Common Value Auctions And The Winner S Curse

An invaluable account of how auctions work—and how to make them work Few forms of market exchange intrigue economists as do auctions, whose theoretical and practical implications are enormous. John Kagel and Dan Levin, complementing their own distinguished research with papers written with other specialists, provide a new focus on common value auctions and the "winner's curse." In such auctions the value of each item is about the same to all bidders, but different bidders have different information about the underlying value. Virtually all auctions have a common value element; among the burgeoning modern-day examples are those organized by Internet companies such as eBay. Winners end up cursing when they realize that they won because their estimates were overly optimistic, which led them to bid too much and lose money as a result. The authors first unveil a fresh survey of experimental data on the winner's curse. Melding theory with the econometric analysis of field data, they assess the design of government auctions, such as the spectrum rights (air wave) auctions that continue to be conducted around the world. The remaining chapters gauge the impact on sellers' revenue of the type of auction used and of inside information, show how bidders learn to avoid the winner's curse, and present comparisons of sophisticated bidders with college sophomores, the usual guinea pigs used in laboratory experiments. Appendixes refine theoretical arguments and, in some cases, present entirely new data. This book is an invaluable, impeccably up-to-date resource on how auctions work--and how to make them work.

This book in microeconomics focuses on the strategic analysis of markets under imperfect competition, incomplete information, and incentives. Part I of the book covers imperfect competition, from monopoly and regulation to the strategic analysis of oligopolistic markets. Part II explains the analytics of risk, stochastic dominance, and risk aversion, supplemented with a variety of applications from different areas in economics. Part III focuses on markets and incentives under incomplete information, including a comprehensive introduction to the theory of auctions, which plays an important role in modern economics.

An examination of an area of economic research whereby economists have begun to use laboratories to evaluate economic propositions under carefully controlled conditions. The authors argue for the effectiveness of this technique in selected circumstances.

The award-winning The New Palgrave Dictionary of Economics, 2nd edition is now available as a dynamic online resource. Consisting of over 1,900 articles written by leading figures in the field including Nobel prize winners, this is the definitive scholarly reference work for a new generation of economists. Regularly updated! This product is a subscription based product.

Annotation This book contains a collection of papers that address various aspects of risk, including riskmanagement and how it is applied to decisionmaking and the impact of risk on markets

Explore cutting-edge statistical methodologies for collecting, analyzing, and modeling online auction data Online auctions are an increasingly important marketplace, as the new mechanisms and formats underlying these auctions have enabled the capturing and recording of large amounts of bidding data that are used to make important business decisions. As a result, new statistical ideas and innovation are needed to understand bidders, sellers, and prices. Combining methodologies from the fields of statistics, data mining, information systems, and economics, Modeling Online Auctions introduces a new approach to identifying obstacles and asking new questions using online auction data. The authors draw upon their extensive experience to introduce the latest methods for extracting new knowledge from online auction data. Rather than approach the topic from the traditional game-theoretic perspective, the book treats the online auction mechanism as a data generator, outlining methods to collect, explore, model, and forecast data. Topics covered include: Data collection methods for online auctions and related issues that arise in drawing data samples from a Web site Models for bidder and bid arrivals, treating the different approaches for exploring bidder-seller networks Data exploration, such as integration of time series and cross-sectional information; curve clustering; semi-continuous data structures; and data hierarchies The use of functional regression as well as functional differential equation models, spatial models, and stochastic models for capturing relationships in auction data Specialized methods and models for forecasting auction prices and their applications in automated bidding decision rule systems Throughout the book, R and MATLAB software are used for illustrating the discussed techniques. In addition, a related Web site features many of the book's datasets and R and MATLAB code that allow readers to replicate the analyses and learn new methods to apply to their own research. Modeling Online Auctions is a valuable book for graduate-level courses on data mining and applied regression analysis. It is also a one-of-a-kind reference for researchers in the fields of statistics, information systems, business, and marketing who work with electronic data and are looking for new approaches for understanding online auctions and processes. Visit this book's companion website by clicking here

Offers a systematic approach to the examination of online procurement auctions. Growth in online auctions reinforces the need for understanding the factors important in auctions and the caveats that both researchers and practitioners need to know in order to effectively study and use the auction tool.