This paper integrates panel VARs and the index models into a unique framework where cross unit interdependencies and time variations in the coefficients are allowed for. The setup used is Bayesian and MCMC methods are used to estimate the posterior distribution of the features of interest and to...

Market response models help managers understand how customers collectively respond to marketing activities, and how competitors interact. When appropriately estimated, market response models can be a basis for improved marketing decision-making. Market response models can be broadly classi.ed...

En génétique des populations, les modèles sont souvent complexes ce qui rend l'évaluation de la vraisemblance difficile, si ce n'est impossible. En revanche, des mécanismes de génération de données sont parfois disponibles ce qui explique pourquoi les méthodes d'inférence bayésienne...

We investigate the relationship between monetary policy and inflation dynamics in the US using a medium scale structural model. The specification is estimated with Bayesian techniques and fits the data reasonably well. Policy shocks account for a part of the decline in inflation volatility;...

We develop a structural demand model that endogenously captures the effect of out-of-stocks on customer choice by simulating a time-varying set of available alternatives. Our estimation method uses store-level data on sales and partial information on product availability. Our model allows for...