报告题目：Dynamic Quantile Panel Data Models with Interactive Effects
报告人：陈佳
时 间：2025年4月3日（星期四）上午10:30-11:30
地 点：西安交通大学创新港涵英楼经济金融研究院8121会议室
报告人简介：
陈佳教授于2008年取得浙江大学理学博士学位，后于2008-2011在澳大利亚阿德莱德大学和莫那什大学从事博士后研究，其后在昆士兰大学和英国约克大学任教，现为澳门大学经济系教授。陈佳教授在非参数和半参数统计，面板数据建模和统计推断，高维统计和计量经济学等领域取得了一系列优秀的研究成果，并有20余篇论文发表于国际知名统计学和计量经济学期刊。陈佳教授同时担任《Journal of Nonparametric Statistics》《Economic Modelling》以及《Australian and New Zealand Journal of Statistics》的副主编。
摘要：
We propose a simple two-step procedure for estimating the dynamic quantile panel data model with unobserved interactive effects. To account for the endogeneity induced by correlation between factors and lagged dependent variable/regressors, wefirst estimate factors consistently via an iterative principal component analysis. In the second step, we run a quantile regression for the augmented model with estimated factors and estimate the slope parameters. In particular, we adopt a smoothed quantile regression analysis where the quantile loss function is smoothed to have well-defined derivatives. The proposed two-step estimator is consistent and asymptotically normally distributed, but subject to asymptotic bias due to the incidental parameters. We then apply the split-panel jackknife approach to correct the bias. Monte Carlo simulations confirm that our proposed estimator has goodfinite sample performance. Finally, we demonstrate the usefulness of our proposed approach with an application to the analysis of bilateral trade for 380 country pairs over 59 years.
经济与金融学院
2025年3月26日
