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岭回归分析在研究城镇失业人数影响因素中的应用
Application of Ridge Regression Analysis in the Study of Factors Affecting the Number of Unemployed in Urban Areas

DOI: 10.12677/SA.2023.125128, PP. 1256-1263

Keywords: 最小二乘回归,岭回归,城镇失业人数,R语言
Least Squares Regression
, Ridge Regression, Urban Unemployment, R Language

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Abstract:

江泽民同志曾说过:“就业是民生之本”。城镇失业问题一直是党和国家高度重视的问题之一,本文以来自国家统计年鉴2013~2022近十年的城镇失业人数为研究对象,选取了2013~2022年国民生产总值、全国财政支出、城镇居民消费水平指数为影响因素,采用最小二乘估计和岭估计方法,针对影响城镇失业人数的因素进行了研究。最终根据模型得出结论,国民生产总值和城镇居民消费水平指数对城镇失业人数有影响,并且城镇居民消费水平指数与城镇失业人数呈负相关。
Comrade Zemin Jiang once said, “Employment is the basis of people’s livelihood”. Urban unemployment has always been one of the issues to which the Party and the State attach great importance. This paper takes the number of urban unemployed from the National Statistical Yearbook 2013~2022 in the past ten years as the object of study, selects the gross national product, the national financial expenditure, and the index of the consumption level of urban residents in the period of 2013~2022 as the influencing factors, and adopts the method of least squares estimation and ridge estimation, in order to research on the factors that affect the number of urban unemployed. Finally, according to the model, it is concluded that the GNP and the index of urban residents’ consumption level have influence on the number of urban unemployed, and the index of urban residents’ consumption level is negatively correlated with the number of urban unemployed.

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