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  • Publisher version of AAM

    Rights statement: This is the author’s version of a work that was accepted for publication in International Journal of Production Economics. 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 International Journal of Production Economics, 199, 2018 DOI: 10.1016/j.ijpe.2018.02.006

    Accepted author manuscript, 1.79 MB, PDF document

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

  • Author Version of AAM

    Rights statement: This is the author’s version of a work that was accepted for publication in International Journal of Production Economics. 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 International Journal of Production Economics, 199, 2018 DOI: 10.1016/j.ijpe.2018.02.006

    Accepted author manuscript, 968 KB, PDF document

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

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Measuring management practices

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>05/2018
<mark>Journal</mark>International Journal of Production Economics
Volume199
Number of pages13
Pages (from-to)65-77
Publication statusPublished
Early online date24/02/18
Original languageEnglish

Abstract

Good management practices are remarkably difficult to robustly measure, especially when unique data on firms and their managers are not available. We propose a new model estimated with Bayesian techniques that requires only the usual accounting data on inputs and outputs and thus can be applied to any firm. We show that our management practices estimates are more than 90% correlated with existing state-of-the-art measures from a very specialized data set by Bloom and Van Reenen (2007). We also obtain very high correlations when conducting an extensive Monte Carlo analysis. Finally, we show that frontier-based methods previously used to estimate management practices do not provide good approximations.

Bibliographic note

This is the author’s version of a work that was accepted for publication in International Journal of Production Economics. 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 International Journal of Production Economics, 199, 2018 DOI: 10.1016/j.ijpe.2018.02.006