In recent years there has been a growing stream of literature in marketing and economics that models consumers as Bayesian learners. Such learning behavior is often embedded within a discrete choice framework which is then calibrated on scanner panel data. At the same time it is now accepted...

"Bayesian statistics can help to provide unique insights into important issues in many fields. Bayesian statistics is not new, but traditionally it has not been widely taught as it is computationally challenging and there were criticisms surrounding the subjectivity of Bayesian methods. As...

This article proposes a distributed Markov chain Monte Carlo (MCMC) algorithm for estimating Bayesian hierarchical models when the number of cross-sectional units is very large and the objects of interest are the unit-level parameters. The two-stage algorithm is asymptotically exact, retains the...