本文通过构建包含节能减排因素的三部门动态随机一般均衡（DSGE）模型，研究环保技术、节能减排补贴、政府治污支出及厂商节能减排努力程度等措施对宏观经济的动态影响，尤其是对实际碳排放量、节能减排量和生态环境质量的影响，并在此基础上分析各项措施的传导机制。研究发现：（1）环保技术能够在实现经济增长的基础上，有效降低实际碳排放量和节能减排量，提高生态环境质量；（2）节能减排补贴仅在短期内对实际碳排放量与节能减排量有明显的抑制作用，长期影响相对较小，且对环境质量的影响也非常有限，同时表现出一定的延迟性；（3）政府治污支出的短期效应不显著，从长期看能够有效降低实际碳排放量，提高生态环境质量，但对宏观经济会产生负效应；（4）厂商减排努力程度的上升能够快速提升节能减排量，并有效降低实际碳排放规模，使得环境质量有效改善。总体上，环保技术与减排努力程度是影响环境质量的关键因素，提升厂商的环保技术水平与节能减排意识是有效改善生态环境质量的重中之重。
In recent years, the air pollution has seriously affected the sustainable development of China's economy, and the key to solve this problem is improving the environmental protection technology and implementing the effective environmental policy. In this paper' a dynamic stochastic general equilibrium (DSGE) model containing energy saving and emissions reduction factors is buit, to research the dynamic effects of environmental technology, energy saving and emissions reduction subsidies, government spending and pollution treatment on China's macro economy, especially for the actual carbon emissions, energy conservation and emission reductions, and ecological environment quality. At the same time, the transmission mechanism of measures based on the impulse response of economic variables is analyzed. First of all, the parameters based are estimated on China's macro economic data by two ways,one is to estimate the static parameters by calibration, and the other is to estimate the dynamic parameters by the bayesian estimation method. Then, the parameter estimation results are used to simulate the theoretical model. The simulation results show that:(1) Improving environmental protection technology can reduce the actual carbon emissions and emission reductions, improve the quality of the ecological environment effectively with economic growth. (2) The energy saving and emissions reduction subsidy only has obvious inhibitory effect on actual carbon emissions and emission reductions in the short term, the long-term effect is relatively smaller, and has a little impact on the environment quality, and show some delay at the same time. (3) Government pollution spending has little effect in the short-term, can effectively reduce the actual carbon emissions in the long-term, and improve the ecological environment quality, but has the negative effects on macro economy. (4) The efforts degree of manufacturer rising can quickly improve energy saving and emission reductions, and effectively reduce the actual scale of carbon emissions, and effectively improve environmental quality. Overall, the environmental protection technology and efforts degree of manufacturer are the key factors of affecting the environment quality. Raising the environmental protection technology and the degree efforts of manufacturers' energy saving and emissions reduction are the key of effectively improving ecological environmental quality. The research provides useful guidance for enterprises to make investment in the environmental protection technology and government make effective policy in energy saving and emission reduction.
[1] Weitzman M L. Prices vs. quantities[J]. Review of Economic Studies, 1974, 41(4):477-91.
[2] Bovenberg A L, Goulder L H. Environmental taxation and regulation[J]. Handbook of Public Economics, 2001, 3:1471-1545.
[3] John A, Pecchenino R. An overlapping generations model of growth and the environment[J]. Economic Journal, 1994, 104(427):1393-1410.
[4] Jouvet P, Michel P, Rotillon G. Optimal growth with pollution:How to use pollution permits?[J]. Journal of Economic Dynamics & Control, 2005, 29(9):1597-1609.
[5] Wissema W, Dellink R. A CGE analysis of the impact of a carbon energy tax on the Irish economy[J]. Ecological Economics, 2007, 61(61):671-683.
[6] 崔连标, 范英, 朱磊,等. 碳排放交易对实现我国"十二五"减排目标的成本节约效应研究[J]. 中国管理科学, 2013, 21(1):37-46.
[7] 时佳瑞, 蔡海琳, 汤铃,等. 基于CGE模型的碳交易机制对我国经济环境影响研究[J]. 中国管理科学, 2015,23(S1):801-806.
[8] Angelopoulos K, Economides G, Philippopoulos A. What is the best environmental policy? Taxes, permits and rules under economic and environmental uncertainty[R].Working Paper,the CEsiof Grounp Munich,2010.
[9] Annicchiarico B, Di Dio F D. GHG emissions control and monetary policy[J]. Environmental & Resource Economics, 2016,67(4):823-851.
[10] 程方楠, 孟卫东. 宏观审慎政策与货币政策的协调搭配——基于贝叶斯估计的DSGE模型[J]. 中国管理科学, 2017, 25(1):11-20.
[11] Fischer C, Springborn M. Emissions targets and the real business cycle:Intensity targets versus caps or taxes[J]. Journal of Environmental Economics & Management, 2009, 62(3):352-366.
[12] Heutel G. How should environmental policy respond to business cycles? Optimal policy under persistent productivity shocks[J]. Review of Economic Dynamics, 2011, 15(2):244-264.
[13] Dissou Y, Karnizova L. Emissions cap or emissions tax? A multi-sector business cycle analysis[J]. Journal of Environmental Economics & Management, 2016, 79:169-188.
[14] Fan Li,Shiwang C,Wei Zhang. Tax policy tropism of Chinese enterprises' energy conservation and pollution reduction:Evidence from Shandong province[J]. Energy Procedia, 2011,5:2468-2473.
[15] 王琳, 肖序, 许家林. "政府-企业"节能减排互动机制研究[J]. 中国人口:资源与环境, 2011, 21(6):102-109.
[16] 郑丽琳, 朱启贵. 技术冲击、二氧化碳排放与中国经济波动——基于DSGE模型的数值模拟[J]. 财经研究, 2012(7):38-49+101.
[17] 齐结斌, 胡育蓉. 环境质量与经济增长——基于异质性偏好和政府视界的分析[J]. 中国经济问题, 2013, (5):28-38.
[18] 徐文成, 薛建宏, 毛彦军. 宏观经济动态性视角下的环境政策选择——基于新凯恩斯DSGE模型的分析[J]. 中国人口·资源与环境, 2015, 25(4):101-109.
[19] Annicchiarico B, Di Dio F D. Environmental policy and macroeconomic dynamics in a new Keynesian model[J]. Journal of Environmental Economics & Management, 2015, 69(1):1-21.
[20] 朱军. 基于DSGE模型的"污染治理政策"比较与选择——针对不同公共政策的动态分析[J]. 财经研究, 2015, 41(2):41-53.
[21] 黄赜琳. 中国经济周期特征与财政政策效应-一个基于三个部门RBC模型的实证分析[J]. 经济研究, 2005, (6):27-39.
[22] 黄勇峰, 任若恩, 刘晓生. 中国制造业资本存量永续盘存法估计[J]. 经济学(季刊), 2002, (2):377-396.
[23] 田友春. 中国分行业资本存量估算:1990~2014年[J]. 数量经济技术经济研究, 2016, (6):3-21.
[24] 张军, 章元. 对中国资本存量K的再估计[J]. 经济研究, 2003, (7):35-43.
[25] Fuentes-Albero C. Financial frictions, the financial immoderation, and the great moderation[R]. Working paoer, Rutgers University,2010.
[26] 胡永刚, 郭新强. 内生增长、政府生产性支出与中国居民消费[J]. 经济研究, 2012,(9):57-71.
[27] Smetst F, Wouters R. Shocks and frictions in US business cycles:A Bayesian DSGE approach[J]. American Economic Review, 2007, 97(3):586-606.
[28] Gerali A, Neri S, Sessa L, et al. Credit and banking in a DSGE model of the euro Area[J]. Journal of Money, Credit and Banking, 2010, 42(S1):107-141.
[29] Khan H, Tsoukalas J. The quantitative importance of news shocks in estimated DSGE models[J]. Journal of Money Credit & Banking, 2012, 44(8):1535-1561.
