We identify an important class of economic problems that arise naturally in several applications: the allocation of multiple resources when there are uncertainties in demand or supply, unresponsive supplies (no inventories and fixed capacities), and significant demand indivisibilities (rigidities). Examples of such problems include: scheduling job shops, airports, or supercomputers; zero-inventory planning; and the allocation and pricing of NASA's planned Space Station. Using experimental methods, we show that the two most common organizations used to deal with this problem, markets and administrative procedures, can perform at very low efficiencies (60-65% efficiency in a seemingly robust example). Thus, there is a need to design new mechanisms that more efficiently allocate resources in these environments. We develop and analyze two mechanisms that arise naturally from auctions used to allocate single-dimensional goods. These new mechanisms involve computer-assisted coordination made possible by the existence of networked computers. Both mechanisms significantly improve on the performance of administrative and market procedures.
Combinatorial auctions allow for more expressive bidding in which participants can submit package bids with logical constraints that limit allowable outcomes. This type of auction can be useful when participants' values are complementary or when participants have production and financial constraints. However, combinatorial auctions are currently rare in practice. The main problems confronted in implementing these auctions are that they have computational uncertainty (i.e., there is no guarantee that the winning bids for such an auction can be found in a ''reasonable'' amount of time when the number of bidders and items becomes larger) and that the auction is cognitively complex and can lead participants to pursue perverse bidding strategies. This article describes a type of combinatorial auction that, during laboratory testing, eliminated these problems and produced extremely efficient outcomes.
Prediction markets are increasingly being considered as methods for gathering, summarizing and aggregating diffuse information by governments and businesses alike. Critics worry that these markets are susceptible to price manipulation by agents who wish to distort decision making. We study the effect of manipulators on an experimental market. We find that manipulators are unable to distort price accuracy. Subjects without manipulation incentives compensate for the bias in offers from manipulators by setting a different threshold at which they are willing to accept trades.
We report 28 new experiment sessions consisting of up to three experience levels to examine the robustness of learning and 'error' elimination by participants in a laboratory asset market and its effect on price bubbles. Our answer to the title question is: "yes."We impose a large increase in liquidity and dividend uncertainty to shock the environment of experienced subjects who have converged to equilibrium, and this treatment rekindles a bubble. However, in replications of that challenging environment across three experience levels we discover that the environment yields a rare residual tendency to bubble even in the third experience session. Therefore, a caveat must be placed on the effect of twice experienced subjects in asset markets: in order for price bubbles to be extinguished, the environment in which the participants engage in exchange must be stationary and bounded by a range of parameters. Experience, including possible 'error' elimination, is not robust to major new environment changes in determining the characteristics of a price bubble.
Combined-value auctions (CVAs) allow participants to make an offer of a single amount for a collection of items. These auctions provide value to both buyers and sellers of goods or services in a number of environments, but they have rarely been implemented, perhaps because of lack of knowledge and experience. Sears Logistics Services (SLS) is the first procurer of trucking services to use a CVA to reduce its costs. In 1993, it saved 13 percent over past procurement practices. Experimental economics played a crucial role in the development, sale, and use of the CVA.
A series of experiments, in which nine participants trade an asset over 15 periods, test the hypothesis that an initial imbalance of asset͞cash will inf luence the trading price over an extended time. Participants know at the outset that the asset or ''stock'' pays a single dividend with fixed expectation value at the end of the 15th period. In experiments with a greater total value of cash at the start, the mean prices during the trading periods are higher, compared with those with greater amount of asset, with a high degree of statistical significance. The difference is most significant at the outset and gradually tapers near the end of the experiment. The results are very surprising from a rational expectations and classical game theory perspective, because the possession of a large amount of cash does not lead to a simple motivation for a trader to bid excessively on a financial instrument. The gradual erosion of the difference toward the end of trading, however, suggests that fundamental value is approached belatedly, offering some consolation to the rational expectations theory. It also suggests that there is a time scale on which an evolution toward fundamental value occurs. The experimental results are qualitatively compatible with the price dynamics predicted by a system of differential equations based on asset f low. The results have broad implications for the marketing of securities, particularly initial and secondary public offerings, government bonds, etc., where excess supply has been conjectured to suppress prices.
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