大数据背景下中国季度失业率的预测研究------基于网络搜索数据的分析

王勇,董恒新

系统科学与数学 ›› 2017, Vol. 37 ›› Issue (2) : 460-472.

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PDF(934 KB)
系统科学与数学 ›› 2017, Vol. 37 ›› Issue (2) : 460-472. DOI: 10.12341/jssms13076
论文

大数据背景下中国季度失业率的预测研究------基于网络搜索数据的分析

    王勇1,2,董恒新1
作者信息 +

The Forecast of China's Quarterly Unemployment Rate in the Background of Big Data --- Analysis Based on Network Search Data

    WANG Yong1,2 ,DONG Hengxin1
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文章历史 +

摘要

目前,中国失业率统计存在一定局限,不利于准确及时地反映劳动市场的就业变动,大数据技术的快速发展为中国失业率统计提供新的发展视角.基于网络搜索数据,文章从5种常用的预测方法中筛选出最优的支持向量机回归模型,对中国季度失业率进行了预测研究.研究表明,基于网络搜索数据预测的失业率能够比官方数据更早地反映失业趋势的变化,预测失业率与修正后的失业率水平接近,能够为政府部门提供中国失业状况的政策预警.

Abstract

At present, there are some limitations in China's unemployment rate statistics, which is not conducive to accurately and timely reflect the employment changes in labor market. The rapid development of large-scale data technology provides a new development perspective for China's unemployment statistics. Based on the network search data, this paper selects the best support vector machine regression model from five commonly used forecasting methods, and forecasts the quarterly unemployment rate in China. The results show that the unemployment rate can reflect the change of the unemployment trend sooner than the official data. The predicted unemployment rate is close to the revised unemployment rate, which can provide the government with the policy warning of the unemployment situation in China.

关键词

失业率预测 / 大数据 / 网络搜索数据 / 支持向量机.

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王勇 , 董恒新. 大数据背景下中国季度失业率的预测研究------基于网络搜索数据的分析. 系统科学与数学, 2017, 37(2): 460-472. https://doi.org/10.12341/jssms13076
WANG Yong , DONG Hengxin. The Forecast of China's Quarterly Unemployment Rate in the Background of Big Data --- Analysis Based on Network Search Data. Journal of Systems Science and Mathematical Sciences, 2017, 37(2): 460-472 https://doi.org/10.12341/jssms13076
中图分类号: 00A69   
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