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Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes

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Author Info
Markku Lanne (University of Helsinki)
Pentti Saikkonen

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Abstract

A new kind of mixture autoregressive model with GARCH errors is introduced and applied to the U.S. short-term interest rate. According to the diagnostic tests developed in the paper and further informal checks the model is capable of capturing both of the typical characteristics of the short-term interest rate: volatility persistence and the dependence of volatility on the level of interest rate. The model also allows for regime switches whose presence has been a third central result emerging from the recent empirical literature on the U.S. short-term interest rate. Realizations generated from the estimated model seem stable and their properties resemble those of the observed series closely. The drift and diffusion functions implied by the new model are in accordance with the results in much of the literature on continuous-time diffusion models for the short-term interest rate, and the term structure implications agree with historically observed patterns.

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Publisher Info
Paper provided by Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance in its series CeNDEF Workshop Papers, January 2001 with number PO5.

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Date of creation: 04 Jan 2001
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Handle: RePEc:ams:cdws01:po5

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  1. Lanne , Markku, 2002. "Nonlinear dynamics of interest rate and inflation," Research Discussion Papers 21/2002, Bank of Finland. [Downloadable!]
    Other versions:
  2. Mandler, Martin, 2007. "The Taylor rule and interest rate uncertainty in the U.S. 1970-2006," MPRA Paper 2340, University Library of Munich, Germany, revised May 2009. [Downloadable!]
  3. Luc Bauwens & Arie Preminger & Jeroen V.K. Rombouts, 2006. "Regime switching GARCH models," Cahiers de recherche 06-08, HEC Montréal, Institut d'économie appliquée. [Downloadable!]
    Other versions:
  4. Markus Haas & Stefan Mittnik & Bruce Mizrach, 2004. "Assessing Central Bank Credibility During the EMS Crises: Comparing Option and Spot Market-Based Forecasts," Departmental Working Papers 200424, Rutgers University, Department of Economics. [Downloadable!]
    Other versions:
  5. Tom Pak-wing Fong & Chun-shan Wong, 2008. "Stress Testing Banks' Credit Risk Using Mixture Vector Autoregressive Models," Working Papers 0813, Hong Kong Monetary Authority. [Downloadable!]
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