Econometrics · 2019 · 20 citations · 16 references
Social SciencesBiostatisticsEconomicsCausal InferenceEconometricsLabor EconomicsCausal Effect EstimationIncome DistributionInstrumental VariablesTreatment EffectsEconometric IdentificationInstrumental Variable AnalysisInstrumental Variables EstimationInstrumental Variables Quantile RegressionNonparametric Instrumental VariablesNonparametric Quantile RegressionRandom ForestsVariable Importance Analysis
We propose an econometric procedure based mainly on the generalized random forests method. Not only does this process estimate the quantile treatment effect nonparametrically, but our procedure yields a measure of variable importance in terms of heterogeneity among control variables. We also apply the proposed procedure to reinvestigate the distributional effect of 401(k) participation on net financial assets, and the quantile earnings effect of participating in a job training program.
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Leo Breiman · Machine Learning · 2001 · 126.2K citations · Full text
Double/debiased machine learning for treatment and structural parameters
Victor Chernozhukov, Denis Chetverikov, Mert Demirer et al. · Econometrics Journal · 2017 · 2.5K citations · Full text