Inter-regional tactical interaction and construction land index control failure
ZHANGShaoyang1,, LIUQiong2,, OUMinghao2 1. College of Political Science and Law, Zhengzhou University of Light Industry, Zhengzhou 450001, China2. College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China 通讯作者:通讯作者: 刘琼,E-mail: liuqiong@njau.edu.cn 收稿日期:2018-03-19 修回日期:2018-11-29 网络出版日期:2019-02-25 版权声明:2019《资源科学》编辑部《资源科学》编辑部 基金资助:国家自然科学基金项目(71673141)郑州轻工业大学博士科研基金项目(0187/13501050023) 作者简介: -->作者简介: 张绍阳,男,河南淅川人,博士,讲师,主要研究方向为土地利用规划与管理、土地经济。E-mail: 309102571@qq.com
关键词:建设用地;指标管控;失灵;策略互动;模仿效应;监管权集中;空间面板;中国 Abstract The index control of construction land is an important public policy in the field of land management in China. However, in practice, it is faced with the dilemma of index control failure. From the perspective of local government competition, this study analyzed the tactical interaction on implementation of construction land index among regions and further discussed the effect of supervision centralization of central government on the tactical interaction among regions. Then, we constructed a spatial-panel model to test these theoretical hypotheses. The study found that, under the system of Chinese style decentralization, local government would take full use of land policy tools to participate in economic competition, revealing that there existed a tactical interaction on implementation of construction land index among regions, which was shown as the demonstration effect of gained excess construction land using space. It led to prevalent failure of index control. The regulatory pressure from supervision centralization of central government, which is the national system of land supervision, can impel local governments to keep the extent of index control failure within the level of their rivals when they scrambled to gain excess construction land using space. It was conducive to weaken the inter-regional tactical interaction, thus reduced the extent of construction land index control failure. The conclusion of this study means that, "top-down" supervision centralization system should be embedded in the environment of local governments’ competition to containment the "race to bottom" style behavior in the implementation of resource and environment controlling policy among regions. Specifically, this study puts forward the following policy recommendations: to move the supervision to superior government, to set up a vertical management institution, to centralize the supervision from different resource and environment sectors, and to set up a comprehensive institution in department of supervision.
尽管地方政府竞争引致了地区间在获取超额建设用地空间上的模仿效应,但事实上各地区在指标执行上并未陷入无底线的逐底竞争状态,而是保持一个“低水平”的指标完成度的博弈均衡,因此必然存在某种约束因素能够弱化地区间的这种策略互动,本文认为这主要来自中央政府的监管制度安排(图1)。 显示原图|下载原图ZIP|生成PPT 图1地区间策略互动、中央监管权集中与建设用地指标执行 -->Figure 1Inter-regional tactical interaction, supervision centralization and implementation of construction land indexes -->
本文所用到的变量如下(表1): Table 1 表1 表1变量设置与变量含义 Table 1Setting and definition of variables
变量属性
变量(代码)
变量含义/单位
计算方法
被解释变量
指标管控失灵程度(Dev)
城乡建设用地规模实际增量与规划总增量之比/%
比值
解释变量
中央集中监管压力(Sup)
被督察地区的行政辖区面积占行政辖区总面积/%
比值
控制变量
GDP增速(GDPr)
GDP实际增长率/%
比值
城市人口密度(Pop)
城市常住人口数量与城区面积之比/(人/km2)
自然对数
财政分权程度(FD)
人均省级与人均全国预算内财政支出之比/%)
比值
土地财政规模(Fin)
土地出让收入与土地抵押融资收入之和/亿元
自然对数
往年土地违法规模(LI)
滞后一期的本年发现违法涉及土地面积/hm2
自然对数
新窗口打开 (1)空间权重矩阵(W)。空间权重矩阵描述了变量空间相关性的来源和大小,一般基于地理权重或经济权重来进行设定,前者的逻辑在于地理空间上越接近的地区相互之间影响越强,后者的逻辑在于经济发展水平越接近的地区相互之间影响越强。本文构建如下两种空间权重矩阵: ①地理权重矩阵W1,其中的元素wij采用Rook法则进行赋值,即当地区i和地区j拥有共同边界时,wij赋值为1,否则为0;为了消除孤岛效应,参照多数文献的做法将海南省设置为与广东省相邻。②经济权重矩阵W2,参照王火根等构建嵌套空间权重矩阵的方法: (3) 式中: 为地区i在样本期内历年GDP的均值, 为样本期内所有地区历年GDP总和的均值;通过这种方式构建的权重矩阵考虑了地区间的经济发展水平差异,且赋予了发达地区对欠发达地区更强的空间影响[21]。 (2)指标管控失灵程度(Dev)。指标管控失灵主要体现在指标执行进度上,若地方政府获取了超额建设用地空间,就会导致指标执行进度过快,进而造成较严重的指标管控失灵;相反,若严格按照指标约束来安排用地空间,则不会造成指标管控失灵。考虑到各项建设用地指标中,“城乡建设用地规模”能较好地反应地方政府的指标执行行为1)(1) 在建设用地分类中,建设用地=城乡建设用地+交通水利及其他用地,由于交通水利等重大项目的用地指标多数由中央政府直接批复,因此地方政府的指标执行行为便主要体现在“城乡建设用地规模”指标上。),同时亦考虑到数据可获得性,本文主要选取该项指标进行分析。具体地,以本轮规划期内(2006—2020年),地区i第t年的城乡建设用地规模“实际增量/规划确定的总增量”来计算指标执行进度Devit;其中“规划确定的总增量”指按照本轮土地利用总体规划(2006—2020年),地区 在整个规划期内可以新增的城乡建设用地规模。变量Devit的值越大,表明该地区的指标管控失灵程度越严重。从图2可以看出,在本轮规划期内(2006—2020年),全国城乡建设用地规模的实际值在2014年就已突破了规划末期目标值,意味着各地区存在较严重的指标管控失灵问题。 显示原图|下载原图ZIP|生成PPT 图2本轮规划期(2006—2020年)内全国城乡建设用地规模指标执行进度 -->Figure 2Implementation of rural-urban construction land indexes in this planning from 2006 to 2020 -->
由于空间计量模型中存在空间滞后项,违背了解释变量严格外生的假定,因此最小二乘法不再适用,需要采用工具变量法或极大似然估计法来进行估计;但是,实际应用中往往很难找到合适的工具变量,故采用极大似然估计法来解决这一问题。就各项统计检验而言,使用面板全局Moran’ I检验来判定被解释变量的空间相关性,在地理权重及经济权重两类空间权重矩阵下,Moran’ I都至少在10%的水平下显著,表明模型引入被解释变量空间滞后项的合理性;通过LM检验来判断模型选择的合理性,LM-Lag检验值比LR-Err检验值要更为显著,意味着本文的模型选择是合理的。 表2为地理权重及经济权重下的模型估计结果。 Table 2 表2 表2不同空间权重矩阵下的模型估计结果 Table 2Estimation results of the model in different spatial weight matrix
上述结论意味着,地区间的“竞次式”策略互动是理解建设用地乃至其他资源环境指标管控失灵问题的一个重要视角。地方政府为了在经济竞争中胜出,往往会在经济发展过程中竞相投入过量资源环境成本,从而造成严重的资源管控政策失灵问题。而对于如何解决这一问题,本文的结论表明,应在资源环境领域进行“自上而下”的集中监管改革,将上收监管权、重设监督机构等制度安排嵌入到地方政府竞争的环境中,以遏制地区间“竞次式”的资源管控政策执行行为。具体政策建议包括: (1)将原本分散于下级地方政府的资源环境监督权力进行上收,由上级政府设立垂直监督机构,使其能够脱离与下级地方政府的关系而独立行使监督权力。 (2)将各个资源环境管理部门的监督性职能划分出来,在其他诸如监察等部门设立针对资源环境领域的综合监督机构,以避免其与资源环境管理部门在业务等方面的交错而影响监督功能发挥。 The authors have declared that no competing interests exist.
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