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珞珈经管创新论坛第62期——数理经济与数理金融论坛
时间:2023-09-23    点击数:

讲座题目:Common Correlated Effects Estimation of Nonlinear Panel Data Models(非线性的常见相关效应估计面板数据模型)

主讲人:陈亮 北京大学汇丰商学院 助理教授

讲座时间:2023年9月28日10:00-11:30

讲座地点:学院B251

讲座内容摘要:

This paper focuses on estimating the coefficients and average partial effects of observed regressors in nonlinear panel data models with interactive fixed effects, using the common correlated effects (CCE, hereafter) framework. The proposed two-step estimation method involves applying principal component analysis to estimate the latent factors based on cross-sectional averages of the regressors in the first step, and jointly estimating the coefficients of the regressors and the factor loadings in the second step. The asymptotic distributions of the proposed estimators are derived under general conditions, assuming that the number of time-series observations is comparable to the number of cross-sectional observations. To correct for asymptotic biases of the estimators, we introduce both analytical and split-panel jackknife methods, and confirm their good performance in finite samples using Monte Carlo simulations. Finally, the proposed method is used to study the arbitrage behavior of non-financial firms across different security markets.

本文使用共同相关效应(CCE,以下简称)框架,估计了具有交互式固定效应的非线性面板数据模型中的回归系数和平均部分效应。所提出的两步估计方法在第一步中应用主成分分析来估计基于解释变量的潜在因子,并在第二步中联合估计解释变量的系数和因子载荷。所提出的估计式的渐近分布是在一般条件下推导的,假设时间序列观测的数量与横截面观测的数量相当。为了纠正估计量的渐近偏差,我们引入了分析和分割面板刀切法,并使用蒙特卡罗模拟确认了它们在有限样本中的良好表现。最后,利用所提方法研究了非金融企业在不同证券市场的套利行为。

主讲人信息:

陈亮,北京大学汇丰商学院助理教授,主要研究方向为理论计量经济学,博士毕业于马德里卡洛斯三世大学(2013),曾就职于牛津大学经济学院(2013-2016)和上海财经大学经济学院(2016-2020),研究成果发表于 Econometrica, Journal of Econometrics,Econometric Theory, The Econometrics Journal, Economics Letters, Economica 等期刊。