地理研究 ›› 2022, Vol. 41 ›› Issue (1): 34-45.doi: 10.11821/dlyj020210462
收稿日期:
2021-06-01
接受日期:
2021-12-06
出版日期:
2022-01-10
发布日期:
2022-03-10
通讯作者:
王琛(1981-),女,湖北天门人,博士,教授,博士生导师,主要从事区域产业和经济发展研究。E-mail: chencwang@zju.edu.cn作者简介:
翁鸿妹(1998-),女,福建莆田人,硕士,研究方向为资源环境与区域经济发展。E-mail: 22038022@zju.edu.cn
基金资助:
WENG Hongmei1,2(), CHEN Guangping1,2, WANG Chen1,2(
)
Received:
2021-06-01
Accepted:
2021-12-06
Published:
2022-01-10
Online:
2022-03-10
摘要:
污染型企业的区位选择、转移及其驱动机制研究是环境经济地理研究的热点话题。现有文献从正式制度的角度深入探讨了地方政府的环境规制对污染型企业进入退出、空间分布和产业转移的影响,相对忽视了地方社会资本如公众环保意识、企业环境责任等非正式制度因素对污染型企业区位选择的作用机制。本文基于2011年中国工业企业数据、中国综合社会调查(CGSS)以及城市统计年鉴等数据资料,从社会规范、社会网络和社会信任三方面构建中国城市尺度社会资本,利用二元logit回归模型探讨了社会资本与环境规制对中国污染型企业退出的影响。研究发现:① 环境规制对污染型企业退出的促进作用存在门槛效应。② 公众环保意识、企业环境责任作为社会规范因素,对污染型企业生存构成了外部非正式环境压力;但社会信任和社会网络并没有直接促进污染型企业退出。③ 社会资本在强环境规制地区中的交互作用显著,能够形成正式制度与非正式制度的良好互动。本研究从社会资本这一非正式制度的视角理解污染型企业退出的影响机制,不仅是对正式制度层面环境规制研究的补充,同时也对污染型企业的区位选择和地方政府环境治理政策的制定具有借鉴意义。
翁鸿妹, 陈广平, 王琛. 社会资本是否促进污染型企业退出?——来自中国城市的微观数据[J]. 地理研究, 2022, 41(1): 34-45.
WENG Hongmei, CHEN Guangping, WANG Chen. Does social capital promote the exit of polluting enterprises? Micro-level evidence from Chinese cities[J]. GEOGRAPHICAL RESEARCH, 2022, 41(1): 34-45.
表1
变量说明
一级指标 | 二级指标(变量代码) | 衡量方法(单位) | 属性 |
---|---|---|---|
被解释变量 | |||
企业退出 | 企业退出(Exit) | 1=退出,0=存活 | |
解释变量 | |||
正式制度 | 环境规制(ER) | 工业废水、工业烟粉尘、工业二氧化硫的单位工业产值排放量进行加权平均后,取倒数 | ? |
社会资本 | 公众环保意识(EA) | 根据“为了保护环境,您在多大程度上愿意支付更高的价格”“为了保护环境,您在多大程度上愿意缴纳更高的税”两项问题得分进行平均处理 | + |
企业环境责任(CR) | 根据上市公司是否披露环境责任信息(1=披露;0=未披露)进行平均处理 | + | |
社会信任(ST) | 根据“总的来说您同不同意在这个社会上,绝大多数人都是可以信任的?”一项问题得分进行平均处理 | + | |
社会网络(SN) | 互联网接入户数占家庭总户数比例(%) | + | |
控制变量 | |||
企业属性 | 企业规模(Output) | 工业总产值(万元) | - |
所有制结构(Ownership) | 1=外资企业,0=内资企业 | - | |
企业经营状况(Profit) | 营业利润率(%) | - | |
区域属性 | 工业用地成本(Land) | 工业用地出让平均价格(万元/km2) | + |
产业结构(Structure) | 第三产业占GDP比例(%) | + |
表2
描述性统计与多重共线性检验
变量 | 均值 | 标准差 | 最小值 | 最大值 | VIF值 |
---|---|---|---|---|---|
Exit | 0.103 | 0.304 | 0 | 1 | |
ER | 30.568 | 59.824 | 2.328 | 325.540 | 3.990 |
EA | 3.056 | 0.329 | 1.897 | 3.933 | 1.150 |
CR | 0.828 | 0.373 | 0 | 1 | 1.490 |
ST | 3.122 | 0.175 | 2.516 | 3.600 | 1.210 |
SN | 0.809 | 0.742 | 0.086 | 3.763 | 6.200 |
Ownership | 0.182 | 0.386 | 0 | 1 | 1.180 |
Output | 9.138 | 1.728 | 4.990 | 13.718 | 1.090 |
Profit | 2.568 | 0.022 | -0.171 | 2.738 | 1 |
Land | 5.618 | 0.560 | 4.122 | 7.189 | 3.590 |
Structure | 43.253 | 10.670 | 18.230 | 76.070 | 3.530 |
表3
Logit模型回归结果
变量 | 模型(1) | 模型(2) | |||||
---|---|---|---|---|---|---|---|
全样本 | 弱环境规制地区 | 强环境规制地区 | 全样本 | 弱环境规制地区 | 强环境规制地区 | ||
ER | 0.001 | -0.061*** | 0.004*** | -0.036*** | 0.068*** | 0.007 | |
EA | 0.370*** | 0.452*** | 0.420*** | 0.543*** | -2.809*** | 1.318*** | |
CR | -1.414*** | -1.613*** | 0.784*** | 0.143 | -3.270*** | 2.489*** | |
SN | -0.502*** | -2.232*** | -0.298** | -0.955*** | 6.252*** | -0.400*** | |
ST | -0.610*** | -1.693*** | -0.932*** | 1.288*** | 1.300 | 0.645 | |
ER | -0.001 | -0.158*** | 0.140*** | ||||
ER | 0.078*** | -0.080** | 0.123*** | ||||
ER | -0.104*** | -0.456*** | -0.030*** | ||||
ER | 0.101*** | 0.114* | 0.076** | ||||
Ownership | -0.313*** | -0.675*** | -0.088** | -0.236*** | -0.648*** | -0.104** | |
Output | -0.202*** | -0.196*** | -0.225*** | -0.208*** | -0.216*** | -0.261*** | |
Profit | -4.923** | -2.673 | -6.675** | -5.712** | -3.801 | -6.915*** | |
Land | 0.866*** | 3.002*** | -0.159 | 1.392*** | 3.453*** | -0.249*** | |
Structure | 0.009*** | 0.034*** | 0.003 | 0.038*** | 0.009*** | -0.010 | |
常数项 | 9.284 | -4.225 | 18.822** | 0.307 | -9.136 | 15.339* | |
观测值 | 18820 | 9223 | 9194 | 18820 | 9223 | 9194 | |
分类正确率(%) | 89.72 | 90.11 | 91.83 | 90.00 | 90.90 | 91.83 |
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