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20210622:分布异质下的个体多维组类识别
时间:2021-06-17

报告时间:2021年6月22日 下午14:00-15:00
报告地点腾讯会议(会议ID:978 988 317)
报告嘉宾:冷旋

报告主题:Multi-dimensional Latent Group Structures with Heterogeneous Distributions

报告摘要

This paper aims to identify the multi-dimensional latent grouped heterogeneity of distributional effects. We consider a panel quantile regression model with additive cross-section and time fixed effects. The cross-section effects and quantile slope coefficients are both characterized by grouped patterns of heterogeneity, but each unit can belong to different groups for cross-section effects and slopes. We propose a composite-quantile approach to jointly estimate multi-dimensional group memberships, slope coefficients, and fixed effects. We show that using multiple quantiles improves clustering accuracy if memberships are quantile-invariant. We apply the methods to examine the relationship between managerial incentives and risk-taking behavior.

个人简介

冷旋,2019年入职厦门大学经济学院统计与数据科学系,王亚南经济研究院助理教授。中国科学技术大学统计学博士(美国佐治亚理工学院联合培养),曾在荷兰Erasmus大学从事博后工作。研究兴趣包括面板计量与极值统计,研究成果发表于Journal of Financial Econometrics, Extremes, Insurance: Mathematics and Economics等国际期刊。现主持国家自然科学基金青年项目。


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