy Rules," Macroeconomic Dynamics, Cambridge University Press, vol. 8(01), pages 27-50, February.
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