This study offers a simultaneous equations model of the birth process with seven endogenous variables: four birth inputs [maternal smoking (S), maternal drinking (D), first trimester prenatal care (PC), and maternal weight gain (WG)], and three birth outputs [gestational age (G), birth length...

This study offers a simultaneous equations model of the birth process with seven endogenous variables: Four birth inputs (maternal smoking, maternal drinking, first trimester prenatal care, and maternal weight gain) and three birth outputs (gestational age, birth length, and birth weight). The...

We develop a simultaneous equations model with four birth inputs (maternal smoking, maternal drinking, first trimester prenatal care, and maternal weight gain), three birth outputs (gestational age, birth length, and birth weight), and twenty-four exogenous variables, and employ the National...

This study offers a simultaneous equations model of the birth process with seven endogenous variables: four birth inputs (maternal smoking, maternal drinking, first trimester prenatal care, and maternal weight gain), and three birth outputs (gestational age, birth length, and birth weight). Our...

The goal of this study is to address directly the predictive value of birth inputs and outputs, particularly birth weight, for measures of early childhood development in a simultaneous equations modeling framework. Strikingly, birth outputs have virtually no structural/casual effects on early...

This paper employs the National Longitudinal Survey of Youth in the US to study the birth process. We develop a simultaneous equations model with seven endogenous variables: four birth inputs (maternal smoking, maternal drinking, first trimester prenatal care, and maternal weight gain), three...

Hierarchical relationships between risk factors are seldom taken into account in epidemiological studies though some authors stressed the importance of doing so, and proposed a conceptual framework in which each level of the hierarchy is modeled separately. The objective of this paper was to...

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 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...

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...