关键词: 空间面板数据模型, Bootstrap方法, LM-Error检验, Monte Carlo模拟

Abstract: Classic spatial correlation tests of panel data models would exist serious deviation with error term is not independent with normal distribution. In this paper, we introduce fast double bootstrap (FDB) method into spatial correlation tests of spatial panel data models, and construct Bootstrap LM tests accordingly. And then, using Monte Carlo simulation experiments, we study effectiveness of Bootstrap LM test statistics from two aspects including size distortions and power, with error terms are normal, heteroscedasticity or time series related distributed. The experiment results show that, asymptotic LM-Error test of spatial panel data model exists serious size distortions when error terms are not independent with normal distribution, while FDB LM-Error test can rectify size distortions of asymptotic LM-Error without losing power, which is a more effective LM test for spatial correlation test of spatial panel data models.

Key words: Spatial Panel Data Model, Bootstrap Method, LM-Error Test, Monte Carlo Simulation