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Prediction for Soybean Comparative Advantage in Heilongjiang Province Based on Time Series Model(PDF)

《大豆科学》[ISSN:1000-9841/CN:23-1227/S]

Issue:
2013年01期
Page:
80-88
Research Field:
Publishing date:

Info

Title:
Prediction for Soybean Comparative Advantage in Heilongjiang Province Based on Time Series Model
Author(s):
MIAO SenZHENG Yu
College of Science,Northeast Forestry University,Harbin 150040,Heilongjiang,China
Keywords:
SoybeanTime series modelComparative advantagePrediction model
PACS:
F326.11
DOI:
10.3969/j.issn.1000-9841.2013.01.019
Abstract:
According to the principle of time series and cropcomparative advantage,taking the yield and planting area of soybean in Heilongjiang province form 1985 to 2010 as the research objects.We established the time series prediction model of the comprehensively comparative advantage of soybean in Heilongjiang province.The results illustrated that from 2012 to 2017 the comparative advantage for soybean production in Heilongjiang province were 1.873,1.7323,1.7592,1.6106 and 1.6383,respectively.This proved the soybean production in Heilongjiang province had an advantage over national level,but the advantage showed a decreasing trend.We suggest that relevant agricultural departments should pay enough attention about this trend.

References:

[1]樊敏,顾兆林.时间序列分析在大气环境中的应用[J].资源环境与发展,2010(1):19-22.(Fan M,Gu Z L.The application of time series analyze for atmosphere environment[J].Sources Environment and Development,2010(1):19-22.)

[2]尹昌斌,陈印军,毕于运.红黄壤地区粮食生产的区域比较优势测度[J].农业技术经济,1998(5):42-45.(Yin C B,Chen Y J,Bi Y Y.Comparative advantage measurement degree of food production in red and yellow area[J].Journal of Agrotechnical Economics,1995(5):42-45.)
[3]李庆华.计量经济学[M].北京:中国经济出版社,2005.(Li Q H.Econometrics[M].Beijing:China Economic Publishing House,2005.)
[4]白万平.经济时间序列模型:方法与应用[M].北京:中国商务出版社,2005.(Bai W P.Economic time series model:method and application[M].Beijing:China Commerce and Trade Press,2005.)
[5]卢二坡.我国能源需求预测模型研究[J].统计与决策,2005(10):29-31.(Lu E P.Research on national energy need prediction model[J].Statistics and Decision,2005(10):29-31.)

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Last Update: 2013-02-20