Exponent of Cross-Sectional Dependence: Estimation and Inference
Exponent of Cross-Sectional Dependence: Estimation and Inference
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DOI：
10.1002/jae.2476
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发表时间：
2016-09-01
影响因子：
2.1
通讯作者：
Pesaran, M. Hashem
中科院分区：
文献类型：
--
作者：
Bailey, Natalia;Kapetanios, George;Pesaran, M. Hashem
本文刻画了二维数组的截面依赖程度，{x(It)，i=1，2，…N；T=1，2，…，T}，表示观测数据的截面平均值的方差随N变化的速率。在某些条件下，这相当于x(T)=(x(1t)，x(2t)，…，x(Nt))的协方差矩阵的最大特征值随N升高的速率。我们用来表示截面依赖程度，我们称之为截面相关性指数‘，并由标准差来定义，它是x(It)的简单截面平均值。我们提出了偏差修正估计量，得到了它们在>；1/2下的渐近性质，并考虑了一些推广。我们包括了详细的蒙特卡罗模拟研究，以支持理论结果。我们还提供了一些实证应用程序，调查全球经济中实际变量和金融变量的相互联系程度。版权所有(C)2015 John Wiley&Sons，Ltd.
This paper provides a characterisation of the degree of cross-sectional dependence in a two dimensional array, {x(it),i = 1,2,...N;t = 1,2,...,T} in terms of the rate at which the variance of the cross-sectional average of the observed data varies with N. Under certain conditions this is equivalent to the rate at which the largest eigenvalue of the covariance matrix of x(t)=(x(1t),x(2t),...,x(Nt)) rises with N. We represent the degree of cross-sectional dependence by , which we refer to as the exponent of cross-sectional dependence', and define it by the standard deviation, is a simple cross-sectional average of x(it). We propose bias corrected estimators, derive their asymptotic properties for > 1/2 and consider a number of extensions. We include a detailed Monte Carlo simulation study supporting the theoretical results. We also provide a number of empirical applications investigating the degree of inter-linkages of real and financial variables in the global economy. Copyright (c) 2015 John Wiley & Sons, Ltd.