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Efficient local IV estimation of an empirical auction model

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  • Hong, Han
  • Nekipelov, Denis
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    Abstract

    In this paper we examine semiparametric efficiency bounds and efficient estimators for the case of a linear local instrument variable (LIV) model under the assumptions studied in Abadie et al. (2002). We apply the semiparametrically efficient estimation method to analyze the relation between bid dispersion and early bidding in an online auction dataset, which is collected from a natural experiment conducted in Nekipelov (2007). The results confirm the theoretical findings developed in Nekipelov (2007). The semiparametric efficient estimation procedure substantially improves the statistical significance of the effect of jump bidding on bid dispersion.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 168 (2012)
    Issue (Month): 1 ()
    Pages: 60-69

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    Handle: RePEc:eee:econom:v:168:y:2012:i:1:p:60-69

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    Web page: http://www.elsevier.com/locate/jeconom

    Related research

    Keywords: Semiparametric efficiency bound; Local treatment effect; Natural experiment; Online auction; Early jump bid;

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    1. Joshua D. Angrist, 2004. "Treatment effect heterogeneity in theory and practice," Economic Journal, Royal Economic Society, vol. 114(494), pages C52-C83, 03.
    2. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, 01.
    3. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
    4. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, 01.
    5. Markus Froelich, 2002. "Nonparametric IV estimation of local average treatment effects with covariates," University of St. Gallen Department of Economics working paper series 2002 2002-19, Department of Economics, University of St. Gallen.
    6. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.
    7. Newey, Whitney K, 1990. "Efficient Instrumental Variables Estimation of Nonlinear Models," Econometrica, Econometric Society, vol. 58(4), pages 809-37, July.
    8. Alberto Abadie & Joshua Angrist & Guido Imbens, 1999. "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings," Working papers 99-16, Massachusetts Institute of Technology (MIT), Department of Economics.
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