1 College of Business, Shanghai University of Finance and Economics, Shanghai 200433, China · 2 Department of Marketing, The Chinese University of Hong Kong, Hong Kong SAR, China · 3 Department of Industrial Engineering and Operations Research & Department of Civil and Environmental Engineering, The University of Hong Kong, Hong Kong SAR, China · 4 Industry Collaborator
Abstract
This paper develops a Deep-DiD method that integrates two deep neural networks into a difference-in-differences framework to estimate heterogeneous treatment effects and applies it to optimizing platform creator selection.