Dr Zsófia Vas (p), Prof Imre Lengyel

Following the 2008 financial crisis, the European Union (EU) has placed increasing emphasis on regional industrial specialisation and reindustrialisation. More recent challenges, including the green and digital transitions and the strengthening of defence capabilities, have further reinforced the strategic importance of industrial development. In Hungary, foreign direct investment (FDI) and EU cohesion funds have been the main drivers of industrial restructuring. The country currently has one of the highest shares of foreign-controlled manufacturing in the EU.
FDI has contributed to productivity growth and technological upgrading, particularly in manufacturing. At the same time, however, it has increased the risk that certain regions become locked into a regional “development trap”, where growth remains dependent on low-cost labour and assembly-based production with limited local innovation capacity.
This study examines whether FDI-led reindustrialisation has contributed to Hungary’s convergence towards the average level of the former EU12 member states. Using NUTS 3-level data, we identify five regional types characterised by different industrial development trajectories. Our results show that reindustrialisation supported Hungary’s catching-up process until around 2015. After that point, several FDI-intensive manufacturing regions appear to have entered a development trap, where weak innovation capacities constrain further upgrading and growth.
We argue that the current pattern of reindustrialisation in Hungary may reinforce long-term structural vulnerabilities in affected regions and may also slow the country’s overall convergence with the EU average.

Ms Irina Plotnikova (p)

This study is devoted to a comparative analysis of the development trajectories of coal towns in Russia and China in the context of global technological transition. The selected cases are the cities of Kuzbass (Russia) and the city of Fuxin (Liaoning Province, China). The choice is justified by their representativeness: both regions are considered the "coal heart" of their countries, symbolizing the coal industry's long-standing key role in the national economy. Kuzbass is an integrated coal industrial complex, where mines, processing plants, metallurgical and chemical production facilities are distributed across several cities, forming a unified production and distribution network. Fuxin serves as a typical example of a Chinese coal industrial city that has undergone a transformation from rapid industrialization to a resource crisis. Today, both regions are experiencing significant population outflow, especially among young people.

The paper examines the historical prerequisites for the deployment and establishment of the coal industry in each region, as well as the profound changes that industrialization brought about in the demographic structure, economy, and cultural identity of the studied cities. Special attention is paid to the phenomenon of "explosive" population growth rates and urban infrastructure expansion, which were a direct consequence of the large-scale mobilization of resources during the Soviet and post-Maoist periods, respectively.

The theoretical framework of the study is the concept of technological transitions. The transformation of cities is viewed through the lens of shifting dominant institutions and technological paradigms, both at the global level and locally. The central research question addresses the problem of desynchronization: to what extent does the dynamics of institutional and technological change in coal towns align with global trends, and at what points does a gap emerge? The analysis explores how this desynchronization affects the prospects of these cities.

As a result of the analysis, similar effects of desynchronization between global energy transition trends and local institutional strategies have been identified. In both cases, the state acts as a key actor shaping adaptation trajectories. However, differences in regulatory models are evident. Further analysis will aim to deepen the understanding of how these divergent strategies influence the prospects of the cities — whether they contribute to the preservation of outdated structures or open up opportunities for integration into a new technological paradigm.

Mr Juan Alvarez Vilanova (p), Professor Riccardo Crescenzi, Dr Lee Mager

Foreign direct investment (FDI) is a critical vehicle for financing and diffusing the capital, skills and know-how needed for the transition toward a green, low-carbon economy. Yet “green FDI” remains systematically under-measured. Existing approaches largely rely on sector proxies – typically renewable energy and waste – that cannot detect green activities embedded within other industries, providing a partial and geographically biased picture of transition-relevant investment. Here, we introduce a taxonomy-guided, project-level measurement framework that combines large language models (LLMs) with the EU Taxonomy for Sustainable Activities to evaluate whether investment activities are consistent with sector-specific green activities and criteria. Applying this approach to 109,084 inward greenfield FDI projects into the EU27+UK over 2013–2024, we classify 15.7% of inward FDI value as green – around twice the share captured by focusing narrowly on renewable energy and waste sectors. In other words, sector-based metrics overlook roughly half of green FDI, missing large volumes of transition-relevant investment in manufacturing and related services, and revealing a geography of green FDI that extends well beyond regions endowed with solar and wind resources. The project-level lens also reveals sharp differences in the geography of investor origins: beyond-energy green FDI is more strongly linked to extra-European sources than renewable-focused green FDI, implying distinct geopolitical dependencies and strategic vulnerabilities in the financing of industrial decarbonisation. Benchmarking against blinded human coding and extensive robustness tests show high accuracy and reproducibility across alternative prompts, parameters and models. Together, the findings demonstrate that green FDI follows multiple pathways beyond renewables and that taxonomy-guided LLM classification enables scalable monitoring of investment alignment with environmental objectives to support the green transition.