非对称DAR模型的估计与检验  

Estimation and Test for Asymmetric DAR Model

作　　者：陈钟秀 张兴发 熊强[1,2] 宋泽芳 CHEN Zhongxiu;ZHANG Xingfa;XIONG Qiang;SONG Zefang(School of Economics and Statistics,Guangzhou University,Guangzhou Guangdong 510006,China;Lingnan Research Institute of Statistical Science,Guangzhou University,Guangzhou Guangdong 510006,China)

机构地区：[1]广州大学经济与统计学院,广东广州510006 [2]广州大学岭南统计科学研究院,广东广州510006

出　　处：《广西师范大学学报（自然科学版）》2022年第1期68-81,共14页Journal of Guangxi Normal University:Natural Science Edition

基　　金：国家自然科学基金(11731015,11701116);广东省自然科学基金(2018A030310068);广州市科技计划(202102020368);广东省普通高校创新团队项目(2020WCXTD8);广州大学科研基金(YG2020029,YG2020030)。

摘　　要：本文研究非对称DAR模型的估计和检验问题。运用拟极大似然方法,构造模型的参数估计,在某些正则条件下,证明估计的相合性和渐近正态性。基于此,构造拟似然比统计量检验模型的非对称性,在原假设和备择假设下,给出该统计量的渐近分布。数值模拟和实证分析结果表明:本文所构造的模型参数估计和检验方法具有良好的有限样本性质。The estimation and testing problems of asymmetric double autoregression(DAR)model are studied in this paper.The parametric component by virtue of quasi maximum likelihood estimation(QMLE)method is firstly proposed.Under some regularity conditions,the resulting estimators are consistent and asymptotically normal.Then,a quasi-likelihood ratio(QLR)statistic to detect asymmetric effect is proposed.The asymptotic properties of the testing statistic are established under null and alternative hypotheses.Finally,both simulation studies and empirical application well demonstrate the finite sample performance of the proposed estimation methodology and testing procedure.

关 键 词：非对称DAR模型 拟极大似然估计 非对称性检验 渐近性质 

分 类 号：O212.1[理学—概率论与数理统计]