@techreport{Bailey2012Exponent,
abstract = {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 cross-sectional 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^2α-2), 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.},
address = {Bonn},
author = {Natalia Bailey and George Kapetanios and Hashem Pesaran},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {C21; C32; 330; cross correlations; cross-sectional dependence; cross-sectional averages; weak and strong factor models; Capital Asset Pricing Model; Querschnittsanalyse; Korrelation; Zeitreihenanalyse; Sch\"{a}tztheorie; Theorie; Sch\"{a}tzung; B\"{o}rsenkurs; Makro\"{o}konomischer Einfluss; USA},
language = {eng},
note = {urn:nbn:de:101:1-2012042310152},
number = {6318},
publisher = {Institute for the Study of Labor (IZA)},
title = {Exponent of cross-sectional dependence: Estimation and inference},
type = {Discussion Paper series, Forschungsinstitut zur Zukunft der Arbeit},
url = {http://hdl.handle.net/10419/58426},
year = {2012}
}