An intertemporal approach to measuring environmental performance with directional distance functions: Greenhouse gas emissions in the European Union

Picazo‐Tadeo, Andrés J.; Castillo-Giménez, Juana; Beltrán-Esteve, Mercedes

doi:10.1016/j.ecolecon.2014.02.004

Cited by 84 publications

(37 citation statements)

References 36 publications

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“…This approach has been followed in applications to agriculture by Picazo-Tadeo et al (2011) andPicazo-Tadeo et al (2012). Both papers provide detailed references to methodological and empirical contributions to the eco-efficiency literature.…”

Section: Frontier Eco-efficiency Modelsmentioning

confidence: 99%

“…Kortelainen (2008) presents a framework for dynamic environmental performance analysis that generalized the method of Kuosmanen and Kortelainen (2005) from a static to a dynamic setting using the Malmquist productivity index. Picazo-Tadeo et al (2014) extend this approach to the assessment of intertemporal environmental performance and its determinants at the level of the management of specific pollutants using directional distance functions and Luenberger productivity indicators.…”

Section: Frontier Eco-efficiency Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Frontier models for evaluating environmental efficiency: an overview

Lansink

Wall

2014

Econom. bus. letters

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Our aim in this paper is to provide a succinct overview of frontier-based models used to evaluate environmental efficiency, with a special emphasis on agricultural activity. We begin by providing a brief, up-to-date review of the main approaches used to measure environmental efficiency, with particular emphasis on eco-efficiency models, the materials balance approach and the exergy balance approach. We then review the principal contributions analyzing the determinants of environmental efficiency, and finish by providing some suggestions for future research.

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Section: Frontier Eco-efficiency Modelsmentioning

confidence: 99%

Section: Frontier Eco-efficiency Modelsmentioning

confidence: 99%

Frontier models for evaluating environmental efficiency: an overview

Lansink

Wall

2014

Econom. bus. letters

View full text Add to dashboard Cite

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“…The estimated slopes generate endogenous trade-offs between pairs of greenhouse gases to be tested for equality. Variants of our DEA-based aggregation methodology have been used to construct composite indices in other environmental contexts, by Zhou et al, Picazo-Tadeo et al and Millington et al [26][27][28][29] among others (The European Environment Agency maintains a reasonably comprehensive list of environmental indicators that can be analysed and aggregated using DEA. See https://www.eea.europa.eu/data-and-maps/indicators/#c5=&c0=10&b_start=0v).…”

Section: The Analytical Frameworkmentioning

confidence: 99%

A New Composite Index for Greenhouse Gases: Climate Science Meets Social Science

Edmonds

Lovell

2017

Resources

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Global greenhouse gas emissions have increased at a rate of nearly 2% per year since 1970, and the rate of increase has been increasing. The contribution of greenhouse gases to global warming constitutes an environmental management challenge requiring interdisciplinary effort and international cooperation. In an effort to meet this challenge, the Kyoto Protocol imposes limits on aggregate CO 2 -equivalent emissions of four greenhouse gases, although it permits countries to trade off one gas for another at specified rates. This requires a definition of trade-off rates, which the Protocol specifies as Global Warming Potentials, although these have been controversial since their introduction. The primary source of concern has been the constancy of the trade-off rates, both across countries and through time. We propose a new composite index that allows freely variable trade-off rates, thereby facilitating the design of efficient abatement policy. In a pair of exercises we compare our composite index with that used by the Protocol. In both exercises we reject the constancy of trade-off rates, although despite the significantly different weighting schemes we find a degree of concordance between the two greenhouse gas indices.

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“…For example, Lee & Min [4] defined EP as carbon emissions, Ghisetti & Quatraro [5] defined EP as the ratio between real value added and CO 2 emissions, Picazo-Tadeo et al [6] defined EP as an environmental productivity index based on Data Envelopment Analysis (DEA). Generally, there are at least three frameworks for investigating the influential factors of EP.…”

Section: Literature On Influential Factors Of Environmental Performanmentioning

confidence: 99%

“…Table 2 reports the estimation results: Columns (1), (3), and (5) focus on the impact of clean innovation, while Columns (2), (4), and (6) focus on the impact of gray innovation. Specifically, Table 3 compares the impacts of clean and gray innovation measured by various proxy indicators: Columns (1) and (2) are about the knowledge stock indicator; Columns (3) and (4) are about the innovation quality indicator; Columns (5) and (6) are about the technology development indicator. Generally speaking, for each pair of comparison such as Columns (1) and (2), the estimated parameters of clean and gray innovation are different in sign and (or) significance.…”

Section: Impacts Of Clean and Gray Innovation On Co 2 Emissionsmentioning

confidence: 99%

Impacts of Low-Carbon Innovation and Its Heterogeneous Components on CO2 Emissions

Yan

et al. 2017

Sustainability

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This paper aims to investigate the impact of low-carbon innovation on CO 2 emissions. Using patent statistics, we measured low-carbon innovations for 15 major economies during the period of 1992-2012. Then, we classified low-carbon technology into clean and gray technology according to the patent classification system. Following the empirical Environmental Kuznets Curve (EKC) framework, we explored the effects of low-carbon innovation and its components on CO 2 emissions. We did not find any evidence of significant influence of low-carbon innovation. Through further estimations, a significantly negative effect of clean innovation was found while the effect of gray innovation is not clear. Heterogeneous impacts within low-carbon technology provide an explanation for the insignificant impact of low-carbon innovation.

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An intertemporal approach to measuring environmental performance with directional distance functions: Greenhouse gas emissions in the European Union

Cited by 84 publications

References 36 publications

Frontier models for evaluating environmental efficiency: an overview

Frontier models for evaluating environmental efficiency: an overview

A New Composite Index for Greenhouse Gases: Climate Science Meets Social Science

Impacts of Low-Carbon Innovation and Its Heterogeneous Components on CO2 Emissions

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