Strategy-proof stochastic assignment

I study strategy-proof assignment mechanisms where the agents reveal their preference rankings over the available objects. A stochastic mechanism returns lotteries over deterministic assignments, and mechanisms are compared according to first-order stochastic dominance. I show that non-wasteful strategy-proof mechanisms are not dominated by strategy-proof mechanisms, however non-wastefulness is highly restrictive when the mechanism involves randomization. Infact, the Random Priority mechanism (i.e.,the Random Serial Dictatorship), and a recently adopted school choice mechanism, Deferred Acceptance with Random Tie-breaking, are wasteful. I find that both these mechanisms are dominated by strategy-proof mechanisms. In general, strategy proof improvement cannot be due to merely reshuffling objects, and therefore must involve assigning more objects

Efficiency and stability under substitutable priorities with ties

Many assignment mechanisms appeal to a priority structure to determine how over-subscribed indivisible goods are assigned to unit-demand individuals. We study substitutable priorities with ties which not only nest important classes of priorities and preferences studied in the literature, but also allow us to formalize plausible priority structures not captured in previous literature. Efficiency is typically in conflict with respecting priorities (i.e., stability), and therefore the natural welfare objective is constrained efficiency. A generalization of the deferred acceptance process yields a stable assignment, but this outcome is not necessarily constrained efficient. We identify an easily verifiable sufficient condition for a stable assignment to be constrained efficient, which then leads to an algorithm to compute a constrained efficient assignment. Finally we illustrate practical applications of our framework and algorithm, including a widely studied matching problem with distributional constraints

What's the Matter with Tie-Breaking? Improving Efficiency in School Choice.

In several school choice districts in the United States, the student proposing deferred acceptance algorithm is applied after indifferences in priority orders are broken in some exogenous way. Although such a tie-breaking procedure preserves stability, it adversely affects the welfare of the students since it introduces artificial stability constraints. Our main finding is a polynomial-time algorithm for the computation of a student-optimal stable matching when priorities are weak. The idea behind our construction relies on a new notion which we call a stable improvement cycle. We also investigate the strategic properties of the student-optimal stable mechanism

What`s the Matter with Tie-breaking? Improving Efficiency in School Choice

Very little is known about the student-optimal stable mechanism when school priorities are weak. In current practice, the student proposing deferred acceptance algorithm is applied after indifferences in priority orders are broken with a lottery. Although such a tie-breaking procedure preserves stability, it adversely affects the welfare of the students since it introduces artificial stability constraints. We propose a simple procedure to compute a student-optimal stable matching when priorities are weak. The idea behind our construction relies on a new notion which we call a stable improvement cycle. Abdulkadiroglu, Pathak, and Roth (2006) report that had our algorithm been applied to the preference data of the 2003-2004 New York City High School Match, 6,854 students (10.5% of the 63,795 matched students) would have been matched with schools higher on their preference lists without hurting the others. We run simulations to understand the qualitative effects of correlation in preferences and of locational preference on the size of the efficiency gain. We also investigate the strategic properties of the class of student-optimal stable mechanisms.School Choice, Student-Optimal Stable Mechanism, Weak Priorities, Stable Improvement Cycles

A New Payment Rule for Core-Selecting Package Auctions

We propose a new, easy-to-implement, class of payment rules, "Reference Rules," to make core-selecting package auctions more robust. Small, almost riskless, profitable deviations from "truthful bidding" are often easy for bidders to find under currently-used payment rules. Reference Rules perform better than existing rules on our marginal-incentive-to-deviate criterion, and are as robust as existing rules to large deviations. Other considerations, including fairness and comprehensibility, also support the use of Reference Rules.combinatorial auction; core; core-selecting auction; multi-object auction; package auction; robust design; simultaneous ascending auction; Vickrey; Vickrey auction

Efficient assignment respecting priorities

A widespread practice in assignment of heterogeneous indivisible objects is to prioritize some recipients over others depending on the type of the object. Leading examples include assignment of public school seats, and allocation of houses, courses, or offices. Each object comes with a coarse priority ranking over recipients. Respecting such priorities constrains the set of feasible assignments, and therefore might lead to inefficiency, highlighting a tension between respecting priorities and Pareto efficiency. Via an easily verifiable criterion, we fully characterize priority structures under which the constrained efficient assignments do not suffer from such welfare loss, and the constrained efficient rule (CER) is indeed efficient. We also identify the priority structures for which the CER is singleton-valued and group strategy-proof.Assignment Priorities Efficiency Consistency

What's the Matter with Tie-Breaking? Improving Efficiency in School Choice

In several school choice districts in the United States, the student proposing deferred acceptance algorithm is applied after indifferences in priority orders are broken in some exogenous way. Although such a tie-breaking procedure preserves stability, it adversely affects the welfare of the students since it introduces artificial stability constraints. Our main finding is a polynomial-time algorithm for the computation of a student-optimal stable matching when priorities are weak. The idea behind our construction relies on a new notion which we call a stable improvement cycle. We also investigate the strategic properties of the student-optimal stable mechanism.