增量与存量建设用地的经济贡献差异

doi:10.18402/resci.2021.10.12

摘要/Abstract

摘要：

如何高效配置利用增量和存量建设用地已成为中国实现高质量增长和城市建设目标的重要问题,增量和存量建设用地的经济贡献量是进行建设用地优化配置的基础依据,但两者尚未得到很好的区分和量化。本文结合土地要素性质和地方政府行为特征,构建和对比了基于不同要素替代率假定的两种土地生产函数,识别了增量和存量建设用地的要素特征,并比较了两者的数量差异及时空变化。研究表明：①投资驱动的中国经济增长模式和地方政府的土地引资行为导致了中国增量与存量建设用地利用偏好的差异。②中国各地区增量和存量建设用地之间具有固定的要素替代率,增量和存量用地的经济贡献比不随两类用地配置比例的多少而变化。③中国增量和存量用地的经济贡献具有显著的数量差异,2003—2016年增量建设用地贡献约为同期存量建设用地的2.82~10.40倍。④增量建设用地指标和经济产出之间存在着显著的内生性关系,忽略这种内生性关系,会导致对增量建设用地贡献的低估。在用地效率相关的绩效考核量化中统筹考虑增量与存量建设用地,有助于激励存量用地开发和建设用地可持续利用。

关键词: 增量建设用地, 存量建设用地, 土地生产函数, 土地出让, 地方政府, 土地要素替代率, 内生性检验, 中国

Abstract:

For achieving the goals of high-quality growth and urban development, it is important to effectively use incremental and stock construction land. However, existing research has not accurately measured the contributions of incremental and stock construction land for the economic development and has not compared the differences between these two types of land. Therefore, studies on the economic contributions of incremental and stock construction land can provide some reference for the improvement of land institution in China. This study first constructed production functions with incremental and stock construction land based on presumptions that the marginal substitution rate between incremental and stock construction land is variable and fixed. Then the study measured and compared the contribution amount of incremental and stock construction land across provinces from 2003-2016. Two statistical indicators, the supply of construction land from converted agricultural land and new construction land, were chosen as the appropriate proxy indicators for incremental construction land. Meanwhile, the method of instrumental variable analysis was used to simulate the production function. The results show that: (1) The economic development model driven by investment and local governments’ attempts to attract investment are reasons for the preference difference between incremental and stock construction land. (2) The marginal substitution rate between incremental and stock construction land is fixed with the changing rate between the input amounts of incremental and stock construction land. (3) The economic contribution amount of incremental construction land is 2.82-10.40 times that of stock construction land. (4) There are significant endogenous relationship between incremental construction land and GDP, which is usually ignored and results in underestimation of the contribution of incremental construction land. The policy implication of these results is further discussed. Integrated analysis and assessment of incremental and stock construction land would encourage development of stock construction land and sustainability of construction land use.

Key words: incremental construction land, stock construction land, production function with land factor, land conveyance, local governments, marginal rate of technical substitution between land factors, endogeneity analysis, China

黄凌翔, 韩杰, 陈竹. 增量与存量建设用地的经济贡献差异[J]. 资源科学, 2021, 43(10): 2081-2092.

HUANG Lingxiang, HAN Jie, CHEN Zhu. Differences between economic contributions of incremental and stock construction land[J]. Resources Science, 2021, 43(10): 2081-2092.

图/表 8

表1

表2

表3

实证模型的表达式

模型编号	模型形式	模型说明
模型1	$ln GD P ij = ln A + α ln K ij + β ln L ij + γ ln L a ij$	基于式（1）
模型2	$ln GD P ij = ln A + α ln K ij + β ln L ij + d M ij ln L s ij + b ln L s ij + γ 2 ln Lg y ij$	基于式（3）,以 $Lg y ij$ 代理Lc; $γ 1 = d M ij + b$ ;M为经济质量; $d$ 、 $b$ 为待估参数
模型3	$ln GD P ij = ln A + α ln K ij + β ln L ij + d' M ij ln L s ij + b' ln L s ij + γ 4 ln (1 + Lg y ij L s ij)$	基于式（4）,以 $Lg y ij$ 代理Lc; $γ 3 = d' M ij + b'$ ; $d' 、 b'$ 为待估参数
模型4	$ln GD P ij = ln A + α ln K ij + β ln L ij + d' M ij ln L s ij + b' ln L s ij + γ 4 ln (1 + Lx z ij L s ij)$	基于式（4）,以 $Lx z ij$ 代理Lc

表3

表4

区分增量、存量建设用地的生产函数拟合结果（N=390）

	模型 1 普通面板回归方法	模型 2 2SLS方法	模型 3 2SLS方法	模型4（模型3的稳健性检验）2SLS方法
第一阶段
	—	被解释变量： $Lg y ij$	被解释变量： $1 + Lg y ij / L s ij$	被解释变量： $1 + Lx z ij / L s ij$
工具变量： $Lg y ij - 1$ 或 $Lx z ij - 1$	—	0.360***	0.385***	0.276***
	—	(0.043)	(0.043)	(0.039)
F统计值	—	41.19	42.01	24.71
10%阈值	—	19.93	19.93	19.93
识别不足检验（LM统计值）	—	67.96	69.06	44.10
P值	—	<0.001	<0.001	<0.001
弱工具变量检验（F统计值）	—	44.73	19.85	8.16
P值	—	<0.001	<0.001	0.003
内生性检验	—	38.29	15.94	2.207
P值	—	<0.001	0.001	0.137
第二阶段
	被解释变量GDP	被解释变量GDP	被解释变量GDP	被解释变量GDP
$1 + Lgy / Ls$	—	—	11.108***	—
$1 + Lgy / Ls$	—	—	(1.975)	—
$1 + Lxz / Ls$	—	—	—	4.059***
$1 + Lxz / Ls$	—	—	—	(1.219)
$Lgy$	—	0.171***	—	—
$Lgy$	—	(0.0235)	—	—
$La$	1.602***	—	—	—
$La$	(0.141)	—	—	—
$Ls$	—	1.084***	1.098***	1.519***
$Ls$	—	(0.175)	(0.167)	(0.153)
$L$	0.134***	0.068	0.073**	0.125**
$L$	(0.038)	(0.042)	(0.040)	(0.037)
$K$	0.303***	0.263***	0.331***	0.292***
$K$	(0.026)	(0.032)	(0.028)	(0.029)
$L s M$	—	0.0007**	0.0007**	0.0003
$L s M$	—	(0.0003)	(0.0003)	(0.0003)
R²	0.935	0.912	0.923	0.932

表4

图1

图2

表5

图3

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数值区间	省（市、自治区）
[0.20, 0.25)	宁夏、云南、青海、西藏
[0.25~0.30)	湖南、新疆、内蒙古、山西、甘肃、广西、吉林、贵州
[0.30~0.35)	重庆、黑龙江、辽宁、陕西、海南、四川、河南、江西、河北
[0.35~0.45)	天津、山东、福建、湖北、安徽
[0.50, 1.00]	广东、北京、江苏、浙江、上海

	变量名称	单位	符号	平均值	标准差	最大值	最小值
被解释变量	第二、三产业产出	亿元	GDP	8578.21	8201.33	44177.10	137.08
内生解释变量	建设用地供应面积（新增建设用地部分）	hm²	Lgz	6598.26	6459.13	31510.30	7.68
内生解释变量	新增建设用地面积（用于稳健性检验）	hm²	Lxz	11861.15	9452.34	66400.00	200.00
外生解释变量	资本存量	亿元	K	29976.25	30377.55	172368.00	454.56
	劳动力人口	万人	L	1776.52	1554.33	8148.41	45.60
	存量建设用地面积	hm²	Ls	510366.77	290988.75	1315533.33	65169.81
	经济发展质量指数	—	M	2.74	2.38	24.99	-0.65
工具变量	上年度建设用地供应面积（新增建设用地部分）	hm²	Lgz_-1	6598.26	6459.13	31510.30	7.68
	上年度新增建设用地面积（用于稳健性检验）	hm²	Lxz_-1	11861.15	9452.34	66400.00	200.00
	人均农地面积^(a)	m²/人	Pn	17235.78	53863.03	320518.00	105.94

省份	模型3			模型4
	增量边际贡献	存量边际贡献	边际贡献比	增量边际贡献	存量边际贡献	边际贡献比
	(1)	(2)	(3)=(1)/(2)	(4)	(5)	(6)=(4)/(5)
北京	0.329	0.034	9.82	0.116	0.043	2.68
天津	0.237	0.024	9.98	0.079	0.030	2.66
河北	0.201	0.019	10.50	0.083	0.029	2.88
辽宁	0.178	0.017	10.44	0.068	0.024	2.85
上海	0.360	0.037	9.74	0.126	0.047	2.65
江苏	0.298	0.029	10.33	0.130	0.045	2.86
浙江	0.310	0.031	9.91	0.111	0.040	2.76
福建	0.237	0.023	10.16	0.077	0.028	2.73
山东	0.242	0.023	10.51	0.110	0.038	2.92
广东	0.331	0.032	10.24	0.148	0.052	2.84
海南	0.085	0.008	10.44	0.025	0.009	2.78
山西	0.144	0.014	10.50	0.053	0.018	2.85
吉林	0.127	0.012	10.59	0.048	0.017	2.89
黑龙江	0.110	0.010	10.72	0.050	0.017	2.97
安徽	0.181	0.017	10.59	0.077	0.026	2.91
江西	0.171	0.016	10.44	0.061	0.022	2.82
河南	0.209	0.020	10.55	0.089	0.031	2.89
湖北	0.195	0.019	10.41	0.074	0.026	2.83
湖南	0.204	0.020	10.41	0.078	0.028	2.83
四川	0.225	0.021	10.49	0.098	0.034	2.87
贵州	0.132	0.013	10.34	0.041	0.015	2.73
云南	0.134	0.013	10.64	0.050	0.017	2.90
西藏	0.045	0.004	10.58	0.012	0.004	2.76
陕西	0.154	0.015	10.44	0.054	0.019	2.81
甘肃	0.093	0.009	10.58	0.029	0.010	2.84
青海	0.075	0.007	10.37	0.021	0.008	2.72
宁夏	0.079	0.008	10.36	0.022	0.008	2.72
新疆	0.081	0.008	10.64	0.030	0.010	2.89
内蒙古	0.100	0.009	10.59	0.041	0.014	2.89
广西	0.139	0.013	10.55	0.051	0.018	2.84