The relationship between two alternative approaches, instrumental variables and control function procedures, for estimating the impact of endogenous treatment effects are examined. Although it is well known that the two approaches generate comparable estimates, the relationship between the...

This paper presents some two-step estimators for a wide range of parametric panel data models with censored endogenous variables and sample selection bias. Our approach is to derive estimates of the unobserved heterogeneity responsible for the endogeneity/selection bias to include as additional...

Linear regression is a powerful tool for investigating the relationships between multiple variables by relating one variable to a set of variables. It can identify the effect of one variable while adjusting for other observable differences. For example, it can analyze how wages relate to gender,...