城镇化对种植业面源污染影响的中介效应分析

罗海平; 何志文; 胡学英

doi:10.13930/j.cnki.cjea.210033

城镇化对种植业面源污染影响的中介效应分析

doi: 10.13930/j.cnki.cjea.210033

1.
南昌大学中国中部经济社会发展研究中心　南昌　330031
2.
南昌大学经济管理学院　南昌　330031
3.
中共江西省委党校　南昌　330038

基金项目: 江西省社会科学基金项目(20MJ02, 20YJ06)、江西省高校人文社会科学重点研究基地项目(JD20111)和中央党校重点调研课题(2021DXXTZDDYKT047)资助

详细信息

作者简介:
罗海平, 主要研究方向为生态安全。E-mail: lhp6322@126.com

通讯作者:
胡学英, 主要研究方向为农村经济。E-mail: 631098728@qq.com

中图分类号: F323.22
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- 被引次数: 0
出版历程
- 收稿日期: 2021-01-16
- 录用日期: 2021-04-19
- 网络出版日期: 2021-07-13
- 刊出日期: 2021-09-06

Analysis of the mediation effect of urbanization on non-point source pollution from the planting industry

LUO Haiping^1
,,
HE Zhiwen²,
HU Xueying^{3
, ,}

1.
Research Center for Centr-China Economic Development, Nanchang University, Nanchang 330031, China
2.
School of Economics and Management, Nanchang University, Nanchang 330031, China
3.
Party School of CPC Jiangxi Provincial Committee, Nanchang 330038, China

Funds: This study was supported by the Social Science Foundation of Jiangxi Province (20MJ02, 20YJ06), the Humanities and Social Science Key Research Base Project of Universities of Jiangxi Province (JD20111) and the Key Project of Party School of the Central Committee of CPC (2021DXXTZDDYKT047)

More Information

Corresponding author: E-mail: 631098728@qq.com

摘要

摘要: 在当前城镇化持续推进的背景下, 探究我国城镇化对化肥面源污染的作用机制, 对缓解我国生态压力, 促进农业绿色高质量发展具有重要现实意义。鉴于此, 本文基于2008—2018年城镇化和化肥施用量等省际面板数据, 运用单元调查评估法测算2008—2018年31个省(市、自治区)化肥面源污染物排放总量及排放强度, 再运用中介效应模型探究城镇化对化肥面源污染的影响机制。结果表明: 1) 2008—2018年我国化肥面源污染排放呈现先增后降的倒“U”型特征, 以2015年为拐点, 到研究期末排放总量及强度均降至该时期最低水平, 分别为516万t和37.65 kg·hm⁻²。2)从全国层面看, 城镇化会通过技术进步、劳动力转移、农地禀赋对化肥面源污染产生中介影响, 其中农地禀赋中介效应绝对值最大(0.0092), 劳动力与技术进步趋近, 分别为0.0040和0.0033。3)城镇化对化肥面源污染的影响机制存在显著的空间异质性。从技术进步看, 粮食主销区的中介效应绝对值最大(0.0160), 粮食主产区次之(0.0118), 粮食产销平衡区无显著中介效应; 从劳动力看, 仅粮食主产区存在显著中介效应(0.0538); 从农地禀赋看, 粮食主销区的中介效应绝对值最大(0.0126), 粮食产销平衡区次之(0.0095), 粮食主产区最小(0.0055), 其中粮食产销平衡区的中介效应方向与其他地区相反。为此, 在粮食主销区应重点加强耕地保护, 加快制定跨区协作的“占补平衡”制度, 在粮食主产区应积极引导优质劳动力回流农业部门, 在粮食平衡区应加快绿色农业技术与管理模式的应用。
- 城镇化 /
- 面源污染 /
- 中介效应模型 /
- 粮食功能区 /
- 空间异质性
Abstract: In the light of continued urbanization, it is important to analyze the effect of urbanization on fertilizer non-point source pollution in China to alleviate ecological pressure and promote green and high-quality agriculture development. This study used the unit survey and assessment method to measure the total emissions and emission intensity of fertilizer non-point source pollution in 31 provinces (cities, autonomous regions) in China from 2008 to 2018. The mediation effect model was used to analyze the influence of urbanization on fertilizer non-point source pollution. Compared with existing studies, this study has two aims. The first is to analyze the influence of urbanization on fertilizer non-point source pollution via the mediation effect, and to clarify the mechanism of how urbanization affects fertilizer non-point source pollution. The second is to analyze the spatial heterogeneity in the impact of urbanization on the fertilizer non-point source pollution in grain function areas, e.g., differences in the mechanisms of various mediation factors in different grain function areas. Our empirical results showed that: 1) from 2008 to 2018, fertilizer non-point source pollution in China had an inverted “U” pattern, first increasing and then decreasing, with 2015 as the inflection point. The total amount and intensity of emissions fell to the lowest levels at the end of the study period, 5.16 million t and 37.65 kg·hm⁻², respectively. 2) On a national level, urbanization had a mediating effect on fertilizer non-point source pollution owing to technological progress, labor migration, and farmland endowment. The mediation effect of farmland endowment had the highest absolute value (0.0092), and the mediation effects of labor and technological progress were increasing to 0.0040 and 0.0033, respectively. 3) There was significant spatial heterogeneity in the influence of urbanization on fertilizer non-point source pollution. For technological progress, the absolute value of the mediation effect in the major grain-consuming areas was the highest (0.0160), followed by that in the major grain-producing areas (0.0118), whereas the grain-balance areas did not have a significant mediation effect. For labor, there was only a significant mediation effect in the major grain-production areas (0.0538). For farmland endowment, the absolute value of the mediation effect in the major grain-consuming areas was the highest (0.0126), followed by that in the grain-balance areas (0.0095), and the major grain-producing areas had the lowest absolute value (0.0055). The direction of the mediation effect in grain-balance areas was opposite to that in other regions. Therefore, it was important to protect arable land in the major grain-consuming areas and to form a cross-regional collaboration system of “occupation-compensation balance”. In the major grain-producing areas, high-quality labor should be actively guided to return to the agricultural sector. In the grain-balance areas, green agricultural technology and management modes should be introduced.
- Urbanization /
- Non-point source pollution /
- Mediation effect model /
- Food functional area /
- Spatial heterogeneity

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图 1 城镇化对化肥面源污染的作用机制

Figure 1. Mechanism of effects of urbanization on non-point source pollution of fertilizer

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表 1 各省(市、自治区)化肥面源污染排放总量及排放强度

Table 1. Total emissions and emission intensity of fertilizers of non-point source pollution in various province (cities, autonomous regions)

省(市、自治区) Province (city, autonomous region)	排放总量 Total emissions ($ \times $10⁴ t)			排放强度 Emission intensity (kg·hm⁻²)
省(市、自治区) Province (city, autonomous region)	2008	2015	2018	2008	2015	2018
北京 Beijing	2.68	1.97	1.30	83.18	113.47	125.30
天津 Tianjin	4.51	3.81	2.56	100.99	81.20	59.68
河北 Hebei	37.70	38.55	34.12	43.27	44.11	41.62
山西 Shanxi	5.79	5.92	5.22	15.53	15.71	14.68
内蒙古 Inner Mongolia	18.16	25.50	23.51	26.47	33.70	26.64
辽宁 Liaoning	16.21	17.78	16.07	43.63	42.14	38.19
吉林 Jilin	18.75	24.00	22.56	37.52	42.26	37.10
黑龙 Heilongjiang	10.04	13.82	13.27	8.30	11.24	9.04
上海 Shanghai	3.10	1.90	1.53	79.79	55.90	54.26
江苏 Jiangsu	65.75	60.47	55.20	87.55	78.07	73.40
浙江 Zhejiang	18.38	16.61	14.60	74.04	72.50	73.81
安徽 Anhui	16.79	17.79	16.30	18.70	19.88	18.58
福建 Fujian	12.31	12.64	11.27	55.44	54.23	71.42
江西 Jiangxi	6.60	6.86	5.79	12.38	12.30	10.42
山东 Shandong	51.33	48.82	43.64	47.68	44.28	39.40
河南 Henan	35.83	40.38	37.81	25.33	27.99	25.58
湖北 Hubei	38.36	37.51	32.27	52.56	47.17	40.57
湖南 Hunan	25.55	26.20	25.12	33.82	30.06	30.97
广东 Guangdong	36.37	39.73	34.50	82.58	83.03	80.62
广西 Guangxi	10.27	11.72	11.63	18.02	19.11	19.47
海南 Hainan	2.30	2.48	2.39	28.34	29.39	33.48
重庆 Chongqing	5.91	6.24	5.87	18.38	17.45	17.52
四川 Sichuan	15.59	15.60	14.36	16.52	16.09	14.94
贵州 Guizhou	10.82	12.83	10.35	23.42	23.15	18.90
云南 Yunnan	21.32	27.75	25.62	35.21	38.62	37.18
西藏 Tibet	0.26	0.31	0.26	10.86	12.40	9.58
陕西 Shaanxi	20.54	25.91	25.19	49.30	60.47	61.58
甘肃 Gansu	4.93	5.54	4.64	12.74	13.09	12.29
青海 Qinghai	0.49	0.60	0.50	9.58	10.67	8.92
宁夏 Ningxia	4.29	4.66	4.44	35.42	36.88	38.12
新疆 Xinjiang	9.04	14.15	14.44	20.14	24.58	23.79

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表 2 城镇化对化肥面源污染影响的回归结果

Table 2. Regression results of the impact of urbanization on fertilizer non-point source pollution

解释变量 Explanatory variable	模型1 Model 1	模型2 Model 2	模型3 Model 3	模型4 Model 4
城镇化 Urbanization	0.0024(0.65)	0.0057^*(2.17)	0.0065^*(1.82)	0.0003(0.10)
技术进步 Technological progress		−0.3096^***(−17.97)
农业劳动力 Agricultural labor			0.4603^***(5.80)
农地禀赋 Farmland endowment				0.3984^***(8.72)
控制变量 Control variable	YES	YES	YES	YES
常数项 Constant	−3.0716^***(−5.26)	−3.6207^***(−14.42)	−3.1423^***(−4.8)	−4.5802^***(−12.40)
中介效应 Mediation effect		−0.0033	−0.0040	−0.0092
个体/时间固定效应 Individual/time fixed effect	YES	YES	YES	YES
拟合优度 Goodness of fit (R²)	0.5526	0.7654	0.5815	0.6239
Wald chi²	4086.80^***	6364.05^***	3121.08^***	5363.68^***
Pesaran’s test	0.2227	0.1006	0.1333	0.0964
括号中的数字为t值, *、和分别表示在P<1%、P<5%和P<10%水平显著; 模型1为直接效应模型, 模型2为技术进步中介效应模型, 模型3为劳动力中介效应模型, 模型4为农地禀赋中介效应模型。The numbers in parentheses are t-values. , , and * indicate significant at P<1%, P<5%, and P<10% levels, respectively. Model 1 is a direct effect model. Model 2 is a mediating effect model of technological progress. Model 3 is a labor force mediating effect model. Model 4 is a farmland endowment mediating effect model.

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表 3 三大粮食功能区城镇化对化肥面源污染的中介效应测算结果

Table 3. Calculation results of the intermediary effect of urbanization on fertilizer non-point source pollution in the three major food functional areas

解释变量 Explanatory variable	粮食主产区 Main grain-producing area		粮食主销区 Main grain-consuming area		粮食平衡区 Grain-balance area
解释变量 Explanatory variable	估计参数 Estimated parameter	中介效应 Mediation effect	估计参数 Estimated parameter	中介效应 Mediation effect	估计参数 Estimated parameter	中介效应 Mediation effect
技术进步 Technological progress	−0.3608^*** (−9.69)	−0.0118	−0.2417^*** (−13.60)	−0.0160	−0.0056 (−0.05)	不显著 Not obvious
农业劳动力 Agricultural labor	0.5074^*** (5.71)	−0.0538	0.0390 (0.90)	不显著 Not obvious	0.1271 (1.43)	不显著 Not obvious
农地禀赋 Farmland endowment	0.4396^*** (3.31)	−0.0055	0.8963^*** (7.84)	−0.0126	−0.4051^*** (−5.28)	0.0095
括号中的数字为t值, *、和分别表示在P<1%、P<5%和P<10%水平显著。The numbers in parentheses are t-values, and , and * indicate significant at P<1%, P<5% and P<10% levels, respectively.

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参考文献(53)

[1]	马道明. 城镇化背景下农村环境持续恶化的内生性探析−基于苏南Q镇的调查[J]. 学海, 2018, (4): 53−58 doi: 10.3969/j.issn.1001-9790.2018.04.007 MA D M. Endogenous analysis of the continuous deterioration of rural environment under the background of urbanization[J]. Academia Bimestrie, 2018, (4): 53−58 doi: 10.3969/j.issn.1001-9790.2018.04.007
[2]	李秀芬, 朱金兆, 顾晓君, 等. 农业面源污染现状与防治进展[J]. 中国人口·资源与环境, 2010, 20(4): 81−84 doi: 10.3969/j.issn.1002-2104.2010.04.014 LI X F, ZHU J Z, GU X J, et al. Current situation and control of agricultural non-point source pollution[J]. China Population, Resources and Environment, 2010, 20(4): 81−84 doi: 10.3969/j.issn.1002-2104.2010.04.014
[3]	杨滨键, 尚杰, 于法稳. 农业面源污染防治的难点、问题及对策[J]. 中国生态农业学报(中英文), 2019, 27(2): 236−245 YANG B J, SHANG J, YU F W. Difficulty, problems and countermeasures of agricultural non-point sources pollution control in China[J]. Chinese Journal of Eco-Agriculture, 2019, 27(2): 236−245
[4]	张利庠, 彭辉, 靳兴初. 不同阶段化肥施用量对我国粮食产量的影响分析−基于1952—2006年30个省份的面板数据[J]. 农业技术经济, 2008, (4): 85−94 ZHANG L X, PENG H, JIN X C. Analysis of the impact of chemical fertilizer application in different stages on my country’s grain output—Based on panel data of 30 provinces from 1952 to 2006[J]. Journal of Agrotechnical Economics, 2008, (4): 85−94
[5]	侯孟阳, 姚顺波. 异质性条件下化肥面源污染排放的EKC再检验−基于面板门槛模型的分组[J]. 农业技术经济, 2019, (4): 104−118 HOU M Y, YAO S B. EKC retest of fertilizer non-point source pollution emission under heterogeneous conditions—grouping based on panel threshold model[J]. Journal of Agrotechnical Economics, 2019, (4): 104−118
[6]	李太平, 张锋, 胡浩. 中国化肥面源污染EKC验证及其驱动因素[J]. 中国人口·资源与环境, 2011, 21(11): 118−123 doi: 10.3969/j.issn.1002-2104.2011.11.020 LI T P, ZHANG F, HU H. Authentication of the kuznets curve in agriculture non-point source pollution and its drivers analysis[J]. China Population, Resources and Environment, 2011, 21(11): 118−123 doi: 10.3969/j.issn.1002-2104.2011.11.020
[7]	栾健, 韩一军. 城镇化会加剧化肥面源污染吗−基于门槛效应与空间溢出的双重视角[J]. 中国农业大学学报, 2020, 25(5): 174−186 doi: 10.11841/j.issn.1007-4333.2020.05.18 LUAN J, HAN Y J. Does urbanization intensify chemical fertilizer non-point source pollution: Based on threshold effects and spatial spillovers[J]. Journal of China Agricultural University, 2020, 25(5): 174−186 doi: 10.11841/j.issn.1007-4333.2020.05.18
[8]	薛蕾, 廖祖君, 王理. 城镇化与农业面源污染改善−基于农民收入结构调节作用的空间异质性分析[J]. 农村经济, 2019, (7): 55−63 XUE L, LIAO Z J, WANG L. Urbanization and improvement of agricultural non-point source pollution: An analysis of spatial heterogeneity based on the adjustment effect of farmers’ income structure[J]. Rural Economy, 2019, (7): 55−63
[9]	邵帅, 李宝礼. 农村劳动力转移如何影响农村环境污染?−基于空间面板模型的实证考察[J]. 中国地质大学学报: 社会科学版, 2020, 20(1): 39−55 SHAO S, LI B L. Effects of rural labor transfer on rural environmental pollution in China: an empirical investigation based on spatial panel model[J]. Journal of China University of Geosciences: Social Sciences Edition, 2020, 20(1): 39−55
[10]	刘燕, 柴原. 农业劳动力转移背景下农业直接补贴对面源污染的影响−以化肥污染为例[J]. 中南林业科技大学学报: 社会科学版, 2020, 14(3): 56−66, 73 LIU Y, CHAI Y. Impact of agricultural direct subsidies on non-point source pollution under the background of agricultural labor transfer: a case study of chemical fertilizer pollution[J]. Journal of Central South University of Forestry & Technology: Social Sciences, 2020, 14(3): 56−66, 73
[11]	闫桂权, 何玉成, 张晓恒. 绿色技术进步、农业经济增长与污染空间溢出−来自中国农业水资源利用的证据[J]. 长江流域资源与环境, 2019, 28(12): 2921−2935 YAN G Q, HE Y C, ZHANG X H. Green technology progress, agricultural economic growth and pollution space spillover effect: evidence of agricultural water utilization process in China[J]. Resources and Environment in the Yangtze Basin, 2019, 28(12): 2921−2935
[12]	侯孟阳, 姚顺波. 中国农村劳动力转移对农业生态效率影响的空间溢出效应与门槛特征[J]. 资源科学, 2018, 40(12): 2475−2486 HOU M Y, YAO S B. Spatial spillover effects and threshold characteristics of rural labor transfer on agricultural eco-efficiency in China[J]. Resources Science, 2018, 40(12): 2475−2486
[13]	夏秋, 李丹, 周宏. 农户兼业对农业面源污染的影响研究[J]. 中国人口·资源与环境, 2018, 28(12): 131−138 XIA Q, LI D, ZHOU H. Study on the influence of farmers’ concurrent business behavior on agricultural non-point source pollution[J]. China Population, Resources and Environment, 2018, 28(12): 131−138
[14]	史常亮, 李赟, 朱俊峰. 劳动力转移、化肥过度使用与面源污染[J]. 中国农业大学学报, 2016, 21(5): 169−180 doi: 10.11841/j.issn.1007-4333.2016.05.022 SHI C L, LI Y, ZHU J F. Rural labor transfer, excessive fertilizer use and agricultural non-point source pollution[J]. Journal of China Agricultural University, 2016, 21(5): 169−180 doi: 10.11841/j.issn.1007-4333.2016.05.022
[15]	廖炜, 李璐, 杨伟, 等. 城镇化过程中的流域面源污染时空变化[J]. 长江流域资源与环境, 2018, 27(8): 1776−1783 LIAO W, LI L, YANG W, et al. Spatio-temporal change of non-point source pollution loads in the process of urbanization[J]. Resources and Environment in the Yangtze Basin, 2018, 27(8): 1776−1783
[16]	吴义根, 冯开文, 李谷成. 人口增长、结构调整与农业面源污染−基于空间面板STIRPAT模型的实证研究[J]. 农业技术经济, 2017, (3): 75−87 WU Y G, FENG K W, LI G C. Population growth, structural adjustment and agricultural non-point source pollution: an empirical study based on the spatial panel STIRPAT model[J]. Journal of Agrotechnical Economics, 2017, (3): 75−87
[17]	徐承红, 薛蕾. 农业产业集聚与农业面源污染−基于空间异质性的视角[J]. 财经科学, 2019, (8): 82−96 XU C H, XUE L. Agricultural industry agglomeration and agricultural non-point source pollution — A perspective based on spatial heterogeneity[J]. Finance & Economics, 2019, (8): 82−96
[18]	温忠麟, 叶宝娟. 中介效应分析: 方法和模型发展[J]. 心理科学进展, 2014, 22(5): 731−745 doi: 10.3724/SP.J.1042.2014.00731 WEN Z L, YE B J. Analyses of mediating effects: the development of methods and models[J]. Advances in Psychological Science, 2014, 22(5): 731−745 doi: 10.3724/SP.J.1042.2014.00731
[19]	徐建玲, 查婷俊. 基于城镇化视角的省域粮食安全研究−以江苏省为例[J]. 资源科学, 2014, 36(11): 2353−2360 XU J L, ZHA T J. Provincial food security from the perspective of urbanization in Jiangsu Province[J]. Resources Science, 2014, 36(11): 2353−2360
[20]	范泽孟, 李赛博. 1990年来中国城镇建设用地占用耕地的效率和驱动机理时空分析[J]. 生态学报, 2021, 41(1): 374−387 FAN Z M, LI S B. Spatio-temporal analysis of the economic benefit and driving mechanism of urban build-up land occupying the cultivated land in China since 1990[J]. Acta Ecologica Sinica, 2021, 41(1): 374−387
[21]	叶中华, 魏玉君. 城镇化背景下粮食安全研究可视化分析−基于Cite Space的图谱量化研究[J]. 中国人口·资源与环境, 2018, 28(S1): 64−66 YE Z H, WEI Y J. Visualization analysis of food security under the background of urbanization: graphite quantization on Cite Space[J]. China Population, Resources and Environment, 2018, 28(S1): 64−66
[22]	向涛, 綦勇. 粮食安全与农业面源污染−以农地禀赋对化肥投入强度的影响为例[J]. 财经研究, 2015, 41(7): 132−144 XIANG T, QI Y. Food security and agricultural non-point source pollution: taking the impact of agricultural land endowments on fertilizer use intensity as an example[J]. Journal of Finance and Economics, 2015, 41(7): 132−144
[23]	赵明正, 赵翠萍, 李天祥, 等. “零增长”行动背景下中国化肥使用量下降的驱动因素研究−基于LMDI分解和面板回归分析[J]. 农业技术经济, 2019, (12): 118−130 ZHAO M Z, ZHAO C P, LI T X, et al. Driving forces analysis for China’s recent fertilizer use reduction under the “zero growth” action plan—estimation based on the LMDI approach and panel regression analysis[J]. Journal of Agrotechnical Economics, 2019, (12): 118−130
[24]	GODFRAY H C J, CRUTE I R, HADDAD L, et al. The future of the global food system[J]. Philosophical Transactions of the Royal Society B: Biological Sciences, 2010, 365(1554): 2769−2777 doi: 10.1098/rstb.2010.0180
[25]	郑旭媛, 徐志刚. 资源禀赋约束、要素替代与诱致性技术变迁−以中国粮食生产的机械化为例[J]. 经济学, 2017, 16(1): 45−66 ZHENG X Y, XU Z G. Endowment restriction, factor substitution and induced technological innovation: a case research on the grain producing mechanization in China[J]. China Economic Quarterly, 2017, 16(1): 45−66
[26]	杨林章, 冯彦房, 施卫明, 等. 我国农业面源污染治理技术研究进展[J]. 中国生态农业学报, 2013, 21(1): 96−101 YANG L Z, FENG Y F, SHI W M, et al. Review of the advances and development trends in agricultural non-point source pollution control in China[J]. Chinese Journal of Eco-Agriculture, 2013, 21(1): 96−101
[27]	江景涛, 杨然兵, 鲍余峰, 等. 水肥一体化技术的研究进展与发展趋势[J]. 农机化研究, 2021, 43(5): 1−9 JIANG J T, YANG R B, BAO Y F, et al. Research progress and development trend of water and fertilizer integration[J]. Journal of Agricultural Mechanization Research, 2021, 43(5): 1−9
[28]	王一格, 王海燕, 郑永林, 等. 农业面源污染研究方法与控制技术研究进展[J]. 中国农业资源与区划, 2021, 42(1): 25−33 WANG Y G, WANG H Y, ZHENG Y L, et al. Advances in research methods and control technologies of agricultural non-point source pollution: a review[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2021, 42(1): 25−33
[29]	黄建强, 李录堂. 从农村劳动力视角探析耕地抛荒行为−基于会同县农村的实证研究[J]. 北京理工大学学报: 社会科学版, 2009, 11(6): 42−47 HUANG J Q, LI L T. The phenomenon of idling arable land in view of rural labour—an empirical study of the phenomenon on the basis of the reality in Huitong County[J]. Journal of Beijing Institute of Technology: Social Sciences Edition, 2009, 11(6): 42−47
[30]	GELLRICH M, BAUR P, KOCH B, et al. Agricultural land abandonment and natural forest re-growth in the Swiss mountains: a spatially explicit economic analysis[J]. Agriculture, Ecosystems & Environment, 2007, 118(1/2/3/4): 93−108
[31]	BOWLUS A J, SICULAR T. Moving toward markets? Labor allocation in rural China[J]. Journal of Development Economics, 2003, 71(2): 561−583 doi: 10.1016/S0304-3878(03)00040-3
[32]	陈敏鹏, 陈吉宁, 赖斯芸. 中国农业和农村污染的清单分析与空间特征识别[J]. 中国环境科学, 2006, 26(6): 751−755 doi: 10.3321/j.issn:1000-6923.2006.06.025 CHEN M P, CHEN J N, LAI S Y. Inventory analysis and spatial distribution of Chinese agricultural and rural pollution[J]. China Environmental Science, 2006, 26(6): 751−755 doi: 10.3321/j.issn:1000-6923.2006.06.025
[33]	赖斯芸, 杜鹏飞, 陈吉宁. 基于单元分析的非点源污染调查评估方法[J]. 清华大学学报: 自然科学版, 2004, 44(9): 1184−1187 LAI S Y, DU P F, CHEN J N. Evaluation of non-point source pollution based on unit analysis[J]. Journal of Tsinghua University: Science and Technology, 2004, 44(9): 1184−1187
[34]	许庆. 技术效率、配置效率与中国的粮食生产−基于农户的微观实证研究[J]. 人民论坛·学术前沿, 2013, (16): 84−95 XU Q. Technical and allocative efficiencies and China’s grain production — A microcosmic empirical study based on data of rural households[J]. People’s Tribune Frontiers, 2013, (16): 84−95
[35]	刘晨跃, 徐盈之. 城镇化如何影响雾霾污染治理?−基于中介效应的实证研究[J]. 经济管理, 2017, 39(8): 6−23 LIU C Y, XU Y Z. How does urbanization affect haze pollution control? — An empirical study based on the mediation effect[J]. Business Management Journal, 2017, 39(8): 6−23
[36]	FARE R, GROSSKOPF S, NORRIS M. Productivity growth, technical progress, and efficiency change in industrialized countries: reply[J]. American Economic Review, 1997, 87(5): 1040−1043
[37]	程惠芳, 陆嘉俊. 知识资本对工业企业全要素生产率影响的实证分析[J]. 经济研究, 2014, 49(5): 174−187 CHENG H F, LU J J. The empirical analysis of knowledge capital impact on total factor productivity of industry enterprises[J]. Economic Research Journal, 2014, 49(5): 174−187
[38]	史常亮, 郭焱, 朱俊峰. 中国粮食生产中化肥过量施用评价及影响因素研究[J]. 农业现代化研究, 2016, 37(4): 671−679 SHI C L, GUO Y, ZHU J F. Evaluation of over fertilization in China and its influencing factors[J]. Research of Agricultural Modernization, 2016, 37(4): 671−679
[39]	杜江, 罗珺. 农业经济增长与污染性要素投入−基于简约式及结构式模型的实证分析[J]. 经济评论, 2013, (3): 56−65, 117 DU J, LUO J. Agricultural economic growth and pollutant factor input: an empirical analysis based on the concise and structural models[J]. Economic Review, 2013, (3): 56−65, 117
[40]	葛继红, 周曙东. 要素市场扭曲是否激发了农业面源污染−以化肥为例[J]. 农业经济问题, 2012, 33(3): 92−98, 112 GE J H, ZHOU S D. Does factor market distortions stimulate the agricultural non-point source pollution? A case study of fertilizer[J]. Issues in Agricultural Economy, 2012, 33(3): 92−98, 112
[41]	张平淡, 袁赛. 决胜全面小康视野的农民收入结构与农业面源污染治理[J]. 改革, 2017, (9): 98−107 ZHANG P D, YUAN S. The income structure of farmers and the treatment of agricultural non-point source pollution in a comprehensive well-off vision[J]. Reform, 2017, (9): 98−107
[42]	武宵旭, 葛鹏飞, 徐璋勇. 城镇化与农业全要素生产率提升: 异质性与空间效应[J]. 中国人口·资源与环境, 2019, 29(5): 149−156 WU X X, GE P F, XU Z Y. Urbanization and the promotion of agricultural total factor productivity: heterogeneity and spatial effect[J]. China Population, Resources and Environment, 2019, 29(5): 149−156
[43]	葛继红, 周曙东. 农业面源污染的经济影响因素分析−基于1978—2009年的江苏省数据[J]. 中国农村经济, 2011, (5): 72−81 GE J H, ZHOU S D. Analysis of economic influencing factors of agricultural non-point source pollution — Based on the data of Jiangsu Province from 1978 to 2009[J]. Chinese Rural Economy, 2011, (5): 72−81
[44]	冷晨昕, 周晓时, 吴丽丽. 人力资本对农业劳动供给的影响−基于分数响应模型和无条件分位数回归模型[J]. 经济问题探索, 2021, (2): 38−48 LENG C X, ZHOU X S, WU L L. Effects of human capital on agricultural labor supply: Based on the fractional response model and the unconditional quintile model[J]. Inquiry into Economic Issues, 2021, (2): 38−48
[45]	吕晓, 屈毅, 彭文龙. 农户化肥施用认知、减施意愿及其影响因素−基于山东省754份农户调查问卷的实证[J]. 干旱区资源与环境, 2020, 34(4): 46−51 LYU X, QU Y, PENG W L. Farmers’ cognition of fertilizer application, willingness to reduce fertilizer application and its influencing factors[J]. Journal of Arid Land Resources and Environment, 2020, 34(4): 46−51
[46]	刘纪远, 宁佳, 匡文慧, 等. 2010—2015年中国土地利用变化的时空格局与新特征[J]. 地理学报, 2018, 73(5): 789−802 doi: 10.11821/dlxb201805001 LIU J Y, NING J, KUANG W H, et al. Spatio-temporal patterns and characteristics of land-use change in China during 2010-2015[J]. Acta Geographica Sinica, 2018, 73(5): 789−802 doi: 10.11821/dlxb201805001
[47]	高延雷, 张正岩, 魏素豪, 等. 城镇化对中国粮食安全的影响−基于省区面板数据的实证分析[J]. 资源科学, 2019, 41(8): 1462−1474 GAO Y L, ZHANG Z Y, WEI S H, et al. The impact of urbanization on China’s food security: An empirical analysis based on panel data of provinces and regions[J]. Resources Science, 2019, 41(8): 1462−1474
[48]	刘笑冰, 申强, 何忠伟. 我国农业科技成果转化资金绩效实证研究[J]. 农业技术经济, 2015, (6): 74−81 LIU X B, SHEN Q, HE Z W. An empirical study on the performance of agricultural science and technology achievements transformation funds in China[J]. Journal of Agrotechnical Economics, 2015, (6): 74−81
[49]	魏君英, 夏旺. 农村人口老龄化对我国粮食产量变化的影响−基于粮食主产区面板数据的实证分析[J]. 农业技术经济, 2018, (12): 41−52 WEI J Y, XIA W. The impact of rural population aging on the change of grain yield in China — Empirical analysis based on panel data of the main grain-producing areas[J]. Journal of Agrotechnical Economics, 2018, (12): 41−52
[50]	程名望, 黄甜甜, 刘雅娟. 农村劳动力转移对粮食安全的影响−基于粮食主销区面板数据的实证分析[J]. 上海经济研究, 2015, (4): 87−92, 100 CHENG M W, HUANG T T, LIU Y J. The impact of rural labor transfer on food security — An empirical analysis based on panel data of major grain sales areas[J]. Shanghai Economic Research, 2015, (4): 87−92, 100
[51]	成德宁, 杨敏. 农业劳动力结构转变对粮食生产效率的影响[J]. 西北农林科技大学学报: 社会科学版, 2015, 15(4): 19−26 CHENG D N, YANG M. Research on effect of agricultural labor force structure change on food production efficiency in China[J]. Journal of Northwest A& F University: Social Science Edition, 2015, 15(4): 19−26
[52]	田云, 张俊飚, 何可, 等. 农户农业低碳生产行为及其影响因素分析−以化肥施用和农药使用为例[J]. 中国农村观察, 2015, (4): 61−70 TIAN Y, ZHANG J B, HE K, et al. Analysis of farmers’ agricultural low-carbon production behavior and its influencing factors — Fertilizer application and pesticide use as an example[J]. China Rural Survey, 2015, (4): 61−70
[53]	杨鑫, 穆月英. 我国农业区域发展差异分析及政策选择[J]. 经济问题探索, 2017, (2): 168−176 YANG X, MU Y Y. Analysis of regional development differences in Chinese agriculture and policy choices[J]. Inquiry into Economic Issues, 2017, (2): 168−176