Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We study the dynamics of the cross‐section distribution of patents per capita for the 48 continental US states from 1930 to 2000 using a discrete‐state Markov chain. We test for and find evidence in favor of the (knowledge) convergence hypothesis. The distribution of patents is converging to a limiting distribution that is significantly more concentrated than its initial distribution. States in the extreme are more mobile than states in the middle of the cross‐sectional distribution and are likely to move to the middle. However, the rate of convergence to the limiting distribution is ‘slow’. Copyright © 2006 John Wiley & Sons, Ltd.