Although it is well known that Markov process theory, frequently applied in the literature on income convergence, imposes some very restrictive assumptions upon the data generating process, these assumptions have generally been taken for granted so far. The present paper proposes, resp. recalls chi-square tests of the Markov property, of spatial independence, and of homogeneity across time and space to assess the reliability of estimated Markov transition matrices. As an illustration we show that the evolution of the income distribution across the 48 coterminous U.S. states from 1929 to 2000 clearly has not followed a Markov process.
Markov process chi-square tests U.S. regional growth Convergence