Weak and Strong Cross Section Dependence and Estimation of Large Panels

58 Pages Posted: 22 Dec 2009

See all articles by Alexander Chudik

Alexander Chudik

Federal Reserve Banks - Federal Reserve Bank of Dallas

M. Hashem Pesaran

University of Southern California - Department of Economics; University of Cambridge - Trinity College (Cambridge)

Elisa Tosetti

University of Cambridge - Faculty of Economics and Politics

Multiple version iconThere are 3 versions of this paper

Date Written: October 16, 2009

Abstract

This paper introduces the concepts of time-specific weak and strong cross section dependence. A double-indexed process is said to be cross sectionally weakly dependent at a given point in time, t, if its weighted average along the cross section dimension (N) converges to its expectation in quadratic mean, as N is increased without bounds for all weights that satisfy certain ‘granularity’ conditions. Relationship with the notions of weak and strong common factors is investigated and an application to the estimation of panel data models with an infinite number of weak factors and a finite number of strong factors is also considered. The paper concludes with a set of Monte Carlo experiments where the small sample properties of estimators based on principal components and CCE estimators are investigated and compared under various assumptions on the nature of the unobserved common effects.

Keywords: Panels, Strong and Weak Cross Section Dependence, Weak and Strong Factors

JEL Classification: C10, C31, C33

Suggested Citation

Chudik, Alexander and Pesaran, M. Hashem and Tosetti, Elisa, Weak and Strong Cross Section Dependence and Estimation of Large Panels (October 16, 2009). ECB Working Paper No. 1100. Available at SSRN: https://ssrn.com/abstract=1484582

Alexander Chudik (Contact Author)

Federal Reserve Banks - Federal Reserve Bank of Dallas ( email )

2200 North Pearl Street
PO Box 655906
Dallas, TX 75265-5906
United States

M. Hashem Pesaran

University of Southern California - Department of Economics

3620 South Vermont Ave. Kaprielian (KAP) Hall 300
Los Angeles, CA 90089
United States

University of Cambridge - Trinity College (Cambridge) ( email )

United Kingdom

Elisa Tosetti

University of Cambridge - Faculty of Economics and Politics ( email )

Austin Robinson Building
Sidgwick Avenue
Cambridge, CB3 9DD
United Kingdom

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
102
Abstract Views
825
rank
201,620
PlumX Metrics