7,487 research outputs found
The Core of the Participatory Budgeting Problem
In participatory budgeting, communities collectively decide on the allocation
of public tax dollars for local public projects. In this work, we consider the
question of fairly aggregating the preferences of community members to
determine an allocation of funds to projects. This problem is different from
standard fair resource allocation because of public goods: The allocated goods
benefit all users simultaneously. Fairness is crucial in participatory decision
making, since generating equitable outcomes is an important goal of these
processes. We argue that the classic game theoretic notion of core captures
fairness in the setting. To compute the core, we first develop a novel
characterization of a public goods market equilibrium called the Lindahl
equilibrium, which is always a core solution. We then provide the first (to our
knowledge) polynomial time algorithm for computing such an equilibrium for a
broad set of utility functions; our algorithm also generalizes (in a
non-trivial way) the well-known concept of proportional fairness. We use our
theoretical insights to perform experiments on real participatory budgeting
voting data. We empirically show that the core can be efficiently computed for
utility functions that naturally model our practical setting, and examine the
relation of the core with the familiar welfare objective. Finally, we address
concerns of incentives and mechanism design by developing a randomized
approximately dominant-strategy truthful mechanism building on the exponential
mechanism from differential privacy
Natural implementation with partially honest agents in economic environments
In this paper, we introduce the weak and the strong notions of partially honest agents (Dutta and Sen, 2012), and then study implementation by natural price-quantity mechanisms (Saijo et al., 1996, 1999) in pure exchange economies with three or more agents in which pure-consequentialistically rational agents and partially honest agents coexist. Firstly, assuming that there exists at least one partially honest agent in either the weak notion or the strong notion, the class of efficient social choice correspondences which are Nash-implementable by such mechanisms is characterized. Secondly, the (unconstrained) Walrasian correspondence is shown to be implementable by such a mechanism when there is at least one partially honest agent of the strong type, which may provide a behavioral foundation for decentralized implementation of the Walrasian equilibrium. Finally, in this set-up, the effects of honesty on the implementation of more equitable Pareto optimal allocations can be viewed as negligible.
Approaching Utopia: Strong Truthfulness and Externality-Resistant Mechanisms
We introduce and study strongly truthful mechanisms and their applications.
We use strongly truthful mechanisms as a tool for implementation in undominated
strategies for several problems,including the design of externality resistant
auctions and a variant of multi-dimensional scheduling
Social Welfare in One-sided Matching Markets without Money
We study social welfare in one-sided matching markets where the goal is to
efficiently allocate n items to n agents that each have a complete, private
preference list and a unit demand over the items. Our focus is on allocation
mechanisms that do not involve any monetary payments. We consider two natural
measures of social welfare: the ordinal welfare factor which measures the
number of agents that are at least as happy as in some unknown, arbitrary
benchmark allocation, and the linear welfare factor which assumes an agent's
utility linearly decreases down his preference lists, and measures the total
utility to that achieved by an optimal allocation. We analyze two matching
mechanisms which have been extensively studied by economists. The first
mechanism is the random serial dictatorship (RSD) where agents are ordered in
accordance with a randomly chosen permutation, and are successively allocated
their best choice among the unallocated items. The second mechanism is the
probabilistic serial (PS) mechanism of Bogomolnaia and Moulin [8], which
computes a fractional allocation that can be expressed as a convex combination
of integral allocations. The welfare factor of a mechanism is the infimum over
all instances. For RSD, we show that the ordinal welfare factor is
asymptotically 1/2, while the linear welfare factor lies in the interval [.526,
2/3]. For PS, we show that the ordinal welfare factor is also 1/2 while the
linear welfare factor is roughly 2/3. To our knowledge, these results are the
first non-trivial performance guarantees for these natural mechanisms
College admissions and the role of information : an experimental study
We analyze two well-known matching mechanismsâthe Gale-Shapley, and the Top
Trading Cycles (TTC) mechanismsâin the experimental lab in three different informational
settings, and study the role of information in individual decision making. Our results suggest
thatâin line with the theoryâin the college admissions model the Gale-Shapley mechanism
outperforms the TTC mechanisms in terms of efficiency and stability, and it is as successful as
the TTC mechanism regarding the proportion of truthful preference revelation. In addition, we
find that information has an important effect on truthful behavior and stability. Nevertheless,
regarding efficiency, the Gale-Shapley mechanism is less sensitive to the amount of information
participants hold
Exploiting Weak Supermodularity for Coalition-Proof Mechanisms
Under the incentive-compatible Vickrey-Clarke-Groves mechanism, coalitions of
participants can influence the auction outcome to obtain higher collective
profit. These manipulations were proven to be eliminated if and only if the
market objective is supermodular. Nevertheless, several auctions do not satisfy
the stringent conditions for supermodularity. These auctions include
electricity markets, which are the main motivation of our study. To
characterize nonsupermodular functions, we introduce the supermodularity ratio
and the weak supermodularity. We show that these concepts provide us with tight
bounds on the profitability of collusion and shill bidding. We then derive an
analytical lower bound on the supermodularity ratio. Our results are verified
with case studies based on the IEEE test systems
Selling Privacy at Auction
We initiate the study of markets for private data, though the lens of
differential privacy. Although the purchase and sale of private data has
already begun on a large scale, a theory of privacy as a commodity is missing.
In this paper, we propose to build such a theory. Specifically, we consider a
setting in which a data analyst wishes to buy information from a population
from which he can estimate some statistic. The analyst wishes to obtain an
accurate estimate cheaply. On the other hand, the owners of the private data
experience some cost for their loss of privacy, and must be compensated for
this loss. Agents are selfish, and wish to maximize their profit, so our goal
is to design truthful mechanisms. Our main result is that such auctions can
naturally be viewed and optimally solved as variants of multi-unit procurement
auctions. Based on this result, we derive auctions for two natural settings
which are optimal up to small constant factors:
1. In the setting in which the data analyst has a fixed accuracy goal, we
show that an application of the classic Vickrey auction achieves the analyst's
accuracy goal while minimizing his total payment.
2. In the setting in which the data analyst has a fixed budget, we give a
mechanism which maximizes the accuracy of the resulting estimate while
guaranteeing that the resulting sum payments do not exceed the analysts budget.
In both cases, our comparison class is the set of envy-free mechanisms, which
correspond to the natural class of fixed-price mechanisms in our setting.
In both of these results, we ignore the privacy cost due to possible
correlations between an individuals private data and his valuation for privacy
itself. We then show that generically, no individually rational mechanism can
compensate individuals for the privacy loss incurred due to their reported
valuations for privacy.Comment: Extended Abstract appeared in the proceedings of EC 201
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