Metropolisation has become one of the defining features of regional development in Central and Eastern Europe. Since the beginning of the transition period, capital city regions have attracted an increasing concentration of economic activity, highly skilled labour and population, while many peripheral regions have experienced economic stagnation and demographic decline. Regional disparities are typically assessed using GDP per capita, which is generally interpreted as a measure of economic performance. However, because GDP per capita is an indicator combining both economic output and population size, demographic change may influence its dynamics and consequently the interpretation of regional convergence. The paper examines the extent to which demographic processes modify the observed pattern of regional inequalities in eleven Central and Eastern European countries during the period 2000–2023. Rather than analysing demographic variables as determinants of economic growth, the study focuses on the arithmetic relationship between GDP, population, and GDP per capita. A simple decomposition framework is applied to separate the economic component of GDP per capita growth from the demographic component resulting from population change. The empirical analysis compares capital city NUTS3 regions, treated as proxies for metropolitan areas, with the remaining regions of each country. In addition, the study examines differences within peripheral regions by comparing areas characterised by the weakest economic performance with those experiencing the strongest population decline. The results demonstrate that capital city regions consistently record faster GDP growth than the rest of their countries, confirming the continuing concentration of economic activity. However, this picture changes considerably when GDP per capita is analysed. Population growth in metropolitan regions mechanically reduces the observed rate of GDP per capita growth, whereas population decline in many non-capital regions inflates per capita indicators despite relatively weak economic performance. Consequently, part of the apparent convergence observed in GDP per capita does not reflect genuine convergence in economic activity but results from demographic adjustment. In several countries, including Poland, Slovakia and Estonia, demographic processes are sufficiently strong to reverse the interpretation of convergence when GDP per capita is compared with GDP measured in absolute terms. The analysis also reveals considerable cross-country variation in the structure of demographic effects. In some countries, convergence is mainly influenced by rapid population concentration in capital city regions, whereas in others it is driven by depopulation of peripheral areas. Demographic processes contribute to reducing observed disparities within peripheral regions themselves, as areas with the weakest economic performance are not necessarily those experiencing the strongest population decline. The findings suggest that GDP per capita should be interpreted as a hybrid indicator reflecting both economic performance and demographic dynamics. Consequently, analyses of regional convergence and evaluations of cohesion policy should explicitly account for demographic processes in order to avoid misleading conclusions concerning the scale and direction of regional development.
This study examines the socio-economic impacts of the M85 and M86 expressways in Northwest Hungary, with particular attention to the development trajectories of rural settlements and changes in commuting patterns. The research is based on the assumption that transport infrastructure investments improve accessibility, increase labour mobility, and contribute to regional development. The analysis focuses on settlements located in Győr-Moson-Sopron and Vas counties and relies on census data from 2011 and 2022, complemented by Spatial Information System (TEIR) and Hungarian Central Statistical Office (KSH) databases. To assess the effects of expressway development, correlation analysis and a difference-in-differences (DiD) approach were applied, enabling comparisons between the affected and the control areas. The findings indicate that proximity to expressways is associated with more favourable demographic and income indicators, whereas the independent effect of accessibility improvement is relatively limited. In rural settlements affected by the new roads, population decline slowed, housing stock expansion remained stronger, and job growth exceeded that observed in control areas. However, these changes did not substantially alter the overall development trajectory. The most notable impacts emerged in labour mobility and commuting systems. Out-commuting increased, labour market catchment areas expanded, and cross-border daily mobility intensified. The Austrian labour market became an increasingly important destination, particularly in the Sopron area and along the M85 corridor. Nevertheless, the results do not confirm a significant strengthening of polycentric relations between the regional centres of Győr, Sopron, and Szombathely. The study concludes that the expansion of the expressway network primarily reinforced existing spatial and labour market structures rather than generating new regional development axes. Transport infrastructure, therefore, appears to be a necessary but insufficient condition for territorial convergence and polycentric regional development.
Europe is losing economic ground. Sluggish dynamism and deepening territorial polarisation have eroded its global standing just as artificial intelligence (AI) is rewriting the rules of the world economy. While AI is widely viewed as a potential source of productivity growth, competitiveness, and new economic opportunities, its regional consequences remain uncertain. Could AI generation - the innovation activity behind AI technologies - help reverse Europe’s slide? We use a panel dataset of 224 NUTS2 regions across 26 European Union member states during the period 2011–2019 to investigate whether regional AI-related inventive capacity contributes to economic and employment growth and whether these effects are evenly distributed across space. The empirical analysis combines several complementary approaches. We estimate region and year fixed-effects panel models to account for unobserved regional characteristics and common temporal shocks, while random-effects models are used as a benchmark. To address potential endogeneity arising from reverse causality and omitted time-varying factors, we employ System-GMM estimators. We further apply fixed-effects quantile regression to examine whether the effects of AI generation differ across the regional growth distribution. In addition, spatial econometric models are estimated as robustness checks to account for geographical dependence and potential spillover effects between neighbouring regions. The results reveal three main findings. First, AI generation is positively associated with both regional economic growth and employment growth. Regions with stronger AI related inventive capacity experience higher subsequent GDP per capita growth and employment expansion, suggesting that AI may be an important source of technological upgrading and regional development potential. Second, the benefits of AI generation are not distributed evenly across European territories. The strongest economic links are concentrated among regions already positioned near the technological and economic frontier, indicating that AI may reinforce existing patterns of regional advantage rather than automatically promoting convergence. Third, potential employment effects display a different spatial pattern: employment gains are more pronounced among intermediate performing regions, suggesting that AI-related innovation may create broader labour market opportunities beyond the most advanced innovation hubs. These findings highlight the dual nature of AI-driven development. AI generation represents a significant opportunity for strengthening European competitiveness, but its benefits depend heavily on regional capabilities, including research capacity, skilled labour, and innovation ecosystems. Without targeted policies that broaden access to AI related knowledge creation and strengthen the absorptive capacity of peripheral regions, AI may contribute to a widening rather than narrowing of Europe’s territorial divide. The study contributes to debates on technology, regional development, and territorial inequality by demonstrating that the economic consequences of AI are shaped not only by technological progress itself but also by the uneven geography of innovation.
Territorial development in the Republic of Moldova is spatially uneven, but district typologies based on absolute volumes risk reproducing differences in population size rather than identifying substantive territorial profiles. This study constructs a size-adjusted district-level typology linking socio-economic development intensity, infrastructure provision, environmental and service-related pressure, and environmental expenditure intensity. The analysis uses the latest available mixed-year cross-section data covering 34 territorial units, while Chișinău is examined separately because of its structurally exceptional profile. Population is used as a denominator and contextual variable rather than as an active clustering indicator. Absolute measures are converted into per-capita or rate-based indicators, positively skewed variables are logarithmically transformed, and all active indicators are standardized. Principal Component Analysis (PCA) is used to summarize the correlation structure, while Fuzzy C-Means (FCM) is applied to the first three descriptive component scores. A two-cluster resolution is reported as a binary benchmark, whereas three clusters are retained as the preferred substantive typology after jointly considering fuzzy validity, membership clarity, interpretability and robustness. The results distinguish between (i) development pressure intensive districts with higher environmental expenditure intensity; (ii) intermediate development districts with lower observed pressure; and (iii) peripheral lower-intensity districts with lower environmental expenditure. GIS mapping and fuzzy membership diagnostics show that several districts occupy transitional positions rather than belonging unambiguously to a single territorial type. The findings provide a size-adjusted account of Moldova’sinternal core–periphery structure and support differentiated, place-based territorial and environmental interventions. The mixed reference years and the proxy character of waste collection and environmental expenditure as indicators are explicitly acknowledged as limitations.
On the 40th anniversary of its foundation, this editorial examines the long-term development and challenges of Tér és Társadalom (“Space and Society”, TéT). It situates the journal’s origins in an intellectual tradition rooted in a multidisciplinary approach, theoretical and methodological plurality, and a focus on the research of complex, spatially embedded social phenomena, with a slight bias towards qualitative and policy studies. It investigates how TéT emerged in the focus point of multiple disciplines concerned with spatial issues, and evolved over four decades. Through the example of four representative issues, the editorial distinguishes between a founding period with a strong emphasis on defining the outlines of the field; an expansionary golden age characterised by a fusion between empirical research and regional policy; an era of institutional uncertainty marked by disciplinary opening and theoretical refocusing; and a period of deepening international integration driven by pressures in modern academic publishing and convergence towards international standards. In contrast with improving journal metrics, the editorial also identifies risks of standardisation associated with selection mechanisms enforcing structural uniformity, while disincentivising exploratory behaviour and viewpoint diversity. This presents the risk of academic publishing’s already apparent loss of social relevance, increasing retrenchment, and increased risks of future disruptive effects. The editorial suggests that an open intellectual tradition embracing complex thinking about complex spatial phenomena, rewarding originality, and remaining open to explore unknown territory, should be the guiding star of Tér és Társadalom in securing its place in modern academic publishing.
