题目：Threshold Spatial Autoregressive Model

主讲人：李鲲鹏, 首都经济贸易大学

时间：2019年4月29日，13:30-15:00

地点：暨南大学中惠楼106B室

主讲人简介：

李鲲鹏，首都经济贸易大学国际经管学院教授、博士生导师、副院长、院学位委员会主任。研究领域为计量经济学，研究兴趣包括高维因子分析、交互效应模型、断点阈值模型、空间计量模型以及非平稳时间序列模型。在Annals of Statistics、Journal of Business & Economic Statistics、Journal of Econometrics、Review of Economics and Statistics等国际优秀期刊发表论文多篇。现为Journal of Business & Economic Statistics期刊的编委(Associate Editor)。

Abstract:

This paper considers 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 framework 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 pre-specified 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.