{"title":"江苏省产业结构与碳交易市场关系的实证研究","authors":"Yaqian Song, Shujing Cao, Qingyu Li, H. Liang","doi":"10.1145/3523286.3524596","DOIUrl":null,"url":null,"abstract":"To study the relationship between industrial structure and carbon trading in Jiangsu Province, this paper selects the trading volume of carbon emissions, the proportion of GDP of primary, secondary and tertiary industries, energy structure, energy efficiency, and trade openness as research variables, and makes a bivariate correlation analysis and multiple regression analysis on the relevant panel data of Jiangsu Province from 2015 to 2019. Finally, the corresponding policy suggestions are given. The results show that the proportion of GDP of primary and secondary industries, energy structure, and trade openness have a significant positive correlation with carbon emissions trading volume, while the proportion of GDP of the tertiary industry has a significant negative correlation with carbon emissions trading volume. The proportion of primary industry GDP has the greatest influence on carbon emissions trading volume.","PeriodicalId":268165,"journal":{"name":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An empirical study on the Relationship between Industrial Structure and Carbon Trading Market in Jiangsu Province\",\"authors\":\"Yaqian Song, Shujing Cao, Qingyu Li, H. Liang\",\"doi\":\"10.1145/3523286.3524596\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To study the relationship between industrial structure and carbon trading in Jiangsu Province, this paper selects the trading volume of carbon emissions, the proportion of GDP of primary, secondary and tertiary industries, energy structure, energy efficiency, and trade openness as research variables, and makes a bivariate correlation analysis and multiple regression analysis on the relevant panel data of Jiangsu Province from 2015 to 2019. Finally, the corresponding policy suggestions are given. The results show that the proportion of GDP of primary and secondary industries, energy structure, and trade openness have a significant positive correlation with carbon emissions trading volume, while the proportion of GDP of the tertiary industry has a significant negative correlation with carbon emissions trading volume. The proportion of primary industry GDP has the greatest influence on carbon emissions trading volume.\",\"PeriodicalId\":268165,\"journal\":{\"name\":\"2022 2nd International Conference on Bioinformatics and Intelligent Computing\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 2nd International Conference on Bioinformatics and Intelligent Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3523286.3524596\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Bioinformatics and Intelligent Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3523286.3524596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An empirical study on the Relationship between Industrial Structure and Carbon Trading Market in Jiangsu Province
To study the relationship between industrial structure and carbon trading in Jiangsu Province, this paper selects the trading volume of carbon emissions, the proportion of GDP of primary, secondary and tertiary industries, energy structure, energy efficiency, and trade openness as research variables, and makes a bivariate correlation analysis and multiple regression analysis on the relevant panel data of Jiangsu Province from 2015 to 2019. Finally, the corresponding policy suggestions are given. The results show that the proportion of GDP of primary and secondary industries, energy structure, and trade openness have a significant positive correlation with carbon emissions trading volume, while the proportion of GDP of the tertiary industry has a significant negative correlation with carbon emissions trading volume. The proportion of primary industry GDP has the greatest influence on carbon emissions trading volume.