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地理研究    2018, Vol. 37 Issue (7): 1406-1420     DOI: 10.11821/dlyj201807012
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贸易开放条件下的区域分工与工业污染排放
毛熙彦1(),贺灿飞2()
1. 南京大学地理与海洋科学学院, 南京 210023
2. 北京大学城市与环境学院, 北京 100871
Regional division of labour and its environmental performance in the context of trade liberalisation
MAO Xiyan1(),HE Canfei2()
1. School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
2. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
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摘要 

对外贸易是否导致专业化区域锁定于污染行业而加剧污染排放?从动态视角出发,将区域分工视为专业化集聚与动态演化的综合,基于中国2003-2009年261个地级市30个制造业大类数据,借助区位商与共现概率描述专业化集聚与动态演化,构建联立方程模型进行实证检验。结果表明:一方面,专业化集聚将形成多个层面拥挤效应,降低污染行业进一步集聚的概率,制约区域朝着污染专业化方向演化;另一方面,环境规制将有效抑制区域进一步朝着污染专业化方向演化。因此,尽管对外贸易扩张在一定程度上强化了污染行业在专业化区域的集聚,但并未因此造成污染排放在区域之间形成两极分化。

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毛熙彦
贺灿飞
关键词 区域分工专业化集聚产业演化对外贸易污染排放强度 
Abstract

Foreign trade can induce the regional division of labour in pollution-intensive sectors. There are also concerns on a likely polarisation of pollution emission in the wake of regional division. This study incorporates a dynamic perspective into the regional division of labour, which becomes a synergy of specialised agglomeration and industrial dynamics. The location quotient is applied to assess the level of specialised agglomeration. An index is also constructed based on co-occurrence probability to capture the route of industrial dynamics. Thus, a simultaneous equation model is constructed to empirically examine the linkage between local environmental performance and regional division of labour, and the role of foreign trade in such a linkage. An "industry-city-year" data panel is established to support the empirical study, which covers 261 prefectural-level cities and 30 industries at the two-digit level with the study period spanning from 2003 to 2009. The results show that an increasing scale of agglomeration is likely to generate various crowding-out effects, resulting in less co-agglomeration of related industries. It will, in turn, keep the industrial mix from moving towards a locked-in way. On the other hand, environmental regulation has been efficient in emission reduction, effectively reducing the probability of introducing new pollution-intensive sectors. To summarize, although the expansion of foreign trade can promote the level of specialised agglomeration, it is less likely to polarise the pollution emission among regions. The results may offer insightful references for managing the tradeoffs between foreign trade and the environment. First, there is a spatial asymmetry between pollution-intensive sectors and their non-pollution-intensive counterparts. The non-pollution-intensive sectors tend to avoid the co-location with the pollution-intensive sectors. In such cases, the co-agglomeration between pollution-intensive and non-pollution-intensive sectors can crowd out the non-pollution intensive ones in its early stage. The efforts on developing non-pollution-intensive sectors should pay off in the long run. Second, there are both active and passive ways to keep regions from being locked in pollution production. Previous efforts may focus on the role of active ways, such as the environmental regulation. However, it is also beneficial to take advantage of the passive ways.

Key wordsregional division of labour    specialisation    industrial dynamics    foreign trade    pollution intensity
收稿日期: 2018-01-10      出版日期: 2018-08-03
基金资助:国家自然科学基金项目(41425001, 41731278)
引用本文:   
毛熙彦, 贺灿飞 . 贸易开放条件下的区域分工与工业污染排放[J]. 地理研究, 2018, 37(7): 1406-1420.
MAO Xiyan, HE Canfei . Regional division of labour and its environmental performance in the context of trade liberalisation[J]. GEOGRAPHICAL RESEARCH, 2018, 37(7): 1406-1420.
链接本文:  
http://www.dlyj.ac.cn/CN/10.11821/dlyj201807012      或      http://www.dlyj.ac.cn/CN/Y2018/V37/I7/1406
Fig. 1  2007年中国大气与水污染行业区域分工
注:分图a和d分别代表大气和水污染多年平均排放强度分区中位于75%分位数以上(Q1)和50%分位数以上(Q2)行业的区位商;b和e只包含大气和水污染排放强度位于75%分位数以上(Q1)的行业;c和f只包含大气和水污染排放强度位于25%分位数以下(Q4)的行业。
Fig. 2  2007年专业化集聚与不同行业共聚概率的相关性
注:该图所示为依据工业SO2排放强度测算的结果。基于工业废水排放测算的结果与该图所示趋势相一致。限于篇幅,此处只展示前者。
工业废气(SO2 工业废水
排放强度 污染专业化 非污染专业化 排放强度 污染专业化 非污染专业化
Dp 0.335*** XLp 0.452*** XLnp 0.113 Dp 0.284*** XLp 0.421** XLnp 0.079
Dnp -0.002 XLp2 -0.189** XLnp2 -0.034 Dnp 0.213 XLp2 -0.187** XLnp2 -0.027
lnP -0.060 XKp -0.312*** XKnp -0.323*** lnP 0.104* XKp -0.228*** XKnp -0.256***
lnY -0.660*** XKp2 -0.003 XKnp2 0.101 lnY -0.934*** XKp2 -0.067 XKnp2 0.079
lnT -0.005 XFp 0.417*** XFnp 0.319*** lnT 0.021 XFp 0.415*** XFnp 0.360***
G -0.039*** XFp2 -0.202** XFnp2 -0.123** G -0.043*** XFp2 -0.199*** XFnp2 -0.136***
I -0.114*** lnS -0.317*** lnS -0.268*** I -0.042*** lnS -0.158*** lnS -0.173***
G 0.049*** G -0.009 G 0.049*** G -0.005
I -0.082** I -0.044** I -0.040*** I -0.008***
样本数 1564 样本数 1564 样本数 1564 样本数 1564 样本数 1564 样本数 1564
调整后R2 0.897 调整后R2 0.912 调整后R2 0.972 调整后R2 0.907 调整后R2 0.924 调整后R2 0.975
Tab. 1  专业化分工与工业污染排放强度的回归结果
工业废气(SO2 工业废水
污染排放强度 污染与非污染行业共聚 污染排放强度 污染与非污染行业共聚
Dtr 0.464*** XLp 0.028 Dtr 0.449*** XLp 0.020
lnP -0.053 XLp2 -0.110 lnP 0.113** XLp2 -0.032
lnY -0.670*** XKp -0.117* lnY -0.923*** XKp -0.025
lnT -0.001 XKp2 0.102* lnT 0.030 XKp2 -0.008
G -0.025* XFp 0.863*** G -0.035*** XFp 0.967***
I -0.115*** XFp2 -0.186** I -0.033** XFp2 -0.264***
XLnp 0.373* XLnp 0.238
XLnp2 -0.157 XLnp2 -0.142
XKnp -0.448*** XKnp -0.356***
XKnp2 0.086 XKnp2 0.037
XFnp -0.676*** XFnp -0.828***
XFnp2 0.286*** XFnp2 0.384***
lnS -0.295*** lnS -0.164***
G -0.008 G 0.001
I -0.062*** I -0.002
样本数 1564 样本数 1564 样本数 1564 样本数 1564
调整后R2 0.894 调整后R2 0.952 调整后R2 0.908 调整后R2 0.956
Tab. 2  多样化与工业污染排放强度的回归结果
工业废气(SO2 工业废水
排放强度 污染专业化 非污染专业化 排放强度 污染专业化 非污染专业化
Dp 0.335*** XLp 0.508*** XLnp 0.140 Dp 0.421*** XLp 0.432*** XLnp 0.131
Dnp -0.335 XLp2 -0.208*** XLnp2 -0.028 Dnp 0.067 XLp2 -0.165*** XLnp2 -0.021
lnP -0.043 XKp -0.191*** XKnp -0.190*** lnP 0.112 XKp -0.176*** XKnp -0.202***
lnY -0.611*** XKp2 -0.045 XKnp2 0.038 lnY -0.932*** XKp2 -0.054 XKnp2 0.040
lnT 0.001 XFp 0.108 XFnp 0.298*** lnT 0.023 XFp 0.192 XFnp 0.323***
G -0.039*** XFp2 -0.049 XFnp2 -0.120** G -0.051*** XFp2 -0.082 XFnp2 -0.125***
I -0.117*** lnS -0.321*** lnS -0.237*** I -0.049*** lnS -0.166*** lnS -0.156***
G 0.050*** G -0.003 G 0.052*** G -0.003
I -0.080*** I -0.043** I -0.036*** I -0.003
样本数 1564 样本数 1564 样本数 1564 样本数 1564 样本数 1564 样本数 1564
调整后R2 0.900 调整后R2 0.911 调整后R2 0.973 调整后R2 0.902 调整后R2 0.919 调整后R2 0.976
Tab. 3  基于3SLS的专业化分工与工业污染排放强度的回归结果
工业废气(SO2 工业废水
污染排放强度 污染与非污染行业共聚 污染排放强度 污染与非污染行业共聚
Dtr 0.463*** XLp 0.003 Dtr 0.457*** XLp -0.015
lnP -0.063 XLp2 -0.096 lnP 0.125** XLp2 -0.070
lnY -0.669*** XKp -0.116** lnY -0.921*** XKp -0.095*
lnT 0.001 XKp2 0.100** lnT 0.022 XKp2 0.091*
G -0.025* XFp 0.888*** G -0.033*** XFp 0.942***
I -0.115*** XFp2 -0.190*** I -0.034** XFp2 -0.226***
XLnp 0.373** XLnp 0.317*
XLnp2 -0.161* XLnp2 -0.149*
XKnp -0.434*** XKnp -0.381***
XKnp2 0.078 XKnp2 0.046
XFnp -0.700*** XFnp -0.741***
XFnp2 0.294*** XFnp2 0.340***
lnS -0.293*** lnS -0.166***
G -0.008 G -0.003
I -0.063*** I -0.001
样本数 1564 样本数 1564 样本数 1564 样本数 1564
调整后R2 0.895 调整后R2 0.952 调整后R2 0.908 调整后R2 0.957
Tab. 4  基于3SLS的多样化与工业污染排放强度的回归结果
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