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Bias Corrections In Testing And Estimating Semiparametric, Single Index Models


  • Klein, Roger
  • Shen, Chan


Semiparametric methods are widely employed in applied work where the ability to conduct inferences is important. To establish asymptotic normality for making inferences, bias control mechanisms are often used in implementing semiparametric estimators. The first contribution of this paper is to propose a mechanism that enables us to establish asymptotic normality with regular kernels. In so doing, we argue that the resulting estimator performs very well in finite samples.

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  • Klein, Roger & Shen, Chan, 2010. "Bias Corrections In Testing And Estimating Semiparametric, Single Index Models," Econometric Theory, Cambridge University Press, vol. 26(06), pages 1683-1718, December.
  • Handle: RePEc:cup:etheor:v:26:y:2010:i:06:p:1683-1718_99

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    References listed on IDEAS

    1. Paarsch, Harry J., 1992. "Deciding between the common and private value paradigms in empirical models of auctions," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 191-215.
    2. 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, July.
    3. Harry J. Paarsch & Han Hong, 2006. "An Introduction to the Structural Econometrics of Auction Data," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262162350, January.
    4. Donald, Stephen G. & Paarsch, Harry J., 1996. "Identification, Estimation, and Testing in Parametric Empirical Models of Auctions within the Independent Private Values Paradigm," Econometric Theory, Cambridge University Press, vol. 12(03), pages 517-567, August.
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    Cited by:

    1. Klein, Roger & Shen, Chan & Vella, Francis, 2015. "Estimation of marginal effects in semiparametric selection models with binary outcomes," Journal of Econometrics, Elsevier, vol. 185(1), pages 82-94.
    2. Roger Klein & Chan Shen & Francis Vella, 2014. "Semiiparametric Selection Models with Binary Outcomes," Departmental Working Papers 201403, Rutgers University, Department of Economics.
    3. Biavaschi, Costanza, 2016. "Recovering the counterfactual wage distribution with selective return migration," Labour Economics, Elsevier, vol. 38(C), pages 59-80.
    4. Chan Shen & Roger Klein, 2017. "Recursive Differencing: Bias Reduction with Regular Kernels," Departmental Working Papers 201701, Rutgers University, Department of Economics.
    5. Lee, Jiyon, 2015. "A semiparametric single index model with heterogeneous impacts on an unobserved variable," Journal of Econometrics, Elsevier, vol. 184(1), pages 13-36.
    6. Roger Klein & Chan Shen & Francis Vella, 2011. "Semiparametric selection models with binary outcomes," CeMMAP working papers CWP30/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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