Multi-item Vickrey-Dutch auctions

Descending price auctions are adopted for goods that must be sold quickly and in private values environments, for instance in flower, fish, and tobacco auctions. In this paper, we introduce ex post efficient descending auctions for two environments: multiple non-identical items and buyers with unit-demand valuations; and multiple identical items and buyers with non-increasing marginal values. Our auctions are designed using the notion of universal competitive equilibrium (UCE) prices and they terminate with UCE prices, from which the Vickrey payments can be determined. For the unit-demand setting, our auction maintains linear and anonymous prices. For the homogeneous items setting, our auction maintains a single price and adopts Ausubel's notion of "clinching" to compute the final payments dynamically. The auctions support truthful bidding in an ex post Nash equilibrium and terminate with an ex post efficient allocation. In simulation, we illustrate the speed and elicitation advantages of these auctions over their ascending price counterparts.

Social psychology and environmental economics: a new look at ex ante corrections of biased preference evaluation

The field of social psychology explores how a person behaves within the context of other people. The social context can play a substantive role in non-market allocation decisions given peoples choices and values extend beyond the classic market-based exchange institution. Herein we explore how social psychology has affected one aspect of environmental economics: preference elicitation through survey work. We discuss social representation, social isolation, framing through cheap talk, and commitment theory through an oath.Social psychology;Commitment;Persuasive communication;Preference elicitation

Fast Iterative Combinatorial Auctions via Bayesian Learning

Iterative combinatorial auctions (CAs) are often used in multi-billion dollar domains like spectrum auctions, and speed of convergence is one of the crucial factors behind the choice of a specific design for practical applications. To achieve fast convergence, current CAs require careful tuning of the price update rule to balance convergence speed and allocative efficiency. Brero and Lahaie (2018) recently introduced a Bayesian iterative auction design for settings with single-minded bidders. The Bayesian approach allowed them to incorporate prior knowledge into the price update algorithm, reducing the number of rounds to convergence with minimal parameter tuning. In this paper, we generalize their work to settings with no restrictions on bidder valuations. We introduce a new Bayesian CA design for this general setting which uses Monte Carlo Expectation Maximization to update prices at each round of the auction. We evaluate our approach via simulations on CATS instances. Our results show that our Bayesian CA outperforms even a highly optimized benchmark in terms of clearing percentage and convergence speed.Comment: 9 pages, 2 figures, AAAI-1

Do people always pay less than they say? Testbed laboratory experiments with IV and HG values

Hypothetical bias is a long-standing issue in stated preference and contingent valuation studies - people tend to overstate their preferences when they do not experience the real monetary consequences of their decision. This view, however, has been challenged by recent evidence based on the elicitation of induced values (IV) in the lab and homegrown (HG) demand function from different countries. This paper uses an experimental design to assess the extent and relevance of hypothetical bias in demand elicitation exercises for both IV and HG values. For testbed purpose, we use a classic second-price auction to elicit preferences. Comparing the demand curve we elicit in both, hypothetical bias unambiguously (i) vanishes in an induced-value, private good context, and (ii) persists in homegrown values elicitation context. This suggests hypothetical bias in preference elicitation appears to be driven by "preference formation" rather than "preference elicitation". In addition, companion treatments highlight two sources of the discrepancy observed in the HG setting: the hypothetical context leads bidders to underestimate the constraints imposed by their budget limitations, whereas the real context creates pressure leading them to bid "zero" to opt out from the elicitation mechanism. As a result, there is a need for a demand elicitation procedure that helps subjects take the valuation exercise sincerely, but without putting extra pressure on them.Auctions; Demand revelation; Experimental valuation; Hypothetical bias

Do people always pay less than they say? Testbed laboratory experiments with IV and HG values

Hypothetical bias is a long-standing issue in stated preference and contingent valuation studies – people generally overstate their preferences when they do not experience the real monetary consequences of their decision. This view, however, has been challenged by recent evidence based on the elicitation of induced values (IV) in the lab and homegrown (HG) demand function from different countries. This paper uses a two experiments design to assess the extent and relevance of hypothetical bias in demand elicitation exercises for both IV and HG values. For testbed purpose, we use a classic second-price auction to elicit preferences. Comparing the demand curve we elicit in both, hypothetical bias unambiguously (i) vanishes in an induced-value, private good context, and (ii) persists in homegrown values elicitation context. This suggests hypothetical bias in preference elicitation appears to be driven by “preference formation” rather than “preference elicitation”. In addition, companion treatments highlight two sources of the discrepancy observed in the HG setting: the hypothetical context leads bidders to underestimate the constraints imposed by their budget limitations, whereas the real context creates pressure leading them to bid “zero” to opt out from the elicitation mechanism. As a result, there is a need for a demand elicitation procedure that helps subjects take the valuation exercise sincerely, but without putting extra pressure on them.Auctions; Demand revelation; Experimental valuation; Hypothetical bias

Inefficiency of equilibria in query auctions with continuous valuations

Query auctions are iterative auctions in which bidders have to select in each round an action from a finite set. We show that, when bidders have continuous valuations, any ex post equilibrium in an ex post individually rational query auction can only be ex post efficient when the running time of the auction is infinite for almost all realizations of valuations of thebidders. Thus, when valuations are drawn from a continuous probability distribution, efficiency can only be bought at the expense of a running time that is infinite with probability one. For two bidders we even show this to be true when we only require efficiency with probability one.mathematical economics;