不同地区经济增长与环境污染关系的VAR模型分析——基于广州、佛山、肇庆经济圈的实证研究被引量：38

VAR model for the analysis of dynamic interactions between economic growth and environmental pollution:A case study on the economic circle of the cities of Guangzhou,Foshan and Zhaoqing

原文传递

导出

摘要利用向量自回归(VAR)计量技术对广州-佛山-肇庆(简称"广佛肇")经济圈各城市表征环境污染的指标(工业废水排放量、工业废气排放量和工业固废产生量)和表征经济增长的指标(人均GDP)的时序数据进行脉冲响应函数及预测方差分解分析,研究处于工业化后期的广州、佛山市及工业化前期的肇庆市经济发展与环境污染在时序维度上的关系及其动态性.结果表明:佛山和肇庆两市环境污染对经济增长的脉冲函数累计响应值均为正,表明两市经济增长将导致环境污染物排放(或产生)量整体上升;广州市工业废水排放量对经济增长变量冲击轨迹的累积响应值为-0.252380,远小于佛山市的-0.052036;预测方差分解中,工业废气排放量平均贡献度基本较大,其中,肇庆市最高,达到80%以上,因此,未来广佛肇经济圈的发展应更关注工业废气的排放. Using the Vector Autoregress （VAR） model,we investigated the time series data of pollution indices and the productivity growth index through impulse response functions and variance decomposition analysis in the economic circle of the cities of Guangzhou,Foshan,and Zhaoqing.The pollution indexes included industrial wastewater discharges,industrial air emissions,and industrial solid wastes.The productivity growth index was represented by GDP per capita.The study aims to investigate the dynamic interactions between economic growth and environmental pollution in three cities which represent different levels of industrialization：Guangzhou and Foshan represent the later stage of industrialization while Zhaoqing represents the earlier stage of industrialization.Results from the VAR model analysis showed that the cumulative value of pollution indices in response to one standard deviation （S.D.） innovations of the productivity growth index was positive in both Foshan and Zhaoqing,which implies that environmental pollutants would increase as the economy of those cities continues to grow.The cumulative value of the productivity growth in response to one S.D.innovations of industrial wastewater discharges was-0.252380 in Guangzhou,much lower than the value （-0.052036） in Foshan.In addition,based on the prediction of variance decomposition,industrial air emissions are the main contributor from economic growth.In Zhaoqing,industrial air emissions may contribute more than 80%,the highest among the three cities.Therefore,industrial air emissions could be a main concern in the future development in the economic circle of the cities of Guangzhou,Foshan,and Zhaoqing.

作者吴丹吴仁海

机构地区中山大学环境科学与工程学院广东省环境污染控制与修复技术重点实验室

出处《环境科学学报》 CAS CSCD 北大核心 2011年第4期880-888,共9页 Acta Scientiae Circumstantiae

关键词广佛肇经济圈经济增长环境污染 VAR模型 economic circle of the cities of Guangzhou Foshan and Zhaoqing economic growth environmental pollution VAR model

分类号 X32 [环境科学与工程—环境工程]

引文网络
相关文献

参考文献22

1Akbostanel E, Tarat-Aslk S, lpek Tunc G. 2009. The relationshipbetween income and environment in Turkey: Is there an environmental Kuznets curve? [ J]. Energy Policy, 37:861-867.
2Borghesi S. 1999. The environmental Kuznets Curve: a survey of the literature [ R ]. No. 85.99. Milan, Italy: FEEM Research Paper. 85-99.
3Chebbi H E, Boujelbene Y. 2008. CO2 emissions, energy consumption and economic growth in Tunisia [ A ]//Burrell A, Heckelei T, Sckokai P. European Review of Agricultural Economics [ C]. UK Oxford University Press. 1-5.
4Cheney H, Robinson S, Syrquin M. 1986. Industrialization and Growth [ M ]. New York : Oxford University. 72.
5Coondoo D, Dinda S. 2002. Causality between income and emission: A country group-specific econometric analysis [ J ]. Ecological Economics. 40:351-367.
6De Bruyn S, Heintz R. 1999. The Environmental Kuznets Curve Hypothesis//Van den Bergh J. Handbook of Environmental and Resource Economics [ M ]. Northampton : Edward Elgar. 656-677.
7Dinda S. 2004. Environmental Kuznets curve hypothesis: A survey [ J]. Ecological Economies, 49:431-455.
8Egli H. 2002. Are eross-eountry studies of the environmental Kuznets eurve misleading? New evidenee from time series data for Germany [ R ]. Greifswald: Ernst-Moritz-Arndt University. 1-28.
9Grosssman G, Krueger A. 1991. Environmental impacts of a North American free trade agreement [ A ]//Garber P. The Mexico- US Free Trade Agreement [ C]. Cambridge: MIT Press. 411-417.
10Koop G, Pesaran M H, Potter S M. 1996. Impulse response analysis in nonlinear multivariate models [ J ]. Journal of Econometrics, 74: 119-247.