"This dissertation considers estimation and inference in three econometric models containing issues commonly encountered with observational data. Fundamental issues of self-selection, endogeneity, missing observations are pervasive in observational data. Moreover, often, the observations in a dataset are rarely statistically independent and have complex dependence structures. These issues can have a significant effect on the causal effect analysis and pose serious limitations on the popular... Show more"This dissertation considers estimation and inference in three econometric models containing issues commonly encountered with observational data. Fundamental issues of self-selection, endogeneity, missing observations are pervasive in observational data. Moreover, often, the observations in a dataset are rarely statistically independent and have complex dependence structures. These issues can have a significant effect on the causal effect analysis and pose serious limitations on the popular methodologies that either maintain restrictive assumptions and/or require complicated and computationally tedious solutions.The dissertation aims to apply control function method as the primary tool to design estimation procedures under relaxed distributional and functional form assumptions. I describe computationally simple solutions to these issues to obtain more precise results. These estimation procedures are obtained under relaxed distributional and functional form assumptions allowing a researcher to incorporate more variability (or heterogeneity)."--from abstract. Show less
