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An information–Theoretic approach to partially identified auction models

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  • Jun, Sung Jae
  • Pinkse, Joris

Abstract

We consider a situation in which we have data from ascending auctions with symmetric bidders, independent private values, and exogenous entry in which the bidders’ value distribution is partially identified. Focusing on the case in which the seller intends to use a second price auction, we discuss how to determine an optimal reserve price. We justify the use of maximum entropy, explore the properties of the estimand, determine the asymptotic properties of our maximum entropy estimator, evaluate its behavior in a simulation study, and demonstrate its use in a modest application. As an extension, we propose a maxmin decision rule with entropy regularization, which includes Aryal and Kim (2013) and the maximum entropy solution as extreme cases.

Suggested Citation

  • Jun, Sung Jae & Pinkse, Joris, 2024. "An information–Theoretic approach to partially identified auction models," Journal of Econometrics, Elsevier, vol. 238(2).
    • Handle: RePEc:eee:econom:v:238:y:2024:i:2:s0304407623002828
    DOI: 10.1016/j.jeconom.2023.105566
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    References listed on IDEAS

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    1. Bulow, Jeremy & Klemperer, Paul, 1996. "Auctions versus Negotiations," American Economic Review, American Economic Association, vol. 86(1), pages 180-194, March.
    2. Gaurab Aryal & Dong-Hyuk Kim, 2013. "A Point Decision for Partially Identified Auction Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(4), pages 384-397, October.
    3. Bradley J Larsen, 2021. "The Efficiency of Real-World Bargaining: Evidence from Wholesale Used-Auto Auctions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(2), pages 851-882.
    4. Susan Athey & Philip A. Haile, 2002. "Identification of Standard Auction Models," Econometrica, Econometric Society, vol. 70(6), pages 2107-2140, November.
    5. Victor Chernozhukov & Han Hong & Elie Tamer, 2007. "Estimation and Confidence Regions for Parameter Sets in Econometric Models," Econometrica, Econometric Society, vol. 75(5), pages 1243-1284, September.
    6. Jun, Sung Jae & Pinkse, Joris, 2020. "Counterfactual prediction in complete information games: Point prediction under partial identification," Journal of Econometrics, Elsevier, vol. 216(2), pages 394-429.
    7. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
    8. Donald W. K. Andrews & Gustavo Soares, 2010. "Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection," Econometrica, Econometric Society, vol. 78(1), pages 119-157, January.
    9. Hsieh, Yu-Wei & Shi, Xiaoxia & Shum, Matthew, 2022. "Inference on estimators defined by mathematical programming," Journal of Econometrics, Elsevier, vol. 226(2), pages 248-268.
    10. Philip A. Haile & Elie Tamer, 2003. "Inference with an Incomplete Model of English Auctions," Journal of Political Economy, University of Chicago Press, vol. 111(1), pages 1-51, February.
    11. Roger B. Myerson, 1981. "Optimal Auction Design," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 58-73, February.
    12. Dominic Coey & Bradley Larsen & Kane Sweeney & Caio Waisman, 2017. "Ascending auctions with bidder asymmetries," Quantitative Economics, Econometric Society, vol. 8(1), pages 181-200, March.
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    More about this item

    Keywords

    English auctions; partial identification; maximum entropy; inequality constraints; nonparametric inference;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C57 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Econometrics of Games and Auctions

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