Asymptotic Variance Estimator for Two-Step Semiparametric Estimators
Daniel Ackerberg (),
Xiaohong Chen () and
No 1803, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University
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.
Keywords: Two-step; semiparametrics (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Pages: 50 pages
New Economics Papers: this item is included in nep-ecm
Note: CFP 1357
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Published in Review of Economics and Statistics, 94(2): 482-498
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Persistent link: https://EconPapers.repec.org/RePEc:cwl:cwldpp:1803
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