Estimating structural bond pricing models via simulated maximum likelihood

This paper describes how structural bond pricing models can be estimated using a Simulated Maximum Likelihood procedure developed by Durbin and Koopman (1997). The approach has the advantage that price data on any traded claim (such as bonds, equity, and credit default swaps), as well as information about the balance sheet (e.g. accounting data) can be used in the estimation, improving efficiency. Monte Carlo evidence as well as a small application to real data indicates that this approach is superior to both traditional estimation methods and recently proposed versions of Maximum Likelihood Estimation (Ericsson, Reneby 2002).

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