机器学习实验室博士生系列论坛（第十九期）——Instrumental variables and LATE in causal learning
报告人：Yujing Chen (PKU)
时间：2021-11-24 15:10-16:10
地点：北大理科一号楼1513会议室 & 腾讯会议 761 4699 1810
Abstract:
A lot of big questions in the social sciences deal with cause and effect. However, many of them cannot be studied using controlled randomized experiments due to practical and ethical considerations. This year’s Prize in Economic Sciences rewards three scholars: David Card, Joshua Angrist and Guido Imbens. They show that conclusions about cause and effect can be drawn from natural experiments. And their approach has spread to other fields and revolutionized empirical research.
In this talk, we will introduce the LATE framework by Angrist and Imbens, which merges the instrumental variables (IV) framework, common in economics, with the potential-outcomes framework for causal inference, common in statistics. Then give a briefly review of studies in economictrics. Moreover, we will give an overview on different research topics based on instrumental variables in machine learning.
