This paper studies a class of information transmission processes called rumors. The distinctive features of these processes are that the information transmission takes place in such a way that the recipient does not quite know whether or not to believe the information and that the probability that someone receives the information depends on how many people already have it. Counter-intuitive comparative statics results are obtained. For example, more information and higher productivity may reduce welfare, while changing the speed with which the rumor spreads has no welfare effect.

This paper develops the stochastic theory of distribution with a dynamic model which focuses on the role of incomplete insurance in generating inequality. Unlike previous work, our approach takes explicit account of the reason for market incompleteness in modeling agents' behaviour; in particular, the amount of risk borne is endogenous. Using a model of growth with altruism in which agents are risk-averse and there is moral hazard, we show that lineage wealth follows a Markov process which converges globally to an ergodic distribution; this also represents the long-run population distribution of wealth. We discuss the role of particular assumptions, such as availability of production loans and unboundedness of utility, in yielding the qualitative properties of the distribution of wealth, the choice of “occupation” and the prevention of poverty traps.