The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
5 Information Impact and Allocation Rules in Auctions with Affiliated Private Values: A Laboratory Study
Abstract
In affiliated private value auctions, each bidder has perfect information regarding own value for the object at auction, but higher values of the item for one bid der make higher values for rivals more likely. The authors report on a series of experiments examining the following predictions: (1) in a first-price auction, public information about rivals valuations incr eases expected revenue, (2) an English auction institution increases expected revenue, (2) an English auction institution increases expect ed revenue compared to a first-price auction, and (3) a second-price auction is isomorphic to an English auction institution. Predictive a dequacy of several ad hoc bidding models are compared with Nash equil ibrium predictions. Copyright 1987 by The Econometric Society.
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Cites
Prospect theory: An analysis of decision under risk
Kahneman, D., & Tversky, A. (1988) · Decision, Probability and Utility · doi:10.1017/cbo9780511609220.014 · Cited by 32,474
Statistical principles in experimental design.
Winer, B. J. (1962) · McGraw-Hill Book Company · doi:10.1037/11774-000 · Cited by 26,755
COUNTERSPECULATION, AUCTIONS, AND COMPETITIVE SEALED TENDERS
Vickrey, W. (1961) · The Journal of Finance · doi:10.1111/j.1540-6261.1961.tb02789.x · Cited by 7,722
A Theory of Auctions and Competitive Bidding
Milgrom, P. R., & Weber, R. J. (1982) · Econometrica · doi:10.2307/1911865 · Cited by 3,753
Competitive Bidding in High-Risk Situations
Capen, E. C., Clapp, R. V., & Campbell, W. M. (1971) · Journal of Petroleum Technology · doi:10.2118/2993-pa · Cited by 647
Cassady, R. (1967) · University of California Press eBooks · doi:10.1525/9780520322257 · Cited by 517
The Winner's Curse and Public Information in Common Value Auctions: Reply
Campbell, C. M., Kagel, J. H., & Levin, D. (1999) · American Economic Review · doi:10.1257/aer.89.1.325 · Cited by 514
Self-citationTheory and Behavior of Single Object Auctions
Cox, J. C., & Roberson, B. (1991) · Cambridge University Press eBooks · doi:10.1017/cbo9780511528354.031 · Cited by 395
INCENTIVES AND BEHAVIOR IN ENGLISH, DUTCH AND SEALED-BID AUCTIONS
COPPINGER, V. M., SMITH, V. L., & TITUS, J. A. (1980) · Economic Inquiry · doi:10.1111/j.1465-7295.1980.tb00556.x · Cited by 301
Cited by
7. Auctions: A Survey of Experimental Research
Kagel, J. H. (1995) · The Handbook of Experimental Economics · doi:10.1515/9780691213255-009 · Cited by 785
Self-citationUsing Field Experiments to Test Equivalence Between Auction Formats: Magic on the Internet
Lucking-Reiley, D. (1999) · American Economic Review · doi:10.1257/aer.89.5.1063 · Cited by 446
Hypothetical Surveys and Real Economic Commitments
Neill, H. R., Cummings, R. G., Ganderton, P. T., Harrison, G. W., & McGuckin, T. (1994) · Land Economics · doi:10.2307/3146318 · Cited by 349
Introduction to Experimental Economics
Roth, A. E. (2020) · The Handbook of Experimental Economics · doi:10.2307/j.ctvzsmff5.5 · Cited by 268
Maximization, learning, and economic behavior
Erev, I., & Roth, A. E. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1402846111 · Cited by 155
Metadata
- Authors
- Kagel, J. H., Harstad, R. M., & Levin, D.
- Venue
- Common Value Auctions and the Winner's Curse
- Publisher
- Princeton University Press
- Published
- 2009-12-31
- Pages
- 177-209
- OpenAlex
- W1985726524
- Cited by
- 458
- References
- 9
- FWCI
- 73.81
- Type
- book chapter
- Language
- en
- Open access
- closed
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