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【5月14日】【中央财经大学经济学院“龙马经济学双周学术论坛”】2019年春季学期第七讲·Threshold spatial autoregressive model

[发表时间]:2019-05-10 [来源]:经济学院 [浏览次数]:

  讲座主题:Threshold spatial autoregressive model

  主讲嘉宾:李鲲鹏(首都经济贸易大学国际经管学院 教授)

  讲座时间:2019年5月14日(周二),下午14:00-15:30

  讲座地点:沙河校区主教501

  嘉宾简介:李鲲鹏,国家自然科学基金优秀青年项目获得者,首都经济贸易大学国际经管学院教授、博士生导师、副院长。研究方向为计量经济学,研究领域包括高维因子模型、交互效应面板模型、空间计量模型、断点门限模型等。在国内外知名期刊发表论文20余篇,包括Annals of Statistics、Journal of Business & Economic Statistics、Journal of Econometrics、Review of Economics and Statistics等。现为中国数量经济学会常务理事、Journal of Business & Economic Statistics期刊编委。

  内容摘要:This paper consider the estimation and inferential issues of threshold spatial autoregressive model, which is a hybrid of threshold model and spatial econometric model. We consider using the quasi maximum likelihood (QML) method to estimate the model. The asymptotic theory of the QML estimator is established under the setup that the threshold effect shrinks to zero along with an increasing sample size. Our analysis indicates that the limiting distribution of the QML estimator for the threshold value is pivotal up to a scale parameter which involves the skewness and kurtosis of the errors due to the misspecification on the distribution of errors. The QML estimators for the other parameters achieve the oracle property, that is, they have the same limiting distributions as the infeasible QML estimators, which are obtained supposing that the threshold value is observed a priori. We also consider the hypothesis testing on the presence of threshold effect, and the hypothesis testing on the threshold value equal to some prespecified one. We run Monte carlo simulations to investigate the finite sample performance of the QML estimators and find that the QML estimators have good performance.


[编辑]:张萌