Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function. (July 2016)
- Record Type:
- Journal Article
- Title:
- Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function. (July 2016)
- Main Title:
- Sources of carbon productivity change: A decomposition and disaggregation analysis based on global Luenberger productivity indicator and endogenous directional distance function
- Authors:
- Wang, Ke
Xian, Yujiao
Wei, Yi-Ming
Huang, Zhimin - Abstract:
- Highlights: We propose a carbon productivity indicator utilizing endogenous directional distance function. The carbon productivity indicator is based on global Luenberger productivity indicator. It can be decomposed into best practice gap change and efficiency change. It can be additionally disaggregated into specific energy driven carbon productivity indicator. The carbon productivity changes of 37 major emitting regions are estimated. Abstract: The measurement of carbon productivity makes the effort of global climate change mitigation accountable and helps to formulate policies and prioritize actions for economic growth, energy conservation, and carbon emissions control. Previous studies arbitrarily predetermined the directions of directional distance function in calculating the carbon productivity indicator, and the traditional carbon productivity indicator itself is not capable of identifying the contribution of different energy driven carbon emissions in carbon productivity change. Through utilizing an endogenous directional distance function selecting approach and a global productivity index, this paper proposes a global Luenberger carbon productivity indicator for computing carbon productivity change. This carbon productivity indicator can be further decomposed into three components that respectively identify the best practice gap change, pure efficiency change, and scale efficiency change. Moreover, the carbon productivity indicator is shown as a combination ofHighlights: We propose a carbon productivity indicator utilizing endogenous directional distance function. The carbon productivity indicator is based on global Luenberger productivity indicator. It can be decomposed into best practice gap change and efficiency change. It can be additionally disaggregated into specific energy driven carbon productivity indicator. The carbon productivity changes of 37 major emitting regions are estimated. Abstract: The measurement of carbon productivity makes the effort of global climate change mitigation accountable and helps to formulate policies and prioritize actions for economic growth, energy conservation, and carbon emissions control. Previous studies arbitrarily predetermined the directions of directional distance function in calculating the carbon productivity indicator, and the traditional carbon productivity indicator itself is not capable of identifying the contribution of different energy driven carbon emissions in carbon productivity change. Through utilizing an endogenous directional distance function selecting approach and a global productivity index, this paper proposes a global Luenberger carbon productivity indicator for computing carbon productivity change. This carbon productivity indicator can be further decomposed into three components that respectively identify the best practice gap change, pure efficiency change, and scale efficiency change. Moreover, the carbon productivity indicator is shown as a combination of individual carbon emissions productivity indicators that account for the contribution of different fossil fuel driven carbon emissions (i.e. coal driven CO2, oil driven CO2, and natural gas driven CO2 ) toward the carbon productivity change. Our carbon productivity indicator is employed to measure and decompose the carbon productivity changes of 37 major carbon emitting countries and regions over 1995–2009. The main findings include: (i) endogenous directions identifying the largest improvement potentials are noticeably different from exogenous directions in estimating the inefficiencies of undesirable outputs. (ii) Carbon productivity indicator calculated with the consideration of emission structure provides a more significant estimation on productivity change. (iii) The aggregated carbon productivity and the specific energy driven carbon productivities significantly improve over our study period which are primarily attributed to technical progress. (iv) Empirical results imply that policies focused on researching and developing energy utilization and carbon control technologies might not be enough; it is also essential to encourage technical efficiency catching-up and economic scale management. … (more)
- Is Part Of:
- Ecological indicators. Volume 66(2016)
- Journal:
- Ecological indicators
- Issue:
- Volume 66(2016)
- Issue Display:
- Volume 66, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 66
- Issue:
- 2016
- Issue Sort Value:
- 2016-0066-2016-0000
- Page Start:
- 545
- Page End:
- 555
- Publication Date:
- 2016-07
- Subjects:
- Data envelopment analysis (DEA) -- Energy driven carbon emissions -- Efficiency change -- Best practice gap change
Environmental monitoring -- Periodicals
Environmental management -- Periodicals
Environmental impact analysis -- Periodicals
Environmental risk assessment -- Periodicals
Sustainable development -- Periodicals
333.71405 - Journal URLs:
- http://www.sciencedirect.com/science/journal/1470160X/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ecolind.2016.02.034 ↗
- Languages:
- English
- ISSNs:
- 1470-160X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3648.877200
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7903.xml