Bayesian Econometrics illustrates the scope and diversity of modern Bayesian econometric applications and highlights many desirable aspects of Bayesian inference and computations. It begins with an historical overview by Arnold Zellner who describes key contributions to the development of Bayesian econometrics and makes predictions for future directions. Then, in a second paper in the introductory section, Paolo Giordani and Robert Kohn make suggestions for improving Markov chain Monte Carlo computational strategies.