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Article
Publication date: 15 October 2021

Monica Raileanu Szeles and Mihaela Simionescu

The paper aims to provide comparative empirical evidence on young people neither in employment nor in education and training (NEET-youth) under the influence of the digital…

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Abstract

Purpose

The paper aims to provide comparative empirical evidence on young people neither in employment nor in education and training (NEET-youth) under the influence of the digital divide, education and sectoral growth across the EU regions, with a focus on the transition patterns followed over time by EU regions in bridging the digital divide and their specific implications on school-to-work transition (STWT).

Design/methodology/approach

Firstly, five variables on Internet usage activities are aggregated into an index of E-skills. Secondly, linear dynamic panel data regression models are used to explain the influence of various factors on regional rates of NEET-youth, with or without grouping regions upon the digital divide in relative terms.

Findings

Advanced digital literary skills are found to have a stronger effect on the STWT than the basic ones. The growth of employment in specific economic activities like “Information and Communication” enhances STWT, but only when considering regional differences in the digital divide and E-skills as well. However, the negative effect of deprivation and low educational attainments on STWT is offset by a low level of the regional digital divide. In addition, more R&D expenditure in higher education is necessary to compensate for the effect of the digital divide on the STWT.

Practical implications

On brief, the policy implications are twofold. Firstly, regions will need to focus more on reducing the digital divide, because it will not only generate positive effects for STWT but will also enhance the positive impact of education and sectoral growth on STWT and even compensate for their low progress. Secondly, in the context of the EU single market, to better address the situation of young people, regions should monitor the relative progress in bridging the digital divide and improving E-skills, with respect to the other EU regions. Improving the relative position on the EU map of E-skills increases the effectiveness of regional policies targeting the STWT.

Originality/value

The originality of the paper lies in the regional approach to the relationship between STWT and the digital divide, which allows us to derive new policy measures for the EU regions. Other innovative contributions rely on the identification of (1) transition patterns that region follow over time in improving STWT while bridging the digital divide and (2) policy measures addressing the NEETs in the context of the regional digital divide.

Details

International Journal of Manpower, vol. 43 no. 7
Type: Research Article
ISSN: 0143-7720

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Article
Publication date: 30 July 2024

Najeb Masoud

The 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…

565

Abstract

Purpose

The 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/approach

This 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.

Findings

The 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/implications

The 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/value

The 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.

Details

Technological Sustainability, vol. 4 no. 1
Type: Research Article
ISSN: 2754-1312

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