Knowledge, Structure, and Growth: Rethinking Economic Development in Eastern Europe Through Economic Complexity

Creative Commons License

Bari B.

SIBR 2025, Osaka, Japonya, 3 - 05 Temmuz 2025, ss.1-2, (Özet Bildiri)

  • Yayın Türü: Bildiri / Özet Bildiri
  • Basıldığı Şehir: Osaka
  • Basıldığı Ülke: Japonya
  • Sayfa Sayıları: ss.1-2
  • Anadolu Üniversitesi Adresli: Evet

Özet

This study investigates the relationship between economic complexity and macroeconomic performance in Eastern European countries. Focusing on ten transition economies—Poland, Hungary, Czechia, Slovakia, Slovenia, Romania, Bulgaria, Croatia, Albania, and North Macedonia—the research explores how variations in the Economic Complexity Index (ECI) affect GDP per capita, export diversification, and foreign direct investment (FDI) between 2000 and 2022. Given their post-socialist transitions, EU integration trajectories, and ongoing industrial restructuring, these countries provide a compelling case.

Preliminary findings suggest that countries with higher ECI levels, such as Czechia and Slovenia, tend to perform better in terms of sustained economic growth and FDI attraction. Conversely, low-complexity economies appear more vulnerable to external shocks and face persistent structural limitations. These insights imply that complexity-driven development pathways may offer resilience and competitiveness advantages, especially in the context of global value chains and technological upgrading.

The study contributes to the literature by focusing on a region that has received limited empirical attention in the context of economic complexity. While ECI has been widely used in cross-country growth models, few studies examine its role in post-transition economies with shared institutional legacies and diverse reform paths. This research fills that gap and highlights the regional and temporal dynamics of complexity and its policy implications.

Methodologically, the study employs a panel data approach combining fixed effects regressions and panel ARDL models to capture both short- and long-term relationships between economic complexity and macroeconomic indicators. Robustness is ensured through the use of alternative estimators, structural break tests, and clustering analysis to group countries based on complexity trajectories. Clustering also supports the identification of regional patterns that are not visible in regression models. The dataset integrates multiple international sources. ECI data is retrieved from Harvard’s Atlas of Economic Complexity, while trade data comes from UN COMTRADE and CEPII’s BACI database. Macroeconomic indicators such as GDP per capita, FDI inflows, and trade openness are sourced from the World Bank’s World Development Indicators (WDI) and World Governance Indicators (WGI). These comprehensive datasets allow for consistent, longitudinal analysis across all countries in the sample.

Ultimately, the study aims to generate new evidence on the structural sources of economic resilience and growth in Eastern Europe. By demonstrating the macroeconomic value of complexity-oriented development strategies, the project seeks to inform national and regional policymaking focused on industrial upgrading, diversification, and integration into higher value-added segments of global production networks