Inferring ascending auction participation from observed bidders
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DOI: 10.1016/j.ijindorg.2017.06.001
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References listed on IDEAS
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Cited by:
- Dominic Coey & Bradley J. Larsen & Brennan C. Platt, 2020.
"Discounts and Deadlines in Consumer Search,"
American Economic Review, American Economic Association, vol. 110(12), pages 3748-3785, December.
- Dominic Coey & Bradley Larsen & Brennan Platt, 2016. "Discounts and Deadlines in Consumer Search," NBER Working Papers 22038, National Bureau of Economic Research, Inc.
- Joachim Freyberger & Bradley J. Larsen, 2022.
"Identification in ascending auctions, with an application to digital rights management,"
Quantitative Economics, Econometric Society, vol. 13(2), pages 505-543, May.
- Joachim Freyberger & Bradley J. Larsen, 2017. "Identification in Ascending Auctions, with an Application to Digital Rights Management," NBER Working Papers 23569, National Bureau of Economic Research, Inc.
- Matthew Backus & Gregory Lewis, 2016. "Dynamic Demand Estimation in Auction Markets," NBER Working Papers 22375, National Bureau of Economic Research, Inc.
- Dominic Coey & Bradley J. Larsen & Kane Sweeney & Caio Waisman, 2021. "Scalable Optimal Online Auctions," Marketing Science, INFORMS, vol. 40(4), pages 593-618, July.
- Cristián Hernández & Daniel Quint & Christopher Turansick, 2020. "Estimation in English auctions with unobserved heterogeneity," RAND Journal of Economics, RAND Corporation, vol. 51(3), pages 868-904, September.
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More about this item
Keywords
Unobserved auction participation; Estimation of number of bidders; Ascending auctions;All these keywords.
JEL classification:
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
- D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
Statistics
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