资源科学 ›› 2021, Vol. 43 ›› Issue (12): 2514-2525.doi: 10.18402/resci.2021.12.13
收稿日期:
2021-05-19
修回日期:
2021-10-25
出版日期:
2021-12-25
发布日期:
2022-02-16
通讯作者:
朱缤绮,女,河南郑州人,硕士研究生,研究方向为技术创新政策。E-mail: zbq6528@163.com作者简介:
李凡,女,吉林吉林人,博士,教授,研究方向为技术创新管理。E-mail: lifan@bisu.edu.cn
基金资助:
LI Fan(), ZHU Binqi(
), SUN Ying
Received:
2021-05-19
Revised:
2021-10-25
Online:
2021-12-25
Published:
2022-02-16
摘要:
可再生能源技术创新是促进能源转型和经济高质量发展的重要一环。已有研究多从国内经济因素探讨环境政策对可再生能源技术创新的影响,较少从制度层面以及开放的国际视域开展研究。本文利用1998—2016年32个国家的面板数据,运用多元回归分析方法,首先引入政策强度计量政策严格性,探索国内外环境政策对本国可再生能源技术创新的动态影响,其次选用制度质量作为制度环境优劣的度量指标,探讨制度因素对环境政策效果的调节作用。研究发现:①国内外环境政策对本国可再生能源技术创新均存在正向影响,但这种影响存在一定的时间滞后期;②国外环境政策对本国可再生能源技术创新的影响早于国内环境政策,国外环境政策的“政策溢出”效应存在;③制度质量正向调节国内环境政策对本国可再生能源技术创新的影响,制度质量的提高能够增强环境政策的创新激励效应。研究结论可为中国进一步优化环境政策体系、推动可再生能源发展提供科学依据。
李凡, 朱缤绮, 孙颖. 环境政策、制度质量和可再生能源技术创新——基于32个国家的实证分析[J]. 资源科学, 2021, 43(12): 2514-2525.
LI Fan, ZHU Binqi, SUN Ying. Environmental policy, institutional quality and renewable energy technology innovation: An empirical analysis of 32 countries[J]. Resources Science, 2021, 43(12): 2514-2525.
表1
变量及其说明
概念测量 | 变量符号 | 指标度量/单位 | 数据来源 |
---|---|---|---|
因变量 | |||
可再生能源技术创新 | INNO | 可再生能源专利申请数占居民专利申请总数的百分比/% | IRENA数据库 |
自变量 | |||
国内环境政策 | EPS | 国内环境政策强度指标 | OECD数据库 |
国外环境政策 | FEPS | 国外环境政策强度指标的加权平均数(以国家间首都地理距离为加权系数) | OECD、CEPII数据库 |
调节变量 | |||
制度质量 | GOV | 政府有效性指数 | 世界银行数据库 |
控制变量 | |||
知识存量 | KS | 考虑衰减率的可再生能源专利累积申请数 | IRENA数据库 |
高技术出口 | HTE | 高技术产品出口额占制成品出口额的百分比/% | 世界银行数据库 |
化石燃料消耗 | FFC | 化石燃料消耗量占全部能源消耗量的百分比/% | 世界银行数据库 |
可再生能源发电 | EPR | 可再生能源发电量(不包括大型水电)占全部能源发电量的百分比/% | 国际能源署数据库 |
研发支出 | R&D | 公共部门研发支出占GDP的百分比/% | 世界银行数据库 |
国际环境协议 | IEAs | 某年7月前是否签署《京都议定书》 | 国际气候公约网站 |
表2
变量描述性统计
变量 | 样本数 | 均值 | 标准差 | 最小值 | 最大值 |
---|---|---|---|---|---|
INNO | 608 | 0.003 | 0.024 | 0.000 | 0.008 |
EPS | 608 | 1.994 | 0.921 | 0.380 | 4.130 |
FEPS | 608 | 1.431 | 1.740 | 0.214 | 3.556 |
GOV | 608 | 1.156 | 0.724 | -0.733 | 2.352 |
KS | 608 | 2.015 | 1.171 | 0.096 | 3.277 |
HTE | 608 | 0.155 | 0.089 | 0.014 | 0.478 |
FFC | 608 | 0.663 | 0.107 | 0.365 | 0.827 |
EPR | 608 | 0.230 | 0.245 | 0.010 | 0.961 |
R&D | 608 | 0.017 | 0.008 | 0.004 | 0.048 |
IEAs | 608 | 0.700 | 0.462 | 0.000 | 1.000 |
表3
解释变量相关性检验
EPS | FEPS | GOV | KS | HTE | FFC | EPR | R&D | |
---|---|---|---|---|---|---|---|---|
EPS | 1.000 | |||||||
FEPS | 0.026 | 1.000 | ||||||
GOV | 0.030 | -0.025 | 1.000 | |||||
KS | 0.077 | 0.069 | 0.033 | 1.000 | ||||
HTE | 0.124 | 0.015 | 0.093 | 0.036 | 1.000 | |||
FFC | -0.012* | 0.159 | -0.110 | 0.149 | 0.009 | 1.000 | ||
EPR | 0.078 | 0.038 | 0.022 | 0.221 | 0.014 | 0.027 | 1.000 | |
R&D | -0.029 | 0.238 | 0.191 | 0.241 | 0.030* | 0.078 | 0.011 | 1.000 |
表5
模型回归结果
变量 | 滞后效应模型(模型1) | 交互效应模型(模型2) | ||
---|---|---|---|---|
滞后2期 | 滞后3期 | 滞后4期 | ||
EPS | 0.523 | 0.458 | 0.241*** | 0.068** |
(0.090) | (0.089) | (2.193) | (1.460) | |
FEPS | 0.914** | 0.967** | 0.816** | 0.225* |
(0.426) | (0.394) | (0.461) | (1.190) | |
GOV | -0.150*** | -0.294*** | -0.605** | 0.846** |
(-2.426) | (-2.425) | (-1.545) | (2.140) | |
EPS | 0.156*** | |||
(4.761) | ||||
KS | 0.268*** | 0.109*** | 0.097 | 0.159 |
(0.255) | (0.371) | (0.064) | (0.046) | |
HTE | 0.164* | 0.041** | 0.031* | 0.145 |
(1.292) | (2.340) | (1.374) | (0.092) | |
FFC | -3.389** | -3.849** | -4.035** | -2.864 |
(-1.841) | (-2.149) | (-2.073) | (-0.083) | |
EPR | -0.675*** | -0.678*** | 0.651 | 0.354* |
(-3.161) | (-3.184) | (0.091) | (1.168) | |
R&D | -0.321 | 0.548 | 0.624 | 0.441* |
(-0.076) | (0.078) | (0.065) | (0.613) | |
IEAs | 0.084 | -0.286 | 0.335 | -0.240 |
(0.210) | (-0.269) | (0.234) | (-0.315) | |
R2 | 0.243 | 0.555 | 0.541 | 0.613 |
F统计量 | 2.135 | 1.859 | 1.960 | 1.243 |
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