@TechReport{iza:izadps:dp6318,
            	author={Bailey, Natalia and Kapetanios, George and Pesaran, M. Hashem},
            	title={Exponent of Cross-sectional Dependence: Estimation and Inference},
            	year={2012},
	month={Jan},
            	institution={Institute of Labor Economics (IZA)},
            	address={Bonn},
            	type={IZA Discussion Paper},
            	number={6318},
            	url={https://www.iza.org/publications/dp6318},
	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.},
	keywords={cross correlations;cross-sectional dependence;cross-sectional averages;weak and strong factor models;Capital Asset Pricing Model},
            }