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Prediction model of total farmland under the condition of unbalanced economic growth AgEcon
Chen, Xiao-yuan; Chen, Xiao-zhu; Zhang, Lei.
The aim of this paper is to discuss the prediction method of the total farmland demand combining with the land utilization status and planning practice. [Method] We use the multiple regression prediction method and time series prediction method. [Result] By applying the data of farmland comprehensive production capacity, population development, changes of arable land, fixed assets investment and so on in Bijie Area, we have established the prediction models of total farmland demand, and determined the optimum model as the prediction proposal of total farmland in Bijie Area through evaluation and explanation. [Conclusion] The prediction proposal is compared with the "shadow index" of Bijie Area, which is instructed by the macro-control of Guizhou Province....
Tipo: Thesis or Dissertation Palavras-chave: Total farmland; Shadow index; Unbalanced economy; China; Agricultural Finance; Financial Economics; Land Economics/Use; Research Methods/ Statistical Methods; Resource /Energy Economics and Policy.
Ano: 2009 URL: http://purl.umn.edu/53470
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Selection of Leading Industry in Anshun Experimental District Based on Analytic Hierarchy Process AgEcon
Lou, Zhao; Xu, Zhong; Zhang, Lei.
Analytic Hierarchy Process is selected according to the selection method of leading industries by both domestic and foreign scholars. Leading industries which can accelerate the overall economic development of Anshun Experimental District is taken as the target layer; and market demand, efficiency standards and local conditions are taken as the criterion layers, so as to construct the select model of leading industry and to choose the leading industry in Anshun Experimental District. Result shows that the priority order of the leading industry selection in Anshun Experimental District is as follows: tourism > pharmacy > transportation > energy > food processing > characteristic agriculture > package and printing > automobile industry >...
Tipo: Journal Article Palavras-chave: Anshun Experimental District; Leading industry; Analytic Hierarchy Process; China; Agribusiness.
Ano: 2011 URL: http://purl.umn.edu/108421
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