Analysis of Panel Vector Error Correction Models Using Maximum Likelihood, the Bootstrap, and Canonical-Correlation Estimators

FRB of St. Louis Working Paper No. 2006-050A

47 Pages Posted: 30 Aug 2006

See all articles by Richard G. Anderson

Richard G. Anderson

Federal Reserve Bank of St. Louis - Research Division

Hailong Qian

Saint Louis University - Department of Economics

Robert Rasche

Michigan State University; National Bureau of Economic Research (NBER)

Date Written: August 2006

Abstract

In this paper, we examine the use of Box-Tiao's (1977) canonical correlation method as an alternative to likelihood-based inferences for vector error-correction models. It is now well-known that testing of cointegration ranks based on Johansen's (1995) ML-based method suffers from severe small sample size distortions. Furthermore, the distributions of empirical economic and financial time series tend to display fat tails, heteroskedasticity and skewness that are inconsistent with the usual distributional assumptions of likelihood-based approach. The testing statistic based on Box-Tiao's canonical correlations shows promise as an alternative to Johansen's ML-based approach for testing of cointegration rank in VECM models.

Keywords: panel cointegration, bootstrap tests, canonical correlation

JEL Classification: C13, C14, C15, C33

Suggested Citation

Anderson, Richard G. and Qian, Hailong and Rasche, Robert, Analysis of Panel Vector Error Correction Models Using Maximum Likelihood, the Bootstrap, and Canonical-Correlation Estimators (August 2006). Available at SSRN: https://ssrn.com/abstract=927443 or http://dx.doi.org/10.2139/ssrn.927443

Richard G. Anderson (Contact Author)

Federal Reserve Bank of St. Louis - Research Division ( email )

411 Locust St
Saint Louis, MO 63011
United States

Hailong Qian

Saint Louis University - Department of Economics ( email )

Lindell Boulevard
Saint Louis, MO 63108
United States

Robert Rasche

Michigan State University ( email )

East Lansing, MI 48824
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
213
Abstract Views
1,372
rank
148,847
PlumX Metrics