784 research outputs found
Rate of Price Discovery in Iterative Combinatorial Auctions
We study a class of iterative combinatorial auctions which can be viewed as
subgradient descent methods for the problem of pricing bundles to balance
supply and demand. We provide concrete convergence rates for auctions in this
class, bounding the number of auction rounds needed to reach clearing prices.
Our analysis allows for a variety of pricing schemes, including item, bundle,
and polynomial pricing, and the respective convergence rates confirm that more
expressive pricing schemes come at the cost of slower convergence. We consider
two models of bidder behavior. In the first model, bidders behave
stochastically according to a random utility model, which includes standard
best-response bidding as a special case. In the second model, bidders behave
arbitrarily (even adversarially), and meaningful convergence relies on properly
designed activity rules
Agri-environmental auctions with synergies
Auctions are increasingly used in agri-environmental contracting. However, the issue of synergy effect between agri-environmental measures has been consistently overlooked, both by decision-makers and by the theoretical literature on conservation auction. Based on laboratory experiments, the objective of this paper is to compare the performance of different procurement auction designs (simultaneous, sequential and combinatorial) in the case of multiple heterogeneous units where bidders may potentially want to sell more than one unit and where their supply cost structure displays positive synergies. The comparison is made by using two performance criteria: budget efficiency and allocative efficiency. We also test if performance results are affected by information feedback to bidders after each auction period. Finally we explain performance results by the analysis of bidding behaviour in the three mechanisms.
Economic Efficiency Requires Interaction
We study the necessity of interaction between individuals for obtaining
approximately efficient allocations. The role of interaction in markets has
received significant attention in economic thinking, e.g. in Hayek's 1945
classic paper.
We consider this problem in the framework of simultaneous communication
complexity. We analyze the amount of simultaneous communication required for
achieving an approximately efficient allocation. In particular, we consider two
settings: combinatorial auctions with unit demand bidders (bipartite matching)
and combinatorial auctions with subadditive bidders. For both settings we first
show that non-interactive systems have enormous communication costs relative to
interactive ones. On the other hand, we show that limited interaction enables
us to find approximately efficient allocations
A General Theory of Sample Complexity for Multi-Item Profit Maximization
The design of profit-maximizing multi-item mechanisms is a notoriously
challenging problem with tremendous real-world impact. The mechanism designer's
goal is to field a mechanism with high expected profit on the distribution over
buyers' values. Unfortunately, if the set of mechanisms he optimizes over is
complex, a mechanism may have high empirical profit over a small set of samples
but low expected profit. This raises the question, how many samples are
sufficient to ensure that the empirically optimal mechanism is nearly optimal
in expectation? We uncover structure shared by a myriad of pricing, auction,
and lottery mechanisms that allows us to prove strong sample complexity bounds:
for any set of buyers' values, profit is a piecewise linear function of the
mechanism's parameters. We prove new bounds for mechanism classes not yet
studied in the sample-based mechanism design literature and match or improve
over the best known guarantees for many classes. The profit functions we study
are significantly different from well-understood functions in machine learning,
so our analysis requires a sharp understanding of the interplay between
mechanism parameters and buyer values. We strengthen our main results with
data-dependent bounds when the distribution over buyers' values is
"well-behaved." Finally, we investigate a fundamental tradeoff in sample-based
mechanism design: complex mechanisms often have higher profit than simple
mechanisms, but more samples are required to ensure that empirical and expected
profit are close. We provide techniques for optimizing this tradeoff
Competition Between Auctions
Even though auctions are capturing an increasing share of commerce, they are typically treated in the theoretical economics literature as isolated. That is, an auction is typically treated as a single seller facing multiple buyers or as a single buyer facing multiple sellers. In this paper, we review the state of the art of competition between auctions. We consider three different types of competition: competition between auctions, competition between formats, and competition between auctioneers vying for auction traffic. We highlight the newest experimental, statistical and analytical methods in the analysis of competition between auctions.auctions, bidding, competition, auction formats, auction houses
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