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18 - A Combinatorial Auction Mechanism for Airport Time Slot Allocation
- from Part III - Alternative Auction Designs
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- By Stephen J. Rassenti, Economic Science Institute, Chapman University, Vernon L. Smith, Economic Science Institute, Chapman University, Robert L. Bulfin, Department of Industrial and Systems Engineering, Auburn University
- Edited by Martin Bichler, Technische Universität München, Jacob K. Goeree, University of New South Wales, Sydney
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- Book:
- Handbook of Spectrum Auction Design
- Published online:
- 26 October 2017
- Print publication:
- 26 October 2017, pp 373-390
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Summary
The Problem of Allocating Airport Slots
In 1968 the FAA adopted a high density rule for the allocation of scarce landing and take-off slots at four major airports (La Guardia,Washington National, Kennedy International, and O'Hare International). This rule establishes slot quotas for the control of airspace congestion at these airports.
Airport runway slots, regulated by these quotas, have a distinguishing feature which any proposed allocation procedure must accommodate: an airline's demand for a takeoff slot at a flight originating airport is not independent of its demand for a landing slot at the flight destination airport. Indeed, a given flight may take off and land in a sequence of several connected demand interdependent legs. For economic efficiency it is desirable to develop an airport slot allocation procedure that allocates individual slots to those airline flights for which the demand (willingness to pay) is greatest.
Grether, Isaac, and Plott (hereafter, GIP) (1979, 1981) have proposed a practical market procedure for achieving this goal. Their procedure is based upon the growing body of experimental evidence on the performance of (1) the competitive (uniform price) sealed-bid auction and (2) the oral double auction such as is used on the organized stock and commodity exchanges. Under their proposal an independent primary market for slots at each airport would be organized as a sealed-bid competitive auction at timely intervals. Since the primary market allocation does not make provision for slot demand interdependence, a computerized form of the oral double auction (with block transaction capabilities) is proposed as an “after market” to allow airlines to purchase freely and sell primary market slots to each other. This continuous after market exchange would provide the institutional means by which individual airlines would acquire those slot packages which support their individual flight schedules. Thus, an airline that acquired slots at Washington National which did not flight-match the slots acquired at O'Hare could either buy additional O'Hare slots or sell its excess Washington slots in the after market.
5 - Combinatorial Auction Design
- from Part II - The Combinatorial Clock Auction Designs
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- By David P. Porter, Economic Science Institute, Chapman University, Stephen J. Rassenti, Economic Science Institute, Chapman University, Anil Roopnarine, Cybernomics Inc, Vernon L. Smith, Economic Science Institute, Chapman University
- Edited by Martin Bichler, Technische Universität München, Jacob K. Goeree, University of New South Wales, Sydney
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- Book:
- Handbook of Spectrum Auction Design
- Published online:
- 26 October 2017
- Print publication:
- 26 October 2017, pp 111-119
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Summary
Introduction
Combinatorial auctions enhance our ability to efficiently allocate multiple resources in complex economic environments. They explicitly allow buyers and sellers of goods and services to bid on packages of items with related values or costs. For example, “I bid $10 to buy 1 unit of item A and 2 units of item B, but I won't pay anything unless I get everything.” They also allow buyers, sellers and the auctioneer to impose logical constraints that limit the feasible set of auction allocations. For example, “I bid $12 to buy 2 units of item C OR $15 to buy 3 units of item D, but I don't want both.” Finally, they can handle functional relationships amongst bids or allocations, such as budget constraints or aggregation limits that allow many bids to be connected together. For example, “I won't spend more than a total of $35 on all my bids” or “This auction will allocate no more than a total of 7 units of items F, G and H.”
There are several reasons to prefer to have the bidding message space expanded beyond the simple space used for traditional single commodity auctions. As Bykowsky et al. (2000) point out, when values have strong complementarities, there is a danger of ‘financial exposure’ that results in losses to bidders if combinatorial bidding is not allowed. For example, in the case of complementary items such as airport take-off and landing times, the ability to reduce uncertainty to the bidder by allowing him to precisely declare his object of value, a cycle of slots for an entire daily flight pattern, is obvious: one component slot not acquired ruins the value of the flight cycle. In the same situation substitution possibilities would also be important to consider: if flight cycle A is not won, cycle B may be an appropriate though less valuable substitute for the crew and equipment available. Allocation inefficiencies due to financial exposure in noncombinatorial auctions have been frequently demonstrated in experiments beginning with Rassenti et al. (1982) (see also Porter (1999), Banks et al. (1989), Ledyard et al. (2002) and Kwasnika et al. (1998)).
8 - Game Theory and Reciprocity in Some Extensive Form Experimental Games
- Vernon L. Smith, University of Arizona
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- Book:
- Bargaining and Market Behavior
- Published online:
- 29 October 2009
- Print publication:
- 12 June 2000, pp 152-176
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Summary
We use variations on a relatively transparent, two-person extensive form bargaining game to examine principles of self-evident play (Kreps, 1990a) using experimental analysis. Our game is transparent if players can be expected to understand the relationship between the possible sequences of plays with their counterparts and the resulting payoffs that can be achieved. However, how to develop strategy for a relatively transparent game may not be self-evident because it requires players to be confident about their counterparts' actions and reactions. So, when are players likely to be mutually confident?
Evolutionary psychology provides one approach to answering this question. Hoffman et al. (1996b) and the references therein give a more extended discussion of the role of evolutionary psychology in explaining many economics experiments that exhibit anomalous behavior relative to standard theory. Even though economic theory assumes that individuals employ general purpose consciously cognitive algorithms to optimize gains in any situation, evolutionary psychology assumes that individuals deploy domain-specific cognitive algorithms, with different algorithms being used for different situations, often in nonconscious ways. Economic theory disciplines our thinking by requiring behaviors that maximize individual utility, whereas evolutionary psychology disciplines our thinking by requiring blue-prints for behavioral activity that can be adapted under natural selection. Of course the relative value of these blueprints from nature depends on their subsequent development by cultural interaction (nurture) and a continuing evaluation of behavioral success through experience.
In this chapter, we address the following question: Can we use principles from game theory, experimental economics, and evolutionary psychology to better understand what is self-evident to players playing our extensive form games?
I. Principles of Behavior
The fundamental principles which underpin the propositions we examine experimentally can be stated as follows:…
31 - Designing ‘Smart’ Computer-Assisted Markets
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- By Kevin A. McCabe, Stephen J. Rassenti, Economic Science Laboratory, University of Arizona, Tucson, AZ 85721, USA
- Vernon L. Smith, University of Arizona
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- Book:
- Papers in Experimental Economics
- Published online:
- 06 July 2010
- Print publication:
- 29 November 1991, pp 678-702
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Summary
We study a sealed bid-offer auction market for simultaneously pricing natural gas at each delivery outlet, source, and on all pipelines that connect sources with delivery points. Wholesale buyers submit location-specific bid schedules for amounts of delivered gas at corresponding prices. Wellhead owners submit location-specific offer schedules for amounts of produced gas they are willing to sell at corresponding offer prices. Pipeline owners submit leg-specific schedules of transportation capacity they are willing to commit at corresponding prices. A computer algorithm maximizes total gains from exchange based on the submitted bids and offers and determines allocations and non-discriminatory prices at all nodes.
As a consequence of technological economies of scale in pipeline transportation, natural gas has been considered a classic case of natural monopoly. But entry, growth and development in the industry in the United States has yielded more than one pipeline in most producing fields. Similarly most wholesale markets are served by at least two pipelines [Norman (1987)]. The concept of natural monopoly is a static concept; i.e. given any level of demand, declining long run marginal planning cost implies that one pipeline - a very large one, if demand is high – yields the least-cost solution to satisfying that demand. But in fact demand is cyclical and tends to grow over time, and new gas wells and gas fields develop over time.