Whereas child mortality has been decreased globally in the last 20 years, high levels persist in Sub-Saharan Africa. This paper analyzes child mortality in 25 Sub-Saharan countries based on household survey data. We employ a new multilevel approach with structured additive predictor within the...

This paper develops new econometric methods to estimate hospital quality and other models with discrete dependent variables and non-random selection. Mortality rates in patient discharge records are widely used to infer hospital quality. However, hospital admission is not random and some...

We develop a Markov Chain Monte Carlo algorithm for estimating nested logit models in a Bayesian framework. Appropriate "heating target" and reparametrization techniques are adopted for fast mixing. For illustrative purposes, we have implemented the algorithm on two real-life examples involving...

We develop a Markov Chain Monte Carlo algorithm for estimating nested logit models in a Bayesian framework. Appropriate "heating target" and reparametrization techniques are adopted for fast mixing. For illustrative purposes, we have implemented the algorithm on two real-life examples involving...

Early work on consumer health insurance preference modeling suggests that workers sorting among employment alternatives reflect their tastes for employment-sponsored health insurance. Focusing on examining the role of health insurance preferences on enrollment decisions into employment sponsored...

This paper uses Hierarchical Bayes Models to model and estimate spatial health effects in Germany. We combine rich individual-level household panel data from the German SOEP with administrative county-level data to estimate spatial county-level health dependencies. As dependent variable we use...

This paper makes use of Hierarchical Bayes Models to model and estimate spatial health effects. We focus on Germany, combining rich individual-level household panel data with administrative county level information to estimate spatial county-level health dependencies. As dependent variable, we...

This paper uses Hierarchical Bayes Models to model and estimate spatial health effects in Germany. We combine rich individual-level household panel data from the German SOEP with administrative county-level data to estimate spatial county-level health dependencies. As dependent variable we use...

Social interactions are generally thought to play an important role in smoking initiation among adolescents. In this paper we exploit detailed friendship nominations in the US Add Health data, and extend the Spatial Autoregressive Model (SAR) model to deal with (i) endogenous peer selection, and...

Social interactions are widely recognized to play an important role in smoking initiation among adolescents. In this paper, we hypothesize that emotionally stable, conscientious individuals are better able to resist peer pressure in the uptake of smoking. We exploit detailed friendship...