Advances in Dynamic Mechanism Design
Saturday, Jan. 5, 2019 8:00 AM - 10:00 AM
- Chair: Vasiliki Skreta, University of Texas-Austin, University College London, and CEPR
Fiscal Rules and Discretion under Limited Enforcement
AbstractWe study a fiscal policy model in which the government is present-biased towards public spending. Society chooses a fiscal rule to trade off the benefit of committing the government to not overspend against the benefit of granting it flexibility to react to privately observed shocks to the value of spending. Unlike prior work, we examine rules under limited enforcement: the government has full policy discretion and can only be incentivized to comply with a rule via the use of penalties which are joint and bounded. We show that optimal incentives must be bang-bang. Moreover, under a distributional condition, the optimal rule is a maximally enforced deficit limit, triggering the largest feasible penalty whenever violated. Violation optimally occurs under high enough shocks if and only if available penalties are weak and such shocks are rare. If the rule is self-enforced in a dynamic setting, penalties take the form of temporary overspending.
Social Insurance, Information Revelation, and Lack of Commitment
AbstractWe study the optimal provision of insurance against unobservable idiosyncratic shocks in a setting in which a benevolent government cannot commit. A continuum of agents and the government play an infinitely repeated game. Actions of the government are constrained by the threat of reverting to the worst perfect Bayesian equilibrium (PBE). We construct a recursive problem that characterizes the allocation of resources and the revelation of information on the Pareto frontier of the set of PBE. We show that the amount of information revealed by an agent depends on the continuation utility with which he enters the period. Agents who enter the period with low continuation utility reveal no information about their current shocks and receive no insurance. Agents who enter the period with high continuation utility reveal precise information about their current shocks and receive ìsecond bestîinsurance as in economies with perfect commitment by the government.
Full Surplus Extraction in Mechanism Design with Information Disclosure
AbstractI study mechanism design settings with quasi-linear utility where the principal can provide agents with additional private information about their valuations beyond the private information they hold at the outset. I demonstrate that the principal can design information and a mechanism so as to fully extract the complete information first-best surplus if agents’ ex ante information only affects their beliefs about, yet not their valuations. Otherwise, the result holds if each agent’s initial private beliefs satisfy a spanning condition.
University of Toronto
Carnegie Mellon University
University of Toronto
- D8 - Information, Knowledge, and Uncertainty
- C7 - Game Theory and Bargaining Theory