Fiscal spending and green economic growth: Evidence from China

被引:142
|
作者
Lin, Boqiang [1 ]
Zhu, Junpeng [1 ]
机构
[1] Xiamen Univ, Sch Management, China Inst Studies Energy Policy, Collaborat Innovat Ctr Energy Econ & Energy Polic, Xiamen 361005, Fujian, Peoples R China
关键词
Fiscal spending; Green economic growth; Non-radial direction distance function; System-GMM estimation; China; CO2 EMISSION PERFORMANCE; RESOURCE-BASED CITIES; DIRECTIONAL DISTANCE FUNCTION; HUMAN-CAPITAL ACCUMULATION; FUEL POWER-PLANTS; REDUCTION POLICY; PANEL-DATA; ENERGY; EFFICIENCY; ENVIRONMENT;
D O I
10.1016/j.eneco.2019.07.010
中图分类号
F [经济];
学科分类号
02 ;
摘要
The green economy is considered as an efficient way for sustainability, but the connection between fiscal spending and green economic growth has not been systematically explained. This paper attempts to fill this research gap. Based on the panel data of 282 prefecture-level cities from 2005 to 2016, we first construct the green economic growth index by using the non-radial direction distance function. Then, by employing the System-GMM estimation, we further evaluate the effect of fiscal education spending and R&D spending on green economic growth. Finally, we explore the potential mechanism and discuss our findings. We obtain the following conclusions: (1) The green economic growth index fluctuated in the study period, we attribute it to the "political tournament" of local governments. (2) The System-GMM estimation results confirm the existence of composition effect and technique effect in the full sample, but the sub-sample analysis suggests that there is a heterogeneous effect in different areas with different resources abundant degree. (3) Mechanism analysis illustrates that fiscal R&D spending and education spending foster the green economic growth through technological activities and human-capital intensive activities, respectively, but they exhibit distinct roles in different areas. Based on these findings, we propose some targeted policy suggestions for promoting green economic growth. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:264 / 271
页数:8
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