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On the bootstrap for Moran's I test for spatial dependence

机译:在Moran's的引导程序上,我测试了空间依赖性

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This paper is concerned with the use of the bootstrap for statistics in spatial econometric models, with a focus on the test statistic for Moran's I test for spatial dependence. We show that, for many statistics in spatial econometric models, the bootstrap can be studied based on linear quadratic (LQ) forms of disturbances. By proving the uniform convergence of the cumulative distribution function for LQ forms to that of a normal distribution, we show that the bootstrap is generally consistent for test statistics that can be approximated by LQ forms, including Moran's I. Possible asymptotic refinements of the bootstrap are most commonly studied using Edgeworth expansions. For spatial econometric models, we may establish asymptotic refinements of the bootstrap based on asymptotic expansions of LQ forms. When the disturbances are normal, we prove the existence of the usual Edgeworth expansions for LQ forms; when the disturbances are not normal, we establish an asymptotic expansion of LQ forms based on martingales. These results are applied to show the second order correctness of the bootstrap for Moran's I test. (C) 2014 Elsevier B.V. All rights reserved.
机译:本文关注在空间计量经济学模型中使用引导程序进行统计,重点关注Moran I检验空间相关性的检验统计量。我们表明,对于空间计量经济模型中的许多统计数据,可以基于扰动的线性二次(LQ)形式研究自举。通过证明LQ形式的累积分布函数与正态分布的一致收敛,我们表明,对于LQ形式(包括Moran's I)可以近似的测试统计量,自举通常是一致的。自举的可能渐近细化为最常使用Edgeworth扩展进行研究。对于空间计量经济学模型,我们可以基于LQ形式的渐近展开来建立自举的渐近精化。当扰动正常时,我们证明了LQ形式通常存在的Edgeworth展开;当干扰不正常时,我们建立基于s的LQ形式的渐近展开。这些结果用于显示Moran I测试的自举的二阶正确性。 (C)2014 Elsevier B.V.保留所有权利。

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