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基于向后逐步回归模型的我国农机需求特征及影响因素研究
引用本文:陈旭,杨印生,魏思琳.基于向后逐步回归模型的我国农机需求特征及影响因素研究[J].数理统计与管理,2017(5):774-782.
作者姓名:陈旭  杨印生  魏思琳
作者单位:1. 吉林大学生物与农业工程学院,吉林长春130022;吉林工程技术师范学院工商管理学院,吉林长春130000;2. 吉林大学生物与农业工程学院,吉林长春,130022
基金项目:高等学校博士学科点专项科研基金资助项目(20130061110043)
摘    要:以2004-2014年数据为样本,以农机总动力为因变量,以农机购置补贴、农机价格、农机作业服务价格、农户人均纯收入、农产品价格、农业劳动力数量和农作物播种总面积为自变量构建了我国农机需求影响因素的回归方程,向后逐步回归结果表明:(1)除农作物播种总面积、农机作业服务价格、农产品价格之外,其余变量对农机总动力的影响均统计上显著;(2)农机购置补贴、农机价格指数、农户人均纯收入及农业劳动力四个变量对农机需求的弹性系数分别为0.027、-0.004、0.457、0.474。最后根据研究结果提出加大与落实农机购置补贴、规范农机价格、培育新型经营主体、加速土地规范流转等政策建议。

关 键 词:农机需求  影响因素  农机总动力  向后逐步回归

A Study on Characteristics and Influencing Factors of Agricultural Machinery Demand in China Based on Backward Stepwise Regression Model
CHEN Xu,YANG Yin-sheng,WEI Si-lin.A Study on Characteristics and Influencing Factors of Agricultural Machinery Demand in China Based on Backward Stepwise Regression Model[J].Application of Statistics and Management,2017(5):774-782.
Authors:CHEN Xu  YANG Yin-sheng  WEI Si-lin
Abstract:Based on the data from 2004 to 2014,the regression equation of the factors affecting the demand of agricultural machinery was constructed with the total power of agricultural machinery as the dependent variable.The backward stepwise regression results show that:(1) In addition to total area sown to crops,agricultural service price,agricultural products prices,the rest of the variables have effect on the total power of agricultural machinery statistically significant;(2) The elasticity coefficients of farm machinery purchase subsidy,agricultural machinery price index,per capita net income of farmers and agricultural labor force to agricultural machinery demand respectively is 0.027,-0.004,0.457,0.474.Finally,according to the results of this study,we puts forward some policy suggestions such as enlarging and implementing the purchase subsidy of agricultural machinery,standardizing the price of agricultural machinery,cultivating new management subject and speeding up the transfer of land standard.
Keywords:agricultural machinery demand  influencing factors  total power of agricultural machinery  backward stepwise regression
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