A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators

Daniel Ackerberg, Xiaohong Chen () and Jinyong Hahn

The Review of Economics and Statistics, 2012, vol. 94, issue 2, 481-498

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 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. © 2012 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Keywords: semiparametric; inference (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (58)

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Working Paper: A practical asymptotic variance estimator for two-step semiparametric estimators (2011)
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