Simulated Likelihood Estimation of Affine Term Structure Models from Panel Data
36 Pages Posted: 23 Feb 2006
Date Written: February 18, 2006
Abstract
We show how to estimate affine term structure models from a panel of noisy bond yields using simulated maximum likelihood based on importance sampling. We approximate the likelihood function of the state-space representation of the model by correcting the likelihood function of a Gaussian first-order approximation for the non-normalities introduced by the affine factor dynamics. Depending on the accuracy of the correction, which is computed through simulations, the quality of the estimator ranges from quasi-maximum likelihood (no correction) to exact maximum likelihood as the simulation size grows.
Keywords: Term Structure, State-Space Representation, Importance Sampling, Simulated Likelihood
JEL Classification: C13, C15, G13
Suggested Citation: Suggested Citation
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