The Computation of Convergence, or: How to Chase a Black Cat in a Dark Room

Journal of European Public Policy, Vol. 16, No. 7, pp. 990-1011, October 2009.

31 Pages Posted: 12 Jan 2007 Last revised: 24 Oct 2011

See all articles by Thomas Pluemper

Thomas Pluemper

University of Essex - Department of Government; Vienna University of Economics and Business - Department of Socioeconomics

Christina J. Schneider

University of California, San Diego; Max Planck Institute for Economics

Date Written: January 8, 2007

Abstract

This paper seeks to bridge the gap between theories of convergence and its empirical tests. We start by assessing the variance approach, which is the dominant way of testing convergence theories. Based on analyzing various artificially generated convergence processes, we find that neither the standard deviation approach nor the coefficient of variation is capable to detect convergence when it is conditional. Based on our findings, we provide guidance to researchers who aim at developing and testing their theories of convergence. First, we recommend a set of questions which scholars should address within their theoretical frameworks. Secondly, we recommend estimating rather than measuring convergence. Estimating convergence bears the crucial advantage that researchers may a) test the causal relationship, b) control for structural constraints, c) control for the existence of convergence clubs, and d) test convergence to an equilibrium level of a policy. In addition, estimation eliminates noise such as unsystematic measurement error. Following both recommendations should help to close the existing gab between theoretical accounts and empirical analyses of convergence.

Keywords: convergence, clubs, variance approach, regression approach

Suggested Citation

Plümper, Thomas and Plümper, Thomas and Schneider, Christina J., The Computation of Convergence, or: How to Chase a Black Cat in a Dark Room (January 8, 2007). Journal of European Public Policy, Vol. 16, No. 7, pp. 990-1011, October 2009., Available at SSRN: https://ssrn.com/abstract=955868

Thomas Plümper (Contact Author)

University of Essex - Department of Government ( email )

Wivenhoe Park
Colchester, Essex CO4 3SQ
United Kingdom

HOME PAGE: http://www.polsci.org/pluemper

Vienna University of Economics and Business - Department of Socioeconomics ( email )

Vienna
Austria

Christina J. Schneider

University of California, San Diego

9500 Gilman Drive
Mail Code 0502
La Jolla, CA 92093-0112
United States

Max Planck Institute for Economics ( email )

Kahlaische Strasse 10
D-07745 Jena, 07745
Germany