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Estimating effects of ICT intensity on productivity, employment and output in South Africa: an industry-level analysis

Estimating effects of ICT intensity on productivity, employment and output in South Africa: an... This article aims to estimate the effects of ICT intensity on labor productivity, employment and output of agro-processing industries. To achieve this, the ICT intensity index is applied to rank industries into ‘more ICT-intensive’ and ‘less ICT-intensive’ groups. Thereafter, the annual growth rates of labor productivity, employment and output were calculated. Ultimately, the effects of ICT intensity were examined using Pooled Mean Group estimation, the Toda and Yamamoto Granger Non-Causality Test, and the Impulse Response Function and Variance Decomposition analyses. The findings suggest that ICT intensity yields higher positive and significant effects on the growth of the more ICT-intensive industries. Evidence of a causal relationship was detected for the more ICT-intensive industries. The findings further proved that ICT intensity contributed more to the forecast error variance in the growth of the more ICT-intensive industries. Overall, this article provides evidence of ICT-led growth for industries that use ICT most intensively. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Information Technology for Development Taylor & Francis

Estimating effects of ICT intensity on productivity, employment and output in South Africa: an industry-level analysis

Estimating effects of ICT intensity on productivity, employment and output in South Africa: an industry-level analysis

Information Technology for Development , Volume 28 (2): 26 – Apr 3, 2022

Abstract

This article aims to estimate the effects of ICT intensity on labor productivity, employment and output of agro-processing industries. To achieve this, the ICT intensity index is applied to rank industries into ‘more ICT-intensive’ and ‘less ICT-intensive’ groups. Thereafter, the annual growth rates of labor productivity, employment and output were calculated. Ultimately, the effects of ICT intensity were examined using Pooled Mean Group estimation, the Toda and Yamamoto Granger Non-Causality Test, and the Impulse Response Function and Variance Decomposition analyses. The findings suggest that ICT intensity yields higher positive and significant effects on the growth of the more ICT-intensive industries. Evidence of a causal relationship was detected for the more ICT-intensive industries. The findings further proved that ICT intensity contributed more to the forecast error variance in the growth of the more ICT-intensive industries. Overall, this article provides evidence of ICT-led growth for industries that use ICT most intensively.

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References (84)

Publisher
Taylor & Francis
Copyright
© 2021 Commonwealth Secretariat
ISSN
1554-0170
eISSN
0268-1102
DOI
10.1080/02681102.2021.1882367
Publisher site
See Article on Publisher Site

Abstract

This article aims to estimate the effects of ICT intensity on labor productivity, employment and output of agro-processing industries. To achieve this, the ICT intensity index is applied to rank industries into ‘more ICT-intensive’ and ‘less ICT-intensive’ groups. Thereafter, the annual growth rates of labor productivity, employment and output were calculated. Ultimately, the effects of ICT intensity were examined using Pooled Mean Group estimation, the Toda and Yamamoto Granger Non-Causality Test, and the Impulse Response Function and Variance Decomposition analyses. The findings suggest that ICT intensity yields higher positive and significant effects on the growth of the more ICT-intensive industries. Evidence of a causal relationship was detected for the more ICT-intensive industries. The findings further proved that ICT intensity contributed more to the forecast error variance in the growth of the more ICT-intensive industries. Overall, this article provides evidence of ICT-led growth for industries that use ICT most intensively.

Journal

Information Technology for DevelopmentTaylor & Francis

Published: Apr 3, 2022

Keywords: ICT intensity; productivity; employment; output

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