What, Why, and How: An Empiricist’s Guide to Double/Debiased Machine Learning
- Bowen Shi,
Bowen Shi
[email protected]School of Economics and Management, Tsinghua University, Beijing 100084, China
- Xiaojie Mao ,
Corresponding Author
Xiaojie Mao
[email protected]https://orcid.org/0000-0003-2985-1741
School of Economics and Management, Tsinghua University, Beijing 100084, China; and Research Center for Contemporary Management, Tsinghua University, Beijing 100084, China
- Mochen Yang ,
Mochen Yang
[email protected]https://orcid.org/0000-0001-5101-9041
Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455
- Bo Li
Bo Li
[email protected]https://orcid.org/0000-0001-5599-8857
School of Economics and Management, Tsinghua University, Beijing 100084, China
Bowen Shi
[email protected]School of Economics and Management, Tsinghua University, Beijing 100084, China
Corresponding Author
Xiaojie Mao
[email protected]https://orcid.org/0000-0003-2985-1741
School of Economics and Management, Tsinghua University, Beijing 100084, China; and Research Center for Contemporary Management, Tsinghua University, Beijing 100084, China
Mochen Yang
[email protected]https://orcid.org/0000-0001-5101-9041
Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455
Bo Li
[email protected]https://orcid.org/0000-0001-5599-8857
School of Economics and Management, Tsinghua University, Beijing 100084, China

