Journal
INTERNATIONAL REGIONAL SCIENCE REVIEW
Volume 26, Issue 3, Pages 363-392Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/0160017603253789
Keywords
Markov chain theory; per capita income; convergence analysis; tests of homogeneity and independence
Ask authors/readers for more resources
Markov chain theory, which has frequently been applied to analyze income convergence, imposes restrictive assumptions on the data-generating process. In most empirical studies, it is taken for granted that per capita income follows a stationary first-order Markov process. To examine the reliability of estimated Markov transition matrices, the authors propose Pearson chi(2) and likelihood ratio tests of the Markov property, spatial independence, and homogeneity overtime and space. As an illustration, it is shown that per capita income in the forty-eight contiguous U.S. states did clearly not follow a common stationary first-order Markov process from 1929 to 2000.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available