Bailey, N., Kapetanios, G. and Pesaran, M. H.
Exponent of Cross-sectional Dependence: Estimation and Inference
CWPE1206
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 
, for 
. 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 Codes: C21 C32
Author links: M. Hashem Pesaran
PDF: https://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe1206.pdf 
Open Access Link: https://doi.org/10.17863/CAM.1063
