Dynamic Mechanism Design
Abstract:
This paper examines the problem of how to design
incentivecompatible mechanisms in environments in which the
agents private information evolves stochastically over time and
in which decisions have to be made in each period. The
environments we consider are fairly general in that the agents
types are allowed to evolve in a nonMarkov way, decisions are
allowed to affect the type distributions and payoffs are not
restricted to be separable over time. Our first result is the
characterization of a dynamic formula for (the derivative of)
the agents equilibrium payoffs in an incentivecompatible
mechanism. The formula summarizes all local firstorder
conditions taking into account how current types affect the
dynamics of expected payoffs. The formula generalizes the
familiar envelope condition from static mechanism design: the
key difference is that a variation in the current types now
impacts payoffs in all subsequent periods both directly and
through the effect on the distributions of future types. We
first identify assumptions on the primitive environment that
guarantee that our dynamic payoff formula is a necessary
condition for incentive compatibility. Next, we specialize this
formula to quasilinear environments and use it to establish a
dynamic revenueequivalence result. Lastly, we turn to the
characterization of sufficient conditions for incentive
compatibility. We then apply the results to study the properties
of revenuemaximizing mechanisms in a variety of applications
that include dynamic auctions with AR(k) values and the
provision of experience goods.
Paper:
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Biography:
Professor Ilya Segal is a Roy and Betty
Anderson Professor in the Humanities and Sciences at Stanford
University. He has taught in the university's Department of
Economics since 2002. Segal is a specialist in contract theory
and has developed models of transactions that take place in
complex situations under conditions of uncertainty. He has
shown, for example, why central governments of some countries
wind up subsidizing failing firms. Firms are unable to commit to
not renegotiate agreements, he argues, and this gives them an
incentive to underinvest in productive assets that might reduce
their subsidies. His work also explains why contracts to cover
complex situations are often relatively incomplete even when
complete contracts could have been written at a low cost. His
research interests lie in the areas of Microeconomic theory,
contract theory, information economics, industrial organization.
He received his Ph.D. Harvard University; M.S. Moscow Institute
of Physics and Technology (Applied Mathematics).
