Simulated Likelihood Estimation of Affine Term Structure Models from Panel Data∗

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. ∗We thank Frank Diebold, Qiang Kang, and Ken Singleton for their comments. Financial support from the Rodney L. White Center for Financial Research at the Wharton School and the Department of Economics is gratefully acknowledged. †Philadelphia, PA 19104-6367. Phone: (215) 898-3609. E-mail: [email protected]. ‡Philadelphia, PA 19104-6297. Phone: (215) 898-0658. E-mail: [email protected].