Driving forces of Spain׳s CO2 emissions: A LMDI decomposition approach
By José M. Cansino, Antonio Sánchez-Braza, María Luisa Rodríguez-Arévalo. 2015
255 citations recorded by the source corpus.
An extended version of the IPAT model and the ‘Kaya identity’ is used to assess the contribution of drivers of CO2 emissions for the 1995–2009 period. The paper carries out a multisector analysis based on the Log-Mean Divisia Index Method (LMDI I). The decomposition factors used are the Carbon Intensity factor (CI), the Energy Intensity factor (EI), the structural composition of Spain׳s economy (Economy Structure, ES), the Economic Activity factor (EA) and Population (P), respectively. Data came from the World Input–Output Database (WIOD) and determined the period under consideration. The paper focuses on the 35 productive sectors included in the WIOD.
Subfields: Economics and Econometrics, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/289b3f609fa6701821ccc370a7229154b714cf1b
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In Economics and Econometrics
- Roula Inglesi-Lotz
- Eyup Dogan
- Mara Madaleno
- V. Moutinho
- Muhammad Shahbaz
- Zhaohua Wang
- Danish
- Fahri Seker
In Environmental Engineering
Citations in the corpus
- Factors affecting CO2 emissions in top countries on renewable energies: A LMDI decomposition application (2018, methodology): “In the energy literature, the decomposition techniques have been a particularly suitable and convenient tool over the last two decades in order to decouple the determinants of various indicators such as energy consumption and efficiency ([5]; [6]; [7]; [8]; [9]; [10]; [11]; [12]; [13]; [2]; [14]; [1”
- Carbon emissions and their drivers for a typical urban economy from multiple perspectives: A case analysis for Beijing city (2018, unknown): “main drivers of the carbon emissions [10].”