Before revision: Many economic studies use shift-share instruments to estimate causal effects of a treatment . Often, this type of instrument implies that all shares fulfill an exclusion restriction, making the identifying assumption very strict. In this paper , I propose the use of machine learning methods that allow to substantially relax the exclusion restriction , by selecting invalid shares.
After revision: Many economic studies use shift-share instruments to estimate causal effects of a treatment . Often, this type of instrument implies that all shares fulfill an exclusion restriction, making the identifying assumption strict. This paper proposes to use methods that relax the exclusion restriction , by selecting invalid shares.