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劳动力析出对生态脆弱区耕地撂荒的影响
  • 期刊名称:中国土地科学
  • 时间:0
  • 页码:4-9
  • 语言:中文
  • 分类:F275[经济管理—企业管理;经济管理—国民经济]
  • 作者机构:[1]中国科学院地理科学与资源研究所,北京100101, [2]中国科学院研究生院,北京100049
  • 相关基金:国家自然科学基金项目(40971062)
  • 相关项目:区域经济增长时空分异量化分析-以京津冀都市圈为例
中文摘要:

农户耕地利用决策分析是研究中国农地利用变化的一个重要视角,而农户的决策必然要考虑其劳动力的务农机会成本。本文以河南省睢县为例,利用农户调查数据,首先区分不同劳动力从业类型和非农从业情况,用不同劳动力类型的非农从业机会对非农工资进行修正,以此估算劳动力务农机会成本。在此基础上,重点分析不同劳动力机会成本水平下农户的耕地利用决策行为,揭示劳动力机会成本上升对区域耕地利用变化的影响。结果表明:劳动力机会成本较高的农户非农收入较高,对农业生产的依赖性较弱,一定程度上促进了耕地转出行为;在种植结构决策中,机会成本较高的农户更倾向于选择劳动生产率较高的粮食作物,土地利用类型趋于单一化;在集约度上,表现为伴随机会成本上升,劳动集约度迅速下降,资本集约度中增产性投入有所减少,省工性投入增加,农户通过增大机械投入来替代劳动力的现象明显;耕地利用中增产性投入的减少在粮食生产中的表现为劳动力机会成本较高的农户粮食单产水平相对较低。

英文摘要:

Increasing labor opportunity cost has become one of the most important influencing factors for agricultural land use changes.Based on 328 household survey data in Suixian County,Henan Province,this paper analyzed the types of labor employment and non-agricultural work time and wages,and then calculated the labor opportunity cost by using different labor types’ chances of getting non-agricultural job as the correction factor to amend wages.It was found that labor opportunity cost significantly affected land use practices of rural households.Households with higher labor opportunity cost always have higher nonfarm income.They are less dependent on agricultural production and more likely to lease their cultivated land to other farmers.These farmers are also inclined to grow food crops which need less labor inputs but have higher labor productivity.This results in homogenization of regional land use structure in terms of crop types.As to land use intensity,along with the increase of labor opportunity cost,labor intensity and yield-increasing inputs in agriculture decrease rapidly,while labor-saving inputs show an increasing trend.The households with larger labor opportunity cost are willing to increase machinery inputs as a substitute for labor inputs.Because of the reduction of yield-increasing inputs,the households with larger labor opportunity cost have lower grain yield per unit area.

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