中国土地市场供给的价格弹性及其影响因素

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清华大学辅仁网/2017-07-07

中国土地市场供给的价格弹性及其影响因素

刘洪玉(

),姜沛言

Price elasticity of land supply and related impact factors in China

Hongyu LIU(

),Peiyan JIANG

Institute of Real Estate, Department of Construction Management,Tsinghua University, Beijing 100084, China

摘要:

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摘要为研究土地供给的价格弹性(以下简称土地供给弹性)所代表的政府土地出让行为对土地和住房市场的影响,该文构建在垄断土地供给条件下的土地和住房市场均衡理论模型,并针对“供过于求”和“供不应求”的市场状态分别进行分析。理论分析表明:土地供给弹性是影响土地和住房市场均衡状态的重要因素,地方政府可以通过提高土地供给弹性增加土地出让收入。基于中国35个大中城市2006-01—2013-09数据的实证分析表明:住房市场价格和交易量的波动以及地方政府财政对土地出让金的依赖程度是决定土地供给弹性的重要因素。政府应当根据城市发展情况,合理确定土地供给计划,确保住房用地的有效供应。

关键词 ：土地供给,供给弹性,土地出让收入

Abstract：This study investigates the influence of the price elasticity of the land supply in China (PELS), which represents the characteristics of the local government land supply behavior, using a theoretical model of the land and housing markets to analyze the situations when the land supply exceeds the demand and the demand exceeds the supply. This paper finds that the PELS greatly affects the land and housing market equilibrium, with a higher PELS bringing local governments more land leasing revenue. Monthly data for 35 major cities in China from January, 2006 to September, 2013 show that the fluctuation in housing price and trading volume and the financial dependence on the land leasing revenue of the local governments significantly affect the PELS. Local governments should make reasonable plans for the land supply according to development in these cities, and ensure an effective land supply for housing.

Key words：land supply price elasticity of supply land leasing revenue

收稿日期: 2014-01-23 出版日期: 2015-05-15

基金资助:国家自然科学基金资助项目(70873072)

引用本文:

刘洪玉,姜沛言. 中国土地市场供给的价格弹性及其影响因素[J]. 清华大学学报（自然科学版）, 2015, 55(1): 56-62.
Hongyu LIU,Peiyan JIANG. Price elasticity of land supply and related impact factors in China. Journal of Tsinghua University(Science and Technology), 2015, 55(1): 56-62.

链接本文:

http://jst.tsinghuajournals.com/CN/或 http://jst.tsinghuajournals.com/CN/Y2015/V55/I1/56

图表:

土地市场供给曲线

变量	平均值	中位数	最大值	最小值	标准差	观测数
LQ	3.892	4.115	7.085	-3.451	1.447	2 784
INC	7.306	7.296	8.022	6.611	0.318	3 255
POP	6.337	6.471	8.111	4.948	0.664	3 255
HP(-1)	5.004	4.984	6.123	4.443	0.29	3 220
LP(-1)	6.786	6.787	9.737	2.625	0.904	2 699
HQ(-1)	3.621	3.671	6.759	-0.357	0.943	3 220
DELTA	1.148	0.593	32.568	0.112	3.234	229

数据的描述性统计

变量	LQ	INC	POP	HP(-1)	LP(-1)	HQ(-1)	DELTA
LQ	1
INC	0.332^***	1
POP	0.325^***	0.214^***	1
HP(-1)	0.260^***	0.624^***	0.060^***	1
LP(-1)	0.100^***	0.284^***	0.098^***	0.141^***	1
HQ(-1)	0.297^***	0.257^***	0.554^***	0.123^***	0.092^***	1
DELTA	0.079^***	-0.113^***	-0.321^***	0.096^***	0.240^***	-0.164^***	1

数据的相关性分析

检验方法	统计量名	统计量
Pedroni检验	Panel v-Statistic	-4.344 5
	Panel rho-Statistic	6.473 4
	Panel PP-Statistic	-29.101^***
	Panel ADF-Statistic	-10.436^***
	Group rho-Statistic	8.772
	Group PP-Statistic	-31.479^***
	Group ADF-Statistic	-11.254^***
Kao检验	ADF	-11.214^***

面板数据Pedroni检验和Kao检验结果

变量名称	OLS方法		TSLS方法
变量名称	模型I	模型II	模型III	模型I	模型II	模型III
C	-11.622^***	-1.802	-1.884	-10.523^***	4.118	3.147
C	(-5.183)	(-0.659)	(-0.709)	(-3.724)	(-1.052)	(-0.778)
INC	2.623^***	1.317^***	1.44^***	2.543^***	0.71^***	0.886^***
INC	(19.217)	(5.658)	(6.430)	(15.414)	(2.296)	(2.921)
POP	-0.588	-0.608	-0.743^*	-0.716^*	-0.494	-0.648
POP	(-1.450)	(-1.423)	(-1.793)	(-1.647)	(-1.099)	(-1.456)
LP	0.002^**	-0.78^***	-0.743^***	0.058^**	-1.543^***	-1.371^***
LP	(2.074)	(-5.999)	(-5.981)	(2.267)	(-3.610)	(-3.502)
HP(-1)·LP		0.136^***	0.126^***		0.185^***	0.175^***
HP(-1)·LP		(5.948)	(5.632)		(5.741)	(5.458)
LP(-1)·LP		-0.005			0.001
LP(-1)·LP		(-1.078)			(-0.191)
HQ(-1)·LP		0.031^***	0.026^***		0.073^***	0.068^***
HQ(-1)·LP		(5.039)	(4.439)		(4.460)	(4.152)
DELTA·LP		0.011^***	0.011^***		0.009^***	0.01^***
DELTA·LP		(4.350)	(4.531)		(3.602)	(3.707)
城市固定效应	Yes	Yes	Yes	Yes	Yes	Yes
观测数	2 412	2 412	2 239	2 443	2 412	2 239
调整后R²	0.369	0.369	0.411	0.400	0.369	0.411
F统计量	39.364	39.364	42.014	44.930	39.364	42.014

模型估计结果

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