Quotation Dimitriadis, Timo, Fissler, Tobias, Ziegel, Johanna F. 2020. The Efficiency Gap.


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Abstract

Parameter estimation via M- and Z-estimation is broadly considered to be equally powerful in semiparametric models for one-dimensional functionals. This is due to the fact that, under sufficient regularity conditions, there is a one-to-one relation between the corresponding objective functions - strictly consistent loss functions and oriented strict identification functions - via integration and differentiation. When dealing with multivariate functionals such as multiple moments, quantiles, or the pair (Value at Risk, Expected Shortfall), this one-to-one relation fails due to integrability conditions: Not every identification function possesses an antiderivative. The most important implication of this failure is an efficiency gap: The most efficient Z-estimator often outperforms the most efficient M-estimator, implying that the semiparametric efficiency bound cannot be attained by the M-estimator in these cases. We show that this phenomenon arises for pairs of quantiles at different levels and for the pair (Value at Risk, Expected Shortfall), where we illustrate the gap through extensive simulations.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Working/discussion paper, preprint
Language English
Title The Efficiency Gap
Year 2020
URL https://arxiv.org/abs/2010.14146
JEL MSC2020 classes: 62F10; 62F12; 62J02; 62M10

Associations

People
Fissler, Tobias (Details)
External
Dimitriadis, Timo (University of Heidelberg, Germany)
Ziegel, Johanna F. (University of Bern, Switzerland)
Organization
Institute for Statistics and Mathematics IN (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
1162 Statistics (Details)
5323 Econometrics (Details)
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