Christina J. Schneider
 Associate Professor and Jean Monnet Chair, UCSD

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The analysis of policy convergence, or: how to chase a black cat in a dark room

Thomas Pluemper, Christina J. Schneider

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


Abstract

Political science research on policy convergence has largely remained inconclu­si­ve. While many studies found support for the convergence hypothesis, an almost equ­ally large number of studies rejected it. Convergence thus could be a less general phenomenon than many theo­rists believe. This article identifies a second possible explanation. The va­ri­ance approach, which domi­nates political science research on policy con­ver­gen­ce, is likely to lead to wrong inferences. Ana­ly­zing various artificially generated convergence proc­esses, we find that neither the standard deviation approach nor the coefficient of variation detects convergence when it is conditional or when theoretically un­identified con­ver­gen­ce clubs exist. Our analysis suggests that researchers should estimate rather than meas­ure conver­gence. By estimating convergence resear­chers may (a) test the cau­sal rela­tionship, (b) account for conditional conver­gen­ce, (c) control for the existence of convergence clubs, and (d) examine convergence to an equilibrium level of a pol­icy.

Keywords:

none.