Causal Random Forests Model Using Instrumental Variable Quantile Regression

Causal Random Forests Model Using Instrumental Variable Quantile Regression
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使用工具变量分位数回归的因果随机森林模型

DOI:
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发表时间:
2019
期刊:
影响因子:
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通讯作者:
Chen
Chen
中科院分区:
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文献类型:
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作者:
Jau‐er Chen;Chen

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我们提出了一个计量经济学的程序,主要是基于广义随机森林方法。这个过程不仅估计分位数治疗效果nonparametrically,但我们的程序产生的变量重要性的控制变量之间的异质性的措施。我们还应用所提出的程序重新调查401(k)参与对净金融资产的分配效应,以及参与就业培训计划的分位数收入效应。
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.