Learning about Learning in Games through Experimental Control of Strategic Interdependence

We conduct experiments in which humans repeatedly play one of two games against a computer decision maker that follows either Roth and Erev's reinforcement learning algorithm or Camerer and Ho's EWA algorithm. The human/algorithm interaction provides results that can't be obtained from the analysis of pure human interactions or model simulations. The learning algorithms are more sensitive than humans in calculating exploitable opponent play. Learning algorithms respond to these calculated opportunities systematically; however, the magnitude of these responses are too weak to improve the algorithm's payoffs. Human play against various decision maker types does not significantly vary. These results demonstrate that humans and currently proposed models of their behavior differ in that humans do not adjust payoff assessments by smooth transition functions and that when humans detect exploitable play they are more likely to choose the best response to this belief.

Procurement Auctions for Differentiated Goods

We consider two mechanisms to procure differentiated goods: a request for quote and an English auction with bidding credits. In the request for quote, each seller submits a price and the inherent quality of his good. Then the buyer selects the seller who offers the greatest difference in quality and price. In the English auction with bidding credits, the buyer assigns a bidding credit to each seller conditional upon the quality of the seller’s good. Then the sellers compete in an English auction with the winner receiving the auction price and his bidding credit. Game theoretic models predict the request for quote is socially efficient but the English auction with bidding credits is not. The optimal bidding credit assignment under compensates for quality advantages, creating a market distortion in which the buyer captures surplus at the expense of the seller’s profit and social efficiency. In experiments, the request for quote is less efficient than the English auctions with bidding credits. Moreover, both the buyer and seller receive more surplus in the English auction with bidding credits.

Do We Detect and Exploit Mixed Strategy Play by Opponents?

We conducted an experiment in which each subject repeatedly played a game with a unique Nash equilibrium in mixed strategies against some computer-implemented mixed strategy. The results indicate subjects are successful at detecting and exploiting deviations from Nash equilibrium. However, there is heterogeneity in subject behavior and performance. We present a one variable model of dynamic random belief formation which rationalizes observed heterogeneity and other features of the data.best response correspondence, mixed strategy

Procurement Auctions for Differentiated Goods

We consider two mechanisms to procure differentiated goods: a request for quote and an English auction with bidding credits. In the request for quote, each seller submits a price and the inherent quality of his good. Then the buyer selects the seller who offers the greatest difference in quality and price. In the English auction with bidding credits, the buyer assigns a bidding credit to each seller conditional upon the quality of the seller’s good. Then the sellers compete in an English auction with the winner receiving the auction price and his bidding credit. Game theoretic models predict the request for quote is socially efficient but the English auction with bidding credits is not. The optimal bidding credit assignment under compensates for quality advantages, creating a market distortion in which the buyer captures surplus at the expense of the seller’s profit and social efficiency. In experiments, the request for quote is less efficient than the English auctions with bidding credits. Moreover, both the buyer and seller receive more surplus in the English auction with bidding creditsAuctions, Product Differentiation, Experiment

The performance of reverse auctions versus request for quotes when procuring goods with quality differences

The use of dynamic auctions is a major component in many enterprises' e-procurement initiatives. In the case where suppliers offer goods and services of inherently different quality the traditional mechanism has been the request for quote. In a request for quote, suppliers submit a sealed bid and the fixed quality of their offering and then the buyer selects the seller who offers the greatest difference between quality and price. The winning seller receives a price equal to his submitted bid. The reverse auction has immerged as the most commonly adopted dynamic auction for this setting. In a reverse auction, suppliers first submit the qualities of their goods and then the suppliers participate in an auction with the same message space as an open outcry English auction (descending because this is a procurement auction.) However, the auction is only used to set each suppliers price. The last price a supplier submits in the auction becomes their actual submitted price. After, the auction the buyer selects the winning seller who offers the greatest difference between quality and actual submitted price. We provide a game theoretic analysis of both mechanisms. We also provide extensive experimental evaluation of the two mechanisms as wellReverse Auction, Request for Quote, procurement

Play to Learn? An Experiment

Does playing a game in class improve students' ability to analyze the game using game theory? We report results from an experimental design which allows us to test a series of related hypotheses. We fail to find support for the conjectured learning-enhancing effects and discuss what lessons can be learned substantially and methodologically.

EconPort: Creating and Maintaining a Knowledge Commons

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Can Intertemporal Choice Experiments Elicit Time Preferences for Consumption? Yes

The most popular experimental method for eliciting time preferences involves subjects making choices over smaller, sooner amounts of money and larger, later amounts of money. Under some theoretically possible configurations of preferences and procedures, the discount rates inferred from these choices could lead to misleading inferences about time preferences for consumption. Using a direct empirical test, we show that those configurations of preferences are empirically implausible.

The Independence Axiom and the Bipolar Behaviorist

Developments in the theory of risk require yet another evaluation of the behavioral validity of the independence axiom. This axiom plays a central role in most formal statements of expected utility theory, as well as popular alternative models of decision-making under risk, such as rank-dependent utility theory. It also plays a central role in experiments used to characterize the way in which risk preferences deviate from expected utility theory. If someone claims that individuals behave as if they "probability weight" outcomes, and hence violate the independence axiom, it is invariably on the basis of experiments that must assume the independence axiom. We refer to this as the Bipolar Behavioral Hypothesis: behavioral economists are pessimistic about the axiom when it comes to characterizing how individuals directly evaluate two lotteries in a binary choice task, but are optimistic about the axiom when it comes to characterizing how individuals evaluate multiple lotteries that make up the incentive structure for a multiple-task experiment. Building on designs that have a long tradition in experimental economics, we offer direct tests of the axiom and the evidence for probability weighting. We reject the Bipolar Behavioral Hypothesis: we find that nonparametric preferences estimated for the rank-dependent utility model are significantly affected when one elicits choices with procedures that require the independence assumption, as compared to choices with procedures that do not require that assumption. We also demonstrate this result with familiar parametric preference specifications, and draw general implications for the empirical evaluation of theories about risk.