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Bayesian Approach to Disentangling Technical and Environmental Productivity

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Department of Economics, St. Lawrence University, Canton, NY 13617, USA
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Department of Economics, State University of New York at Binghamton, Binghamton, NY 13902, USA
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Norwegian Agricultural Economics Research Institute, NO-0030 Oslo, Norway
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Department of Economics, Lancaster University Management School, Lancaster LA1 4YX, UK
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Author to whom correspondence should be addressed.
Academic Editor: Kerry Patterson
Econometrics 2015, 3(2), 443-465; https://doi.org/10.3390/econometrics3020443
Received: 16 April 2015 / Accepted: 8 June 2015 / Published: 16 June 2015
This paper models the firm’s production process as a system of simultaneous technologies for desirable and undesirable outputs. Desirable outputs are produced by transforming inputs via the conventional transformation function, whereas (consistent with the material balance condition) undesirable outputs are by-produced via the so-called “residual generation technology”. By separating the production of undesirable outputs from that of desirable outputs, not only do we ensure that undesirable outputs are not modeled as inputs and thus satisfy costly disposability, but we are also able to differentiate between the traditional (desirable-output-oriented) technical productivity and the undesirable-output-oriented environmental, or so-called “green”, productivity. To measure the latter, we derive a Solow-type Divisia environmental productivity index which, unlike conventional productivity indices, allows crediting the ceteris paribus reduction in undesirable outputs. Our index also provides a meaningful way to decompose environmental productivity into environmental technological and efficiency changes. View Full-Text
Keywords: bad output; by-production; efficiency; MCMC; productivity bad output; by-production; efficiency; MCMC; productivity
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Malikov, E.; Kumbhakar, S.C.; Tsionas, E.G. Bayesian Approach to Disentangling Technical and Environmental Productivity. Econometrics 2015, 3, 443-465.

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