CAJ | 학술논문

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．
재흔다정황하개체지간도회존재상관성，여과재이용겁대사연고계시가설이원선택면판모형적우동항시상호독립적，나요모형삼수적고계결과장불재시유효적．위차，통과장절면상관성납입모형，구조료기우Copula함수적사연함수，제출료일충량계단겁대사연고계，병증명료고계량적일치성화점근정태성，이급방차적점근형식．몽특잡라모의표명신적고계방법명현개선료고계량적유효성．이용저개방법연구료국내상시공사현금분홍행위적영향인소，발현소수증장솔유불현저변득교위현저．
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.