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Article: Distributional impact of carbon pricing in Chinese provinces

TitleDistributional impact of carbon pricing in Chinese provinces
Authors
KeywordsCarbon pricing
Carbon tax
Climate change
Income distribution
Inequality
Input-output analysis
Issue Date2019
Citation
Energy Economics, 2019, v. 81, p. 327-340 How to Cite?
AbstractBased on a Multi-Regional Input-Output (MRIO)model, and combined with the 2012 MRIO table for 30 Chinese provinces, this paper analyzes the distributional impacts of carbon pricing on households within and across Chinese provinces. The results show regressive distributional effects of carbon pricing across provinces, i.e. poor provinces are affected more by the price. Carbon pricing also shows rural-urban regressivity (i.e. rural households are impacted more heavily than urban households)in more than half of the provinces. Within each selected province, carbon pricing has mostly regressive effects, i.e. poorer urban households are more affected than richer urban households in all provinces and poorer rural households more than richer rural households in one third of the provinces. When looking more specifically at direct energy consumption, we find that the carbon pricing on domestic fuels generally shows regressivity, while pricing carbon on transport fuels shows progressivity. In addition, the impact of carbon pricing on residential direct expenditures (mainly on electricity and coal)is the most important contributor to the regional regressivity across provinces.
Persistent Identifierhttp://hdl.handle.net/10722/369321
ISSN
2023 Impact Factor: 13.6
2023 SCImago Journal Rankings: 3.555

 

DC FieldValueLanguage
dc.contributor.authorWang, Qian-
dc.contributor.authorHubacek, Klaus-
dc.contributor.authorFeng, Kuishuang-
dc.contributor.authorGuo, Lin-
dc.contributor.authorZhang, Kun-
dc.contributor.authorXue, Jinjun-
dc.contributor.authorLiang, Qiao Mei-
dc.date.accessioned2026-01-22T06:16:33Z-
dc.date.available2026-01-22T06:16:33Z-
dc.date.issued2019-
dc.identifier.citationEnergy Economics, 2019, v. 81, p. 327-340-
dc.identifier.issn0140-9883-
dc.identifier.urihttp://hdl.handle.net/10722/369321-
dc.description.abstractBased on a Multi-Regional Input-Output (MRIO)model, and combined with the 2012 MRIO table for 30 Chinese provinces, this paper analyzes the distributional impacts of carbon pricing on households within and across Chinese provinces. The results show regressive distributional effects of carbon pricing across provinces, i.e. poor provinces are affected more by the price. Carbon pricing also shows rural-urban regressivity (i.e. rural households are impacted more heavily than urban households)in more than half of the provinces. Within each selected province, carbon pricing has mostly regressive effects, i.e. poorer urban households are more affected than richer urban households in all provinces and poorer rural households more than richer rural households in one third of the provinces. When looking more specifically at direct energy consumption, we find that the carbon pricing on domestic fuels generally shows regressivity, while pricing carbon on transport fuels shows progressivity. In addition, the impact of carbon pricing on residential direct expenditures (mainly on electricity and coal)is the most important contributor to the regional regressivity across provinces.-
dc.languageeng-
dc.relation.ispartofEnergy Economics-
dc.subjectCarbon pricing-
dc.subjectCarbon tax-
dc.subjectClimate change-
dc.subjectIncome distribution-
dc.subjectInequality-
dc.subjectInput-output analysis-
dc.titleDistributional impact of carbon pricing in Chinese provinces-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.eneco.2019.04.003-
dc.identifier.scopuseid_2-s2.0-85064750401-
dc.identifier.volume81-
dc.identifier.spage327-
dc.identifier.epage340-

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