Speaker: Myoung-jae Lee, Korea University

Time: 10:00-11:30 a.m., November 1, 2023, GMT+8

Venue: Chengze Campus, Room 131

Abstract:

For a binary treatment D, an outcome Y and covariates X, a linear model with a constant treatment effect is widely used, but the linear model is untenable if Y is a limited dependent variable (LDV) with a continuous covariate. Despite this problem, motivations to use a linear model are strong when D is endogenous, because dealing with a binary endogenous D and a LDV Y is particularly difficult unless a fully parametric approach is adopted. Hence, practitioners often apply instrumental variable estimator (IVE) to a linear model with a LDV Y. In this paper, firstly, we show that IVE with a binary instrument Z for D estimates a 'weighted average of X-heterogeneous effects on compliers' plus a bias term, where the bias is not zero in general unless a restrictive condition is met. Secondly, the bias can be reduced much by specifying the X-part in the linear model such that the X-part explains Z well, not necessarily Y. Thirdly, a modified IVE using the 'instrument residual' instead of Z has zero bias without the restrictive condition. An empirical analysis is provided to demonstrate these points.

Biography:

Professor Myoung-jae Lee is an econometrician/statistician in Korea University. He held regular positions in many universities around the world, including Penn State, Tilburg University, Chinese University of Hong Kong, and Australian National University. He published six single-authored books on micro-econometrics and treatment effect analysis, and more than 90 papers in SCI/SSCI-listed journals on economics, statistics, transportation, medicine, sociology and political science.  

Source: National School of Development