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A novel dataset of emission abatement sector extended input-output table for environmental policy analysis
KTH, School of Chemical Science and Engineering (CHE).ORCID iD: 0000-0001-9129-7265
2018 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 231, p. 1259-1267Article in journal (Refereed) Published
Abstract [en]

Environmentally extended input-output table (EEIOT), a balanced matrix of industrial commodity and environmental resources, is widely used to evaluate environmental policy impacts. However, the existing EEIOTs contain energy consumption and pollution emission but neglect emission abatement cost and benefit. In this study, a novel Chinese emission abatement sector extended input-output table (EAS-IOT) is developed through introducing abatement cost, emission charge and abatement benefit into the conventional input-output table. Furthermore, this new EAS-IOT is applied to estimate the environmental efficiency and assess the effects of environmental policies on economy and environment. Results show that the new framework of EAS-IOT has advantage on solving the problem of biased efficiency estimation related to the conventional input-output table. 

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 231, p. 1259-1267
Keywords [en]
Data on emission abatement cost and benefit, Emission abatement sector, Environmental policy, Extended input-output table
National Category
Environmental Engineering
Identifiers
URN: urn:nbn:se:kth:diva-236554DOI: 10.1016/j.apenergy.2018.09.010ISI: 000452345400097Scopus ID: 2-s2.0-85054074577OAI: oai:DiVA.org:kth-236554DiVA, id: diva2:1266140
Note

Funding details: 161076, FYTEF, Fok Ying Tung Education Foundation; Funding details: Beijing Municipal Commission of Education; Funding details: 16JDGLB013, Beijing Social Science Fund; Funding details: 2016YFA0602603; Funding details: 71521002, NSFC, National Natural Science Foundation of China; Funding details: 71828401, NSFC, National Natural Science Foundation of China; Funding details: 71871022, NSFC, National Natural Science Foundation of China; Funding details: 71471018, NSFC, National Natural Science Foundation of China; Funding text: We gratefully acknowledge the financial support from the National Natural Science Foundation of China (Grant Nos. 71871022 , 71471018 , 71521002 and 71828401 ), the Fok Ying Tung Education Foundation (Grant No. 161076 ), the Social Science Foundation of Beijing (Grant No. 16JDGLB013 ), the Joint Development Program of Beijing Municipal Commission of Education, the International Clean Energy Talent Program of Chinese Scholarship Council, and the National Key R&D Program (Grant No. 2016YFA0602603 ). QC 20181127

Available from: 2018-11-27 Created: 2018-11-27 Last updated: 2019-01-09Bibliographically approved

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