The finite sample properties of simultaneous equations' estimates and estimators Bayesian and non-Bayesian approaches

Abstract After discussing the need for good finite sample estimation procedures for simultaneous equations models and showing the inadequacies of asymptotically justified estimators, it is shown how the Bayesian method of moments (BMOM) provides an exact, finite sample analysis of unrestricted reduced form systems. Then optimal, finite sample estimates of structural coefficients are derived using three standard loss functions and they are compared to traditional Bayesian optimal estimates. Monte Carlo experimental evidence from four studies on the relative performance of Bayesian and non-Bayesian estimators is reviewed with the finding that the performance of Bayesian estimators is better.

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