NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Estimating Affine Multifactor Term Structure Models Using Closed-Form Likelihood Expansions

Yacine Aït-Sahalia, Robert Kimmel

NBER Technical Working Paper No. 286
Issued in December 2002
NBER Program(s):   TWP

We develop and implement a technique for closed-form maximum likelihood estimation (MLE) of multifactor affine yield models. We derive closed-form approximations to likelihoods for nine Dai and Singleton (2000) affine models. Simulations show our technique very accurately approximates true (but infeasible) MLE. Using US Treasury data, we estimate nine affine yield models with different market price of risk specifications. MLE allows non-nested model comparison using likelihood ratio tests; the preferred model depends on the market price of risk. Estimation with simulated and real data suggests our technique is much closer to true MLE than Euler and quasi-maximum likelihood (QML) methods.

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This paper was revised on March 5, 2010

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Document Object Identifier (DOI): 10.3386/t0286

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