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Asymptotic Variance Estimator for Two-Step Semiparametric Estimators

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Abstract

The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric variances using standard formulas derived in the already-well-known parametric literature. This means that for computational purposes, an empirical researcher can ignore the semiparametric nature of the problem and do all calculations "as if" it were a parametric situation. We hope that this simplicity will promote the use of semiparametric procedures.

Suggested Citation

  • Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn, 2011. "Asymptotic Variance Estimator for Two-Step Semiparametric Estimators," Cowles Foundation Discussion Papers 1803, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:1803
    Note: CFP 1357
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    File URL: http://cowles.yale.edu/sites/default/files/files/pub/d18/d1803.pdf
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    Cited by:

    1. Maican, Florin & Orth, Matilda, 2008. "Productivity Dynamics and the Role of “Big-Box” Entrants in Retailing," Working Papers in Economics 328, University of Gothenburg, Department of Economics.
    2. Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn, 2012. "A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 481-498, May.
    3. Guofang Huang & Yingyao Hu, 2011. "Estimating Production Functions with Robustness Against Errors in the Proxy Variables," Economics Working Paper Archive 583, The Johns Hopkins University,Department of Economics.
    4. Satimanon, Monthien & Lupi, Frank, 2010. "Comparison of Approaches to Estimating Demand for Payment for Environmental Services," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61288, Agricultural and Applied Economics Association.

    More about this item

    Keywords

    Two-step semiparametrics;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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