Skilled labor convergence across Turkish regions: a club convergence algorithm approach


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ERİŞ DERELİ B., Pinar M.

Empirical Economics, vol.69, no.4, pp.2267-2309, 2025 (SSCI, Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 69 Issue: 4
  • Publication Date: 2025
  • Doi Number: 10.1007/s00181-025-02789-y
  • Journal Name: Empirical Economics
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, IBZ Online, International Bibliography of Social Sciences, ABI/INFORM, Business Source Elite, Business Source Premier, EconLit, Geobase, Public Affairs Index
  • Page Numbers: pp.2267-2309
  • Keywords: Convergence, Convergence clubs, Skilled labor, White-collar
  • Marmara University Affiliated: Yes

Abstract

Human capital and skill differences are among the main determinants of income per capita, technology and productivity differences across regions and countries. This paper uses the Phillips and Sul convergence club algorithm to investigate convergence in skilled labor force shares across Turkish regions between 2005 and 2022. The findings highlight that there is no overall convergence in skilled labor shares across Turkish regions and identify two convergence clubs, one consisting of regions with high shares of the skilled labor force and another with relatively low shares of the skilled labor force. The results indicate a regional heterogeneity in the convergence of skilled labor across different geographical clusters. Finally, the IV Probit (IV-GMM) analyses highlight that the likelihood of being part of a highly skilled club (skilled labor force share) significantly increases with GDP per capita, R&D investment per capita, net migration, and the percentage of higher education graduates, and decreases with the agricultural share of production.