中国城乡差距对农地违法非农化的影响

doi:10.18402/resci.2019.12.11

摘要/Abstract

摘要：

城乡差距对于农村土地利用特别是农地违法非农化有着不可忽视的影响。本文首先从理论层面探讨了城乡差距对农地违法非农化的影响机理;在此基础上通过构建计量模型,并运用1999—2016年中国大陆31个省（市、区）的面板数据,进行了系统的实证检验。结果显示：城乡差距扩大会导致农地违法非农化规模显著增长,尤其是随着财政支农支出占比的下降和城乡居民人均可支配收入差距的扩大,农地违法非农化规模增幅明显。具体地,在省级层面,财政支农支出占比每下降一个百分点,农地违法非农化规模会增加近25 hm ²;城乡居民人均可支配收入差距每扩大10%,农地违法非农化规模也会增加约15 hm ²;而城乡土地产出效益差的扩大对农地违法非农化的影响则小得多。此外,在不同经济发展地区（或不同经济发展阶段）,城乡差距变化对农地违法非农化的影响存在显著差异。最后从有效遏制农地违法非农化的角度,针对性地提出了缩小城乡差距的相关路径和建议。

关键词: 城乡差距, 农地非农化, 土地违法, 财政支农支出, 城乡居民收入, 土地产出效益, 中国

Abstract:

Urban-rural gap has a wide and far-reaching impact on China’s economic and social development. This study first explored the influencing mechanisms of urban-rural gap on illegal farmland conversion in theory, then an econometric model was built to test the impacts of China’s urban-rural gap change on illegal farmland conversion using the panel data of China’s mainland during 1999 to 2016. The results show that the widening gap between urban and rural areas led to a significant increase in the scale of illegal farmland conversion. Especially with the decrease of the proportion of financial support for agriculture and rural development, and the widening gap of per capita disposable income between urban and rural residents, the scale of illegal farmland conversion increased significantly. At the provincial level, for every 1% reduction in the proportion of financial support for agriculture and rural development, the scale of illegal farmland conversion increased by nearly 25 hm ². For every 10% increase in the per capita disposable income gap between urban and rural residents, the scale of illegal farmland conversion increased by nearly 15 hm ². The widening gap between urban and rural land output has a much smaller impact on illegal farmland conversion. Furthermore, in different areas (or stages) of economic development, there are significant differences in the impact of urban-rural gap changes on illegal farmland conversion. At the end of this article, from the perspective of effectively curbing the illegal conversion of farmland, we put forward some relevant approaches and suggestions to narrow the urban-rural gap.

Key words: urban-rural gap, farmland conversion, illegal land use, financial support for agriculture and rural development, income of urban and rural residents, land output, China

王青, 陈志刚. 中国城乡差距对农地违法非农化的影响[J]. 资源科学, 2019, 41(12): 2274-2283.

WANG Qing, CHEN Zhigang. Impact of urban-rural gap on illegal farmland conversion in China[J]. Resources Science, 2019, 41(12): 2274-2283.

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变量	样本量	平均值	标准差	最小值	最大值
IFC	558	365.976	602.516	0.000	5561.240
INV	558	7223.037	8733.038	53.557	53322.938
DPEO	558	26.348	111.936	-859.000	1372.000
LAND	558	1678.517	1004.334	82.421	4436.117
PLC	558	0.556	0.497	0.000	1.000
AOF	558	9.180	3.368	2.133	18.966
DLE	558	300.732	861.046	14.280	6369.370
DUR	558	2.936	0.636	1.845	5.605

IFC	模型1	模型2	模型3	模型4	模型5	模型6
C	-367.213 (261.276)	-268.495 (243.622)	-359.419 (261.832)	1193.541*** (338.435)	-319.962 (278.789)	1011.746*** (343.499)
INV	—	0.022*** (0.007)	—	—	—	0.025*** (0.009)
INV²	—	-1.14e-06*** (1.79e-07)	—	—	—	-1.08e-06*** (1.93e-07)
DPEO	—	—	-0.108 (0.196)	—	—	-0.095 (0.178)
LAND	—	—	—	-11.157*** (1.627)	—	-8.599*** (1.645)
PLC	—	—	—	—	33.308 (68.194)	56.368 (75.060)
AOF	-26.069*** (8.746)	-18.485* (10.744)	-26.081*** (8.752)	-13.042 (8.598)	-31.457** (14.083)	-24.395* (12.891)
DLE	0.219*** (0.093)	0.168** (0.087)	0.218** (0.093)	0.134 (0.090)	0.214** (0.093)	0.108 (0.087)
DUR	308.816*** (74.460)	252.216*** (69.983)	307.244*** (74.564)	170.406** (74.188)	303.760*** (75.230)	149.617** (72.187)
N	558	558	558	558	558	558
R²	0.063	0.190	0.064	0.140	0.063	0.233
F	11.73	24.56	8.86	21.33	8.84	19.69

IFC	发达地区		欠发达地区
IFC	估计系数	标准差	估计系数	标准差
C	1065.230**	539.474	770.128*	469.130
INV	0.047***	0.015	0.024*	0.013
INV²	-1.37e-06***	2.81e-07	-1.25e-06***	3.89e-07
DPEO	-0.074	0.239	-0.043	0.280
LAND	-8.455***	2.143	-8.375***	2.802
PLC	33.110	120.522	42.321	95.916
AOF	-82.786***	25.276	-6.171	14.577
DLE	-0.276	0.597	0.065	0.080
DUR	358.938**	153.069	102.483	78.485
N	270		288
R²	0.299		0.173
F	13.15		6.90