Atlantic Economic Journal

, Volume 39, Issue 4, pp 329–341 | Cite as

A Consistent Econometric Test for Bid Interdependence in Repeated Second-Price Auctions with Posted Prices

  • Andreas C. Drichoutis
  • Rodolfo M. NaygaJr
  • Panagiotis Lazaridis
  • Beom Su Park
Article

Abstract

In repeated second-price experimental auctions, the winning bid is normally posted after each round. The posting of these winning prices after each round can result in bids submitted in later rounds to be interdependent with posted prices from earlier rounds. Several approaches in the past have tried to scrutinize their experimental data for value interdependence by regressing bids on lagged market prices or lagged bids and ignoring the inherent endogeneity problem. This paper introduces a formal test for bid interdependence in repeated second-price auctions with posted prices using a dynamic panel model. We then apply this test to formally check the presence of bid interdependence in three datasets used in previous studies.

Keywords

Experimental auctions Bid interdependence Dynamic panel estimator Second-price auction 

JEL

B4 D8 C23 

References

  1. Alfnes, F., & Rickertsen, K. (2003). European Consumers’ Willingness to Pay for U.S. Beef in Experimental Auction Markets. American Journal of Agricultural Economics, 85(2), 396–405.CrossRefGoogle Scholar
  2. Andersen, S., Harrison, G. W., Lau, M. I., & Rutström, E. E. (2006). Elicitation using multiple price list formats. Experimental Economics, 9(4), 383–405.CrossRefGoogle Scholar
  3. Andersen, S., Harrison, G. W., Lau, M. I., & Rutström, E. E. (2007). Valuation using multiple price list formats. Applied Economics, 39(6), 675–682.CrossRefGoogle Scholar
  4. Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297.CrossRefGoogle Scholar
  5. Buhr, B. L., et al. (1993). Valuing ambiguity: the case of genetically engineered growth enhancers. Journal of Agricultural and Resource Economics, 18(2), 175–184.Google Scholar
  6. Corrigan, J. R., & Rousu, M. C. (2006). Posted prices and bid affiliation: evidence from experimental auctions. American Journal of Agricultural Economics, 88(4), 1078–1090.CrossRefGoogle Scholar
  7. Drichoutis, A. C., Lazaridis, P., Rodolfo, J., & Nayga, M. (2008). The role of reference prices in experimental auctions. Economics Letters, 99(3), 446–448.CrossRefGoogle Scholar
  8. Fox, J. A., Hayes, D. J., & Shogren, J. F. (2002). Consumer preferences for food irradiation: how favorable and unfavorable descriptions affect preferences for irradiated pork in experimental auctions. Journal of Risk and Uncertainty, 24(1), 75–95.CrossRefGoogle Scholar
  9. Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica, 50(4), 1029–1054.CrossRefGoogle Scholar
  10. Harrison, G. W. (2006). Experimental evidence on alternative environmental valuation methods. Environmental and Resource Economics, 36, 125–162.CrossRefGoogle Scholar
  11. Harrison, G. W., Harstad, R. M., & Rutström, E. E. (2004). Experimental methods and elicitation of values. Experimental Economics, 7(2), 123–140.CrossRefGoogle Scholar
  12. Holtz-Eakin, D., Newey, W., & Rosen, H. S. (1988). Estimating vector autoregressions with panel data. Econometrica, 56(6), 1371–1395.CrossRefGoogle Scholar
  13. Klemperer, P. (2004). Auctions: Theory and practice. The Toulouse Lectures in Economics: Princeton University Press.Google Scholar
  14. List, J. A., & Shogren, J. F. (1999). Price information and bidding behavior in repeated second-price auctions. American Journal of Agricultural Economics, 81(4), 942–949.CrossRefGoogle Scholar
  15. Lusk, J. L., & Shogren, J. F. (2007). Experimental auctions, Methods and applications in economic and marketing research. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  16. Lusk, J. L., Feldkamp, T., & Schroeder, T. C. (2004a). Experimental auction procedure: impact on valuation of quality differentiated goods. American Journal of Agricultural Economics, 86(2), 389–405.CrossRefGoogle Scholar
  17. Lusk, J. L., House, L. O., Valli, C., Jaeger, S. R., Moore, M., Morrow, J. L., & Traill, W. B. (2004b). Effect of information about benefits of biotechnology on consumer acceptance of genetically modified food: evidence from experimental auctions in the United States, England, and France. European Review of Agricultural Economics, 31(2), 179–204.CrossRefGoogle Scholar
  18. Roodman, D. M. (2002). XTABOND2: Stata module to extend xtabond dynamic panel data estimator. Downloadable from http://fmwww.bc.edu/repec/bocode/x/xtabond2.ado .
  19. Roodman, D. M. (2006). How to do xtabond2: An introduction to “Difference” and “System” GMM in Stata. Center for Global Development, Working paper number 103.Google Scholar
  20. Roodman, D. M. (2008). A note on the theme of too many instruments. Oxford Bulletin of Economics and Statistics, 71(1), 135–158.CrossRefGoogle Scholar
  21. Sargan, J. (1958). The estimation of economic relationships using instrumental variables. Econometrica, 26(3), 393–415.CrossRefGoogle Scholar
  22. Shogren, J. F. (2006). Valuation in the lab. Environmental and Resource Economics, 34(1), 163–172.CrossRefGoogle Scholar

Copyright information

© International Atlantic Economic Society 2011

Authors and Affiliations

  • Andreas C. Drichoutis
    • 1
  • Rodolfo M. NaygaJr
    • 2
  • Panagiotis Lazaridis
    • 3
  • Beom Su Park
    • 4
  1. 1.Department of EconomicsUniversity of IoanninaIoanninaGreece
  2. 2.Department of Agricultural Economics and AgribusinessUniversity of ArkansasFayettevilleUSA
  3. 3.Department of Agricultural Economics and Rural DevelopmentAgricultural University of AthensAthensGreece
  4. 4.Department of Agricultural EconomicsTexas A&M UniversityCollege StationUSA

Personalised recommendations