Digital–Green Twin Transformation and Economic Growth: The Asymmetric Moderating Role of Industrial Competitiveness in Transition Economies
Post-socialist economies in Central and Eastern Europe, the Western Balkans, the Eastern Partnership, and Central Asia inherited energy-intensive industrial structures and now diverge widely in digital adoption and decarbonisation, which makes them a revealing setting for the twin transition. This study examines how the digital and green transitions relate to real GDP per capita growth in 24 transition economies over 1996–2023 and whether industrial competitiveness conditions these relationships. Composite indices are constructed through principal component analysis. Following first- and second-generation diagnostic tests, the analysis employs fixed effects with Driscoll–Kraay standard errors, panel-corrected standard errors, system GMM, common correlated effects, and cross-sectionally augmented ARDL estimators, together with panel Granger non-causality tests robust to cross-sectional dependence. The digital transition, the green transition, and industrial competitiveness are each positively associated with growth. The central finding is an asymmetric moderation pattern. Industrial competitiveness strengthens the growth association of digitalisation but weakens that of greening, so that the green growth association appears concentrated in less industrialised economies. Granger predictive relationships run in both directions between each transition and growth and from industrial competitiveness to the green transition. The pattern is robust across subregions, EU and non-EU groups, the 2005–2023 period, alternative index constructions, and alternative treatments of missing data, although the green coefficient and its interaction with industrial competitiveness are not statistically significant in the 1997–2004 subsample. The system GMM and CS-ARDL estimates are treated as supplementary evidence. The evidence, which consists of conditional associations rather than causal effects, suggests that twin transition support may be more effective when it takes the industrial conditions of each economy into account rather than being applied as a uniform package.
Authors
- Zokir Toshtemirovich Mamadiyarov (ORCID: https://orcid.org/0000-0002-1508-488X)
- Shamshinur Shuxratovna Yakubova (ORCID: https://orcid.org/0000-0002-6593-5195)
- Egamov Sevinchbek Maxsud O‘g‘li (ORCID: https://orcid.org/0009-0005-7862-8679)
- Sofiya Alimova
- Oydin Kurbanova
- Bekzod Khalilov (ORCID: https://orcid.org/0009-0005-8611-9049)
- Nargiza Yormonqulova
Institutions
- Urgench State University (UZ)
- Karshi State University (UZ)
- Kokand University (UZ)
- Alfraganus University (UZ)
- Termez University of Economics and Service (UZ)
- Mamun University (UZ)
- Kokand State University (UZ)
- Urganch RANCH Texnologiya Universiteti (UZ)
- Tashkent State University of Economics (UZ)
- Westminster International University in Tashkent (UZ)
Publication Details
- Journal
- Economies
- Published
- 2026-11-03
- DOI
- https://doi.org/10.3390/economies14110516
- Primary Topic
- Digital Economy and Transformation
- Type
- article
- Field-Weighted Citation Impact
- 0.00