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, 285, 3, 2020 DOI: 10.1016/j.ejor.2020.02.025
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - On a model of environmental performance and technology gaps
AU - Tsionas, Mike G.
N1 - 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, 285, 3, 2020 DOI: 10.1016/j.ejor.2020.02.025
PY - 2020/9/16
Y1 - 2020/9/16
N2 - In this paper we consider a stochastic directional technology distance function to re-examine the results of recent research in which the authors estimate a generalized directional distance function using programming methods, derive technology gaps and, in a second stage, they fit a Markov process to the technology gaps. One problem is that in the second stage efficiencies and gaps are themselves estimated. Moreover, the authors consider two groups (Annex I and non-Annex I countries according to the Kyoto protocol). We allow for endogeneity of good and bad outputs and inputs, endogenously determined groups of countries, endogenous directions for each country and group, and a distribution of technological gaps (with respect to the meta-technology) which isbased on a Markov process. We use a semi-parametric directional technology distance function and we propose stochastic envelopment of different frontiers allowing for its own “meta-inefficiency”. All quantities of interest are estimated jointly using numerical Bayesian techniques.
AB - In this paper we consider a stochastic directional technology distance function to re-examine the results of recent research in which the authors estimate a generalized directional distance function using programming methods, derive technology gaps and, in a second stage, they fit a Markov process to the technology gaps. One problem is that in the second stage efficiencies and gaps are themselves estimated. Moreover, the authors consider two groups (Annex I and non-Annex I countries according to the Kyoto protocol). We allow for endogeneity of good and bad outputs and inputs, endogenously determined groups of countries, endogenous directions for each country and group, and a distribution of technological gaps (with respect to the meta-technology) which isbased on a Markov process. We use a semi-parametric directional technology distance function and we propose stochastic envelopment of different frontiers allowing for its own “meta-inefficiency”. All quantities of interest are estimated jointly using numerical Bayesian techniques.
KW - Environment and climate change
KW - Efficiency
KW - Metafrontier
KW - Technology gaps
KW - Bayesian analysis
U2 - 10.1016/j.ejor.2020.02.025
DO - 10.1016/j.ejor.2020.02.025
M3 - Journal article
VL - 285
SP - 1141
EP - 1152
JO - European Journal of Operational Research
JF - European Journal of Operational Research
SN - 0377-2217
IS - 3
ER -