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sidenav header background[5月10日]计量、金融和大数据分析workshop
发布日期：2019-05-07 01:56 来源：
【讲座时间】：5月10日（周五）上午9:00-11:00
【讲座地点】：北京大学经济学院，107会议室
【讲座标题】：Inference in Partially Identified Panel Data Models with Interactive Fixed Effects
【摘要】：This paper develops methods for statistical inferences in a partially identified nonparametric panel data model with endogeneity and interactive fixed effects. We consider the case where the number of cross-sectional units (N) is large and the number of time series periods (T) as well as the number of unobserved common factors (R) are fixed. Under some normalization rules, we can concentrate out the large dimensional parameter vector of factor loadings and specify a set of conditional moment restrictions that are involved with only the finite dimensional factor parameters along with the infinite dimensional nonparametric component. For a conjectured restriction on the parameter, we consider testing the null hypothesis that the restriction is satisfied by at least one element in the identified set and propose a test statistic based on a novel martingale difference divergence (MDD) measure for the distance between a conditional expectation object and zero. We derive the limiting distribution of the resultant test statistic under the null and show that it is divergent at rate-N under the global alternative based on the U-process theory. To obtain the critical values for our test, we propose a version of multiplier bootstrap and establish its asymptotic validity. Simulations demonstrate the finite sample properties of our inference procedure. We apply our method to study Engel curves for major nondurable expenditures in China by using a panel dataset from the China Family Panel Studies (CFPS).
【主讲人】：洪圣杰（助理教授）
【主讲人简介】：清华大学经管学院经济系助理教授。主要研究领域为计量经济学理论，应用计量经济学，主要研究成果发表在英文顶级期刊《 Journal of Econometrics 》。
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教学项目展开 / 收起
sidenav background教学项目
sidenav header background[5月10日]计量、金融和大数据分析workshop
发布日期：2019-05-07 01:56 来源：
【讲座时间】：5月10日（周五）上午9:00-11:00
【讲座地点】：北京大学经济学院，107会议室
【讲座标题】：Inference in Partially Identified Panel Data Models with Interactive Fixed Effects
【摘要】：This paper develops methods for statistical inferences in a partially identified nonparametric panel data model with endogeneity and interactive fixed effects. We consider the case where the number of cross-sectional units (N) is large and the number of time series periods (T) as well as the number of unobserved common factors (R) are fixed. Under some normalization rules, we can concentrate out the large dimensional parameter vector of factor loadings and specify a set of conditional moment restrictions that are involved with only the finite dimensional factor parameters along with the infinite dimensional nonparametric component. For a conjectured restriction on the parameter, we consider testing the null hypothesis that the restriction is satisfied by at least one element in the identified set and propose a test statistic based on a novel martingale difference divergence (MDD) measure for the distance between a conditional expectation object and zero. We derive the limiting distribution of the resultant test statistic under the null and show that it is divergent at rate-N under the global alternative based on the U-process theory. To obtain the critical values for our test, we propose a version of multiplier bootstrap and establish its asymptotic validity. Simulations demonstrate the finite sample properties of our inference procedure. We apply our method to study Engel curves for major nondurable expenditures in China by using a panel dataset from the China Family Panel Studies (CFPS).
【主讲人】：洪圣杰（助理教授）
【主讲人简介】：清华大学经管学院经济系助理教授。主要研究领域为计量经济学理论，应用计量经济学，主要研究成果发表在英文顶级期刊《 Journal of Econometrics 》。
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