- Vijay Krishna
Vijay Krishnaâs 2e of Auction Theory improves upon his 2002 bestseller with a new chapter on package and position auctions as well as end-of-chapter questions and chapter notes. Complete proofs and new material about collusion complement Krishnaâs ability to reveal the basic facts of each theory in a style that is clear, concise, and easy to follow. With the addition of a solutions manual and other teaching aids, the 2e continues to serve as the doorway to relevant theory for most students doing empirical work on auctions.
Graduate students and professors working in finance, economics, and industrial organization, and professionals learning about or developing auctions, either in a university setting or in industry.
Hardbound, 336 Pages
Published: August 2009
Imprint: Academic Press
"Krishnaâs superbAuction Theory is an ideal text and reference because his clear and precise exposition distills the vast literature and provides excellent motivation, examples, exercises, and connections to commercial applications."--Robert B. Wilson, Stanford University "On its publication in 2002, Vijay Krishna's book immediately became a central reference in auction theory. But the subject has continued to develop, and so we're very fortunate that Krishna has now updated the text."-- Eric Maskin, Institute for Advanced Study, Nobel Laureate in Economics
I. Single Object Auctions: Private Value Auctions, The Revenue Equivalence Principle, Qualifications and Extensions, Mechanism Design, Auctions with Interdependent Values, The Revenue Ranking ("Linkage") Principle, Asymmetries and Other Complications, Efficiency and the English Auction, Mechanism Design with Interdependent Values, Bidding Rings
II. Multiple Object Auctions: An Introduction to Multiple Object Auctions, Equilibrium and Efficiency with Private Values, Some Revenue Considerations, Sequential Sales, Nonidentical Objects, Packages and Positions, Multiple Objects and Interdependent Values
III. Appendices: Continuous Distributions, Stochastic Orders, Order Statistics, Affiliated Random Variables, Some Linear Algebra