Classical economic growth theory suggests that regions will converge. Using data from 198 countries, we test the convergence hypothesis by investigating whether GDP, per capita GDP, and population follow a power law distribution. We are unable to reject the hypothesis that these variables follow a power law distribution. Our research supports the hypothesis of random growth, which is consistent with both log normal and power law distributions.
AxtellR.2001. “Zipf Distribution of U.S. Firm Sizes. Science293(5536): 1818–1820.
2.
FurceriD.2008. “Zipf's Law and the World Income Distribution.” Applied Economic Letters15(12): 921–923.
3.
GabaixX.1999. “Zipf's Law for Cities: An Explanation.” The Quarterly Journal of Economics114(3): 739–767.
4.
GabaixX.2009. “Power Laws in Economics and Finance.” Annual Review of Economics1(1): 255–293.
5.
HestonA.SummersR., and AtenB., Penn World Table Version 7.1, Center for International Comparisons of Production, Income and Prices at the University of Pennsylvania, August2009. Retrieved October 30, 2012 (http://pwt.econ.upenn.edu/php_site/pwt_index.php.).
6.
Mankiw, GregoryN., DavidRomer, and WeilDavid N.1992. “A Contribution to the Empirics of Economic Growth.” The Quarterly Journal of Economics107(2): 407–437.
7.
MartinR. and SunleyP.. 1998. “Slow Convergence? The New Endogenous Growth Theory and Regional Development.” Economic Geography74(3): 201–227.
8.
NewmanM.2005. Power laws, Pareto distributions and Zipf's law. Contemporary Physics46(5): 323–351.
9.
RoseA.2006. “Cities and Countries.” Journal of Money, Credit, and Banking38(8): 2225–2245.
10.
ZipfG.K.1949. Human Behavior and the principle of Least Effort. Reading, MA: Addison-Wesley.
