Co, Catherine Y. Landon-Lane, John S. Yun, Myeong-Su
Year of Publication:
Working Paper No. 2005-11
We study the dynamics of the cross-section distribution of patents per capita for the 48 continental U.S. states from 1930 to 2000 using a discrete-state Markov chain. We test for and find evidence in favor of the (knowledge) convergence hypothesis as we find that 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 and are more likely to move to the middle than states in the middle of the cross-sectional distribution and the rate of convergence to the limiting distribution is slow.