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宛圆渊|第249期双周学术论坛

作者:     日期:2018-08-07    来源:

  一、主题:Testing Identifying Assumptions in Fuzzy Regression Discontinuity Designs

  二、主讲人:宛圆渊,多伦多大学经济系,经济学终身副教授。2011年在宾夕法尼亚州立大学获得经济学博士,硕士就读于北京大学国家发展研究院(原中国经济研究中心),本科就读于北京师范大学经济学院。研究领域为计量经济理论和应用计量经济学,在国际知名期刊 Review of Economics and Statistics, Journal of Econometrics, Journal of Business, Statistics, and Economics, Econometric Theory 以及《经济研究》等中文顶级期刊发表论文十余篇。

  三、时间:2018年8月10日,下午14:30-17:00

  四、地点:中央财经大学主教学楼908会议室

  五、主持人:谭小芬,中央财经大学金融学院副院长,教授

  六、讲座资助:中央财经大学引智计划

 

  摘要:We propose a new specification test for assessing the validity of fuzzy regression discontinuity designs (FRD-validity). We derive a new set of testable implications, characterized by a set of inequality restrictions on the joint distribution of observed outcomes and treatment status at the cut-off. We show that this new characterization exploits all the information in the data useful for detecting violations of FRD-validity. Our approach differs from, and complements existing approaches that test continuity of the distributions of running variables and baseline covariates at the cut-off since ours focuses on the distribution of the observed outcome and treatment status. We show that the proposed test has appealing statistical properties. It controls size in large sample uniformly over a large class of distributions, is consistent against all fixed alternatives, and has non-trivial power against some local alternatives. We apply our test to evaluate the validity of two FRD designs. The test does not reject the FRD-validity in the class size design studied by Angrist and Lavy (1999) and rejects in the insurance subsidy design for poor households in Colombia studied by Miller etc (2013) for some outcome variables, while existing density tests suggest the opposite in each of the cases.