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Evaluating Structural Models for the U.S. Short Rate Using EMM and Particle Filters


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  • Drew Creal
  • Ying Gu
  • Eric Zivot


We combine the efficient method of moments with appropriate algorithms from the optimal filtering literature to study a collection of models for the U.S. short rate. Our models include two continuous-time stochastic volatility models and two regime switching models, which provided the best fit in previous work that examined a large collection of models. The continuous-time stochastic volatility models fall into the class of nonlinear, non-Gaussian state space models for which we apply particle filtering and smoothing algorithms. Our results demonstrate the effectiveness of the particle filter for continuous-time processes. Our analysis also provides an alternative and complementary approach to the reprojection technique of Gallant and Tauchen (1998) for studying the dynamics of volatility.

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Bibliographic Info

Paper provided by University of Washington, Department of Economics in its series Working Papers with number UWEC-2006-18.

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Date of creation: Aug 2006
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Handle: RePEc:udb:wpaper:uwec-2006-18

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