统计研究 ›› 2010, Vol. 27 ›› Issue (9): 91-96.

• 论文 • 上一篇    下一篇

空间经济计量滞后模型Bootstrap Moran检验功效的模拟分析

欧变玲等   

  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2010-09-15 发布日期:2010-09-15

Simulation Analysis for Power of Bootstrap Moran Diagnostic Tests in Spatial Econometric Autoregressive Models

Bian-Ling et al.   

  • Received:1900-01-01 Revised:1900-01-01 Online:2010-09-15 Published:2010-09-15

摘要: 当误差项不服从独立同分布时,利用Moran’s I统计量的渐近检验,无法有效判断空间经济计量滞后模型2SLS估计残差间存在空间关系与否。本文采用两种基于残差的Bootstrap方法,诊断空间经济计量滞后模型残差中的空间相关关系。大量Monte Carlo模拟结果显示,从功效角度看,无论误差项服从独立同分布与否,与渐近检验相比,Bootstrap Moran检验都具有更好的有限样本性质,能够更有效地进行空间相关性检验。尤其是,在样本量较小和空间衔接密度较高情况下,Bootstrap Moran检验的功效显著大于渐近检验。

关键词: 空间经济计量滞后模型, Bootstrap Moran检验, 功效, 蒙特卡洛

Abstract: The asymptotic distribution of Moran’s I statistic can’t effectively test spatial correlation among 2SLS residuals in spatial econometric autoregressive models with the i.i.d. error. In this paper, we apply two residual-based bootstrap methods for diagnostic testing spatial correlation in a spatial econometric autoregressive model. In comparison with the theoretical asymptotic test, our extensive Monte Carlo simulation indicates that in view of power whether the errors are i.i.d or not, bootstrap test for this model has superior finite sample properties, and can more effectively check spatial dependence than the asymptotic test. Especially, the power of bootstrap test is remarkably more than one of asymptotic test with the small sample and Queen spatial weight matrix.

Key words: Spatial Econometric Autoregressive Models, Bootstrap Moran Test, Power, Monte Carlo