Artificial Intelligence and Employment

Chokri Terzi

Journal of Academic Finance, 2025, vol. 16, issue 1

Abstract: Purpose: The purpose of this paper is to revisit the relationship between artificial intelligence (AI) and employment for eleven sectors of Tunisian economy in the period 2010-2022.Method: In order to study the variability that captures the impact of administrative barriers on investment in a particular sector of activity, we apply a Swamy random coefficients linear regression model, which takes into account cross-sectional heterogeneity issues.Results: The empirical results show a global negative effect of AI on employment. Sectoral analysis detected a non-significant positive effect for the energy and agricultural and food industries. Originality / relevance: This study finds its originality through the application of Swamy’s method to take into account the heterogeneity of the sectors of the Tunisian economy in the adherence to AI.

Keywords: Artificial intelligence; Employment; Slope homogeneity test; Swamy model (search for similar items in EconPapers)
JEL-codes: G3 M1 N8 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://34.195.102.181/journal/index.php/index/article/view/900 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jaf:journl:v:16:y:2025:i:1:n:784

Access Statistics for this article

Journal of Academic Finance is currently edited by Jamel Henchiri

More articles in Journal of Academic Finance from RED research unit, university of Gabes, Tunisia Contact information at EDIRC.
Bibliographic data for series maintained by Oussama Quentin Kasseh ().