中国城镇化的农村减贫及其空间溢出效应——基于省级面板数据的空间计量分析

doi:10.11821/dlyj020190775

摘要/Abstract

摘要：

利用中国省级面板数据,运用空间计量模型,重点检验了2010—2017年间中国省域人口城镇化、土地城镇化和经济城镇化的农村减贫及其空间溢出效应。结果表明：①2010—2017年间中国省域农村贫困、人口城镇化和土地城镇化均表现出显著的空间集聚特征,而经济城镇化集聚现象呈现逐渐消减的态势。②人口城镇化对农村贫困主要表现为先缓解后加剧的“U”型特征,而经济城镇化则刚好与之相反,呈倒“U”型特点,土地城镇化对农村贫困的作用尚不明显,但主要表现出加剧农村贫困发生的潜在可能。③人口城镇化和经济城镇化对农村贫困产生了明显的空间溢出效应,同时,二者对农村贫困的空间溢出效应存在“门槛”现象。东部和中部地区的人口城镇化减贫直接效应门槛已基本突破,减贫潜力较弱,而大部分省份的人口城镇化减贫溢出效应门槛依然存在,益贫性的溢出效应仍然明显。相比之下,各省域经济城镇化减贫的直接效应和溢出效应门槛均已突破,整体上以益贫性为主。④城镇化发展过程中,应合理推进人口城镇化,加快完善相关制度改革。有效、有序地扩张城镇空间,优化城镇产业结构调整,壮大第三产业发展规模和强化其质量升级,增加城镇就业空间,提升城镇整体辐射带动效应。统筹协调区域人口、空间、资源等的分配与利用,充分发挥要素集聚带来的正向“外部性”作用,合力推进农村长效、稳定减贫,促进城乡协调与可持续发展。

关键词: 城镇化, 农村贫困, 空间计量模型, 空间溢出效应, 中国

Abstract:

Taking 27 provinces in China as an example, this paper mainly examines the rural poverty reduction and its spatial spillover effects of population urbanization, land urbanization and economic urbanization in China from 2010 to 2017. The results show that: (1) From 2010 to 2017, rural poverty, population urbanization and land urbanization in China's provinces show significant characteristics of spatial agglomeration, while the spatial agglomeration of economic urbanization gradually decreased. (2) Population urbanization has a "U"-shaped character in the rural poverty, while economic urbanization has an inversed "U"-shaped character. Land urbanization has no obvious effect on the rural poverty; however, it mainly shows the potential to aggravate the occurrence of rural poverty. (3) Population urbanization and economic urbanization have obvious spatial spillover effect on rural poverty, meanwhile, they have a "threshold" phenomenon in the spatial spillover effect of rural poverty. The direct effect threshold of population urbanization in poverty reduction in the eastern and central regions has basically been broken through, and the poverty reduction potential is weak, while the spillover effect threshold of population urbanization on poverty reduction in most provinces still exists, and the beneficial spillover effect is still obvious. In contrast, the direct and spillover effects of economic urbanization in all the provinces have broken through the threshold. (4) The urbanization of population should be pushed forward reasonably, and the related system reform should be quickened. We will expand urban space effectively in an orderly manner, optimize the adjustment of urban industrial structure, expand the scale of tertiary industry of the economic development and strengthen its quality upgrading, increase urban employment rate and enhance the overall radiation-driven effect of cities and towns. The allocation and utilization of population, space and resources in the region should be coordinated in an overall way, and the positive "externalities" caused by factor aggregation should be brought into full play to promote long-term, stable and poverty reduction in rural areas, and promote urban-rural coordination and sustainable development.

Key words: urbanization, rural poverty, spatial econometric model, spatial spillover effects, China

张博胜, 杨子生. 中国城镇化的农村减贫及其空间溢出效应——基于省级面板数据的空间计量分析[J]. 地理研究, 2020, 39(7): 1592-1608.

ZHANG Bosheng, YANG Zisheng. Rural poverty reduction and its spatial spillover effects of Chinese urbanization: Based on the analysis of spatial econometric model with provincial panel data[J]. GEOGRAPHICAL RESEARCH, 2020, 39(7): 1592-1608.

图/表 11

图1

表1

表2

表3

图2

表4

表5

空间固定效应模型与非空间面板固定效应模型估计结果"

变量	SPDM			SPLM	SPEM	非空间固定效应	SPDM空间滞后项（W_X）
	空间固定	时间固定	双固定	空间固定	空间固定	非空间固定效应	空间固定	时间固定	双固定
	模型（1）	模型（2）	模型（3）	模型（4）	模型（5）	模型（6）	模型（1）	模型（2）	模型（3）
urb_p	-3.851^***	-3.279^***	-4.035^***	-3.758^***	-4.232^***	-4.524^***	-1.733	-5.248^***	-2.637^**
	(-8.63)	(-7.02)	(-9.02)	(-9.56)	(-10.05)	(-5.29)	(-1.52)	(-4.60)	(-2.27)
(urb_p)²	0.039^***	0.029^***	0.039^***	0.031^***	0.036^***	0.034^***	0.012	0.057^***	0.023^*
	(8.37)	(6.25)	(8.55)	(7.48)	(8.21)	(3.64)	(1.01)	(5.07)	(1.81)
urb_l	1.848	-7.626^***	3.845	5.068	2.326	11.285	9.828	-7.051^**	18.255^*
	(0.42)	(-5.69)	(0.87)	(1.26)	(0.53)	(1.45)	(1.04)	(-2.34)	(1.84)
(urb_l)²	0.149	1.670^***	-0.302	-0.475	-0.835	-1.314	-1.984	1.108	-1.629
	(0.26)	(5.71)	(-0.50)	(-0.89)	(-1.44)	(-1.45)	(-1.25)	(1.42)	(-1.00)
urb_e	1.100^***	1.319^***	0.773^*	0.397	-0.218	0.017	1.624^**	-0.420	1.247
	(2.93)	(3.07)	(1.85)	(1.21)	(-0.60)	(0.02)	(2.18)	(-0.44)	(1.26)
(urb_e)²	-0.013^***	-0.017^***	-0.010^**	-0.006^*	0.001	-0.003	-0.022^**	-0.011	-0.019^*
	(-3.16)	(-3.37)	(-1.98)	(-1.68)	(0.31)	(-0.31)	(-2.55)	(-0.95)	(-1.68)
gdp_g	-0.013	0.076	-0.119	0.063	0.006	0.226	0.222	-0.925^***	-0.436^*
	(-0.12)	(0.57)	(-1.14)	(0.64)	(0.05)	(1.23)	(1.08)	(-3.11)	(-1.67)
u_r_d	0.378	1.081	-0.049	-1.122	2.612^*	-0.236	-3.250	-6.638^***	-1.689
	(0.25)	(1.01)	(-0.03)	(-0.90)	(1.81)	(-0.08)	(-1.36)	(-2.99)	(-0.48)
empl	1.898^***	-2.014^***	1.787^***	2.093^***	2.422^***	3.340^***	3.418^**	1.915^*	1.815
	(3.18)	(-5.02)	(3.05)	(3.50)	(3.70)	(3.44)	(2.07)	(1.66)	(1.05)
huma	-1.572	3.118^***	-1.372	-3.739^***	-3.697^***	-5.409^**	1.814	-0.266	4.269
	(-1.24)	(2.85)	(-1.09)	(-2.79)	(-2.75)	(-2.62)	(0.69)	(-0.10)	(1.47)
mart	3.038	-5.176^***	3.179	2.186	3.259^**	4.071^*	-5.708	-0.170	-5.400
	(1.52)	(-3.89)	(1.63)	(1.46)	(2.02)	(1.75)	(-1.50)	(-0.05)	(-1.31)
capi	-25.592^***	-5.970	-27.078^***	-21.471^***	-26.196^***	-27.301	-13.473	-60.926^***	2.430
	(-4.02)	(-1.13)	(-4.20)	(-4.20)	(-4.94)	(-1.25)	(-1.01)	(-4.66)	(0.16)
tech	0.690	0.392	0.578	0.335	0.884	0.203	-0.843	1.815	-0.691
	(1.04)	(0.54)	(0.87)	(0.52)	(1.37)	(0.18)	(-0.62)	(1.25)	(-0.44)
prod	-0.039^**	-0.037^***	-0.041^**	-0.022	-0.039^**	-0.038	0.016	-0.100^***	0.021
	(-2.05)	(-2.99)	(-2.14)	(-1.38)	(-2.03)	(-1.68)	(0.49)	(-3.27)	(0.59)
poli	0.249^***	0.096	0.231^***	0.092^**	0.196^***	0.115^**	-0.178^**	0.214	-0.108
	(3.70)	(1.13)	(3.50)	(2.17)	(2.63)	(2.17)	(-2.30)	(1.49)	(-1.00)
ρ/λ	0.361^***	0.205^**	0.080	0.465^***	0.780^***
R²	0.936	0.829	0.321	0.914	0.836	0.889
Log L	-386.542	-475.152	-373.455	-415.473	-429.328	-449.930

表5

表6

图3

图4

图5

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变量类型	具体指标（变量）	指标含义（单位）
被解释变量	农村贫困发生率（pove）	农村贫困人口占农村总人口比例（%）
核心解释变量	人口城镇化（urb_p）	城镇常驻人口占总人口比例（%）
	土地城镇化（urb_l）	建成区面积占总面积比例（%）
	经济城镇化（urb_e）	第三产业产值占GDP的比例（%）
控制变量	经济增长（gdp_g）	GDP增长率（%）
	农村收入水平（inco）	农民人均纯收入（元）
	城乡收入差距（u_r_d）	城乡居民人均收入之比
	农村转移人口就业环境（empl）	城镇登记失业率（%）
	农村人力资本（huma）	农村人口平均受教育年限（年）
	农村市场化水平（mark）	农村人均社会消费品零售额（万元）
	农村资本投入（capi）	农村住户人均固定资产投资（万元）
	农村技术进步（tech）	农林牧渔业单位产值农用机械总动力（kW/万元）
	农村劳动生产率（prod）	农村单位劳动力农林牧渔业产出（万元）
	农村扶贫政策（poli）	农村低保人口与总人口之比（%）

变量	样本数	均值	方差	最小值	最大值
pove	216	10.1255	8.6124	0.0000	45.1000
urb_p	216	52.6840	8.3339	33.8100	69.8500
urb_l	216	1.0372	0.9466	0.0200	4.3100
urb_e	216	41.8125	5.8811	28.6000	56.1000
gdp_g	216	9.8121	2.8180	-2.5000	17.1000
u_r_d	216	2.7782	0.4432	2.0600	4.0700
empl	216	3.3942	0.5460	1.7300	4.4700
huma	216	8.3059	0.3220	7.4300	9.0700
mart	216	0.4719	0.3213	0.1100	2.0400
capi	216	0.1580	0.0542	0.0600	0.3700
tech	216	1.2882	0.5384	0.3900	2.7000
prod	216	81.3034	37.1621	17.6600	178.7300
poli	216	7.8815	4.9441	1.0900	23.5300

年份	pove		urb_p		urb_l		urb_e
年份	Moran′s I	P值	Moran′s I	P值	Moran′s I	P值	Moran′s I	P值
2010	0.476	<0.001	0.330	0.002	0.379	<0.001	0.202	0.027
2011	0.511	<0.001	0.307	0.003	0.381	<0.001	0.171	0.048
2012	0.501	<0.001	0.291	0.005	0.392	<0.001	0.142	0.078
2013	0.490	<0.001	0.293	0.005	0.400	<0.001	0.139	0.082
2014	0.496	<0.001	0.286	0.005	0.498	<0.001	0.016	0.334
2015	0.492	<0.001	0.293	0.005	0.409	<0.001	-0.155	0.182
2016	0.457	<0.001	0.301	0.004	0.396	<0.001	-0.184	0.128
2017	0.453	<0.001	0.302	0.004	0.406	<0.001	-0.045	0.481

普通OLS模型检验统计量	数值	P值	空间面板模型检验统计量	数值	P值
F值	68.26	<0.001	Hausman	72.73	<0.001
Adj R²	0.82		Robust Hausman	210.99	<0.001
LM_Spatial error	26.86	<0.001	Wald_Spatial error	61.66	<0.001
Robust LM_Spatial error	0.24	0.623	LR_Spatial error	69.13	<0.001
LM_Spatial lag	62.57	<0.001	Wald_Spatial lag	55.91	<0.001
Robust LM_Spatial lag	35.96	<0.001	LR_Spatial lag	51.11	<0.001

变量	直接效应		间接效应		总效应
变量	系数	P值	系数	P值	系数	P值
urb_p	-4.148^***	<0.001	-4.669^***	0.004	-8.817^***	<0.001
(urb_p)²	0.041^***	<0.001	0.040^**	0.036	0.081^***	<0.001
urb_l	3.245	0.470	14.000	0.321	17.246	0.289
(urb_l)²	-0.083	0.886	-2.697	0.249	-2.780	0.286
urb_e	1.294^***	0.001	2.984^***	0.009	4.278^***	0.002
(urb_e)²	-0.016^***	<0.001	-0.039^***	0.003	-0.055^***	0.001
gdp_g	0.012	0.913	0.324	0.257	0.335	0.282
u_r_d	0.045	0.974	-4.602	0.186	-4.557	0.194
empl	2.354^***	<0.001	6.244^**	0.019	8.598^***	0.005
huma	-1.434	0.304	1.776	0.696	0.341	0.949
mart	2.545	0.260	-6.603	0.307	-4.059	0.616
capi	-27.285^***	<0.001	-32.802^*	0.095	-60.087^***	0.010
tech	0.633	0.353	-0.767	0.705	-0.134	0.954
prod	-0.040^**	0.037	0.006	0.902	-0.034	0.147
poli	0.244^***	<0.001	-0.127	0.159	0.117	0.538