Exponent of Cross-Sectional Dependence: Estimation and Inference

By Natalia Bailey, George Kapetanios, M. Pesaran. Social Science Research Network, 2016

241 citations recorded by the source corpus.

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 the exponent of the cross-sectional dimension, N, being between 1/2 and 1. We refer to this as the exponent of cross-sectional dependence. We derive an estimator of this exponent 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 the exponent of cross-sectional dependence using the S&P 500 data-set, and a large number of macroeconomic variables across and within countries.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7cc0dfc686da881545ec0b7abb68f99f1296db16

Citations in the corpus

• Testing Weak Cross-Sectional Dependence in Large Panels (2012, unknown): “The null hypothesis of the CD test is shown to be < (2 − )/4, where is the exponent of cross-sectional dependence introduced in Bailey et al. (2012), and measures the degree to which T expands relative to N , as defined by T = O(N ), for values of 0 < ≤ 1. It is shown that the CD test is particularl”
• Econometric analysis of production networks with dominant units (2020, unknown): “Following Bailey et al. (2016), we denote the cross-section exponent of the factor loadings by , de…ned by the value of that ensures”
• Estimation and inference for spatial models with heterogeneous coefficients: An application to US house prices (2020, unknown): “Pairwise geodesic distances, dij , between MSAs are computed using the Haversine formula, as described in Appendix C of Bailey et al. (2016).”