Instrumental variables with unordered treatments: Theory and evidence from returns to fields of study
无序多值处理的工具变量:理论与专业学习收益证据
We revisit the identification argument of Kirkeboen et al. (2016) who showed how one may combine instruments for multiple unordered treatments with information about individuals' ranking of these treatments to achieve identification while allowing for both observed and unobserved heterogeneity in treatment effects. We show that the key assumptions underlying their identification argument have testable implications. We also provide a new characterization of the bias that may…