本文選題：失業(yè)率預測 + 大數(shù)據(jù)�。� 參考：《系統(tǒng)科學與數(shù)學》2017年02期

【摘要】：目前,中國失業(yè)率統(tǒng)計存在一定局限,不利于準確及時地反映勞動市場的就業(yè)變動,大數(shù)據(jù)技術(shù)的快速發(fā)展為中國失業(yè)率統(tǒng)計提供新的發(fā)展視角.基于網(wǎng)絡搜索數(shù)據(jù),文章從5種常用的預測方法中篩選出最優(yōu)的支持向量機回歸模型,對中國季度失業(yè)率進行了預測研究.研究表明,基于網(wǎng)絡搜索數(shù)據(jù)預測的失業(yè)率能夠比官方數(shù)據(jù)更早地反映失業(yè)趨勢的變化,預測失業(yè)率與修正后的失業(yè)率水平接近,能夠為政府部門提供中國失業(yè)狀況的政策預警.
[Abstract]:At present, there are some limitations in the statistics of China's unemployment rate, which is not conducive to accurately and timely reflecting the employment changes in the labor market. The rapid development of big data's technology provides a new perspective for the development of China's unemployment rate statistics. Based on the network search data, this paper selects the optimal support vector machine regression model from five commonly used forecasting methods, and makes a prediction study on the quarterly unemployment rate in China. The study shows that the unemployment rate predicted on the basis of web search data is able to reflect changes in unemployment trends earlier than the official data, and that the predicted unemployment rate is close to the revised unemployment rate. To provide government departments with a policy warning of unemployment in China.
【作者單位】： 東北財經(jīng)大學統(tǒng)計學院;東北財經(jīng)大學博士后科研流動站;
【基金】：國家社科基金重大項目(2015YZD08);國家社科基金項目(14CRK019) 國家自然科學基金項目(71573034) 遼寧省教育廳項目(LN2016JD020) 中國博士后科學基金(2016M601318)資助課題
【分類號】：F249.2

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