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Frontiers of Earth Science

Front. Earth Sci.    2015, Vol. 9 Issue (2) : 308-318     DOI: 10.1007/s11707-014-0471-6
RESEARCH ARTICLE |
Agricultural land use intensity and its determinants: A case study in Taibus Banner, Inner Mongolia, China
Haiguang HAO1,2,*(),Xiubin LI2,Minghong TAN2,Jiping ZHANG3,Huiyuan ZHANG1
1. Chinese Research Academy of Environmental Sciences, Beijing 100012, China
2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
3. Beijing Municipal Research Institute of Environmental Protection, Beijing 100037, China
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Abstract

Based on rural household survey data from Taibus Banner, in the Inner Mongolia Autonomous Region, China, this study separately categorizes agricultural land use intensity into labor intensity, capital intensity, the intensity of labor-saving inputs, and the intensity of yield-increasing inputs, and then analyzes their determinants at the household level. The findings reveal that within the study area: (1) labor intensity is higher and capital intensity is lower than in the major grain-producing and economically developed areas of eastern and central China; (2) the most widely planted crops are those with the lowest labor intensity (oats) and capital intensity (benne); (3) there are marked differences in agricultural land use intensity among households; a major factor affecting land use decision-making is the reduced need for labor intensity for those households with high opportunity costs, such as those with income earned from non-farming activities which alleviates financial constraints and allows for increased capital intensity. As a result, these households invest more in labor-saving inputs; (4) households with a larger number of workers will allocate adequate time to manage their land and thus they will not necessarily invest more in labor-saving inputs. Those households with more land to manage tend to adopt an extensive cultivation strategy. Total income has a positive impact on capital intensity and a negative impact on labor intensity. Households that derive a higher proportion of their total income through farming are more reliant upon agriculture, which necessitates significant labor and yield-increasing inputs. Finally, the authors contend that policy makers should clearly recognize the impacts of non-farming employment on agricultural land use intensity. In order to ensure long-term food security and sustainable agricultural development in China, income streams from both farming and non-farming employment should be balanced.

Keywords agricultural land use intensity      labor intensity      capital intensity      opportunity cost of farm workers      Taibus Banner     
Corresponding Authors: Haiguang HAO   
Online First Date: 17 November 2014    Issue Date: 30 April 2015
 Cite this article:   
Haiguang HAO,Xiubin LI,Minghong TAN, et al. Agricultural land use intensity and its determinants: A case study in Taibus Banner, Inner Mongolia, China[J]. Front. Earth Sci., 2015, 9(2): 308-318.
 URL:  
http://journal.hep.com.cn/fesci/EN/10.1007/s11707-014-0471-6
http://journal.hep.com.cn/fesci/EN/Y2015/V9/I2/308
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Haiguang HAO
Xiubin LI
Minghong TAN
Jiping ZHANG
Huiyuan ZHANG
Fig.1  Location of Taibus Banner and of the villages sampled in the survey
Labor intensityWheatOatsBennePotatoes
Mean108.15?99.00?87.15108.45134.25
Maximum150.90136.80131.10152.25160.80
Minimum?57.45?57.45?57.45?61.65?80.85
Tab.1  Descriptive statistics for agricultural land use labor intensity (day/ha)
Unstandardized coefficientsStandardized coefficientstSig.
BStd. errorbeta
Constant0.447?0.057???7.7810.000
X30.023?0.007???0.300????3.5370.001
X4-0.002?0.000-0.669-11.4790.000
X5-0.063?0.036-0.129?-4.5750.000
X6??-8.584E-050.000-0.236?-3.2660.001
X70.043?0.021???0.151????3.0500.002
Tab.2  Estimated parameters of the stepwise regression model for agricultural land use labor intensity
Capital intensityIntensity of labor-saving inputsIntensity of yield-increasing inputsOatsBenneWheatPotatoes
Mean1,404.45???607.95???796.501,137.45723.451,039.353,417.15
Maximum3,450.001,125.002,025.001,440.00960.001,305.004,200.00
Minimum???780.00???120.00???420.00???945.00495.00???975.002,850.00
Tab.3  Descriptive statistics for agricultural land use capital intensity (CNY/ha)
Unstandardized coefficientsStandardized coefficientstSig.
BStd. errorbeta
Constant??4.1510.205?20.2300.000
X2??0.5530.127??0.308??4.3420.000
X3-0.4360.084-0.552-5.1570.000
X4-0.2260.063-0.290-3.5590.000
X5??0.0430.004??0.609?10.3050.000
X65.728E-050.000??0.017??3.9730.000
Tab.4  Estimated parameters of the stepwise regression model for agricultural land use capital intensity
Unstandardized coefficientsStandardized coefficientstSig.
BStd. errorbeta
Constant?20.3194.304??4.7210.000
X3-2.0840.967-0.232-2.1550.032
X5??0.0400.007??0.395??5.7600.000
X8-0.0360.015-0.138-2.4280.016
Tab.5  Estimated parameters of the stepwise regression model for the intensity of labor-saving inputs, and overall testing of the model
Unstandardized coefficientsStandardized coefficientstSig.
BStd. errorbeta
Constant??7.4702.687??2.7800.006
X1-0.1340.043-0.097-3.0920.002
X2??1.8380.831??0.163??2.2120.028
X4-0.0880.021-0.136-4.2270.000
X6???????2.825E-050.000??0.033??3.8240.000
X7??0.0640.050??0.095??2.4280.016
Tab.6  Estimated parameters of the stepwise regression model for the intensity of yield-increasing inputs, and overall testing of the model
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