政府干预、时空效应与典型城市碳减排
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摘要
借助显示性比较优势指数,将21个典型城市政府节能环保财政支出和科学技术财政支出对称化处理为政府干预代理变量,通过动态空间杜宾模型,考察政府干预及其他因素对典型城市碳减排的影响机制。实证结果显示:政府干预提高减排成效,其作用存在明显的时空效应。短期内,科学技术支出的减排效果优于节能环保支出,但长期作用效果存在边际效应递减规律,同时节能环保支出由于"辐射带动"作用短期内具有负向空间溢出效应,综合来看,政府节能环保支出具有"可持续性",而科学技术支出则可解决"燃眉之急";经济因素始终是碳排放增长的主要推动力,结构效应对碳排放增长的贡献高于规模效应,且结构效应短期内存在显著的正向空间溢出效应;人口结构效应的减排贡献优于规模效应;能源结构与技术创新抑制碳排放,其中技术创新具有"过程性"。
By means of the displayed comparative advantage index, the governments energy-conserving and environmental expenditures, scientific, technological and fiscal expenditures of 21 cities are symmetrically treated as governmental intervention variables in this paper. Meanwhile, dynamic spatial durbin model are constructed, to investigate the impact mechanism of government intervention and other factors on carbon emission reduction of typical cities. The empirical results show that: government intervention can improve the effectiveness of emission reduction, and it has obvious time and space effects.In the short term, the emission reduction effect relying on science and technology expenditure is better than energy-conserving and environmental expenditure, but the long-term effect has a law of diminishing marginal effect. At the same time, the energy-conserving and environmental expenditure has a negative spatial spillover effect in the short-term due to the radiationdriven effect. Overall, energy conservation and environmental protection expenditures are sustainable, while science and technology expenditures can solve emergency. Economic factors are always the main driving forces for carbon emission growth. The contribution of structural effects to carbon emission growth is higher than that of scale effect, and there is a significant positive spatial spillover effect in the short-term structure effect. Emission reduction contribution of population structure effect is superior to scale effect. Energy structure and technological innovation restrain carbon emission, among them;technological innovation is the process.
By means of the displayed comparative advantage index, the governments energy-conserving and environmental expenditures, scientific, technological and fiscal expenditures of 21 cities are symmetrically treated as governmental intervention variables in this paper. Meanwhile, dynamic spatial durbin model are constructed, to investigate the impact mechanism of government intervention and other factors on carbon emission reduction of typical cities. The empirical results show that: government intervention can improve the effectiveness of emission reduction, and it has obvious time and space effects.In the short term, the emission reduction effect relying on science and technology expenditure is better than energy-conserving and environmental expenditure, but the long-term effect has a law of diminishing marginal effect. At the same time, the energy-conserving and environmental expenditure has a negative spatial spillover effect in the short-term due to the radiationdriven effect. Overall, energy conservation and environmental protection expenditures are sustainable, while science and technology expenditures can solve emergency. Economic factors are always the main driving forces for carbon emission growth. The contribution of structural effects to carbon emission growth is higher than that of scale effect, and there is a significant positive spatial spillover effect in the short-term structure effect. Emission reduction contribution of population structure effect is superior to scale effect. Energy structure and technological innovation restrain carbon emission, among them;technological innovation is the process.
引文
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[19]韩秀艳,孙涛,高明.新型城镇化建设、能源消费增长与碳排放强度控制研究[J].软科学,2018,32(9):90-93.
[20] Jordaan S M, Romo Rabago E, Mcleary R, et al. The Role of Energy Technology Innovation in Reducing Greenhouse Gas Emissions:A Case Study of Canada[J]. Renewable&Sustainable Energy Reviews, 2017, 78:1397-1409.
[2] Petit Boix A, Lorach Massana P, Sanjuan Delmás D, et al. Application of Life Cycle Thinking Towards Sustainable Cities:A Review[J]. Journal of Cleaner Production, 2017, 166:939-951.
[3]林毅夫.产业政策与我国经济的发展:新结构经济学的视角[J].复旦学报(社会科学版),2017,59(2):148-153.
[4]朱富强.林毅夫的新结构经济学为何引发如此争议———兼论如何正确认识和参与学术争论[J].学习与探索,2017(5):123-132.
[5]张维迎.我为什么反对产业政策———与林毅夫辩[J].比较,2016(6):174-202.
[6]田国强.林毅夫、张维迎之争的对与错:兼谈有思想的学术与有学术的思想[J].比较, 2016(6):203-219.
[7]江飞涛,李晓萍.产业政策中的市场与政府———从林毅夫与张维迎产业政策之争说起[J].财经问题研究,2018(1):33-42.
[8] Balassa B. Trade Liberalization and Revealed Comparative Advantage[J]. Manchester School, 1965, 33(2):99-123.
[9] Laursen K. Revealed Comparative Advantage and the Alternatives as Measures of International Specialization[J]. Eurasian Business Review, 2015, 5(1):99-115.
[10]熊灵,齐绍洲.金融发展与中国省区碳排放———基于STIRPAT模型和动态面板数据分析[J].中国地质大学学报(社会科学版),2016,16(2):63-73.
[11]赵桂梅,赵桂芹,陈丽珍,等.中国碳排放强度的时空演进及跃迁机制[J].中国人口·资源与环境,2017,27(10):84-93.
[12]吕承超,商圆月.高技术产业集聚模式与创新产出的时空效应研究[J].管理科学,2017,30(2):64-79.
[13]林光平,龙志和,吴梅.中国地区经济σ-收敛的空间计量实证分析[J].数量经济技术经济研究,2006(4):14-21,69.
[14] Elhorst J P. Dynamic Spatial Panels:Models, Methods, and Inferences[J]. Journal of Geographical Systems, 2012, 14(1):5-28.
[15]邱立新,袁赛.中国典型城市碳排放特征及峰值预测———基于“脱钩”分析与EKC假设的再验证[J].商业研究,2018(7):50-58.
[16]魏霄,孟科学.武汉城市圈经济辐射机理探析———基于复杂性系统论视角[J].华东经济管理,2016,30(5):73-80.
[17]朱小会,陆远权.环境财税政策与金融支持的碳减排治理效应———基于财政与金融相结合的视角[J].科技管理研究,2017,37(3):203-209.
[18]马晓君,董碧滢,于渊博,等.东北三省能源消费碳排放测度及影响因素[J].中国环境科学,2018,38(8):3170-3179.
[19]韩秀艳,孙涛,高明.新型城镇化建设、能源消费增长与碳排放强度控制研究[J].软科学,2018,32(9):90-93.
[20] Jordaan S M, Romo Rabago E, Mcleary R, et al. The Role of Energy Technology Innovation in Reducing Greenhouse Gas Emissions:A Case Study of Canada[J]. Renewable&Sustainable Energy Reviews, 2017, 78:1397-1409.