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Study on Price Fluctuation Characteristics,Prediction and Early Warning of Qi Chrysanthemum in Post Epidemic Era

《北方园艺》[ISSN:1001-0009/CN:23-1247/S]

Issue:
2022年11
Page:
135-14
Research Field:
Publishing date:

Info

Title:
Study on Price Fluctuation Characteristics,Prediction and Early Warning of Qi Chrysanthemum in Post Epidemic Era
Author(s):
XUE QinglinWEI ZikunHAN QiaoCUI YuanpeiWANG Jianzhong
(School of Economics and Management,Hebei Agricultural University,Baoding,Hebei 071000)
Keywords:
price of Qi chrysanthemumCOVID-19decomposition of price fluctuationprediction and early warning
PACS:
-
DOI:
10.11937/bfyy.20214445
Abstract:
Qi chrysanthemum,as novel coronavirus pneumonia ‘three drugs three parties’ main ingredient,fluctuated frequently in recent years.In order to explore the law of Qi chrysanthemum price fluctuation and promote the orderly and healthy development of Qi chrysanthemum industry,we selected monthly data of Qi chrysanthemum from July 2014 to November 2020,decomposed the price sequence of Qi chrysanthemum by X-12 seasonal adjustment method and H-P filtering method,and found out the contribution rate of different fluctuation components.Then with the help of ARIMA model and black early warning model,the price of Qi chrysanthemum was predicted and warned.The results showed that among the factors affecting price fluctuation,the trend factor was in the dominant position.Among the random factors,the contribution rate of periodic factor was the largest,which was 11.84%,and the contribution rate of seasonal factor and found factor was 3.96%.Subsequently,the price in the next 15 months was predicted.There was one negative heavy alarm and three negative light alarms,and the other index volatility were also negative,indicating that there was great downward pressure on Qi chrysanthemum price in the next 15 months.Finally,the countermeasures and suggestions to improve the degree of industrial integration,price monitoring and risk sharing are put forward.

References:

[1]常征宇,王树进.我国中药材价格波动影响因素的实证研究:基于因子分析和向量自回归模型[J].科技与经济,2015,28(5):101-105.[2]马宏阳,赵霞.中国小宗农产品价格波动特征的实证分析:以大蒜为例[J].农业技术经济,2021(6):33-48.[3]李苏,宝哲.我国猪肉价格波动特征及预测研究[J].价格理论与实践,2020(6):80-83,153.[4]卞靖,陈曦.中国蔬菜价格波动的特征、原因及调控思路研究[J].宏观经济研究,2020(4):142-152.[5]茅鸯对,常峰.基于GM(1,1)预测模型的中药材价格指数预测[J].中国药房,2014(23):2200-2202.[6]常峰,茅鸯对.基于ARIMA预测模型的中药材价格预警研究[J].中国中药杂志,2014(9):1721-1723.[7]李化.中药材价格传导研究[J].卫生经济研究,2015(10):58-61.[8]任长秋.中药材价格变动成因及影响[J].人民论坛,2011(1):142-143.[9]魏子鲲,韩乔,薛庆林,等.河北省中药材质量追溯体系浅析[J].合作经济与科技,2021(2):110-112.[10]张晋之,杨元娟,许燕.中药材价格波动的原因及优化策略[J].价格月刊,2016(2):35-38.[11]胡友,祁春节.基于HP滤波模型的农产品价格波动分析:以水果为例[J].华中农业大学学报(社会科学版),2014(4):57-61.[12]魏子鲲,韩乔,王亚荣,等.河北省中药材产业发展的SWOT分析[J].河北农业科学,2021,25(3):34-36,49.[13]付雅美,李泽华,卢秀茹.基于Logit模型的河北省棉花市场价格波动影响因素分析[J].河北农业大学学报(社会科学版),2019,21(5):43-48.[14]石自忠,王明利,高海秀.中国猪肉价格波动的双重非对称效应:基于MS-GARCH类模型[J].农林经济管理学报,2019,18(5):675-683.

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Last Update: 2022-07-19