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A practical asymptotic variance estimator for two-step semiparametric estimators

Author

Listed:
  • Daniel Ackerberg

    (Institute for Fiscal Studies and The University of Texas at Austin)

  • Xiaohong Chen

    (Institute for Fiscal Studies and Yale University)

  • Jinyong Hahn

    (Institute for Fiscal Studies)

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. "A practical asymptotic variance estimator for two-step semiparametric estimators," CeMMAP working papers CWP22/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:22/11
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    References listed on IDEAS

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    JEL classification:

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

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