  We study a dynamic model of information provision. A state of nature evolves
according to a Markov chain. An informed advisor decides how much information
to provide to an uninformed decision maker, so as to influence his short-term
decisions. We deal with a stylized class of situations, in which the decision
maker has a risky action and a safe action, and the payoff to the advisor only
depends on the action chosen by the decision maker. The greedy disclosure
policy is the policy which, at each round, minimizes the amount of information
being disclosed in that round, under the constraint that it maximizes the
current payoff of the advisor. We prove that the greedy policy is optimal in
many cases -- but not always.
