Analytic Bias Correction for Maximum Likelihood Estimators When the Bias Function is Non-Constant

Ryan T. Godwin and David Giles

No 1702, Econometrics Working Papers from Department of Economics, University of Victoria

Abstract: Recently, many papers have obtained analytic expressions for the biases of various maximum likelihood estimators, despite their lack of closed-form solution. These bias expressions have provided an attractive alternative to the bootstrap. Unless the bias function is “flat,” however, the expressions are being evaluated at the wrong point(s). We propose an “improved” analytic bias adjusted estimator, in which the bias expression is evaluated at a more appropriate point (at the bias adjusted estimator itself). Simulations illustrate that the improved analytic bias adjusted estimator can eliminate significantly more bias than the simple estimator which has been well established in the literature.

Keywords: bias reduction; maximum likelihood; nonlinear bias function (search for similar items in EconPapers)
JEL-codes: C13 C15 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2017-07-21
New Economics Papers: this item is included in nep-ecm
Note: ISSN 1485-6441
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