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. I apply the methods to simulated data and the estimation of the effects of trade exposure and immigration on wages . After removing shares selected as endogenous, the positive effects of immigration decrease while the effects of Chinese import exposure are not affected .
Many economic studies use shift-share instruments to estimate causal effects . Often, all shares need to fulfill an exclusion restriction, making the identifying assumption strict. This paper proposes to use methods that relax the exclusion restriction by selecting invalid shares. I apply the methods in simulations and two empirical examples: the effect of immigration on wages and of Chinese import exposure on employment. I find that weak instruments and strong violations of the exclusion restriction do not worsen the performance of the estimators. In both applications, the coefficients change considerably but this is reconcilable with the arguments made in the literature .
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of a treatment
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this type of instrument implies that all shares
all shares need to
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very strict. In this paper , I propose the use of machine learning methods that allow to substantially
strict. This paper proposes to use methods that
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,
R
to simulated data and the estimation of the effects of trade exposure and
in simulations and two empirical examples: the effect of
R
. After removing shares selected as endogenous, the positive effects of immigration decrease while the effects of
and of
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are not affected
on employment. I find that weak instruments and strong violations of the exclusion restriction do not worsen the performance of the estimators. In both applications, the coefficients change considerably but this is reconcilable with the arguments made in the literature