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  • Approximation HDMR-revised

    Rights statement: This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 284, 3, 2020 DOI: 10.1016/j.ejor.2020.01.026

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    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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On a High-Dimensional Model Representation method based on Copulas

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<mark>Journal publication date</mark>1/08/2020
<mark>Journal</mark>European Journal of Operational Research
Issue number3
Volume284
Number of pages13
Pages (from-to)967-979
Publication StatusPublished
Early online date18/01/20
<mark>Original language</mark>English

Abstract

This article provides an alternative to High-Dimensional Model Representation (HDMR) using a Copula approximation of an unknown functional form. We apply our methodology in the context of an extensive Monte Carlo study and to a sample of large US commercial banks. In the Monte Carlo experiment, the approximations errors of the Copula approach are small and behave randomly. In our empirical application, we find that the Copula Approximation performs much better, in terms of Bayes factors for model comparison, compared to HDMR, which, in turn, provides better results when compared with standard flexible functional forms, like the translog, the minflex Laurent, and the Generalized Leontief, or a Multilayer Perceptron. Moreover, the choice of approximation has significant implications for productivity and its components (returns to scale, technical inefficiency, technical change, and efficiency change).

Bibliographic note

This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 284, 3, 2020 DOI: 10.1016/j.ejor.2020.01.026