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Quantile-Based Nonparametric Inference for First-Price Auctions

  • Marmer, Vadim
  • Shneyerov, Artyom

We propose a quantile-based nonparametric approach to inference on the probability density function (PDF) of the private values in first-price sealed-bid auctions with independent private values. Our method of inference is based on a fully nonparametric kernel-based estimator of the quantiles and PDF of observable bids. Our estimator attains the optimal rate of Guerre, Perrigne, and Vuong (2000), and is also asymptotically normal with the appropriate choice of the bandwidth.

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File URL: http://microeconomics.ca/vadim_marmer/auc-pdf_15.pdf
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Paper provided by Vancouver School of Economics in its series Microeconomics.ca working papers with number marmer-08-01-17-12-16-12.

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Length: 33 pages
Date of creation: 17 Jan 2008
Date of revision: 16 May 2013
Handle: RePEc:ubc:pmicro:marmer-08-01-17-12-16-12
Contact details of provider: Web page: http://www.economics.ubc.ca/

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  1. Guerre, E. & Perrigne, I. & Vuong, Q., 1995. "Nonparametric Estimation of First-Price Auctions," Papers 9504, Southern California - Department of Economics.
  2. Marmer, Vadim & Shneyerov, Artyom, 2012. "Quantile-based nonparametric inference for first-price auctions," Journal of Econometrics, Elsevier, vol. 167(2), pages 345-357.
  3. Haile,P.A. & Tamer,E.T., 2000. "Inference with an incomplete model of English auctions," Working papers 18, Wisconsin Madison - Social Systems.
  4. Emmanuel Guerre & Isabelle Perrigne & Quang Vuong, 2009. "Nonparametric Identification of Risk Aversion in First-Price Auctions Under Exclusion Restrictions," Econometrica, Econometric Society, vol. 77(4), pages 1193-1227, 07.
  5. Elliott, Graham & Muller, Ulrich K., 2007. "Confidence sets for the date of a single break in linear time series regressions," Journal of Econometrics, Elsevier, vol. 141(2), pages 1196-1218, December.
  6. repec:cup:cbooks:9780521586115 is not listed on IDEAS
  7. Philip A. Haile & Han Hong & Matthew Shum, 2004. "Nonparametric Tests for Common Values in First-Price Sealed-Bid Auctions," Working Papers 2004.149, Fondazione Eni Enrico Mattei.
  8. repec:cup:cbooks:9780521355643 is not listed on IDEAS
  9. Athey, Susan & Haile, Philip A., 2007. "Nonparametric Approaches to Auctions," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 60 Elsevier.
  10. repec:cup:cbooks:9780521496032 is not listed on IDEAS
  11. Emmanuel Guerre & Isabelle Perrigne & Quang Vuong, 2000. "Optimal Nonparametric Estimation of First-Price Auctions," Econometrica, Econometric Society, vol. 68(3), pages 525-574, May.
  12. Marmer, Vadim & Shneyerov, Artyom, 2009. "Supplement to "Quantile-Based Nonparametric Inference for First-Price Auctions"," Microeconomics.ca working papers vadim_marmer-2009-61, Vancouver School of Economics, revised 09 Sep 2010.
  13. Newey, Whitney K., 1994. "Kernel Estimation of Partial Means and a General Variance Estimator," Econometric Theory, Cambridge University Press, vol. 10(02), pages 1-21, June.
  14. Rosa L. Matzkin, 2003. "Nonparametric Estimation of Nonadditive Random Functions," Econometrica, Econometric Society, vol. 71(5), pages 1339-1375, 09.
  15. Li, Qi & Racine, Jeffrey S, 2008. "Nonparametric Estimation of Conditional CDF and Quantile Functions With Mixed Categorical and Continuous Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 423-434.
  16. Matt Shum & Phil Haile & Han Hong, 2003. "Nonparametric Tests for Common Values in First-Price Auctions," Economics Working Paper Archive 501, The Johns Hopkins University,Department of Economics.
  17. Paarsch, Harry J., 1997. "Deriving an estimate of the optimal reserve price: An application to British Columbian timber sales," Journal of Econometrics, Elsevier, vol. 78(2), pages 333-357, June.
  18. Li, Tong & Perrigne, Isabelle & Vuong, Quang, 2003. "Semiparametric Estimation of the Optimal Reserve Price in First-Price Auctions," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 53-64, January.
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