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There is another reason Bayesian econometrics may be appealing in the absence of strong external knowledge. Econometrics models often describe complex economic theories and thus tend to have many parameters—often so many that it becomes infeasible to fit the models without incorporating some information about model parameters.
Nonlinear, joint, SEM-like, and more.
Assess heterogeneity
Finally, as we briefly mentioned earlier, the estimation precision in Bayesian analysis is not limited by the sample size—Bayesian simulation methods may provide an arbitrary degree of precision. Despite the conceptual and methodological advantages of the Bayesian approach, its application in practice is still considered controversial sometimes. There are two main reasons for this—the presumed subjectivity in specifying prior information and the computational challenges in implementing Bayesian methods. Along with the objectivity that comes from the data, the Bayesian approach uses potentially subjective prior distribution. That is, different individuals may specify different prior distributions. ation in practi
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