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http://dx.doi.org/10.38121/kpea.2021.03.37.1.197

Machine Learning Prediction of Economic Effects of Busan's Strategic Industry through Ridge Regression and Lasso Regression  

Yi, Chae-Deug (부산대학교 무역학부)
Publication Information
Journal of Korea Port Economic Association / v.37, no.1, 2021 , pp. 197-215 More about this Journal
Abstract
This paper analyzes the machine learning predictions of the economic effects of Busan's strategic industries on the employment and income using the Ridge Regression and Lasso Regression models with regulation terms. According to the Ridge estimation and Lasso estimation models of employment, the intelligence information service industry such as the service platform, contents, and smart finance industries and the global tourism industry such as MICE and specialized tourism are predicted to influence on the employment in order. However, the Ridge and Lasso regression model show that the future transportation machine industry does not significantly increase the employment and income since it is the primitive investment industry. The Ridge estimation models of the income show that the intelligence information service industry and global tourism industry are also predicted to influence on the income in order. According to the Lasso estimation models of income, four strategic industries such as the life care, smart maritime, the intelligence machine, and clean tech industry do not influence the income. Furthermore, the future transportation machine industry may influence the income negatively since it is the primitive investment industry. Thus, we have to select the appropriate economic objectives and priorities of industrial policies.
Keywords
Strategic Industry; Ridge Regression; Lasso Regression; Employment; Income;
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