Reputation and Screening in a Noisy Environment with Irreversible Actions

Economics & Decision Sciences Dept.

Speaker : Mehmet EKMEKCI (Boston College)

HEC Campus - Building T - Room T004

"Reputation and Screening in a Noisy Environment with Irreversible Actions"

 (joint work with Lucas Maestri)

Abstract :

We introduce a class of two-player dynamic games to study the effectiveness of screening in
a principal-agent problem. In every period, the principal chooses either to irreversibly stop the
game, or to continue. In every period until the game is stopped, the agent chooses an action
that affects the flow payoffs to the players. The agent’s type is his private information, and
his actions are imperfectly observed. Players receive a lump-sum payoff when the game stops,
and the principal’s payoff depends on the agent’s type. Both players are long-lived and share
a common discount factor. We study the limit of the equilibrium outcomes as both players get
arbitrarily patient. We show that Nash equilibrium outcomes of the dynamic game converge
to the unique Nash equilibrium outcome of an auxiliary two-stage game with observed mixed
actions. Hence, dynamic screening eliminates noise in monitoring, but beyond that, it is
ineffective. We calculate the probability that the principal eventually stops the game, against
each type of the agent. The principal learns some but not all information about the agent’s
type. All payoff relevant information is revealed at the beginning of the game. Applications
include procurement, promotions and demotions within organizations and venture-capital
financing.