  Consider an nxn random matrix X with i.i.d. nonnegative entries with bounded
density, mean m, and finite positive variance sigma^2. Let M be the nxn random
Markov matrix with i.i.d. rows obtained from X by dividing each row of X by its
sum. In particular, when X11 follows an exponential law, then M belongs to the
Dirichlet Markov Ensemble of random stochastic matrices. Our main result states
that with probability one, the counting probability measure of the complex
spectrum of n^(1/2)M converges weakly as n tends to infinity to the uniform law
on the centered disk of radius sigma/m. The bounded density assumption is
purely technical and comes from the way we control the operator norm of the
resolvent.
