A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators

Daniel Ackerberg; Xiaohong Chen; Jinyong Hahn

doi:10.1162/rest_a_00251

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A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators

Daniel Ackerberg¹; Xiaohong Chen²; Jinyong Hahn³

¹ University of Michigan–Ann Arbor · ² Yale University · ³ UCLA Health

The Review of Economics and Statistics 2012

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.

DOI: 10.1162/rest_a_00251
Volume: 94 (2)
Pages: 481-498
Language: en
Export: BibTeX
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