基于土地出让视角的中国装备制造业发展态势

doi:10.13249/j.cnki.sgs.2017.03.004

摘要/Abstract

摘要：

基于土地出让视角,构建产业发展驱动力评价体系综合测度2009~2013年全国装备制造业的发展态势,借助ESDA分析方法和空间计量模型分析装备制造业发展的空间特征及其影响因素。研究表明：① 全国装备制造业的总体发展格局与宏观经济发展格局基本一致,呈现由东部沿海向西北内陆逐步递减的态势;② 依赖用地规模扩张的产业驱动结构仍有待突破,东部应进一步强化产业结构分工和土地资源市场配置;③ 国家政策扶持是装备制造业驱动格局形成的重要推动因素,城市化发展、企业集聚水平和基础设施优势对其发展亦具有积极作用。

关键词: 装备制造业, 发展态势, 影响因素, 空间计量分析, 工业用地出让

Abstract:

The orderly spatial pattern of industrial development is an important driving force for the achievement of new-typed urbanization and industrialization in China. In view of industrial land transaction, the article derived a general evaluation system of industrial development driving capacity, and measured the developing status of China's equipment manufacturing industry during 2009-2013. The basic data for analysis were collected from the national dynamic monitoring system of urban land price. Then based on the ESDA analysis method and spatial econometrics modes, we further revealed the spatial characteristics of equipment manufacturing industry development and its influencing mechanism. Several results were acquired:1) The comprehensive evaluation system of industrial development driving capacity was composed of six transfer parameters and three driving indicators, respectively, including the degree of dominance, activity, agglomeration, association, marketability as well as premium of industrial land transaction, and the development level of industrial scale, industrial structure, market efficiency. On a macro scale, the above measuring method targeted land use mode and industrial development into an integrated analysis framework. It can reflect the industry developing trend through the mapping of industrialland supply pattern, and provide decision basis for industrial space organization and relevant resources regulation. 2) The general developing status of equipment manufacturing industry was consistent with the macroeconomic development pattern, presenting gradually decreasing trend from eastern coastal to northwest inland. The high-value area of industrial development driving capacity were distributed in the Bohai Rim region, the Yangtze River Delta and other comprehensive industrial base. The development drivingstructure of equipment manufacturing industrial should be further optimized that used to rely on the land use scale expansion. The eastern regions in China should strengthen industrial structure and regional division as well as the market allocation of land resources, meanwhile the central and western regions should speed up the industrial radiation. 3) The spatial-temporal differences of industry development was a synthesis result that affected by operating of land market and local conditions. The national policy support played an significant role in boosting the formation of the industrial pattern, and urbanization development, enterprise agglomeration, infrastructure advantage also had positive effect on China’s equipment manufacturing industrial development. More specifically, equipment manufacturing industry can be developed in an orderly pattern by propelling some effective national strategies, accelerating industrial transformation and upgrading in eastern area, and promoting infrastructure construction and expanding investment of major manufacturing enterprises in central and western areas.

Key words: equipment manufacturing industry, developing status, influencing mechanism, spatial econometrics models, industria land transaction

中图分类号:

K902

项晓敏, 金晓斌, 张志宏, 范业婷, 谢锦园, 周寅康. 基于土地出让视角的中国装备制造业发展态势[J]. 地理科学, 2017, 37(3): 347-355.

Xiaomin Xiang, Xiaobin Jin, Zhihong Zhang, Yeting Fan, Jinyuan Xie, Yinkang Zhou. Developing Status of China’s Equipment Manufacturing Industry in View of Industrial Land Transaction[J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(3): 347-355.

图/表 4

表1

产业发展驱动力的测度指标及其含义"

测度指标	出让参数	计算公式	描述
规模发展指数（IS）	优势度（Q₁）	$E ki E i E kr E r$	测度研究单元k产业在全国制造业用地供给上的比较优势。E_ki表示i市k产业的用地出让面积,E_i表示i市制造业所有产业的用地出让总面积,E_kr表示全国k产业的用地出让面积,E_r表示全国制造业所有产业的用地出让总面积
规模发展指数（IS）	活跃度（Q₂）	$Z ki Z i Z kr Z r$	测度研究单元k产业在全国制造业用地供给上的相对活跃性。Z_ki表示i市k产业的用地出让宗数,Z_i表示i市制造业所有产业的用地出让总宗数,Z_kr表示全国k产业的用地出让宗数,Z_r表示全国制造业所有产业的用地出让总宗数
结构分工指数（IF）	匀质度（Q₃）	$Z ki Z i 1 + E ki E i log E ki E i$	衡量研究单元i市域范围内k产业用地供给的内部集聚度。参数含义同上
结构分工指数（IF）	关联度（Q₄）	$1 n ∑ j = 1 n E ki E i - E kj E j$	衡量城市之间k产业的分工水平,以i城市与j城市间的制造业用地出让结构差异来表示。其中E_kj表示j市k产业的用地出让面积,E_j表示j市制造业所有产业的用地出让总面积,区域j与区域i空间相邻或属于同一省（区）
市场效率指数（IM）	市场度（Q₅）	$W ka G ki E ki + W kb S ki Z ki$	测度研究单元k产业的土地利用效率及市场化配置程度,以存量用地出让面积比和招拍挂出让宗数比来表示。其中G_ki表示i市k产业来源于存量建设用地的出让面积,S_ki表示i市k产业以招拍挂方式出让的用地宗数,W_ka和W_kb分别表示k产业在两者上的权重值,本文均取0.5
市场效率指数（IM）	溢价度（Q₆）	$P ki - P imin P imin$	衡量研究单元k产业的发展高度^[8],以地价溢出率来表示。P_ki表示i市k产业的用地出让均价,P_i_min表示i市的最低工业用地出让价格^④

表1

图1

图2

表2

基于空间计量经济模型的影响因素结果"

	（1）OSL	（2）SEM	（3）SEM时间固定	（4）SEM空间固定
常数	0.212926（1.3294）	0.155159（0.9650）	0.762468^***（4.1643）	-0.087505^*（-1.8468）
X₁	-0.024114^***（-3.8226）	-0.018476^***（-2.6400）	-0.012244（-1.4624）
X₂	-0.000141^**（-4.5240）	-0.000128^***（-3.4014）	-0.000142^***（-2.6311）
X₃	0.005220^***（2.3612）	0.005838^**（2.2037）	0.008994^**（2.3590）
X₄	0.001749^***（3.7840）	0.001797^***（3.7739）		0.00132^***（2.70806）
X₅	-0.005946^***（-4.5460）	-0.004634^***（-3.3529）		-0.000361（-0.3189）
X₆	0.001344^**（1.2530）	0.0006759（0.6140）		0.000850（0.7358）
X₇	0.004137（1.4402）	0.004959^*（1.7790）		0.006713^**（2.3347）
X₈	-0.00151^**（-4.5460）	-0.001205^*（-1.9292）		-0.000741（-1.2005）
X₉	0.001331^**（2.3290）	0.001178^**（2.1167）		0.001710^***（3.0823）
X₁₀	2.6957e-006^***（2.7747）	2.8441e-006^***（2.8774）		2.5047e-006^***（2.5889）
X₁₁	0.051088^***（6.0709）	0.043260^***（5.0235）		0.049268^***（5.7492）
X₁₂	-0.002324（-0.7033）	-0.002879（-0.9371）	-0.000602（-0.1923）
X₁₃	-0.013943（-1.4213）	-0.010937（-1.1278）	-0.039764^**（-3.5782）
X₁₄	-0.002789（-1.3394）	-0.002121（-1.0612）	-0.004530^*（-1.9525）
X₁₅	0.029314^**（1.9914）	0.026078^*（1.6879）	0.047291（2.9272）
X₁₆	0.017850（1.5337）	0.028541^**（2.1910）	0.047291^***（2.8083）
X₁₇	-0.069940^***（-2.5440）	-0.058317^**（-2.3283）	0.007816^***（0.2986）
X₁₈	-0.038848^*（-1.6848）	-0.048798^**（-2.1962）		-0.036955^*（-1.7500）
X₁₉	0.078204^***（5.0081）	0.075396^***（4.9000）		0.065069^***（4.4454）
λ		0.352244^***（4.9569）	0.572956^***（10.1276）	0.463867^**（7.2067）
R²	0.7192	0.7413	0.6304	0.7166
LogL	319.115	328.424	260.880	309.751
LR		18.6162^***	72.4985^***	38.8466^***
AIC	-598.231	-616.847	-501.76	-597.501
SC	-522.188	-540.805	-463.738	-555.678

表2

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