Exponent of Cross-sectional Dependence: Estimation and Inference
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چکیده
Exponent of Cross-sectional Dependence: Estimation and Inference An important issue in the analysis of cross-sectional dependence which has received renewed interest in the past few years is the need for a better understanding of the extent and nature of such cross dependencies. In this paper we focus on measures of crosssectional dependence and how such measures are related to the behaviour of the aggregates defined as cross-sectional averages. We endeavour to determine the rate at which the cross-sectional weighted average of a set of variables appropriately demeaned, tends to zero. One parameterisation sets this to be O(N ), for 1/2 < α ≤ 1. Given the fashion in which it arises, we refer to as the exponent of cross-sectional dependence. We derive an estimator of from the estimated variance of the cross-sectional average of the variables under consideration. We propose bias corrected estimators, derive their asymptotic properties and consider a number of extensions. We include a detailed Monte Carlo study supporting the theoretical results. Finally, we undertake an empirical investigation of using the S&P 500 data-set, and a large number of macroeconomic variables across and within countries. JEL Classification: C21, C32
منابع مشابه
Supplementary Appendices to: Exponent of Cross-sectional Dependence: Estimation and Inference
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تاریخ انتشار 2011