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How would Automation Impact Employment in the Manufacturing Sector of Bangladesh? An Empirical Projection

Author

Listed:
  • Mahtab Uddin

    (The University of Manchester
    University of Dhaka
    South Asian Network on Economic Modeling (SANEM))

  • Farhin Islam

    (Bangladesh Institute of Development Studies (BIDS))

Abstract

Using the two rounds of the Survey of Manufacturing Industries, this paper empirically investigates the likely scenarios of the impacts of technological progress on sectoral employment by divisions in the manufacturing sector in Bangladesh. We performed multiple linear regression of output on labour, capital stock, region fixed effects, year fixed effect, and cluster our robust standard errors at the industrial classification to obtain the Solow residual where the technology parameter comes from the residual of this regression. Then, we introduce advancements in the technology parameter and estimate the impacts on the labour, holding other things fixed. The manufacturing industry in Bangladesh has a total of 5.3 million employees, with the majority in the textile and apparel sector. A 15% increase in productivity due to technological advancement would eliminate 688,000 jobs in Bangladesh, a 30% increase would eliminate 1.22 million, and a 50% increase would result in a dire consequence, with a total job loss of 1.8 million. The largest affected sectors are textiles and apparel. Dhaka would be affected most, followed by Chattogram, Rajshahi, and Khulna. Assuming a 10% annual growth in the industry, the net increase in total manufacturing employment would be 2.02 million in 2025. The unemployment we have forecasted will not occur with the rise in technology if the technology is augmenting instead of labour replacing.

Suggested Citation

  • Mahtab Uddin & Farhin Islam, 2024. "How would Automation Impact Employment in the Manufacturing Sector of Bangladesh? An Empirical Projection," The Indian Journal of Labour Economics, Springer;The Indian Society of Labour Economics (ISLE), vol. 67(4), pages 1045-1071, December.
  • Handle: RePEc:spr:ijlaec:v:67:y:2024:i:4:d:10.1007_s41027-024-00538-w
    DOI: 10.1007/s41027-024-00538-w
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    References listed on IDEAS

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    1. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    2. Bogliacino, Francesco & Pianta, Mario, 2010. "Innovation and Employment: a Reinvestigation using Revised Pavitt classes," Research Policy, Elsevier, vol. 39(6), pages 799-809, July.
    3. Rolf Fare & Daniel Primont, 2002. "Inada Conditions and the Law of Diminishing Returns," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(1), pages 1-8, April.
    4. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
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    More about this item

    Keywords

    Technology; Automation; Employment; Job loss; Growth; Skill demand;
    All these keywords.

    JEL classification:

    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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