China’s low-carbon economic growth: an empirical analysis based on the combination of parametric and nonparametric methods
As the world’s most populous developing country and the world’s largest carbon emitter, China has already completed its 2020 Intended National Determined Contribution set out in the Paris Agreement. It achieved this result by adopting a dual-goal strategy of economic growth and reducing carbon emiss...
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Veröffentlicht in: | Environmental science and pollution research international 2023-03, Vol.30 (13), p.37219-37232 |
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description | As the world’s most populous developing country and the world’s largest carbon emitter, China has already completed its 2020 Intended National Determined Contribution set out in the Paris Agreement. It achieved this result by adopting a dual-goal strategy of economic growth and reducing carbon emission, that is, low-carbon economic growth. Based on both parametric and nonparametric methods, quantitative and qualitative conclusions about China’s low-carbon economic growth are presented. It is found that since the beginning of this century, China has maintained an annual growth efficiency of 1% in low-carbon total factor productivity (TFP) and low-carbon technological progress rate. The Eastern region has leading advantages in low-carbon TFP, low-carbon technology advancement, low-carbon efficiency, and low-carbon technology revolution. It has the potential to be the first to reach its CO
2
turning point. The inefficiency ratio of labor and CO
2
is higher at the national level and in the Eastern region, with the two accounting for about seven tenths and eight to nine tenths, respectively. The difference is that at the national level, the input–output inefficiency is similar, and the inefficiency in the Eastern region is more from the input side, about eight tenths. At the present stage, China is still lenient in the implementation of low-carbon environmental regulations. In the future, the adjustment of low-carbon policy should pay attention to regional heterogeneity, focus on reducing labor and CO
2
inefficiency, and be more stringent in policy implementation. |
doi_str_mv | 10.1007/s11356-022-24775-y |
format | Article |
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2
turning point. The inefficiency ratio of labor and CO
2
is higher at the national level and in the Eastern region, with the two accounting for about seven tenths and eight to nine tenths, respectively. The difference is that at the national level, the input–output inefficiency is similar, and the inefficiency in the Eastern region is more from the input side, about eight tenths. At the present stage, China is still lenient in the implementation of low-carbon environmental regulations. In the future, the adjustment of low-carbon policy should pay attention to regional heterogeneity, focus on reducing labor and CO
2
inefficiency, and be more stringent in policy implementation.</description><identifier>ISSN: 1614-7499</identifier><identifier>EISSN: 1614-7499</identifier><identifier>DOI: 10.1007/s11356-022-24775-y</identifier><identifier>PMID: 36567394</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Aquatic Pollution ; Atmospheric Protection/Air Quality Control/Air Pollution ; carbon ; Carbon - analysis ; carbon dioxide ; Carbon Dioxide - analysis ; China ; Earth and Environmental Science ; Economic Development ; Ecotoxicology ; empirical research ; Environment ; Environmental Chemistry ; Environmental Health ; issues and policy ; labor ; Research Article ; Technology ; United Nations Framework Convention on Climate Change ; Waste Water Technology ; Water Management ; Water Pollution Control</subject><ispartof>Environmental science and pollution research international, 2023-03, Vol.30 (13), p.37219-37232</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c424t-b22b506ab58f9ff8f29632f1b2e60adcbf481da07b635ce47bfa81f2de2c156d3</citedby><cites>FETCH-LOGICAL-c424t-b22b506ab58f9ff8f29632f1b2e60adcbf481da07b635ce47bfa81f2de2c156d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11356-022-24775-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11356-022-24775-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36567394$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xiu, Jing</creatorcontrib><creatorcontrib>Zang, Xiaoqiang</creatorcontrib><creatorcontrib>Piao, Zhenggang</creatorcontrib><creatorcontrib>Li, Liang</creatorcontrib><creatorcontrib>Kim, Kwansoo</creatorcontrib><title>China’s low-carbon economic growth: an empirical analysis based on the combination of parametric and nonparametric methods</title><title>Environmental science and pollution research international</title><addtitle>Environ Sci Pollut Res</addtitle><addtitle>Environ Sci Pollut Res Int</addtitle><description>As the world’s most populous developing country and the world’s largest carbon emitter, China has already completed its 2020 Intended National Determined Contribution set out in the Paris Agreement. It achieved this result by adopting a dual-goal strategy of economic growth and reducing carbon emission, that is, low-carbon economic growth. Based on both parametric and nonparametric methods, quantitative and qualitative conclusions about China’s low-carbon economic growth are presented. It is found that since the beginning of this century, China has maintained an annual growth efficiency of 1% in low-carbon total factor productivity (TFP) and low-carbon technological progress rate. The Eastern region has leading advantages in low-carbon TFP, low-carbon technology advancement, low-carbon efficiency, and low-carbon technology revolution. It has the potential to be the first to reach its CO
2
turning point. The inefficiency ratio of labor and CO
2
is higher at the national level and in the Eastern region, with the two accounting for about seven tenths and eight to nine tenths, respectively. The difference is that at the national level, the input–output inefficiency is similar, and the inefficiency in the Eastern region is more from the input side, about eight tenths. At the present stage, China is still lenient in the implementation of low-carbon environmental regulations. In the future, the adjustment of low-carbon policy should pay attention to regional heterogeneity, focus on reducing labor and CO
2
inefficiency, and be more stringent in policy implementation.</description><subject>Aquatic Pollution</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>carbon</subject><subject>Carbon - analysis</subject><subject>carbon dioxide</subject><subject>Carbon Dioxide - analysis</subject><subject>China</subject><subject>Earth and Environmental Science</subject><subject>Economic Development</subject><subject>Ecotoxicology</subject><subject>empirical research</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>issues and policy</subject><subject>labor</subject><subject>Research Article</subject><subject>Technology</subject><subject>United Nations Framework Convention on Climate Change</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><issn>1614-7499</issn><issn>1614-7499</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkbtOwzAYhS0EoqXwAgzII0vAdnxJ2FDFTarEArNlO3abKomLnaqqxMBr8Ho8CYYW1Amm__adM_wHgFOMLjBC4jJinDOeIUIyQoVg2XoPDDHHNBO0LPd3-gE4inGOEEElEYdgkHPGRV7SIXgdz-pOfby9R9j4VWZU0L6D1vjOt7WB0-BX_ewKqrRrF3WojWrSoJp1rCPUKtoKJr6fWWh8q5NVX6fZO7hQQbW2T4rEV7Dz3c4mlZmv4jE4cKqJ9mRbR-D59uZpfJ9NHu8exteTzFBC-0wTohniSrPClc4VjpQ8Jw5rYjlSldGOFrhSSGieM2Op0E4V2JHKEoMZr_IRON_4LoJ_WdrYy7aOxjaN6qxfRkmKQnBSMsz-RwUrckY5pQklG9QEH2OwTi5C3aqwlhjJr4DkJiCZApLfAcl1Ep1t_Ze6tdWv5CeRBOQbIKZTN7VBzv0ypI_Hv2w_ARB-n9Q</recordid><startdate>20230301</startdate><enddate>20230301</enddate><creator>Xiu, Jing</creator><creator>Zang, Xiaoqiang</creator><creator>Piao, Zhenggang</creator><creator>Li, Liang</creator><creator>Kim, Kwansoo</creator><general>Springer Berlin Heidelberg</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20230301</creationdate><title>China’s low-carbon economic growth: an empirical analysis based on the combination of parametric and nonparametric methods</title><author>Xiu, Jing ; Zang, Xiaoqiang ; Piao, Zhenggang ; Li, Liang ; Kim, Kwansoo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c424t-b22b506ab58f9ff8f29632f1b2e60adcbf481da07b635ce47bfa81f2de2c156d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Aquatic Pollution</topic><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>carbon</topic><topic>Carbon - analysis</topic><topic>carbon dioxide</topic><topic>Carbon Dioxide - analysis</topic><topic>China</topic><topic>Earth and Environmental Science</topic><topic>Economic Development</topic><topic>Ecotoxicology</topic><topic>empirical research</topic><topic>Environment</topic><topic>Environmental Chemistry</topic><topic>Environmental Health</topic><topic>issues and policy</topic><topic>labor</topic><topic>Research Article</topic><topic>Technology</topic><topic>United Nations Framework Convention on Climate Change</topic><topic>Waste Water Technology</topic><topic>Water Management</topic><topic>Water Pollution Control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xiu, Jing</creatorcontrib><creatorcontrib>Zang, Xiaoqiang</creatorcontrib><creatorcontrib>Piao, Zhenggang</creatorcontrib><creatorcontrib>Li, Liang</creatorcontrib><creatorcontrib>Kim, Kwansoo</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Environmental science and pollution research international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xiu, Jing</au><au>Zang, Xiaoqiang</au><au>Piao, Zhenggang</au><au>Li, Liang</au><au>Kim, Kwansoo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>China’s low-carbon economic growth: an empirical analysis based on the combination of parametric and nonparametric methods</atitle><jtitle>Environmental science and pollution research international</jtitle><stitle>Environ Sci Pollut Res</stitle><addtitle>Environ Sci Pollut Res Int</addtitle><date>2023-03-01</date><risdate>2023</risdate><volume>30</volume><issue>13</issue><spage>37219</spage><epage>37232</epage><pages>37219-37232</pages><issn>1614-7499</issn><eissn>1614-7499</eissn><abstract>As the world’s most populous developing country and the world’s largest carbon emitter, China has already completed its 2020 Intended National Determined Contribution set out in the Paris Agreement. It achieved this result by adopting a dual-goal strategy of economic growth and reducing carbon emission, that is, low-carbon economic growth. Based on both parametric and nonparametric methods, quantitative and qualitative conclusions about China’s low-carbon economic growth are presented. It is found that since the beginning of this century, China has maintained an annual growth efficiency of 1% in low-carbon total factor productivity (TFP) and low-carbon technological progress rate. The Eastern region has leading advantages in low-carbon TFP, low-carbon technology advancement, low-carbon efficiency, and low-carbon technology revolution. It has the potential to be the first to reach its CO
2
turning point. The inefficiency ratio of labor and CO
2
is higher at the national level and in the Eastern region, with the two accounting for about seven tenths and eight to nine tenths, respectively. The difference is that at the national level, the input–output inefficiency is similar, and the inefficiency in the Eastern region is more from the input side, about eight tenths. At the present stage, China is still lenient in the implementation of low-carbon environmental regulations. In the future, the adjustment of low-carbon policy should pay attention to regional heterogeneity, focus on reducing labor and CO
2
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subjects | Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution carbon Carbon - analysis carbon dioxide Carbon Dioxide - analysis China Earth and Environmental Science Economic Development Ecotoxicology empirical research Environment Environmental Chemistry Environmental Health issues and policy labor Research Article Technology United Nations Framework Convention on Climate Change Waste Water Technology Water Management Water Pollution Control |
title | China’s low-carbon economic growth: an empirical analysis based on the combination of parametric and nonparametric methods |
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