A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators

51 Pages Posted: 24 May 2011

See all articles by Daniel A. Ackerberg

Daniel A. Ackerberg

University of California, Los Angeles (UCLA) - Department of Economics

Xiaohong Chen

Yale University - Cowles Foundation

Jinyong Hahn

University of California, Los Angeles

Date Written: May 23, 2011

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.

Keywords: Two-step semiparametrics

JEL Classification: C14

Suggested Citation

Ackerberg, Daniel A. and Chen, Xiaohong and Hahn, Jinyong, A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators (May 23, 2011). Cowles Foundation Discussion Paper No. 1803, Available at SSRN: https://ssrn.com/abstract=1850613 or http://dx.doi.org/10.2139/ssrn.1850613

Daniel A. Ackerberg

University of California, Los Angeles (UCLA) - Department of Economics ( email )

Box 951477
405 Hilgard Avenue
Los Angeles, CA 90095-1477
United States

Xiaohong Chen (Contact Author)

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States

Jinyong Hahn

University of California, Los Angeles ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095-1361
United States

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