{"title":"Research on Influences of Employment in Manufacturing Industry on that in the Service Industry Based on Bayes Model","authors":"Yue Sun","doi":"10.26549/JFR.V2I3.1173","DOIUrl":null,"url":null,"abstract":"Using the data of 285 prefectural and the above-level cities from 2004 to 2016, this thesis reveals the impact of employment in China's urban manufacturing industry on the employment of service industries with the Bayesian model. Under the Bayesian framework, partial linear semi-parametric model is proposed. The nonlinear functions are fitted by using truncation base cardinal spline and considering the random error terms of mixed normal fitting models. The results show that: employment in the urban manufacturing industry in China has significant influence on the employment in the service industry. When the number of employees in the manufacturing industry changes from 0 to 650,000, the manufacturing industry has less influence. When the number of the employees in the manufacturing industry changes from 650,000 to 900,000, the employees of the service industry will dramatically increase. When the number of the employees in the manufacturing industry is more than 900,000, the employees in the service industry will be prone to stable growth.","PeriodicalId":390233,"journal":{"name":"Journal of Finance Research","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Finance Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26549/JFR.V2I3.1173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Using the data of 285 prefectural and the above-level cities from 2004 to 2016, this thesis reveals the impact of employment in China's urban manufacturing industry on the employment of service industries with the Bayesian model. Under the Bayesian framework, partial linear semi-parametric model is proposed. The nonlinear functions are fitted by using truncation base cardinal spline and considering the random error terms of mixed normal fitting models. The results show that: employment in the urban manufacturing industry in China has significant influence on the employment in the service industry. When the number of employees in the manufacturing industry changes from 0 to 650,000, the manufacturing industry has less influence. When the number of the employees in the manufacturing industry changes from 650,000 to 900,000, the employees of the service industry will dramatically increase. When the number of the employees in the manufacturing industry is more than 900,000, the employees in the service industry will be prone to stable growth.