We review the literature on robust Bayesian analysis as a tool for global sensitivity analysis and for statistical decision-making under ambiguity. We discuss the methods proposed in the literature, including the different ways of constructing the set of priors that are the key input of the...

There are a vast range of estimates for the effect of demographics on interest rates. I show that these magnitudes are not well-identified without data on capital and life-cycle consumption. However, these data are often omitted. Using nonparametric prior sensitivity analysis for an overlapping...

We propose a joint model to combine models for hospital visits and out-of-pocket medical expenditures. It allows for the presence of non-linear effects of covariates using splines to capture the effects of aging on healthcare demand. Sample heterogeneity is modeled robustly with the random...

This paper extends the Baltagi et al. (2018, 2021) static and dynamic ε-contamination papers to dynamic space-time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach departs from the...