Bayesian limited-information analysis of nonlinear simultaneous equations systems

This paper presents a Bayesian limited-information estimation method that can be used to estimate a single nonlinear equation that forms part of a system of simultaneous equations. The method can be looked upon as the Bayesian counterpart of Amemiya's nonlinear limited-information maximum-likelihood estimator as well as a generalization of Drèze's Bayesian limited-information estimator for linear simultaneous equations systems. The method is illustrated by applying it to the problem of estimating a CES-production function which forms part of a complete model of firm behavior.