Journal ArticleDOI
Environmental efficiency with multiple environmentally detrimental variables : estimated with SFA and DEA
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TLDR
In this paper, the authors compare two methods for the calculation of efficiency; namely Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA), and reveal the strengths and weaknesses for estimating environmental efficiency of the methods applied.About:
This article is published in European Journal of Operational Research.The article was published on 2000-03-01. It has received 566 citations till now. The article focuses on the topics: Data envelopment analysis.read more
Citations
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Technical efficiency in farming: a meta-regression analysis
Boris E. Bravo-Ureta,Daniel Solis,Victor H. Moreira Lopez,José F. Maripani,José F. Maripani,Abdourahmane Thiam,Teodoro E. Rivas +6 more
TL;DR: In this article, a meta-regression analysis including 167 farm level technical efficiency (TE) studies of developing and developed countries was undertaken, and the econometric results suggest that stochastic frontier models generate lower mean TE (MTE) estimates than non-parametric deterministic models, while the primal approach is the most common technological representation.
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A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency
Abbas Mardani,Edmundas Kazimieras Zavadskas,Dalia Streimikiene,Ahmad Jusoh,Masoumeh Khoshnoudi +4 more
TL;DR: In this article, a review of 144 published scholarly papers appearing in 45 high-ranking journals between 2006 and 2015 have been obtained to achieve a comprehensive review of DEA application in energy efficiency, where the selected articles have been categorized based on year of publication; author (s) nationalities, scope of study, time duration, application area, study purpose, results and outcomes.
Journal ArticleDOI
A literature study for DEA applied to energy and environment
TL;DR: In this article, the authors summarized previous research efforts on Data Envelopment Analysis (DEA) applied to energy and environment in the past four decades, including concepts and methodologies on DEA environmental assessment.
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China’s regional energy and environmental efficiency: A DEA window analysis based dynamic evaluation
Ke Wang,Shiwei Yu,Wei Zhang +2 more
TL;DR: Improved DEA models are used to measure the energy and environment efficiency of 29 administrative regions of China during the period of 2000 to 2008 and the empirical results show that east area of China has the highest energy and environmental efficiency, while the efficiency of west area is worst.
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How does green finance affect green total factor productivity? Evidence from China
Chi-Chuan Lee,Chien-Chiang Lee +1 more
TL;DR: Wang et al. as discussed by the authors employed panel data of 30 China's provinces for the period 2006-2018 to explore the influence of green finance on green total factor productivity, revealing estimation results that green finance development significantly improves the level of green productivity.
References
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Journal ArticleDOI
Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis
TL;DR: The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs as mentioned in this paper.
Journal ArticleDOI
Formulation and estimation of stochastic frontier production function models
TL;DR: In this paper, the authors define the disturbance term as the sum of symmetric normal and (negative) half-normal random variables, and consider various aspects of maximum-likelihood estimation for the coefficients of a production function with an additive disturbance term of this sort.
Journal ArticleDOI
Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error
Book
Introduction to Econometrics
TL;DR: In this article, the authors discuss diagnostic checking, model selection, and specification testing for Econometrics, including Diagnostic Checking, Model Selection, and Specification Testing, as well as a discussion of nonlinear regression, models of expectations, and nonnormality errors in Variables.