Bayesian dynamic panel models for tourism research

Abstract This paper describes several innovative dynamic panel data models that allow variations in slope coefficients both across time and cross-sectional units. We replace time variation with a dynamic (autoregressive) component and introduce several variations of the so-called Mundlak device in which random intercepts are linear function of the average values of the regressors. We develop all models in a Bayesian framework, and test their performance using an interesting application on the impact of advertising on firm sales. We provide technical details of all these models and present tools to compare their performance in a Bayesian framework. Moreover, model averaging and posterior model pools are presented to gain more insight into the relationship between advertising and sales.

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