Journal of Korea Trade

한국무역학회 (Korea Trade Research Association)
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Prediction of the Probability of Job Loss due to Digitalization and Comparison by Industry: Using Machine Learning Methods

  • 투고 : 2021.07.11
  • 심사 : 2021.08.10
  • 발행 : 2021.08.31
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초록

Purpose - The essential purpose of this study is to analyze the possibility of substitution of an individual job resulting from technological development represented by the 4th Industrial Resolution, considering the different effects of digital transformation on the labor market. Design/methodology - In order to estimate the substitution probability, this study used two data sets which the job characteristics data for individual occupations provided by KEIS and the information on occupational status of substitution provided by Frey and Osborne(2013). In total, 665 occupations were considered in this study. Of these, 80 occupations had data with labels of substitution status. The primary goal of estimation was to predict the degree of substitution for 607 of 665 occupations (excluding 58 with markers). It utilized three methods a principal component analysis, an unsupervised learning methodology of machine learning, and Ridge and Lasso from supervised learning methodology. After extracting significant variables based on the three methods, this study carried out logistics regression to estimate the probability of substitution for each occupation. Findings - The probability of substitution for other occupational groups did not significantly vary across individual models, and the rank order of the probabilities across occupational groups were similar across models. The mean of three methods of substitution probability was analyzed to be 45.3%. The highest value was obtained using the PCA method, and the lowest value was derived from the LASSO method. The average substitution probability of the trading industry was 45.1%, very similar to the overall average. Originality/value - This study has a significance in that it estimates the job substitution probability using various machine learning methods. The results of substitution probability estimation were compared by industry sector. In addition, This study attempts to compare between trade business and industry sector.

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과제정보

This work was supported by Korea Maritime Institute.

참고문헌

  1. Autor, D. H., Levy, F., and Murnane, R. J. (2003), "The skill content of recent technological change: An empirical exploration", The Quarterly Journal of Economics, 118(4), 1279-1333. https://doi.org/10.1162/003355303322552801
  2. Arntz, M., T. Gregory and U. Zierahn (2016), The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis (Employment and Migration Working Papers, No. 189), OECD Social Publishing
  3. Frey, C. B., and Osborne, M. (2013), The future of employment: How susceptible are jobs to computerisation? (Unpublished Paper)
  4. Frey, C. B., and Osborne, M. (2015), Technology at work: The Future of Innovation and Employment, Oxford Martin School and Citi GPS.
  5. Frey, C. B., and Osborne, M. A. (2017), "The future of employment: How susceptible are jobs to computerisation?", Technological Forecasting and Social Change, 114, 254-280. https://doi.org/10.1016/j.techfore.2016.08.019
  6. Hur, J. J., (2016), The Future of Work and Labor Market Strategies (Unpublished Paper).
  7. Kim, J. J., and Kwon, Y. S., (2019), Korea Dictionary of Occupations, Korea Employment Information Service
  8. Kim, H. J., Kim, J. J., and Yeo, I. K., (2017) New Jobs in the Era of the 4th Industrial Revolution (Issue Paper), Korea Employment Information Service.
  9. Murphy, K. P. (2012), Machine learning: a probabilistic perspective, MIT press.
  10. Park, G. Y., Chun, Y. M., Hong, S. M., and Son, Y. S., (2016), A Study on the Impact of Technological Change on Jobs (Issue Paper), Korea Employment Information Service
  11. Oh, E. J., (2018), Diagnosis of the Seoul Labor Market in the Era of the 4th Industrial Revolution and Response Direction (Policy Report), The Seoul Institute
  12. Oh, E. J., Shin, S. M., Goo, M. Y., Kwon, S. Y., and Gil, H. J., (2018), Prospects for women's job prospects and response strategies according to technological development - 1 (Policy Paper), Korean Women's Development Institute
  13. Oh, E. J., Shin, S. M., Goo, M. Y., Kwon, S. Y., and Gil, H. J., (2019), Prospects for women's job prospects and response strategies according to technological development - 2 (Policy Paper), Korean Women's Development Institute.