Teaching Causal Inference in Undergraduate Econometrics

Abstract

This paper argues that the current way in which the undergraduate introductory econometrics course is taught is neither inline with current empirical practice nor very intuitive. It proposes a shift in focus of the course on causal inference using the Roy-Rubin Causal Model (RRCM). A second theme of the paper is the suggestion to use random regressors from the start to improve the ability of students to intuitively relate to the regression model and to enable the teacher to present many regression pitfalls under the umbrella of the non-zero covariance between regressors and the regression error term. Finally, the paper discusses how to make room for the new material and suggests ways of dealing with the added complexity of the approach.