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An Estimable Demand System for a Large Auction Platform Market

Author

Listed:
  • Gregory Lewis

    (Harvard University)

  • Matthew Backus

    (University of Michigan)

Abstract

Economists have developed a range of empirically tractable demand systems for fixed price markets. But auction mechanisms also play an important part in allocating goods, and yet existing empirical auction techniques treat each auction in isolation, obscuring market interactions. Here we provide a framework for estimating a demand system in a large auction platform market with a dynamic population of buyers, heterogeneous objects and unit demand. We construct a model of repeated second-price auctions in which bidders have multidimensional private valuations, developing an equilibrium concept under which strategies reflect option values. We prove existence of this equilibrium and characterize the ergodic distribution of types. Having developed a demand system, we show that it is non-parametrically identified from panel data. Relatively simple nonparametric and semiparametric estimation procedures are proposed and tested by Monte Carlo simulation. Our analysis highlights the importance of both dynamic bidding strategies and panel data sample selection issues when analyzing these markets.

Suggested Citation

  • Gregory Lewis & Matthew Backus, 2010. "An Estimable Demand System for a Large Auction Platform Market," 2010 Meeting Papers 158, Society for Economic Dynamics.
    • Handle: RePEc:red:sed010:158
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    Cited by:

    1. Said, Maher, 2012. "Auctions with dynamic populations: Efficiency and revenue maximization," Journal of Economic Theory, Elsevier, vol. 147(6), pages 2419-2438.
    2. Said, Maher, 2011. "Sequential auctions with randomly arriving buyers," Games and Economic Behavior, Elsevier, vol. 73(1), pages 236-243, September.

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