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GEOGRAPHICAL RESEARCH >

2018 , Vol. 37 >Issue 9: 1724 - 1735

DOI: https://doi.org/10.11821/dlyj201809006

Orginal Article

The empirical determination on appropriate management scale of cultivated land in mountainous areas: A case study of Chongqing

  • FAN Qiaoxi , 1 ,
  • SHAO Jing'an , 2, 3 ,
  • YING Shouying 1
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  • 1. Chengdu University of Information Technology, School of Statistics, Chengdu, 610103, China
  • 2. College of Geography and Tourism, Chongqing Normal University, Chongqing 400047, China
  • 3. Key Laboratory of Surface Process and Environment Remote Sensing in the Three Gorges Reservoir Area, Chongqing 400047, China

Received date: 2018-03-07

  Request revised date: 2018-07-03

  Online published: 2018-10-22

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《地理研究》编辑部
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Abstract

In the context of the state allowing the transfer of rural contracted management rights and the development of modern agriculture, what scale is appropriate in the mountain area, and which is characteristic of the ups and downs of the topography, the fragmentation of the land and the far radius of the distribution? This is one of the scientific problems that must be clarified at the moment. Using 480 valid questionnaires, with the investment of agricultural labor force as the calculating unit, and with per labor net income as the evaluation index, we constructed econometric model from two aspects of crop type and radius of plot distribution. The results showed that: (1) In the current social and economic conditions, the area of moderate scale management of agricultural land is 24-32 mu. Per labor net income is far higher than the current rural per capita net income at moderate scale, and the gap between the urban and rural residents has significantly reduced. (2) The type of crops has little influence on the moderate scale, but it has a great influence on the net income of farmers. The moderate scale of economic crops and grain crops were 24.33 mu and 24.63 mu, respectively, but the difference was not significant. Per labor net income gap is 3638 yuan by planting economic crops and grain crops at moderate scale. The huge gap will prompt the development of economic crops in some areas suitable for economic crops. (3) The distance has great influence on the land moderate scale, but has little effect on the per labor net income. The areas within the distance of 0.5 km and 0.5-1 km at moderate scale were 28.62 mu and 31.83 mu, respectively, and the gap between moderate scales of average labor is 3 mu. This shows that distance is an important factor in agricultural production. However, the gap between per labor net income is small, which illustrates that the expansion of the moderate scale is mainly attributed to machinery with the increase of working distance. The model of land outside of 1 km fails to pass statistical test, which is further confirmed. Therefore, large-scale operation and mechanized farming are effective ways to solve the problem of distance; (4) Moderate scales of land are feasible and the feasibility and necessity for promoting the moderate scale of land management are demonstrated. This will provide scientific reference for the government to formulate the rural land management policy.

Key words： cultivated land; appropriate management scale; crop types; cultivated land distribution radius; mountainous areas

Cite this article

FAN Qiaoxi , SHAO Jing'an , YING Shouying . The empirical determination on appropriate management scale of cultivated land in mountainous areas: A case study of Chongqing[J]. GEOGRAPHICAL RESEARCH, 2018 , 37(9) : 1724 -1735 . DOI: 10.11821/dlyj201809006

1 引言

适度规模经营是山区耕地利用过程中破解比较劣势显著的主要方向,而在目前农村要素资源尚处低端、分散、整合受阻的情况下,合适耕地经营规模的确定一直是山区耕地利用、土地整治、产业选择、经营主体培育等所不可逾越的问题。山区农村大量劳动力的非农化不仅给耕地有效利用带来诸多挑战,更给耕地资源的优化组合和再配置提供了机遇[1,2,3]。伴随非农务工工资不断提升,从事农业生产的机会成本不断加大,农村大量青壮年劳动力从农业“析出”从事非农生产,致使农村人地关系发生较大变化,如劳动力老龄化、劳均耕地增加、耕作半径萎缩、耕地撂荒等[4,5]。在这一过程中,农民收入来源不再主要依靠农业生产,新的非农收入来源日渐形成且趋于稳定。目前看,传统分散化、碎块化土地经营模式无法适应新时期人地关系变化的需要,无法再依靠土地将其他要素资源有效整合起来。在国家新的政策导向下（如承包权经营权分离、培育新型经营主体、允许部分耕地休养生息等）新型人地关系并未完全形成,且稳定性仍需时间与实践来检验和调整,如在新型经营主体培育过程中[6],部分主体常以其拥有的要素资源优势参与承包权与经营权的分离,不切实际地圈占大量土地,结果给涉及农户带来很大的影响,也浪费较大的要素投入,且对所在区未来经营主体的培育以及耕地资源再配置与优化带来不良连带效应。
在山区多大的规模是合适的?多大的规模才有助于新型经营主体的培育?多大的规模才适应山区农村目前的要素资源特征?这些都是现阶段急需回答的重要课题。近年就如何发展农业、如何促进农民增收等问题[7,8,9,10],有学者提出扩大农业经营规模,而农业生产规模首先表现为耕地规模,根据报酬递减规律,过大的规模不仅不会带来规模经济,反而会造成效益下降。土地经营规模的扩大不是无度的,而是有地区性、动态性、层次性及适应性特征的,如何确定适度规模大小?需因地制宜多方考量。有学者从人均收入、单位面积产量、亩均纯收益、机会成本、投资效益率等方面提出土地适度规模的量化标准[11,12,13],但因农村大量人口多从事非农业生产,以人均收入测算土地适度规模并不合理,加之,现阶段农民问题的实质是增加收入、缩小城乡差距,以土地生产率为指标也不合理。农业生产中,劳动力投入占据主要地位,具有劳动力的农户才是农业生产经营活动的主体,为此,本文以劳动力为测算单位,选取劳均净收入来衡量土地适度规模大小,以期为未来山区农业适度规模经营、土地整治、产业选择、要素资源投入等方面提供科学支撑。

2 数据来源

2.1 样本基本情况

本文的调查与访谈区涉及武隆区长坝镇的鹅冠村和东升村、白马镇的车盘村、酉阳县木叶乡梨耳村和大板营村、巫山县龙溪镇老鸭村。样本村是典型的山区聚落,地形起伏大,经济欠发达,劳动力输出现象明显,留守劳动力以老弱病为主,农业是其收入的主要来源。
所用数据主要采用参与式农村访谈方式获取。课题组于2015年7月15日至8月10日对车盘村、东升村、大板营村、鹅冠村、老鸭村、梨耳村等村入户调查,回收有效问卷480份。为更准确计算农业劳动力的投入,以实际投入农业的劳动力为标准,根据务农程度予以赋权,不务农权数为0,只在农忙时务农权数为0.3,边工作、边务农权数为0.5,只务农权数为1,其他权数为0.1。
表1可知,鹅冠村拥有较好的劳动力资源,投入农业的劳动力也最多,说明农户实际从事农业生产的程度较高。老鸭村人口多、劳动力少,留守老人与儿童居多,劳动力资源较薄弱。东升村和大板营村人口与劳动力均相对较多,但因劳动力大部分流入城镇从事非农业生产,实际投入农业的劳动力不高。在现有劳动力情况下,样本村若要使务农者有较好收益,需推行农业生产的适度规模经营,有效提升农业生产的产投比,实现土地和劳动力的有效利用及农户增收的双赢。
Tab. 1 Basic situation of population in the sample village (person)

表1 样本村人口基本情况（人）

类型 村名
车盘村 大板营村 东升村 鹅冠村 老鸭村 梨耳村 合计
人口 306 342 325 354 411 318 2055
劳动力 214.4 234.5 236.5 261.5 163 223 1333
实际投入农业的劳动力 135.15 139.75 107.00 196.25 121.05 122.95 822
文化程度 1.文盲 55 50 54 51 63 57 330
2.小学 123 153 126 118 209 147 876
3.初中 67 77 76 98 80 64 462
4.高（职）中 25 25 29 37 22 22 160
5.大专及以上 10 1 10 7 9 3 40
6.学龄前 26 36 30 43 28 25 187
培训程度 1.专业培训 17 24 20 31 48 33 173
2.学徒 6 3 17 16 5 16 63
3.1+2 0 0 2 2 12 1 17
4.无 282 315 286 305 346 268 1802
文化程度方面,样本村总体文化教育水平偏低,各村间差异较小,以小学、初中为主。农户在接受现代农业科学技术与管理知识方面的能力、自主创新的潜力均会受到很大程度限制。
培训程度方面,样本村大部分农民未受过任何培训,受过专业培训的仅占约6%,即便个别农户积极投身于农业技术的传播、改进与应用,但大部分农户仍采取传统的生产方式,效率低且收益差。

2.2 种植收入情况

总体来看,烤烟带来的经济收入最高,其次是薯类、玉米、水稻和土豆。样本村中（表2）,车盘村、东升村和鹅冠村的种植业收入居于前列,农业发展情况较好。但是,不同村间主要收入来源有较大差异,车盘村、东升村、梨耳村以烤烟为主,经济作物的贡献率较大。鹅冠村、大板营村、老鸭村以种植粮食作物为主,主要收入来源有薯类、土豆、水稻和玉米。不用说,以种植经济作物为主和以种植粮食作物为主的村在收入方面差距较大,两类型样本村农业总收入相差约1.5倍。车盘村种植业收入是大板营的3倍,前者主要收入来源为烤烟,而后者为薯类。由于烤烟收入最高,玉米和薯类次之,导致前者农业发展状况较好,而后者较差。这也表明经济作物是农户增收的关键,应因地制宜适时发展,以提高农户收入。由于土地资源禀赋差异,车盘村、东升村和梨耳村生产烤烟前景较好,而鹅冠村、老鸭村和大板营村则适宜种植粮食作物。
Tab. 2 Main crop revenue in the sample village (yuan)

表2 样本村主要作物收入情况（元）

作物 村名
车盘村 大板营村 东升村 鹅冠村 老鸭村 梨耳村 总计
总收入 1239821.08 358573.30 991357.38 952090.13 505498.20 648341.86 4695681.95
烤烟 1038245.88 0.00 183577.96 0.00 0.00 248723.36 1470547.20
薯类 92760.00 155106.00 105357.72 299213.00 182670.00 152910.00 988016.72
玉米 50842.20 59457.80 242784.01 217673.42 95569.40 86710.00 753036.83
水稻 0.00 33696.00 207214.79 224950.51 0.00 45332.00 511193.30
土豆 17870.00 64612.50 70097.90 800.00 74452.00 90505.50 318337.90
蔬菜 25693.00 25751.00 125590.00 153943.20 56199.00 16000.00 403176.20

2.3 种植支出情况

车盘村作物种植面积较广（表3）,人力、物力和管理等投入较多,其次是东升村、梨耳村,而老鸭村用于农业的土地面积较小,支出最少。车盘村和鹅冠村主要支出均为化肥、种子,大板营村和老鸭村主要种植物为薯类,投入成本较低,种子、化肥支出最多。老鸭村人口老龄化较为严重,农忙时多靠机械生产,机械租金投入较多;而车盘村农户承包面积大,具有一定规模,作物种植以营利为主,机械化程度较高。梨耳村农户经营地块分散、破碎,不益于大型机械作业,且村中从事农业的劳动力充足,机械租金接近0。样本村亩均投入498元,支出主要是种子、化肥和农药。样本村土地破碎化严重,无法降低经营成本获得规模经济;其次,单位面积综合投入过低,不利于土地集约化利用;最后,农户为追求较好的经济效益,化肥、农药投入过多。
Tab. 3 Expenditure in the sample village (yuan)

表3 样本村支出情况（元）

类型 村名
车盘村 大板营村 东升村 鹅冠村 老鸭村 梨耳村 总计
种子 103372.77 101736.12 136388.25 66868.81 51249.95 110254.67 569870.57
除草剂 2675.30 3320.00 9658.00 5390.00 2956.50 7025.50 31025.30
农药 13089.00 3780.00 16998.00 9663.00 1329.00 6002.30 50861.30
地膜 10155.37 1643.20 3239.00 1751.50 1264.50 2718.30 20771.87
化肥 318725.51 58621.99 134488.95 140493.54 12109.54 99284.54 763724.06
机械租金 5340.40 820.00 1457.50 730.00 4390.00 0.00 12737.90
其他费用 230804.00 510.00 23172.00 3221.40 800.00 39196.00 297703.40
总支出 684162.35 170431.31 325401.70 228118.25 74099.49 264481.30 1746694.40
亩均投入 1146.31 545.10 421.75 175.13 74.71 884.23 497.87

2.4 收支总体情况

本文劳均纯收入以实际投入农业的劳动力为计算单位,亩均纯收入以实际种植的作物面积为计算单位。表4可知,适度的经营规模与农业收入、劳均纯收入、亩均纯收入呈正相关关系,但达到适度规模的最优点后继续扩大面积,会带来规模不经济效应。大板营村农业劳动力投入比东升村好,东升村单位土地劳动力投入最少,而鹅冠村在农业劳动力投入方面具备明显优势。在劳均纯收入方面,不同村间收入差距较大,尤其是大板营村与东升村相差近5倍。鹅冠村和车盘村在亩均收入方面均较高,大板营村和梨耳村相对较少。鹅冠村和车盘村发展较好,老鸭村地少但利用效率好,梨耳村地广,但单位面积纯收入与劳均纯收入低,综合土地利用效率较差。
Tab. 4 Income and expenditure in the sample village (yuan)

表4 样本村收入支出情况（元）

类型 村名
地块面积（亩） 农业投入
劳动力（人）		 总收入 总支出 纯收入 劳均纯收入 亩均纯收入 劳均
耕地（亩）
车盘村 596.84 135.15 1239821.08 684162.35 555658.73 4111.42 931.00 4.42
大板营村 312.66 139.75 358573.30 170431.31 188141.99 1346.28 601.75 2.24
东升村 771.55 107.00 991357.38 325401.7 665955.68 6223.88 863.14 7.21
鹅冠村 651.28 196.25 952090.13 228118.25 723971.88 3689.03 1111.61 3.32
老鸭村 495.52 121.05 505498.20 74099.49 431398.71 3563.81 870.60 4.09
梨耳村 680.05 122.95 648341.86 264481.3 383860.56 3122.09 564.46 5.53
总计 3508.31 822.15 4695681.95 1746694.4 2948987.55 3586.92 840.57 4.27

3 实证分析

3.1 模型建立

综合现有衡量土地适度经营规模指标,主要分土地生产率和劳动生产率两大类。黄新建等[14]以单产和亩均纯收益确定江西省适度规模为70亩~150亩,齐城[15]以提高农业劳动生产率为目标发现信阳市适度规模为5.12亩,张成玉[16]以城镇在岗职工人均工资性收入为比较指标算出河南省适度规模为劳均72亩;阚酉浔等[17]认为农户人均纯收入最大时经营规模为19亩。就目前小农国情看,以收入为量化标准最为可行,有助于发挥市场在新型经营主体培育、资源整合中的基础性作用。
农户作为理性经济人,以追求利益最大化为目标,本文以能获得最大纯收入为衡量指标符合经济人的行为设定。根据土地边际报酬递减规律,土地经营规模有一个最优度,此时土地规模报酬是最高的,而在达到最优度前增加投入、扩大土地规模可带来规模效益,提高土地收入,但超过最优度后继续扩大规模会引起成本增加、规模不经济,土地收入下降。基于此,以收集到的480份有效调查数据为基础建立劳均纯收入与劳均土地面积间的回归模型：
Y = a X 2 + bX + c （1）
式中：Y为劳均纯收入;X为劳均土地面积。在二阶偏导为负的条件下通过对模型一阶偏导可求出单位劳动力最优土地经营规模,再根据回归方程求出最优规模下的劳均纯收入。
值得说明的是,本文的研究目标旨在确定山区耕地适度经营的规模,这里的劳均纯收入主要指留守劳动力从事农业生产可能获得的纯收入,不包含兼业非农收入部分。当然,在山区农业生产的比较劣势较为明显,耕地资源和劳动力资源均受市场的影响而发生再配置和再优化,从而出现部分留守劳动力的兼业、部分劣质耕地的撂荒。通过对农户劳均纯收入与城镇居民人均收入、农村人均纯收入的比较,判断最优规模是否可行,以此确定单位劳动力的土地适度规模大小。最后,根据家庭劳动力多少确定农户可能经营土地规模的大小。从收入角度看,在推行适度经营规模后,务农收入只有高于目前收入且与城镇收入差距缩小或略高的情况下,农户才会愿意扩大再生产,否则会出现土地撂荒、大量农村人口从事非农业生产等现象。确保农户收入是推行土地适度规模经营的决定因素,以劳均纯收入为适度规模的衡量指标符合现实需求。从农业区位论看,单位土地收益不仅与生产成本、产品价格相关,更与农业生产结构、利用方式与集约利用程度密切相关。样本村在自然地理、社会经济等方面迥异,种植业生产结构存在明显差异。
根据农业区位论分类建立模型综合考量,将经济作物是主要收入来源的车盘村、东升村、梨耳村列为1类,考察经济作物的适度规模,建立第1个模型;将粮食作物是主要收入来源的鹅冠村、大板营村、老鸭村列为1类,考察粮食作物的适度规模,建立第2个模型;最后,将所有样本村整合为1类,综合考察农户纯收入最大时农业适度规模经营状况,建立第3个模型。从农业圈层布局来看,地块距农户居住地的分布半径影响农户对单位土地面积的投入,分布半径大的地块成本投入较多,且不易于开展日常管理。在考虑地块规模大小时应从地块分布半径予以分类考量。依据样本数据将地块分布半径分为0~0.5 km、0.5~1 km和1 km以上3大类,分别进行相关性分析和建模,求出不同分类标准下适度经营规模的大小,最后综合考量农业土地的适度规模。
模型中劳均纯收入是通过劳均总收入减去劳均总支出得出的。劳均纯收入指标下土地规模是以单个劳动力创造出的农产品所能获得最大纯收入下的土地适度经营规模。因个体年龄、性别、健康程度不同,单个农户投入农业的劳动力有一定差异。受文化教育与技能培训程度的影响,单个个体实际从事农业的程度不同,表现为不务农、只在农忙时务农、边工作边务农、只务农4种情形。样本村大部分劳动力从事非农业生产,在测量适度规模时不应笼统以人均计算。从柯布—道格拉斯生产函数看,以劳动力为测量基础、以劳均为计量单位才能正确反映单位劳动力实际应经营多大土地面积,获得最佳收益,进而测量出农户所应经营的合理面积。本文主要研究种植业的适度经营规模,总收入仅指种植业收入。从机会成本出发,农户用于满足自身需要的那部分产量应转化为收入,属农户的农业收入。因此农户种植业收入包括满足自身量化收入和实际销售收入。

3.2 相关分析

土地适度经营规模是动态的,受多因素综合影响,本文从地貌、作物类别、距离远近三个方面进行劳均纯收入与劳均土地面积的相关性分析,以观察不同条件下的相关 程度。
（1）地貌相关性
自然环境对经营规模的影响有明显的作用。考虑样本村的典型山区地貌及地块分布的微地貌特征,将地块的地貌类型分为：槽坝、低山、中山和丘陵,分别作Pearson相关分析。
地块的4类微地貌类型中,位于槽坝和低山的地块最多,中山、丘陵次之。由表5可知,当地块属中山地貌时,劳均纯收入与劳均土地面积的皮尔森相关系数为0.530,地块规模大小对收入影响较为明显,存在规模经济。槽坝、低山地貌条件下劳均纯收入与劳均土地面积的相关系数为0.205、0.147,这说明适当扩大劳均土地面积可增加劳均纯收入。丘陵区因样本数较少,劳均土地面积对劳均纯收入的影响不显著。不同地貌类型下劳均土地面积与劳均纯收入的相关程度均较弱,但相关系数均为正,这说明劳均土地面积的扩大能带动劳均纯收入的增加。根据以上分析,农户在考虑土地规模大小时可依据地块所属地貌合理调整土地面积,在中山区可适宜增加土地面积,在槽坝、低山、丘陵区不宜过度扩张,尤其是丘陵区增加地块面积,长期平均成本会呈递增状态。
Tab. 5 Correlation between income per worker and per capita cultivated land area under relief types

表5 不同地貌类型下劳均收入与劳均土地面积间的相关性

参数 地貌类型
槽坝 低山 中山 丘陵
Pearson相关性 0.205** 0.147** 0.530** -0.021
显著性（单侧） 0.000 0.000 0.000 0.453
N 1983 1736 806 36

注：**表示通过1%的显著性水平检验

通常情况下,地貌对山区的适度规模经营是有较大影响的,而回归的相关系数极低,这与目前的研究发现有一定出入。分析发现,样本村虽属典型山区,但供当地居民使用的水田主要分布在槽坝区、旱坡地基本位于低山区,致使耕作地块分布的微地貌以槽坝、低山为主,进而使得在此地貌条件下,劳均纯收入与劳均土地面积体现出正向的弱相关性。尽管如此,样本村拥有显著的立体气候,可通过发展特色农业来提高收入,如烤烟、经果林、蔬菜等,而且,目前山区普遍采取的人地关系优化措施“人下山,产业上山”更为通过规模经营来提高收入提供可能。
Tab. 6 Correlation between income per worker and per capita cultivated land area under different crop categories

表6 不同作物类别下劳均收入与劳均土地面积间的相关性

参数 作物类别
经济作物 粮食作物 所有作物
Pearson相关性 0.729** 0.727** 0.739**
显著性（单侧） 0.000 0.000 0.000
N 159 156 315

注：**表示通过1%的显著性水平检验

（2）作物类别相关性
不同作物类型所具有的商品价值差异较大,以经济作物与粮食作物分类作Pearson相关性分析。由表6可知,3种分类情况下劳均纯收入与劳均土地面积均高度显著相关。经济作物、粮食作物和所有作物的相关系数分别为0.729、0.727、0.739,属强相关。伴随劳均土地规模的扩大,劳均纯收入趋于递增,扩大土地规模能有效提高农户收入。3种分类状态下相关度均较高,可通过建模进一步研究最佳的劳均土地规模,探究适度经营规模大小的问题。
Tab. 7 Correlation between income per worker and per capita cultivated land area under different tillage distances

表7 不同地块分布半径下劳均收入与劳均土地面积间的相关性

参数 分布半径
0~0.5 km 0.5 km~1 km 1 km以上
Pearson相关性 0.303** 0.232** 0.128*
显著性（单侧） 0.000 0.000 0.031
N 2556 799 213

注：**和*分别表示通过1%和5%的显著性水平检验

（3）距离分类相关性
地块分布半径不同,农户的管理投入差异较大。对样本数据按地块分布半径分析劳均纯收入与劳均土地面积间的相关程度。由表7可知,1 km内的土地其劳均纯收入与劳均土地面积的相关度在0.01水平下显著,0~0.5 km的相关系数为0.303,0.5~1 km的相关系数为0.232,相关系数差距不大。1 km外的土地显著性不高,劳均土地面积与劳均纯收入的相关程度较弱。目前样本村农业生产主要依靠人力,大量分布半径较远的土地被闲置或撂荒,因样本量有限而无法通过检验。1 km内的土地适度增加规模,土地收益呈缓慢递增状态。农户在进行规模化种植时,最好选择半径在1 km内的地块。据生产要素的不可分性,土地过于分散化会增加破碎、分散土地的投入成本,地块分布半径较远不利于管理,在推行适度规模经营时尽可能的选择距离农户居住地在1 km内的土地。

3.3 模型检验与参数估计

根据样本分类,结合以上分析结果,以作物分类、距离分类予以建模分析,利用SPSS 18.0对调查获得的480份有效样本数据进行曲线估计,分别算出参数a、b估计值。
（1）作物类别建模
由表8可知,经济作物为主样本村建立模型,检验F值为77.210,显著性结果小于0.01,a、b参数估计值分别为-27.571、1341.622,均通过显著性检验,模型拟合效果较好,建立回归方程（2）。
Y = - 27.571 X 2 + 1341.622 X - 3.315 （2）
Tab. 8 Model aggregation and parameter estimation of economic crops

表8 经济作物模型汇总和参数估计值

方程 模型汇总 参数估计值
R2 F df1 df2 Sig 常数 a b
二次 0.399 77.210 2 233 0.000 -3.315 -27.571 1341.622

注：劳均纯收入为因变量,劳均土地面积为自变量。

由（2）式可看出,劳均纯收入与劳均土地面积二次方呈负相关、与劳均土地面积呈正相关,说明回归模型的二阶偏导为负,故其一阶偏导为零的劳均土地面积即为适度规模经营面积。
表9可知,粮食作物为主样本村建立模型,检验Sig值明显小于0.05,模型通过显著性检验。a、b参数估计值分别为-22.753、1120.700,回归系数具有显著性,建立回归方程（3）。
Tab. 9 Model aggregation and parameter estimation of grain crops

表9 粮食作物模型汇总和参数估计值

方程 模型汇总 参数估计值
R2 F df1 df2 Sig 常数 a b
二次 0.671 93.736 2 92 0.000 -463.006 -22.753 1120.700

注：劳均纯收入为因变量,劳均土地面积为自变量。

Y = - 22.753 X 2 + 1120.7 X - 463.006 （3）
在以粮食作物为主要收入来源的样本村中,劳均纯收入与劳均土地面积二次方同样呈负相关、与劳均土地面积呈正相关。与经济作物模型相比,增加单位土地面积所带来的纯收入相对较小。粮食需求与供给缺乏弹性,粮食作物的商品化程度、市场竞争力较经济作物低,其商品价值相应较低。尽管国家安全层面对粮食实行保护价制度,但经济作物是农户收入的主要来源,且生产的集约化、商品化程度高,综合利用潜力大,在进行规模生产时往往投入较高的生产要素。
（2）距离分类建模
从成本投入角度看,地块分布半径影响农户对土地的投入,分布半径对适度规模有一定影响。由表10、表11可知,2种分类状态下Sig值均通过显著性检验。当地块分布半径为0~0.5 km时,a、b参数估计值分别为-22.517、1289.044,均通过t值检验,建立回归方程（4）。当分布半径为0.5~1 km时,回归系数通过显著性检验,a、b参数估计值分别为-18.149、1155.422,建立回归方程（5）。
Y = - 22.517 X 2 + 1289.044 X - 708.752 （4）
Y = - 18.149 X 2 + 1155.422 X - 418.570 （5）
Tab. 10 Model aggregation and parameter estimation of 0-0.5 km tillage distance

表10 0~0.5 km分布半径模型汇总和参数估计值

方程 模型汇总 参数估计值
R2 F df1 df2 Sig 常数 a b
二次 0.097 136.409 2 2551 0.000 -708.752 -22.517 1289.044

注：劳均纯收入为因变量,劳均土地面积为自变量。

Tab. 11 Model aggregation and parameter estimation of 0.5-1 km tillage distance

表11 0.5~1 km分布半径模型汇总和参数估计值

方程 模型汇总 参数估计值
R2 F df1 df2 Sig 常数 a b
二次 0.104 137.859 2 2365 0.000 -418.570 -18.149 1155.422

注：劳均纯收入为因变量,劳均土地面积为自变量。

（3）整体建模
由表12可知,因数据来源为实地调研资料,样本点数据差异明显,R2较低,模型检验F值为207.111通过显著性检验,Sig值均明显小于0.05,拒绝了原假设,回归模型有效。根据表12,a、b参数估计值分别为-20.302、1213.360,均通过t检验,建立回归方程（6）。劳均纯收入与劳均土地面积的二次方呈负相关,与劳均土地面积一次方呈正相关,表明劳均纯收入与劳均土地面积之间存在适度规模,这说明用样本村劳均纯收入与劳均土地面积指标可进行适度规模的测算。
Tab. 12 Model aggregation and parameter estimation for all sample village data

表12 所有样本村数据模型汇总和参数估计值

方程 模型汇总 参数估计值
R2 F df1 df2 Sig 常数 a b
二次 0.465 207.111 2 477 0.000 -37.172 -20.302 1213.360

注：劳均纯收入为因变量,劳均土地面积为自变量。

Y = - 20.302 X 2 + 1213.360 X - 37.172 （6）

3.4 模型运行结果与分析

据倒U曲线理论,对模型一阶偏导,计算劳均纯收入最大时单位劳动力应经营的土地面积,再对模型二阶偏导验证是否为最优规模点。首先,由方程（2）可知,种植经济作物条件下,当劳均纯收入最大时土地最优规模为24.33亩。对模型二次偏导结果小于0,证明此最优土地规模是有效的。进一步分析,当农户土地经营规模达到最优规模24.33亩时,所带来的劳均纯收入最大,为16320元。同理,对方程（3）计算可得,种植粮食作物时最优土地规模面积为24.63亩,最大劳均纯收入为12682元。在纯收入方面,同等条件下经济作物能带来更好的收益,未来经济作物会以较小的土地投入获得较高的报酬,从而促使其种植面积和投入的增加,粮食作物则相反。
距离分类建模来看,对方程（4）偏导得出劳均纯收入最大时劳均土地面积为28.62亩,适度劳均纯收入为18911元。对方程（5）求一阶偏导发现最优劳均土地面积为31.83亩,最优劳均纯收入为18389元。分布半径越大,需要的农机投入越多。考虑到农户日常生产生活的便捷性,分布半径不宜过大。地块集中,扩大规模可分担单位面积投入成本,长远看有利于促使边际成本递减,当规模达到长期平均成本最低点时不宜继续扩大。然而,当分布半径小的土地面积有限时,要扩大地块面积,实现规模化经营,获得规模收益,需实施承包经营权的流转,整合相对分散的土地资源。
从所有样本数据看,对方程（6）一阶偏导得出最优劳均纯收入下土地经营规模为29.88亩,适度规模劳均纯收入为18129元。目前样本村人均纯收入为8332元,城镇居民人均可支配收入为25216元。以作物分类或以距离分类建模,计算出适度规模下劳均纯收入均远高于目前样本村人均纯收入,且与城镇居民的收入差距在显著缩小。进一步分析,重庆属亚热带季风气候,农作物一年两熟或三熟,每年两季轮作获得的收入远高于进城务工。若推行适度规模经营,可获得高于目前务农者的收入,缩小务农收入与城镇非农生产收入的差距。为此,模型运行结果是可行的。
综上,在考量农户土地适度经营规模时,应结合收入、地貌、距离、作物类型等因素,制定弹性规模区间。以经济作物为主测算的劳均土地适度规模为24.33亩,以粮食作物为主时为24.63亩,综合建模时为29.88亩。在以距离分类建模时,0.5 km内的适度土地规模为28.62亩,0.5~1 km内为31.83亩。土地经营规模的适度值随时间推移和条件变化是动态的,在新型城镇化和工业化背景下,样本村农业劳动力定会持续“析出”,农业现代化的发展对土地利用的集约度逐渐加强,劳动力投入比例逐渐降低,资金、机械、科技等要素投入逐渐增加。样本村达到劳动力工作满负荷时土地适度经营规模的弹性区间为24~32亩。本文样本村地貌属典型山区,地势起伏频繁,王国敏[18]提出山区农业土地适度规模应在25~35亩之间,这说明本文研究结论具有可行性。当规模小于24亩时,此阶段属规模报酬递增阶段;当规模大于32亩时属规模报酬递减阶段;当规模处于24~32亩时是适度的土地经营规模,此时专业务农劳动者的收入与城镇居民收入相当。

4 结论

（1）在现有社会经济条件下,样本村农业土地适度规模经营面积为24亩~32亩,适度规模下劳均纯收入远高于当前农村人均纯收入,且与城镇居民人均可支配收入的差距明显缩小。
（2）作物类型对适度规模影响不大,但对农民纯收入产生较大影响。经济作物和粮食作物的适度规模分别为24.33亩、24.63亩,差异不显著。但是,不同作物类型带来的劳均纯收入却表现出较大差异,种植经济作物和粮食作物在适度规模下带来的劳均纯收入分别为16320元、12682元,相差3638元,从而促使经济作物种植规模不断扩大,粮食作物种植规模萎缩。
（3）地块分布半径对土地适度规模影响较大,但对劳均纯收入作用不显著。0.5 km内、0.5~1 km的适度规模分别为28.62亩、31.83亩,单位劳动力适度经营规模相差3亩,这表明分布半径是目前从事农业生产时劳动力投入要考虑的重要因素。但对应的劳均纯收入分别为18911元、18389元,相差较小,这又说明伴随耕作半径的增加,更多的投入主要依靠机械完成,从而带动适度规模的扩大。但因目前未实现规模经营,单位土地分摊的机械成本较高,故劳均纯收入差距不大。1 km外的土地建模未通过统计检验,进一步说明没有进行机械化耕作,离家远的土地收支严重不平衡,撂荒严重,因此规模化经营,机械化耕作,是解决分布半径问题的有效途径。
以投入农业的劳动力为测算单位,以劳均纯收入为评价指标,本文得出的土地适度规模是可行的,存在土地规模经济。样本村为典型山区,在耕地规模经营受到地形条件限制的作用下,通常要经营20多亩土地,如果没有机械化水平的保驾,难度是非常大,致使目前样本村耕作实际离适度规模仍有较大差距,如从样本村的农户调查看,即便在槽坝地区,受微地貌和土地使用政策的影响,农户的耕地仍较分散、零碎,尚没有达到上述适度规模的农户（因人均土地较少,现户均经营规模4.27亩）。但是,样本村逐渐开展的土地整治、设施配套等为改善耕作条件提供外在动力,土地流转的开启为耕地资源整合提供政策优势,农机补贴为微耕机的普及和机械替代人力提供较大可能,现存大量坡地或零碎地的撂荒为耕地规模的提升提供较大空间,这些都为农户的耕作达到适度规模提供可能。而且,本文所计算的劳动力是实际投入农业生产的劳动力,一个劳动力完全投入农业生产完全能耕作20多亩土地。但是,如何确定规模大小,须考察生产力要素层次和农业经营方式的特殊性,以及地形、产业结构、农户意愿、市场需求等影响因素。本文研究结论验证了推进土地适度规模经营的可行性和必要性,为政府制定农村土地经营政策提供科学参考。

The authors have declared that no competing interests exist.

References

Publishing order | Descend order by publishing year | Descend order by cited within
[1]
姜松, 曹峥林, 刘晗. 农业社会化服务对土地适度规模经营影响及比较研究: 基于CHIP微观数据的实证. 农业技术经济, 2016, (11): 4-13 .

[Jiang Song, Cao Zhenglin, Liu Han.The impact of agricultural social services on moderate scale management of land and comparative study: An empirical study based on CHIP micro data. Journal of Agrotechonical Economics, 2016, (11): 11-14.]

[2]
王微恒, 朱会义. 中国省域农户土地经营规模与地区专业化实证分析. 地理学报, 2017, 72(2): 269-278 .中国农地利用的地区专业化水平明显落后于西方发达国家,对其农产品国际竞争力产生了重要影响.农户土地经营规模不足被认为是造成这一现象的主要原因.但是这种观念主要来自于定性分析和经验总结,缺乏针对两者关系的实证检验.本文采用赫芬达尔专业化指数,利用农作物种植面积数据和农户土地经营规模数据,在省域尺度上检验农户土地经营规模与地区专业化的关系.结果显示,扩大农户土地经营规模既不是地区专业化的充分条件也不是必要条件.空间维度上,规模越大的地区,其专业化水平并非越高,各年份两变量的秩相关系数均很小;时间维度上,随着规模的上升(或下降),其专业化水平不一定随之上升(或下降),29个省域样本中仅有12个省区两变量的时间序列呈显著正相关.农户土地经营规模仅对部分地区的专业化水平有一定影响且与区域优势作物类型有关.结果表明,仅依靠扩大农户土地经营规模,并不能有效提高地区专业化水平,要提高中国农地利用专业化水平必须寻找其他有效途径.

DOI

[Wang Weiheng, Zhu Huiyi.Household farmland area and regional specialization: An empirical analysis at provincial level. Acta Geographica Sinica, 2017, 72(2): 269-278.]

[3]
Nigussie Z, Tsunekawa A, Haregeweyn N, et al.Factors influencing small-scale farmers' adoption of sustainable land management technologies in north-western Ethiopia. Land Use Policy, 2017, 67: 57-64.

[4]
Shao Jing'an, Zhang Shichao, Li Xiubin. Farmland marginalization in the mountainous areas: Characteristics, influencing factors and policy implications. Journal of Geographical Sciences, 2015, 25(6): 701-722.lt;p>Based on SPOT-5 images, 1:1 million topographic maps, the maps of the returning farmland to forest project and the Chongqing forest project, social and economic statistics, etc., this paper identifies the features and factors influencing farmland marginalization. The results showed: (1) During 2002-2012, the rate of farmland marginalization was 16.18%, which was mainly found in the high areas of northern Qiyao mountains and the medium-altitude areas of southern Qiyao mountains. And this farmland marginalization will increase, associated with non-agriculturalization of rural labourers and aging of the remaining labourers. (2) Elevation, distance radius from villages and road connections had a great influence on farmland marginalization. Farmland marginalization rates showed an increasing trend with the increase of elevation, and 60.88% of the total farmland marginalization area is found at an altitude greater than 1000 m above sea level. The marginalization trend also increases with slope and distance from the distribution network. (3) Farmland area per labourer and the average age of farm labourers were major factors driving farmland marginalization. Farmland transfer and small agricultural machinery sets affect farmland marginalization with respect to management and productivity efficiency. (4) Farmland with “comparative- disadvantage-dominated marginalization” accounted for 55.32% of the total farmland marginalization area, followed by “location-dominated marginalization” (33.80%). (5) According to the specifics of each real situation, different policies are suggested to mitigate the marginalization. A “continuous marginalization” policy will encourage the return of farmland to forest in “terrain-dominated marginalization”. An “anti-marginalization” policy is suggested to create new rural accommodation and improve the rural road system to counteract “terrain-dominated marginalization”. And another “anti-marginalization” policy is planned to improve management and micro-mechanization for “comparative-disadvantage-dominated marginalization”. A new idea was developed to integrate high resolution remote sensing and statistical data with survey information to identify land marginalization and its driving forces in mountainous areas.</p>

DOI

[5]
项晓敏, 金晓斌, 杜心栋, 等. 基于“强度—潜力—难度”综合测度的中国农用地整治实施协调性分析. 地理研究, 2016, 35(2): 285-298 .农用地整治实施协调性分析可为土地整治的宏观决策与绩效评价提供参考。基于整治强度、整治潜力和整治难度等土地整治实施的核心指标,借助力学平衡模型和地理空间统计分析,综合评判2006-2012年中国农用地整治的实施协调性。结果表明:研究期间中国农用地整治协调度F合均值为1.33,核心要素的实施匹配总体上处于拮抗状态,各实施协调度类型在数量占比上无明显差别,实施重点尚不突出;实施偏度θ以过渡型象限(II、V)居多,在协同特征上总体表现为区域农用地整治的强度和潜力间的不匹配;在空间格局上,实施协调度呈显著集聚和空间正相关性,农用地整治实施亟待优化的6类问题区域主要集中在陕甘宁、川渝等西北地区以及长三角、珠三角等地。

DOI

[Xiang Xiaomin, Jin Xiaobin, Du Xindong, et al.The coordination of agricultural land implementation in China by comprehensive measure of "intensity, potential and difficulty". Geographical Research, 2016, 35(2): 285-298.]

[6]
Takoutsing B, Martín J A R, Weber J C, et al. Landscape approach to assess key soil functional properties in the highlands of cameroon: Repercussions of spatial relationships for land management interventions. Journal of Geochemical Exploration, 2017, 178: 35-44.

[7]
Tang Xiumei, Pan Yuchun, Liu Yu.Analysis and demonstration of investment implementation model and paths for China's cultivated land consolidation. Applied Geography, 2017, 82: 24-34.

[8]
邵景安, 张仕超, 李秀彬. 山区土地流转对缓解耕地撂荒的作用. 地理学报, 2015, 70(4): 636-649 .Farmland abandonment is a type of land use change in the mountainous areas, and this change is under rapid development. Whether farmland transfer can prevent this process or not and promote the effective allocation of land resources is a question worth studying and discussing. With the help of the previous research findings, the objective of this paper was to find out the role of farmland transfer on mitigating farmland abandonment, by using the multiple view methods with two factors, and single factor correlation analysis. The results showed that: (1) At village level, there was a significant negative correlation between farmland transfer and farmland abandonment, especially for the farmland with high grade farming conditions, which indicated that farmland transfer could prevent the abandonment of farmland with high grade farming conditions. (2) At plot level, the abandonment rate of farmland with high grade farming conditions was significantly lower than that with poor grade farming conditions. Abandoned farmland was mainly the grade farming conditions in the study site. (3) At village level, the role of farming conditions on farmland abandonment was insignificant. The farming condition to the difference of farmland abandonment rate at village level was not obvious. The abandonment of farmland with high farming conditions still existed, which illustrated that farmland transfer, as one of the land rental markets, was still not developed. (4) However, for the villages with higher rate of farmland transfer, there was lower abandonment rate for those high grade farming conditions, which incicated that farmland abandonment was still controlled by the improvement of land rental market. Furthermore, the function of land rental market played an important role in optimizing the utilization of farmland resources. (5) To further improve the marketing degree of land rent, the probability of farmland abandonment could be reduced. Especially, their function to farmland with high grade farming conditions was very obvious, and could avoid the waste of farmland resources with high grade farming conditions.

DOI

[Shao Jing'an, Zhang Shichao, Li Xiubin. The role of rural farmland transfer in preventing farmland abandonment in the mountainous areas. Acta Geographica Sinica, 2015, 70(4): 636-649.]

[9]
梁流涛, 翟彬, 樊鹏飞. 基于环境因素约束的农户土地利用效率及影响因素分析: 以河南省粮食生产核心区为例. 地理科学, 2016, 36(10): 1522-1530 .

[Liang Liutao, Zhai Bin, Fan Pengfei.Household land use efficiency based on environment factor and its influence factors: A case of grain production core areas in Henan province. Scientia Geographica Sinica, 2016, 36(10): 1522-1530.]

[10]
何艳冰, 黄晓军, 杨新军. 快速城市化背景下城市边缘区失地农民适应性研究: 以西安市为例. 地理研究, 2017, 36(2): 226-240 .全球变化背景下的适应性研究是当前地学领域关注的焦点议题,为可持续发展研究提供了新的视角.将适应性分析框架应用到城市边缘区失地农民研究中,基于失地农民适应性内涵,从认知能力、缓冲能力、学习能力、转型能力和管理能力五方面构建适应能力评价指标体系,以西安城市边缘区为案例,通过实地调研、问卷调查与深度访谈获取数据,在对失地农民适应模式进行分类的基础上,采用熵权TOPSIS法评价不同类型失地农民的适应能力,辨识制约失地农民适应能力提升的障碍因素.结果表明:①失地农民的适应模式分为短期雇工型、租金主导型、自主创业型、工资保障型和社保依赖型五种类型;②不同类型失地农民适应能力的评价结果依次为自主创业型＞租金主导型＞工资保障型＞短期雇工型＞社保依赖型;③不同类型失地农民适应能力的障碍因素呈趋同态势,其中职业技能培训、收入多样性指数、社会保障满意度、职业稳定程度和政府帮扶程度是主要障碍因子.最后,提出失地农民适应性管理对策建议及未来需进一步关注的问题.

DOI

[He Yanbing, Huang Xiaojun, Yang Xinjun.Adaptation of land-lost farmers to rapid urbanization in urban fringe: A case study of Xi'an. Geographical Research, 2017, 36(2): 226-240.]

[11]
Guo Shan, Shen Qiping Geoffrey, Chen Zhan-Ming, et al.Embodied cultivated land use in China 1987-2007. Ecological Indicators, 2014, 47: 198-209.The recent trend of rapid urbanization draws more and more concerns on the land use pattern in China. This study employs an ecological input–output model to reveal the impact of domestic consumption and international trade on cultivated land distributions in China during 1987–2007. According to the high-sectoral-resolution dataset, Agriculture and Food Processing are identified as the two key sectors which contribute the largest volumes of embodied cultivated land to meet household food demand in 2007. The indicators of production- and consumption-based cultivated land are highly correlated during the research period: both experience a phase of stability during 1987–1995, then a boom from 1995 to 1997, and a steady decrease afterward. Although the total cultivated land use in China is fluctuating, the embodied intensity shows a declining trend from 7.12ha/thousand Yuan in 1987 to 0.43ha/thousand Yuan in 2007, with an annual decrease rate of 13.09%. With respect to trade pattern, the Agriculture sector is China's largest net importer of cultivated land, in contrast to the Textile sector as the largest net exporter. When China is shown to be a net embodied cultivated land exporter throughout the concerned years, the variation of embodied cultivated land balance is closely related to the country's international trade pattern.

DOI

[12]
King L, Adusei B, Stehman S V, et al.A multi-resolution approach to national-scale cultivated area estimation of soybean. Remote Sensing of Environment, 2017, 195: 13-29.Satellite remote sensing data can provide timely, accurate, and objective information on cultivated area by crop type and, in turn, facilitate accurate estimates of crop production. Here, we present a generic multi-resolution approach to sample-based crop type area estimation at the national level using soybean as an example crop type. Historical MODIS (MODerate resolution Imaging Spectroradiometer) data were used to stratify growing regions into subsets of low, medium and high soybean cover. A stratified random sample of 20km-20km sample blocks was selected and Landsat data for these sample blocks classified into soybean cover. The Landsat-derived soybean area was used to produce national estimates of soybean area. Current year MODIS-indicated soybean cover served as an auxiliary variable in a stratified regression estimator procedure. To evaluate the approach, we prototyped the method in the USA, where the 2013 USDA Cropland Data Layer (CDL) was used as a reference training data set for mapping soybean cover within each sample block. Three individual Landsat images were sufficient to accurately map soybean cover for all blocks, revealing that a rather sparse sample of phenological variation is needed to separate soybean from other cover types. In addition to stacks of images, we also evaluated standard radiometrically normalized Landsat inputs for mapping blocks individually (local-scale) and all at once (national-scale). All tested inputs resulted in area estimates comparable to the official USDA estimate of 30.86Mha, with lower accuracy and higher standard error for national-scale mapping implementations. The stratified regression estimator incorporating current year MODIS-indicated soy reduced the standard error of the estimated soybean area by over 25% relative to the standard error of the stratified estimator. Finally, the method was ported to Argentina. A stratified random sample of blocks was characterized for soybean cultivated area using stacks of individual Landsat images for the 2013-2014 southern hemisphere growing season. A sub-sample of these blocks was visited on the ground to assess the accuracy of the Landsat-derived soy classification. The stratified regression estimator procedure performed similarly to the US application as it resulted in a reduction in standard error of about 25% relative to the stratified estimator not incorporating current year MODIS-indicated soybean. Our final estimated soybean area was 28% lower than that reported by the USDA, corresponding to a 20% field-based omission error related to underdeveloped fields. Lessons learned from this study can be ported to other regions of comparable field size and management intensity to assess soybean cultivated area. Results for the USA and Argentina may be viewed and downloaded at http://glad.geog.umd.edu/us-analysis and http://glad.geog.umd.edu/argentina-analysis , respectively.

DOI

[13]
李广东, 邱道持, 王利平, 等. 生计资产差异对农户耕地保护补偿模式选择的影响: 渝西方山丘陵不同地带样点村的实证分析. 地理学报, 2012, 67(4): 504-515 .Economic compensation plays a crucial role in promoting farmland protection and raising farmland utilization ratio. Farmer households' willingness is one of the most important factors that determines the economic compensation pattern for farmland protection, and their difference in livelihood assets has influence on pattern choice of economic compensation for farmland protection significantly. Through participatory rural appraisal method, three villages and 392 households were investigated and sampled in Tabular mountainous and hilly areas of western Chongqing City. A quantitative analysis framework of household livelihood assets of hexagon is constructed; through Gray relation analysis model and Probit regression analysis, the existence and influencing degree of coupling relationship between the divergence of farmer household livelihood assets and compensation pattern choice were analyzed. Furthermore, differential patterns of economic compensation for farmland protection were designed. The results are shown as follows. (1) There exist different qualities and spatial heterogeneity in household livelihood assets. We can find a general trend that the total assets transfer from pure self-sufficiency households to off-farm households, and a spatial trend that the higher the altitude, the less household livelihood assets. (2) There is a trend that household choice willingness about compensation pattern varies from Chengdu Pattern to Foshan Pattern, and there exists spatial heterogeneity in their choice willingness in different areas. (3) The coupling relationship exists between household livelihood assets and compensation pattern. Negative correlation is observed between natural assets value and household pattern choice and the other livelihood assets have different positive impacts on compensation pattern, which from the top are psychological assets, human assets and physical assets, financial assets, and social assets. (4) Based on seven types of the lack of household livelihood assets, the paper designs a conceptual compensation pattern system. Moreover, compensation method, compensation basis, compensation standard and the source of compensation funds are discussed.

DOI

[Li Guangdong, Qiu Daochi, Wang Liping, et al.Impacts of difference among livelihood assets on the choice of economic compensation pattern for farmer households farmland protection in Chongqing city. Acta Geographica Sinica, 2012, 67(4): 504-515.]

[14]
黄新建, 姜睿清, 付传明. 以家庭农场为主体的土地适度规模经营研究. 求实, 2013, (6): 94-96 .家庭农场是我国未来重点培育的农业经营主体。根据家庭农场的内涵并以江西水稻种植为例进行分析,家庭农场的土地适度规模为70-150亩。要达到这样的适度规模,存在农业基础设施投入不足、农民工看重土地的社会保障功能、农村人力资源匮乏、农业保险保障水平低等制约因素。推进新型城镇化建设、做好农民承包权流转服务、提高财政补贴对农业保险的支持力度等措施将有效促进家庭农场的适度规模经营。

DOI

[Huang Xinjian, Jang Ruoqing, Fu Chuanming.Study on the proper scale management of land with family farm as the main part. Truth Seeking, 2013, (6): 94-96.]

[15]
齐城. 农村劳动力转移与土地适度规模经营实证分析: 以河南省信阳市为例. 农业经济问题, 2008, (4): 40-43 .本文以研究农村劳动力转移与土地适度规模经营为基本任务,选择河南省信阳市为抽样调查对象,通过建立模型,对当前生产力条件下的农户适度经营规模作了定量分析,据此推算出农村劳动力转移率,并对推进土地适度规模经营提出了政策建议。

DOI

[Qi Cheng.Empirical analysis of rural labor transfer and moderate scale operation of land: A case of Xinyang city of Henan province. Issues in Agricultural Economy, 2008, (4): 40-43.]

[16]
张成玉. 土地经营适度规模的确定研究: 以河南省为例. 农业经济问题, 2015, (11): 57-63 .

[Zhang Chengyu.Study on the determination of appropriate scale of land management: A case Henan province. Issues in Agricultural Economy, 2015, (11): 57-63.]

[17]
阚酉浔, 周春芳. 农户农地经营适度规模的测度研究: 以武汉市江夏区为例. 华中农业大学学报: 社会科学版, 2013, (3): 67-70 .Appropriate scale of land operation is the important method to improve modern agricultural productivity and agricultural competitiveness.Furthermore,moderate scale of agricultural land operation can increase per unit area yield as well as households’ income.This paper makes a thorough study on optimum-scale agricultural land operation and analyzes 163 rural households in Jiang-xia district of Wuhan by establishing quadratic regression model.The result shows that the optimum-scale of agricultural land is 1.27 hm2 when the per capita net income of rural household achieves maximum level.17

DOI

[Kan Youxun, Zhou Chunfang.Estimation of moderate scale of rural households' agricultural land operatio: A case study in Jiangxia district of Wuhan. Journal of Huazhong Agricultural University: Social Sciences Edition, 2013, (3): 67-70.]

[18]
王国敏, 唐虹. 山地丘陵区农地适度规模经营的有效性及其限度: 对适度规模经营危害论的一个批判. 社会科学研究, 2014, (6): 16-23 .

[Wang Guomin, Tang Hong.Effectiveness and limits of moderate scale management of Agricultural land in mountain and hilly area: A critique of the harm of moderate scale management. Social Science Research, 2014, (6): 16-23.]

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