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

Atkinson, Scott E. and Primont, Daniel and Tsionas, Mike G. (2018) Statistical inference in efficient production with bad inputs and outputs using latent prices and optimal directions. Journal of Econometrics, 204 (2). pp. 131-146. ISSN 0304-4076

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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.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Econometrics
Additional Information:
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
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2604
Subjects:
ID Code:
123914
Deposited By:
Deposited On:
07 Mar 2018 15:04
Refereed?:
Yes
Published?:
Published
Last Modified:
31 Mar 2020 05:18