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http://dx.doi.org/10.29220/CSAM.2020.27.4.459

Statistical analysis of the employment future for Korea

Lee, SangHyuk (Department of Applied Statistics, Chung-Ang University)
Park, Sang-Gue (Department of Applied Statistics, Chung-Ang University)
Lee, Chan Kyu (Department of Korean Language and Literature, Chung-Ang University)
Lim, Yaeji (Department of Applied Statistics, Chung-Ang University)

Publication Information

Communications for Statistical Applications and Methods / v.27, no.4, 2020 , pp. 459-468 More about this Journal

Abstract

We examine the rate of substitution of jobs by artificial intelligence using a score called the "weighted ability rate of substitution (WARS)." WARS is a indicator that represents each job's potential for substitution by automation and digitalization. Since the conventional WARS is sensitive to the particular responses from the employees, we consider a robust version of the indicator. In this paper, we propose the individualized WARS, which is a modification of the conventional WARS, and compute robust averages and confidence intervals for inference. In addition, we use the clustering method to statistically classify jobs according to the proposed individualized WARS. The proposed method is applied to Korean job data, and proposed WARS are computed for five future years. Also, we observe that 747 jobs are well-clustered according to the substitution levels.

Keywords

automation; employment; job clustering; job replacement; weighted ability rate of substitution;

Citations & Related Records

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