基于Copula的带截面相关二元选择面板模型估计研究  

Copula-based estimation for binary choice panel models with cross-sectional dependence

作　　者：韩本三[1] 黎伟[1] 黎实[2] 

机构地区：[1]西南财经大学经济数学学院,成都610074 [2]西南财经大学统计学院,成都610074

出　　处：《系统工程理论与实践》2013年第3期593-600,共8页Systems Engineering-Theory & Practice

基　　金：国家自然科学基金(71071130);中央高校基本科研业务费专项资金(JBK20405);西南财经大学"211工程"三期青年教师成长项目(211QN2011038)

摘　　要：在很多情况下个体之间都会存在相关性,如果在利用极大似然估计时假设二元选择面板模型的扰动项是相互独立的,那么模型参数的估计结果将不再是有效的.为此,通过将截面相关性纳入模型,构造了基于Copula函数的似然函数,提出了一种两阶段极大似然估计,并证明了估计量的一致性和渐近正态性,以及方差的渐近形式.蒙特卡罗模拟表明新的估计方法明显改善了估计量的有效性.利用这个方法研究了国内上市公司现金分红行为的影响因素,发现销售增长率由不显著变得较为显著.Cross-sectional dependence is often encountered in study. The MLE estimators are inefficient when cross section independence is assumed. Therefore, Copula-based log-likelihood functions are intro- duced to consider the cross section dependence. To avoid the nuisance parameters problem, a method called two-step MLE is proposed. The consistency and the asymptotic normality of the estimator are proved. And the asymptotic covariance matrix is given as well. Monte Carlo experiments show that the two-step MLE improves the efficiency of the estimators significantly. This model is applied to study the characters that affect the cash dividend policies of the listed companies, and it is shown that the sale growth rate becomes more significant relatively.

关 键 词：二元选择模型 截面相关 COPULA函数 

分 类 号：F064.1[经济管理—政治经济学]