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Reserve price effects in auctions: estimates from multiple RD designs

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  • Syngjoo Choi
  • Lars Nesheim

    ()
    (Institute for Fiscal Studies and University College London)

  • Imran Rasul

    ()
    (Institute for Fiscal Studies and University College London)

Abstract

We present evidence from 260,000 online auctions of second-hand cars to identify the impact of public reserve prices on auction outcomes. To establish causality, we exploit multiple discontinuities in the relationship between reserve prices and vehicle characteristics to present RD estimates of reserve price effects on auction outcomes. Our first set of results show that, in line with the robust predictions of auction theory, an increase in reserve price decreases the number of bidders, increases the likelihood the object remains unsold, and increases expected revenue conditional on sale. Reserve price effects are found to be larger when there are more entrants, and when the reserve price is lower to begin with. Our second set of results then combine these estimates to calibrate the reserve price effect on the auctioneer's expected revenue. This reveals the auctioneer's reserve price policy to be locally optimal. Our final set of results provide novel evidence on reserve price effects on the composition of bidders. We find that an increase in reserve price: (i) decreases the number of potential bidders as identified through individual web browsing histories; (ii) leads to only more experienced and historically successful bidders still entering the auction; (iii) the characteristics of actual winners are less sensitive to the reserve price than those of the average bidder, suggesting auction winners are not the marginal entrant.

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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP30/10.

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Date of creation: Oct 2010
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Handle: RePEc:ifs:cemmap:30/10

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  1. Thomas Lemieux & Kevin Milligan, 2004. "Incentive Effects of Social Assistance: A Regression Discontinuity Approach," NBER Working Papers 10541, National Bureau of Economic Research, Inc.
  2. Babur De Los Santos & Ali Hortacsu & Matthijs R. Wildenbeest, 2012. "Testing Models of Consumer Search Using Data on Web Browsing and Purchasing Behavior," American Economic Review, American Economic Association, vol. 102(6), pages 2955-80, October.
  3. Guido Imbens & Thomas Lemieux, 2007. "Regression Discontinuity Designs: A Guide to Practice," NBER Working Papers 13039, National Bureau of Economic Research, Inc.
  4. Stephanie Rosenkranz & Patrick W. Schmit, 2005. "Reserve prices in auctions as reference points," Working Papers 05-14, Utrecht School of Economics.
  5. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
  6. Guofu Tan & Okan Yilankaya, 2005. "Equilibria in Second Price Auctions with Participation Costs," IEPR Working Papers 05.7, Institute of Economic Policy Research (IEPR).
  7. Ostrovsky, Michael & Schwarz, Michael, 2009. "Reserve Prices in Internet Advertising Auctions: A Field Experiment," Research Papers 2054, Stanford University, Graduate School of Business.
  8. Levin, Dan & Smith, James L, 1996. "Optimal Reservation Prices in Auctions," Economic Journal, Royal Economic Society, vol. 106(438), pages 1271-83, September.
  9. 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.
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Cited by:
  1. Ricardo Gonçalves, 2013. "Empirical Evidence on the Impact of Reserve Prices in E nglish Auctions," Journal of Industrial Economics, Wiley Blackwell, vol. 61(1), pages 202-242, 03.
  2. Philippe Jehiel & Laurent Lamy, 2011. "Absolute auctions and secret reserve prices: Why are they used?," Levine's Working Paper Archive 786969000000000316, David K. Levine.

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