Home > Research > Publications & Outputs > Statistical inference in efficient production w...

Electronic data

  • AAM Publisher Version

    Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Econometrics. 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 Journal of Econometrics, 204, 2, 2018 DOI: 10.1016/j.jeconom.2017.12.009

    Accepted author manuscript, 1.34 MB, PDF document

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

  • AAM Author Version_final_pub_copy_with_online_appendix_JE

    Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Econometrics. 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 Journal of Econometrics, ??, ?, 2018 DOI: 10.1016/j.jeconom.2017.12.009

    Accepted author manuscript, 718 KB, PDF document

    Embargo ends: 1/01/50

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

Links

Text available via DOI:

View graph of relations

Statistical inference in efficient production with bad inputs and outputs using latent prices and optimal directions

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
Close
<mark>Journal publication date</mark>2/06/2018
<mark>Journal</mark>Journal of Econometrics
Issue number2
Volume204
Number of pages16
Pages (from-to)131-146
Publication StatusPublished
Early online date15/02/18
<mark>Original language</mark>English

Abstract

Researchers employ the directional distance function (DDF) to estimate multiple-input and multiple-output production, firm inefficiency, and productivity growth. We relax restrictive assumptions by computing optimal directions subject to profit maximization and cost minimization, correct for the potential endogeneity of inputs and outputs, estimate latent prices for bad outputs, measure firms’ responses to shadow prices rather than actual prices, and introduce an unobserved productivity term into the DDF. For an unbalanced panel of U.S. electric utilities, a model assuming profit-maximization outperforms one assuming cost-minimization, while lagged productivity and energy price have the greatest effect on productivity.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Journal of Econometrics. 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 Journal of Econometrics, 204, 2, 2018 DOI: 10.1016/j.jeconom.2017.12.009