The nonlinear impact of technologies import on industrial employment: A panel threshold regression approach

Bouattour, Afef; Kalai, Maha; Helali, Kamel

doi:10.1016/j.heliyon.2023.e20266

Cited by 3 publications

(1 citation statement)

References 74 publications

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“…In the view that modern information technology and digital technology increase employment, the literature holds that foreign direct investment (Fokam et al 2023), economic systems (Bouattour et al 2023), labour skills and structure (Yang 2022), industrial technological intensity (Graf and Mohamed 2024), and the easing of information friction (Jin et al 2023) are important mechanisms. The research on whether AI technology crowds out jobs is voluminous, but the conclusions are inconsistent (Filippi et al 2023).…”

Section: Literature Reviewmentioning

confidence: 99%

The impact of artificial intelligence on employment: the role of virtual agglomeration

Shen,

Zhang

2024

Humanit Soc Sci Commun

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Sustainable Development Goal 8 proposes the promotion of full and productive employment for all. Intelligent production factors, such as robots, the Internet of Things, and extensive data analysis, are reshaping the dynamics of labour supply and demand. In China, which is a developing country with a large population and labour force, analysing the impact of artificial intelligence technology on the labour market is of particular importance. Based on panel data from 30 provinces in China from 2006 to 2020, a two-way fixed-effect model and the two-stage least squares method are used to analyse the impact of AI on employment and to assess its heterogeneity. The introduction and installation of artificial intelligence technology as represented by industrial robots in Chinese enterprises has increased the number of jobs. The results of some mechanism studies show that the increase of labour productivity, the deepening of capital and the refinement of the division of labour that has been introduced into industrial enterprises through the introduction of robotics have successfully mitigated the damaging impact of the adoption of robot technology on employment. Rather than the traditional perceptions of robotics crowding out labour jobs, the overall impact on the labour market has exerted a promotional effect. The positive effect of artificial intelligence on employment exhibits an inevitable heterogeneity, and it serves to relatively improves the job share of women and workers in labour-intensive industries. Mechanism research has shown that virtual agglomeration, which evolved from traditional industrial agglomeration in the era of the digital economy, is an important channel for increasing employment. The findings of this study contribute to the understanding of the impact of modern digital technologies on the well-being of people in developing countries. To give full play to the positive role of artificial intelligence technology in employment, we should improve the social security system, accelerate the process of developing high-end domestic robots and deepen the reform of the education and training system.

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Section: Literature Reviewmentioning

confidence: 99%

The impact of artificial intelligence on employment: the role of virtual agglomeration

Shen,

Zhang

2024

Humanit Soc Sci Commun

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Artificial intelligence and unemployment dynamics: an econometric analysis in high-income economies

Masoud

2024

TECHS

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PurposeThe purpose of the study is to investigate the impact of artificial intelligence (AI), machine learning (ML), and data science (DS) on unemployment rates across ten high-income economies from 2015 to 2023.Design/methodology/approachThis study takes a unique approach by employing a dynamic panel data (DPD) model with a generalised method of moments (GMM) estimator to address potential biases. The methodology includes extensive validation through Sargan, Hansen, and Arellano-Bond tests, ensuring the robustness of the results and adding a novel perspective to the field of AI and unemployment dynamics.FindingsThe study’s findings are paramount, challenging prevailing concerns in AI, ML, and DS, demonstrating an insignificant impact on unemployment and contradicting common fears of job loss due to these technologies. The analysis also reveals a positive correlation (0.298) between larger government size and higher unemployment, suggesting bureaucratic inefficiencies that may hinder job growth. Conversely, a negative correlation (−0.201) between increased labour productivity and unemployment suggests that technological advancements can promote job creation by enhancing efficiency. These results refute the notion that technology inherently leads to job losses, positioning AI and related technologies as drivers of innovation and expansion within the labour market.Research limitations/implicationsThe study’s findings suggest a promising outlook, positioning AI as a catalyst for the expansion and metamorphosis of employment rather than solely a catalyst for automation and job displacement. This insight presents a significant opportunity for AI and related technologies to improve labour markets and strategically mitigate unemployment. To harness the benefits of technological progress effectively, authorities and enterprises must carefully evaluate the balance between government spending and its impact on unemployment. This proposed strategy can potentially reinvent governmental initiatives and stimulate investment in AI, thereby bolstering economic and labour market reliability.Originality/valueThe results provide significant perspectives for policymakers and direct further investigations on the influence of AI on labour markets. The analysis results contradict the common belief of technology job loss. The study’s results are shown to be reliable by the Sargan, Hansen, and Arellano-Bond tests. It adds to the discussion on the role of AI in the future of work, proposing a detailed effect of AI on employment and promoting a strategic method for integrating AI into the labour market.

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Threshold effects of technology import on industrial employment: a panel smooth transition regression approach

Bouattour,

Kalai,

Helali

2024

Economic Structures

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The relationship between imported technology and employment is a controversial issue. This study aims to test the hypothesis that the relationship between imported technology and employment is non-linear and evolves with the level of technology imports. The study covers two groups of developed and developing countries over the period 2000–2019. The Panel Smooth Transition Regression (PSTR) model is used to estimate the technology import threshold and its impact on industrial employment. The study finds a positive relationship between imported technology and industrial employment for technology import rates above the 13.667% threshold, above which imported technology begins to improve industrial employment in developed countries. In contrast, for developing countries, the results showed a negative relationship between imported technology and industrial employment for technology import rates above the 3.44% threshold above which imported technology begins to reduce industrial employment. These results suggest that the threshold level of technology imports can be considered as an indicator for promoting innovation policies in both developed and developing countries to minimize the negative effect of process innovation resulting from imported technology.

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The nonlinear impact of technologies import on industrial employment: A panel threshold regression approach

Cited by 3 publications

References 74 publications

The impact of artificial intelligence on employment: the role of virtual agglomeration

The impact of artificial intelligence on employment: the role of virtual agglomeration

Artificial intelligence and unemployment dynamics: an econometric analysis in high-income economies

Threshold effects of technology import on industrial employment: a panel smooth transition regression approach

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