
浙江农业科学 ›› 2026, Vol. 67 ›› Issue (1): 271-280.DOI: 10.16178/j.issn.0528-9017.20250531
• 农业经济与信息 • 上一篇
收稿日期:2025-07-23
出版日期:2026-01-11
发布日期:2026-01-19
通讯作者:
孔令成
作者简介:孔令成,E-mail:konglingcheng110@sina.com。基金资助:
ZHANG Hang(
), KONG Lingcheng(
)
Received:2025-07-23
Online:2026-01-11
Published:2026-01-19
Contact:
KONG Lingcheng
摘要:
本研究基于空间溢出效应理论,以长江经济带11省市2007—2023年的面板数据为样本,系统探究环境规制与农业绿色全要素生产率之间的内在关系与机理。研究采用熵值法衡量环境规制强度,运用超效率SBM-GML模型评估农业绿色全要素生产率,并借助双向固定效应空间杜宾模型分析其空间溢出效应。 结果表明: 长江经济带环境规制不仅对本地区农业绿色全要素生产率具有显著正向促进作用,也表现出明显的空间溢出效应,且其影响存在空间异质性,并受到地区经济发展水平的显著制约。基于此,长江经济带应科学利用环境规制的约束与激励作用,通过提升技术创新水平培育农业新质生产力,因地制宜地实施差异化、动态化的环境规制政策,同时加强区域协同,推动跨流域环境污染共治与联防联控。
中图分类号:
张杭, 孔令成. 环境规制、空间溢出与农业绿色全要素生产率——基于长江经济带面板数据的分析[J]. 浙江农业科学, 2026, 67(1): 271-280.
ZHANG Hang, KONG Lingcheng. Environmental regulation, spatial spillover, and agricultural green total factor productivity: an analysis based on panel data from the Yangtze River economic belt[J]. Journal of Zhejiang Agricultural Sciences, 2026, 67(1): 271-280.
| 变量 | 观测值 | 平均值 | 标准差 | 最小值 | 最大值 |
|---|---|---|---|---|---|
| A | 187 | 1.105 | 0.112 | 0.798 | 1.712 |
| E | 187 | -0.464 | 0.161 | -0.924 | -0.190 |
| L | 187 | 2.276 | 0.131 | 1.823 | 2.538 |
| S | 187 | 1.192 | 0.416 | 0.619 | 3.058 |
| O | 187 | 9.838 | 0.341 | 6.772 | 12.200 |
| N | 187 | 0.298 | 0.333 | 0.027 | 1.670 |
表1 变量的描述性统计结果
Table 1 Descriptive statistics of variables
| 变量 | 观测值 | 平均值 | 标准差 | 最小值 | 最大值 |
|---|---|---|---|---|---|
| A | 187 | 1.105 | 0.112 | 0.798 | 1.712 |
| E | 187 | -0.464 | 0.161 | -0.924 | -0.190 |
| L | 187 | 2.276 | 0.131 | 1.823 | 2.538 |
| S | 187 | 1.192 | 0.416 | 0.619 | 3.058 |
| O | 187 | 9.838 | 0.341 | 6.772 | 12.200 |
| N | 187 | 0.298 | 0.333 | 0.027 | 1.670 |
| 年份 | 环境规制 | 农业全要素生产率 | ||
|---|---|---|---|---|
| Moran's I指数 | p值 | Moran's I指数 | p值 | |
| 2010 | 0.156 | 0.110 | 0.378*** | <0.001 |
| 2013 | 0.182* | 0.071 | 0.527*** | <0.001 |
| 2014 | 0.168* | 0.090 | 0.522*** | <0.001 |
| 2015 | 0.188* | 0.064 | 0.401*** | <0.001 |
| 2017 | 0.188* | 0.064 | 0.396*** | <0.001 |
| 2019 | 0.165* | 0.096 | 0.354** | 0.001 |
| 2022 | 0.162* | 0.100 | 0.148 | 0.121 |
| 2023 | 0.168* | 0.090 | 0.146 | 0.117 |
表2 空间自相关检验结果
Table 2 Spatial autocorrelation test results
| 年份 | 环境规制 | 农业全要素生产率 | ||
|---|---|---|---|---|
| Moran's I指数 | p值 | Moran's I指数 | p值 | |
| 2010 | 0.156 | 0.110 | 0.378*** | <0.001 |
| 2013 | 0.182* | 0.071 | 0.527*** | <0.001 |
| 2014 | 0.168* | 0.090 | 0.522*** | <0.001 |
| 2015 | 0.188* | 0.064 | 0.401*** | <0.001 |
| 2017 | 0.188* | 0.064 | 0.396*** | <0.001 |
| 2019 | 0.165* | 0.096 | 0.354** | 0.001 |
| 2022 | 0.162* | 0.100 | 0.148 | 0.121 |
| 2023 | 0.168* | 0.090 | 0.146 | 0.117 |
| 检验方法 | 原假设 | 统计值 | p值 | 结果 |
|---|---|---|---|---|
| LR检验 | SDM退化为SAR | 17.161 | 0.004 | 拒绝原假设 |
| SDM退化为SEM | 9.771 | 0.082 | 拒绝原假设 | |
| Wald检验 | SDM退化为SAR | 18.150 | 0.003 | 拒绝原假设 |
| SDM退化为SEM | 14.971 | 0.020 | 拒绝原假设 |
表3 空间计量模型的LR检验和Wald检验结果
Table 3 Results of LR test and Wald test for spatial econometric models
| 检验方法 | 原假设 | 统计值 | p值 | 结果 |
|---|---|---|---|---|
| LR检验 | SDM退化为SAR | 17.161 | 0.004 | 拒绝原假设 |
| SDM退化为SEM | 9.771 | 0.082 | 拒绝原假设 | |
| Wald检验 | SDM退化为SAR | 18.150 | 0.003 | 拒绝原假设 |
| SDM退化为SEM | 14.971 | 0.020 | 拒绝原假设 |
| 变量 | 不同固定效应下的回归结果 | ||
|---|---|---|---|
| 双向固定 效应 | 个体固定 效应 | 时间固定 效应 | |
| E | 0.274** | 0.053 | 0.099* |
| (2.140) | (0.368) | (1.924) | |
| L | -0.287*** | -0.371*** | -0.303*** |
| (-4.567) | (-4.969) | (-4.748) | |
| S | -0.016 | 0.012 | -0.103*** |
| (-0.254) | (0.233) | (-3.540) | |
| O | -0.010 | 0.014 | -0.021** |
| (-0.441) | (0.619) | (-2.405) | |
| N | 0.069 | 0.041 | -0.003 |
| (0.627) | (0.336) | (-0.077) | |
| w·E | 0.810*** | 0.038 | 0.128 |
| (2.792) | (0.138) | (0.868) | |
| w·L | 0.403*** | 0.349*** | 0.391*** |
| (4.453) | (3.795) | (4.210) | |
| w·S | -0.053 | 0.057 | -0.117* |
| (-0.384) | (0.560) | (-1.912) | |
| w·O | -0.094 | -0.008 | -0.045** |
| (-1.469) | (-0.332) | (-2.314) | |
| w·N | 0.312* | 0.174 | 0.172** |
| (1.848) | (1.017) | (2.174) | |
| rho(空间自回归系数) | -1.065*** | 0.477*** | -0.117 |
| (-4.887) | (7.777) | (-1.206) | |
| Log-likelihood | 244.670 | 202.492 | 237.504 |
| (对数似然值) | |||
| AIC(赤池信息量准则) | -14.652 | -7.360 | -10.647 |
| BIC(贝叶斯信息量准则) | -14.534 | -7.243 | -10.532 |
表4 空间杜宾模型(SDM)的估计结果
Table 4 Estimation results of the spatial Dubin model (SDM)
| 变量 | 不同固定效应下的回归结果 | ||
|---|---|---|---|
| 双向固定 效应 | 个体固定 效应 | 时间固定 效应 | |
| E | 0.274** | 0.053 | 0.099* |
| (2.140) | (0.368) | (1.924) | |
| L | -0.287*** | -0.371*** | -0.303*** |
| (-4.567) | (-4.969) | (-4.748) | |
| S | -0.016 | 0.012 | -0.103*** |
| (-0.254) | (0.233) | (-3.540) | |
| O | -0.010 | 0.014 | -0.021** |
| (-0.441) | (0.619) | (-2.405) | |
| N | 0.069 | 0.041 | -0.003 |
| (0.627) | (0.336) | (-0.077) | |
| w·E | 0.810*** | 0.038 | 0.128 |
| (2.792) | (0.138) | (0.868) | |
| w·L | 0.403*** | 0.349*** | 0.391*** |
| (4.453) | (3.795) | (4.210) | |
| w·S | -0.053 | 0.057 | -0.117* |
| (-0.384) | (0.560) | (-1.912) | |
| w·O | -0.094 | -0.008 | -0.045** |
| (-1.469) | (-0.332) | (-2.314) | |
| w·N | 0.312* | 0.174 | 0.172** |
| (1.848) | (1.017) | (2.174) | |
| rho(空间自回归系数) | -1.065*** | 0.477*** | -0.117 |
| (-4.887) | (7.777) | (-1.206) | |
| Log-likelihood | 244.670 | 202.492 | 237.504 |
| (对数似然值) | |||
| AIC(赤池信息量准则) | -14.652 | -7.360 | -10.647 |
| BIC(贝叶斯信息量准则) | -14.534 | -7.243 | -10.532 |
| 变量 | 直接效应 | 间接效应 | 总效应 |
|---|---|---|---|
| E | 0.244* | 0.716*** | 0.959*** |
| (1.876) | (2.820) | (3.188) | |
| L | -0.310*** | -0.411*** | -0.105 |
| (-4.934) | (4.722) | (1.551) | |
| S | -0.008 | -0.043 | -0.050 |
| (-0.137) | (-0.369) | (-0.331) | |
| O | -0.006 | -0.080 | -0.086 |
| (-0.271) | (-1.393) | (-1.366) | |
| N | 0.062 | 0.278* | 0.339** |
| (0.564) | (1.801) | (2.480) | |
| rho | — | — | -1.065*** |
| (-4.887) | |||
| Sigma2_e | — | — | 0.006*** |
| (随机误差项的方差) | (9.539) | ||
| 样本量 | 187 | 187 | 187 |
表5 空间溢出效应的分解
Table 5 Decomposition of spatial spillover effects
| 变量 | 直接效应 | 间接效应 | 总效应 |
|---|---|---|---|
| E | 0.244* | 0.716*** | 0.959*** |
| (1.876) | (2.820) | (3.188) | |
| L | -0.310*** | -0.411*** | -0.105 |
| (-4.934) | (4.722) | (1.551) | |
| S | -0.008 | -0.043 | -0.050 |
| (-0.137) | (-0.369) | (-0.331) | |
| O | -0.006 | -0.080 | -0.086 |
| (-0.271) | (-1.393) | (-1.366) | |
| N | 0.062 | 0.278* | 0.339** |
| (0.564) | (1.801) | (2.480) | |
| rho | — | — | -1.065*** |
| (-4.887) | |||
| Sigma2_e | — | — | 0.006*** |
| (随机误差项的方差) | (9.539) | ||
| 样本量 | 187 | 187 | 187 |
| 变量 | 模型(1) | 模型(2) | 模型(3) |
|---|---|---|---|
| E | — | 1.109** | 1.328** |
| (0.546) | (1.741) | ||
| w·E | — | 0.810*** | 0.787** |
| (2.792) | (1.833) | ||
| AIR(空气流通系数) | 0.247* | — | — |
| (1.727) | |||
| 控制变量 | 控制 | 控制 | 控制 |
| 时间/个体固定 | 固定 | 固定 | 固定 |
| 样本量 | 187 | 187 | 187 |
| rho | -0.459*** | -0.538*** | -0.507*** |
| (7.303) | (7.459) | (6.967) | |
| Log-likehood | 198.348 | 237.807 | 235.337 |
表6 稳健性检验结果
Table 6 Robustness test results
| 变量 | 模型(1) | 模型(2) | 模型(3) |
|---|---|---|---|
| E | — | 1.109** | 1.328** |
| (0.546) | (1.741) | ||
| w·E | — | 0.810*** | 0.787** |
| (2.792) | (1.833) | ||
| AIR(空气流通系数) | 0.247* | — | — |
| (1.727) | |||
| 控制变量 | 控制 | 控制 | 控制 |
| 时间/个体固定 | 固定 | 固定 | 固定 |
| 样本量 | 187 | 187 | 187 |
| rho | -0.459*** | -0.538*** | -0.507*** |
| (7.303) | (7.459) | (6.967) | |
| Log-likehood | 198.348 | 237.807 | 235.337 |
| 变量 | 在不同子区域上的回归结果 | ||
|---|---|---|---|
| 上游 | 中游 | 下游 | |
| E | 0.249** | 0.201** | -0.882* |
| (2.101) | (2.501) | (1.774) | |
| w·E | 0.210** | 0.247** | -1.200* |
| (1.984) | (1.895) | (-1.814) | |
| rho | -0.755*** | -0.396*** | -0.583*** |
| (-5.016) | (-0.113) | (-0.162) | |
| 控制变量 | 控制 | 控制 | 控制 |
| 时间/个体固定 | 固定 | 固定 | 固定 |
| 样本量 | 68 | 51 | 68 |
| Log-likehood | 114.803 | 78.308 | 122.707 |
表7 异质性分析结果
Table 7 Heterogeneity analysis results
| 变量 | 在不同子区域上的回归结果 | ||
|---|---|---|---|
| 上游 | 中游 | 下游 | |
| E | 0.249** | 0.201** | -0.882* |
| (2.101) | (2.501) | (1.774) | |
| w·E | 0.210** | 0.247** | -1.200* |
| (1.984) | (1.895) | (-1.814) | |
| rho | -0.755*** | -0.396*** | -0.583*** |
| (-5.016) | (-0.113) | (-0.162) | |
| 控制变量 | 控制 | 控制 | 控制 |
| 时间/个体固定 | 固定 | 固定 | 固定 |
| 样本量 | 68 | 51 | 68 |
| Log-likehood | 114.803 | 78.308 | 122.707 |
| 门槛变量 | 门槛性质 | 临界值 | F值 | p值 |
|---|---|---|---|---|
| ln Y | 单门槛 | 0.357 | 30.63 | <0.05 |
| ln Y | 双门槛 | 0.301 | 10.47 | 0.56 |
表8 门槛效应检验结果
Table 8 Threshold effect test results
| 门槛变量 | 门槛性质 | 临界值 | F值 | p值 |
|---|---|---|---|---|
| ln Y | 单门槛 | 0.357 | 30.63 | <0.05 |
| ln Y | 双门槛 | 0.301 | 10.47 | 0.56 |
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