The widespread use of prior information in formulating, estimating, and using econometric models is reviewed. Attempts to avoid the use of prior information by formulating multivariate statistical VAR and ARMA time series models for economic time series data have resulted in heavily over-parametrized models. A simple demand, supply, and entry model is presented to contrast models utilizing prior information provided by economic theory and other sources with multivariate statistical time series models. Formal Bayesian methods for incorporating prior information in econometric estimation, testing, and prediction are presented. A number of published applied Bayesian studies are cited in which Bayesian methods have proved to be effective. It is concluded that wise use of the Bayesian approach will produce improved econometric results.