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Integrated-quantile-based estimation for first price auction models

Listed author(s):
  • Yao Luo
  • Yuanyuan Wan
Registered author(s):

    This paper considers nonparametric estimation of first-price auction models under the monotonicity restriction on the bidding strategy. Based on an integrated-quantile representation of the first-order condition, we propose a tuning-parameter-free estimator for the valuation quantile function. We establish its cube-root-n consistency and asymptotic distribution under weaker smoothness assumptions than those typically assumed in the empirical literature. If the latter are true, we also provide a trimming-free smoothed estimator and show that it is asymptotically normal and achieves the optimal rate of Guerre, Perrigne, and Vuong (2000). We illustrate our methods using Monte Carlo simulations and an empirical study of the California highway procurements auctions.

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    File URL: https://www.economics.utoronto.ca/public/workingPapers/tecipa-539.pdf
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    Paper provided by University of Toronto, Department of Economics in its series Working Papers with number tecipa-539.

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    Length: Unknown pages
    Date of creation: 06 May 2015
    Handle: RePEc:tor:tecipa:tecipa-539
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    1. Matthew Shum, 2000. "Nonparametric Tests for Common Values," Econometric Society World Congress 2000 Contributed Papers 1598, Econometric Society.
    2. Nianqing Liu & Yao Luo, 2014. "A Nonparametric Test of Exogenous Participation in First-Price Auctions," Working Papers tecipa-519, University of Toronto, Department of Economics.
    3. Marmer, Vadim & Shneyerov, Artyom, 2012. "Quantile-based nonparametric inference for first-price auctions," Journal of Econometrics, Elsevier, vol. 167(2), pages 345-357.
    4. Brent R. Hickman & Timothy P. Hubbard, 2015. "Replacing Sample Trimming with Boundary Correction in Nonparametric Estimation of Firstā€Price Auctions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 739-762, 08.
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