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

Author

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

Abstract

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.

Suggested Citation

  • Greene, William H. & Gillman, Max & Harris, Mark N. & Spencer, Christopher, 2013. "The Tempered Ordered Probit (TOP) Model with an Application to Monetary Policy," CEI Working Paper Series 2013-04, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    • Handle: RePEc:hit:hitcei:2013-04
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    Cited by:

    1. Varotto, Silvia F. & Farah, Haneen & Toledo, Tomer & van Arem, Bart & Hoogendoorn, Serge P., 2018. "Modelling decisions of control transitions and target speed regulations in full-range Adaptive Cruise Control based on Risk Allostasis Theory," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 318-341.
    2. Greene, William & Harris, Mark N. & Knott, Rachel & Rice, Nigel, 2023. "Reporting heterogeneity in modeling self-assessed survey outcomes," Economic Modelling, Elsevier, vol. 124(C).
    3. William Greene & Mark N. Harris & Bruce Hollingsworth & Rachel Knott & Nigel Rice, 2016. "Reporting heterogeneity effects in modelling self reports of health," Working Papers 16-12, New York University, Leonard N. Stern School of Business, Department of Economics.
    4. Sarah Brown & Mark N. Harris & Christopher Spencer, 2020. "Modelling Category Inflation with Multiple Inflation Processes: Estimation, Specification and Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1342-1361, December.

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    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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