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Comments on “Unobservable Selection and Coefficient Stability: Theory and Evidence” and “Poorly Measured Confounders are More Useful on the Left Than on the Right”
Journal of Business & Economic Statistics ( IF 3 ) Pub Date : 2019-05-08 , DOI: 10.1080/07350015.2019.1575743
Giuseppe De Luca 1 , Jan R. Magnus 2 , Franco Peracchi 3
Affiliation  

Abstract–

We establish a link between the approaches proposed by Oster (2019 Oster, E. (2019), “Unobservable Selection and Coefficient Stability: Theory and Evidence,” Journal of Business and Economic Statistics, 37(2). DOI: 10.1080/07350015.2016.1227711.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) and Pei, Pischke, and Schwandt (2019 Pei, Z., Pischke, J.-S., and Schwandt, H. (2019), “Poorly Measured Confounders Are More Useful on the Left Than on the Right,” Journal of Business and Economic Statistics, 37(2). DOI: 10.1080/07350015.2018.1462710.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) which contribute to the development of inferential procedures for causal effects in the challenging and empirically relevant situation where the unknown data-generation process is not included in the set of models considered by the investigator. We use the general misspecification framework recently proposed by De Luca, Magnus, and Peracchi (2018 De Luca, G., Magnus, J. R., and Peracchi, F. (2018), “Balanced Variable Addition in Linear Models,” Journal of Economic Surveys, 32, 11831200. DOI: 10.1111/joes.12245.[Crossref], [Web of Science ®] , [Google Scholar]) to analyze and understand the implications of the restrictions imposed by the two approaches.



中文翻译:

评论“无法观察的选择和系数稳定性:理论和证据”和“测度混杂因素在左侧比右侧更有用”

摘要-

我们在Oster(2019 Oster,E。(2019年),“不可观察的选择和系数稳定性:理论和证据”,《 商业与经济统计》,37(2)。DOI:10.1080 / 07350015.2016.1227711[Taylor&Francis Online],[Web of  Science® ] ,[Google Scholar])和Pei,Pischke和Schwandt(2019年 Pei,Z.Pischke,J.-S. ,以及Schwandt,H。(2019年),“衡量不佳的混杂因素在左侧比在右侧更有用”,《 商业与经济统计杂志,第37(2)页。DOI:10.1080 / 07350015.2018.1462710[Taylor&Francis Online],[Web of Science®]  ,[Google Scholar])有助于开发具有挑战性和与经验相关的情况下因果关系的推理程序,在这种情况下,调查人员考虑的模型集未包括未知数据生成过程。我们使用De Luca,Magnus和Peracchi(2018 De Luca,G.Magnus,JRPeracchi,F。(2018),“线性模型中的平衡变量加法”,《 经济调查杂志,第32卷,1183年至1200年。DOI:10.1111 / joes.12245[Crossref],[Web ofScience®]和[  Google Scholar]来分析和理解这两种方法所施加的限制的含义。

更新日期:2019-05-08
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