There is a large and rapidly growing causal inference literature, yet little is known about the
impact of heteroskedasticity in popular causal settings. In observational studies where the …

This dissertation comprises three chapters that expand upon Bayesian econometrics and
game theory. Chapter 1 integrates heteroskedasticity into various models including …

The likelihood function of simultaneous equation models for discrete data is derived as the
invariant distribution of a suitably defined Markov chain. The formulation dispenses with …

Generalized Linear Models (GLMs) are an important class of models that provide a unifying
framework for the analysis and estimation of several types response variables, including …

A conceptual framework for the analysis of dichotomous and ordinal polychotomous
responses within a penalized multivariate Generalized Linear Model is introduced. The …