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Empirical Models of Auctions

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  • Susan Athey
  • Philip A. Haile

Abstract

Many important economic questions arising in auctions can be answered only with knowledge of the underlying primitive distributions governing bidder demand and information. An active literature has developed aiming to estimate these primitives by exploiting restrictions from economic theory as part of the econometric model used to interpret auction data. We review some highlights of this recent literature, focusing on identification and empirical applications. We describe three insights that underlie much of the recent methodological progress in this area and discuss some of the ways these insights have been extended to richer models allowing more convincing empirical applications. We discuss several recent empirical studies using these methods to address a range of important economic questions.

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  • Susan Athey & Philip A. Haile, 2006. "Empirical Models of Auctions," NBER Working Papers 12126, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:12126
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    Cited by:

    1. ,, 2011. "Manipulative auction design," Theoretical Economics, Econometric Society, vol. 6(2), May.
    2. Ivaldi, Marc & Motis, Jrissy, 2007. "Mergers as Auctions," CEPR Discussion Papers 6434, C.E.P.R. Discussion Papers.
    3. Blancas, Luis & Chioda, Laura & Cordella, Tito & Oliveira, Alexandre & Vardy, Felix, 2011. "Do procurement rules impact infrastructure investment efficiency ? an empirical analysis of inversao das fases in Sao Paulo state," Policy Research Working Paper Series 5528, The World Bank.
    4. Philip A Haile & Yuichi Kitamura, 2019. "Unobserved heterogeneity in auctions," The Econometrics Journal, Royal Economic Society, vol. 22(1), pages 1-19.
    5. J. Levin & L. Einav., 2012. "Empirical Industrial Organization: A Progress Report," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 1.
    6. Bruno Bosco & Lucia Parisio & Matteo Pelagatti, 2010. "Estimating Marginal Costs and Market Power in the Italian Electricity Auctions," Working Papers 20100201, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
    7. Bigerna, Simona & Bollino, Carlo Andrea & D'Errico, Maria Chiara & Polinori, Paolo, 2017. "The Ideal Competitive Electricity Market. A simulation for Italy," MPRA Paper 94893, University Library of Munich, Germany.
    8. Armantier, Olivier & Ghysels, Eric & Sarkar, Asani & Shrader, Jeffrey, 2015. "Discount window stigma during the 2007–2008 financial crisis," Journal of Financial Economics, Elsevier, vol. 118(2), pages 317-335.
    9. Gian Luigi Albano & Federico Dini & Roberto Zampino, 2008. "Bidding for Complex Projects: Evidence From the Acquisitions of IT Services," Working Papers 2008.86, Fondazione Eni Enrico Mattei.
    10. Sang Won Kim & Marcelo Olivares & Gabriel Y. Weintraub, 2014. "Measuring the Performance of Large-Scale Combinatorial Auctions: A Structural Estimation Approach," Management Science, INFORMS, vol. 60(5), pages 1180-1201, May.
    11. Song, Zirui & Landrum, Mary Beth & Chernew, Michael E., 2013. "Competitive bidding in Medicare Advantage: Effect of benchmark changes on plan bids," Journal of Health Economics, Elsevier, vol. 32(6), pages 1301-1312.
    12. Marcelo Olivares & Gabriel Y. Weintraub & Rafael Epstein & Daniel Yung, 2012. "Combinatorial Auctions for Procurement: An Empirical Study of the Chilean School Meals Auction," Management Science, INFORMS, vol. 58(8), pages 1458-1481, August.
    13. Jehiel, Philippe & Moldovanu, Benny, 2005. "Allocative and Informational Externalities in Auctions and Related Mechanisms," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 142, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    14. Bosco, Bruno & Parisio, Lucia & Pelagatti, Matteo, 2012. "Strategic bidding in vertically integrated power markets with an application to the Italian electricity auctions," Energy Economics, Elsevier, vol. 34(6), pages 2046-2057.
    15. Albano, Gian Luigi & Dini, Federico & Zampino, Roberto, 2008. "Bidding for Complex Projects: Evidence From the Acquisitions of IT Services," Privatisation Regulation Corporate Governance Working Papers 46547, Fondazione Eni Enrico Mattei (FEEM).
    16. Quang Vuong & Ayse Pehlivan, 2016. "Nonparametric Identification and Estimation of Productivity Distributions and Trade Costs," 2016 Meeting Papers 1618, Society for Economic Dynamics.
    17. Sweeting, Andrew & Bhattacharya, Vivek, 2015. "Selective entry and auction design," International Journal of Industrial Organization, Elsevier, vol. 43(C), pages 189-207.
    18. Bierens, Herman J. & Song, Hosin, 2012. "Semi-nonparametric estimation of independently and identically repeated first-price auctions via an integrated simulated moments method," Journal of Econometrics, Elsevier, vol. 168(1), pages 108-119.
    19. Veronika Grimm, 2007. "Paarsch, H. J., and Hong, H.: An Introduction to the Structural Econometrics of Auction Data," Journal of Economics, Springer, vol. 92(2), pages 205-208, October.
    20. Wenchuan Liu & Yu Zhang & Qi Li, 2015. "A semiparametric varying coefficient model of monotone auction bidding processes," Empirical Economics, Springer, vol. 48(1), pages 313-335, February.
    21. Committee, Nobel Prize, 2020. "Improvements to auction theory and inventions of new auction formats," Nobel Prize in Economics documents 2020-2, Nobel Prize Committee.
    22. Maria Chiara D?Errico, 2020. "Competition in the Italian electricity market: The unforeseen social welfare losses of reform," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2020(2), pages 75-91.
    23. 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.
    24. Charles A. Holt & William Shobe & Dallas Burtraw & Karen Palmer & Jacob K. Goeree, 2007. "Auction Design for Selling CO2 Emission Allowances Under the Regional Greenhouse Gas Initiative," Reports 2007-03, Center for Economic and Policy Studies.

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    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • D4 - Microeconomics - - Market Structure, Pricing, and Design

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