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A Gaussian approach for continuous time models of the short-term interest rate

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Author Info

  • JUN YU

    ()

  • PETER C. B. PHILLIPS

    ()

Abstract

This paper proposes a Gaussian estimator for nonlinear continuous time models of the short-term interest rate. The approach is based on a stopping time argument that produces a normalizing transformation facilitating the use of a Gaussian likelihood. A Monte Carlo study shows that the finite-sample performance of the proposed procedure offers an improvement over the discrete approximation method proposed by Nowman (1997). An em-pirical application to US and British interest rates is given.

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Bibliographic Info

Article provided by Royal Economic Society in its journal The Econometrics Journal.

Volume (Year): 4 (2001)
Issue (Month): 2 ()
Pages: 3

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Handle: RePEc:ect:emjrnl:v:4:y:2001:i:2:p:3

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Related research

Keywords: Gaussian Estimation; Continuous Time Models; Stochastic Differential Equation; Nonlinear Diffusion; Short-term Interest Rate; Normalizing Transformation; Maximum Likelihood; Level Effect.;

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Cited by:
  1. Huang, J. & Kobayashi, M. & McAleer, M.J., 2011. "Testing the Box-Cox Parameter for an Integrated Process," Econometric Institute Research Papers EI 2010-77, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. McCrorie, J. Roderick & Chambers, Marcus J., 2006. "Granger causality and the sampling of economic processes," Journal of Econometrics, Elsevier, vol. 132(2), pages 311-336, June.
  3. James E. Griffin & Mark F.J. Steel, 2002. "Inference With Non-Gaussian Ornstein-Uhlenbeck Processes for Stochastic Volatility," Econometrics 0201002, EconWPA, revised 04 Apr 2003.
  4. Chang, Yoosoon, 2004. "Taking a New Contour: A Novel Approach to Panel Unit Root Tests," Working Papers 2004-05, Rice University, Department of Economics.
  5. Terence D.Agbeyegbe & Elena Goldman, 2005. "Estimation of threshold time series models using efficient jump MCMC," Hunter College Department of Economics Working Papers 406, Hunter College: Department of Economics, revised 2005.

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