Informational Robustness in Intertemporal Pricing

Libgober, Jonathan; Mu, Xiaosheng

doi:10.2139/ssrn.2892096

Cited by 6 publications

(2 citation statements)

References 41 publications

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“…I show that when

N = 1

, the revenue guarantee of the exponential price auction is exactly the seller's optimal revenue at the Roesler–Szentes information structure, thus proving the optimality of the revenue guarantee. The Roesler–Szentes information structure and the exponential price auction have proved to be useful in the study of a robust dynamic pricing problem by Libgober and Mu ().…”

Section: Introductionmentioning

confidence: 99%

Robust Mechanisms Under Common Valuation

Du¹

2018

Econometrica

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I construct an informationally robust auction to sell a common‐value good. I examine the revenue guarantee of an auction over all information structures of bidders and all equilibria. As the number of bidders gets large, the revenue guarantee of my auction converges to the full surplus, regardless of how information changes as more bidders are added. My auction also maximizes the revenue guarantee when there is a single bidder.

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“…I show that when

N = 1

Section: Introductionmentioning

confidence: 99%

Robust Mechanisms Under Common Valuation

Du¹

2018

Econometrica

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“…See alsoBergemann and Schlag (2011), Wolitzky (2016),Carroll (2015Carroll ( , 2017Carroll ( , 2019,Libgober and Mu (2019), and Chen and Li (2018) for work on robust mechanism design in other environments or with alternative speci cations.3 I analyzed the Stackelberg version unaware of their contribution. Since my version focuses on the part of the results comparable to the simultaneous game model studied in the current paper, I collect my analysis of the Stackelberg model in the Supplemental Appendix.…”

mentioning

confidence: 99%

Robust Reserve Pricing in Auctions Under Mean Constraints

Che

2019

SSRN Journal

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Robust Mechanisms Under Common Valuation

2018

SSRN Journal

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We study robust mechanisms to sell a common-value good. We assume that the mechanism designer knows the prior distribution of the buyers' common value but is unsure of the buyers' information structure about the common value. We use linear programming duality to derive mechanisms that guarantee a good revenue among all information structures and all equilibria. Our mechanism maximizes the revenue guarantee when there is one buyer. As the number of buyers tends to infinity, the revenue guarantee of our mechanism converges to the full surplus.2 In other words, Roesler and Szentes (2016) characterize for one buyer: min info. structure max mechanism, equilibrium Revenue, while we characterize: max mechanism min info. structure, equilibriumRevenue, and show it is equal to their min-max value. Equilibrium here is a mapping from signals of the information structure to messages in the mechanism, such that there is no incentive to deviate. 3 When the prior is the uniform [0, 1] distribution, a posted price of p ≤ 1/2 guarantees a revenue of

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Informational Robustness in Intertemporal Pricing

Cited by 6 publications

References 41 publications

Robust Mechanisms Under Common Valuation

Robust Mechanisms Under Common Valuation

Robust Reserve Pricing in Auctions Under Mean Constraints

Robust Mechanisms Under Common Valuation

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