Bayesian methods have become widespread in the marketing literature. We review the essence of the Bayesian approach and explain why it is particularly useful for marketing problems. While the appeal of the Bayesian approach has long been noted by researchers, recent developments in computational...

This paper investigates the role of persuasion mechanisms in collective decision-making. A persuasion mechanism consists of a family of conditional distributions over the underlying state space and the generated noisy signals. A biased, perfectly informed sender adopts a persuasion mechanism to...

Hierarchical Bayes models free researchers from computational constraints and allow for the development of more realistic models of buyer behavior and decision making. Moreover, this freedom enables exploration of marketing problems that have proven elusive over the years, such as models for...

We develop a new method to sample from posterior distributions in hierarchical models without using Markov chain Monte Carlo. This method, which is a variant of importance sampling ideas, is generally applicable to high-dimensional models involving large data sets. Samples are independent, so...

Firms use aggregate data from data brokers (e.g., Acxiom, Experian) and external data sources (e.g., Census) to infer the likely characteristics of consumers and thus better predict consumers' profiles and needs, unobtrusively. We demonstrate that the simple count method most commonly used in...

Estimated dynamic stochastic equilibrium (DSGE) models are now widely used for empirical research in macroeconomics as well as for quantitative policy analysis and forecasting at central banks around the world. This paper reviews recent advances in the estimation and evaluation of DSGE models,...

This paper analyzes to what extent changes in monetary policy regimes influence the business cycle in a small open economy and investigates the impact of policy breaks on the estimation procedure. We estimate a DSGE model on Swedish data, explicitly taking into account the monetary regime change...

This paper analyzes to what extent changes in monetary policy regimes influence the business cycle in a small open economy and investigates the impact of policy breaks on the estimation procedure. We estimate a DSGE model on Swedish data, explicitly taking into account the monetary regime change...

Bayesian inference requires an analyst to set priors. Setting the right prior is crucial for precise forecasts. This paper analyzes how optimal prior changes when an economy is hit by a recession. For this task, an autoregressive distributed lag model is chosen. The results show that a sharp...

This paper proposes a simple method to structurally estimate a model over a period of time containing a regime shift. It then evaluates to which degree it is relevant to explicitly acknowledge the break in the estimation procedure. We apply our method on Swedish data, and estimate a DSGE model...