One aspect of the UK housing crisis is the high number of households living in temporary accommodation. This paper looks at temporary accommodation households placed ‘out of area’ into other local authority areas. Whilst this may appear to be a chaotic picture of households being moved in an expedient manner to wherever there is a space, using freedom of information request data, it is possible to identify patterns in these journeys, which can be defined as linear, reciprocal and stellate. Linear describes a general movement of households in a line through various local authorities, starting with a net placer and ending with a net receiver. A reciprocal pattern is whereby two or three local authorities are, in effect, exchanging comparable numbers of households, whilst a stellate pattern is where one local authority is a hub that is placing households into a variety of neighbouring local authorities. The paper further argues that the nature of out of area housing illustrates the increasingly important yet persistently overlooked nature of what we call ‘local-local relationality’.
The role of agency and local leadership is gaining attention as a key driver of regional economic resilience. This paper addresses two underexplored questions in this growing body of literature: (1) How do institutional factors shape the emergence of local leadership? and (2) What forms does local leadership take? To address these questions, we examine three cases: Lille (France), Dortmund (Germany) and the Basque Country (Spain), which all experienced severe socio-economic decline due to structural shifts in the global economy, compounded by a series of interrelated global shocks. However, each of the cases managed to carve out new development paths and are now frequently cited as models of regional economic resilience. Despite differing approaches to renewal, a common thread across the cases is the central role of local leadership in driving long-term transformation, making them ideal case studies to explore our two research questions.Our findings show that, although the Basque Country, Lille and Dortmund operated within distinct institutional settings, local public sector institutions were key initiators of renewal strategies. However, success depended on their ability to create a shared vision and foster collaboration among a range of actors. Personal leadership emerged as a critical enabling factor, especially during the early phases of transition, providing the essential backbone from which both multi-actor, place-based leadership and institutional leadership could emerge and consolidate. The institutional framework also served as a key facilitator: the interaction between crisis conditions and the decentralisation of competences and funding created an opportunity space for local leadership.
This study proposes an approach for measuring the spatial configuration of corruption risk in public procurement across regions, moving beyond traditional incidence-based indicators to capture how corruption risk is spatially distributed and clustered. Using a novel municipal-level public procurement dataset for Italy, we apply Local Indicators of Spatial Association (LISA) and develop the procurement index of corruption shape (PICS). The empirical application to the Italian case illustrates the analytical properties and interpretability of the index. Results reveal heterogeneous spatial configurations across Italian regions. Northern regions display concentrated high-risk clusters, consistent with localised and more visible rent-seeking behaviour. In contrast, southern regions exhibit widespread low-risk clusters, indicative of more systemic and less detectable forms of corruption, often linked to pre-bidding collusion and cartelisation. The paper’s main contribution is methodological as it introduces a spatial dimension into corruption risk measurement that can be adapted to different institutional contexts. Empirically, it provides granular sub-national evidence and, theoretically, it suggests that corruption adapts to institutional contexts and may coexist with economic performance. Our findings highlight the importance of spatially and context-specific anti-corruption policies and have broader relevance for countries characterised by regional disparities.
This paper investigates the influence of a shock and associated uncertainty in the context of higher education in a peripheral region, offering a novel perspective. By using an integrated methodology, based on multivariate Biplot and Combination of Uniform and Shifted Binomial (CUB) models, the study explores how an exogenous event, such as the COVID-19 pandemic, has affected students’ decision-making processes regarding their higher education choices and mobility preferences amid uncertainty. The empirical application employs online survey data from a representative sample of university students in Sardinia (Italy). Its geographical isolation from the mainland provides a controlled environment to address the effect of the shock on higher education. Findings indicate that bachelor’s students are greater risk takers and prefer blended learning, while master’s students focus on personal and career goals. Missed migrants, who would have studied outside the region if not for COVID-19, prioritise educational quality and economic returns. Although the shock affected both stayers and missed migrants similarly, it did not fundamentally shift mobility motivations.
Regional development faces mounting challenges, including persistent inequalities, climate change and social fragmentation, that render regional futures increasingly complex and contested. Traditional approaches grounded in path dependence and structural analysis often overlook the role of imagination, agency and contested visions in shaping future trajectories, leaving a critical gap: the absence of forward-looking, inclusive and methodologically diverse tools to study and influence regional futures. This article presents a comparative review of eight methodological approaches that together constitute a pluralistic toolbox for studying regional futures. We organise these methods into three clusters evaluating each by purpose, techniques, data requirements and user suitability. Drawing on recent literature and empirical cases, we show how their integration reveals power dynamics, fosters agency and supports ethical, inclusive futures. We conclude with a call for critical reflexivity regarding the politics of knowledge production.
This study measures the regional inequality embedded in Mexico's interregional productive articulation by combining the hypothetical extraction method with the spatial Gini decomposition, applied to Mexico's 2018 multi-state input-output matrix. Productive articulation is concentrated in the Central and Northern regions, while the Southern region remains structurally disconnected. Within this uneven geography, the capacity to supply intermediate inputs is more territorially concentrated than the capacity to consume them, generating supply-chain bottleneck risks. The regional disparities arise primarily from gaps between distant clusters of entities rather than between neighbours. This spatial pattern varies across sectoral categories, as services and technology-based manufacturing contribute significantly to regional inequality, whereas strengthening the primary sector and resource-based manufacturing may help narrow regional disparities. These findings are relevant to Mexico's current industrial policy agenda, offering insights into the design of instruments that strengthen productive linkages without deepening regional inequality.
Similar to other markets, the housing market has a supply side. As previous studies focused on the demand side of the market, this study departs from this known literature by examining the local and broader influences of the housing supply markets across metropolitan cities. Theoretically anchored in DiPasquale and Wheaton's (1994) housing stock flow model, I adopt the Poisson regression and seemingly unrelated regression (SUR) to examine housing supply dynamics within and beyond. I contribute to the literature in several ways: first, external market drivers like housing lending rates, net internal migration and the number of investors resulted in a three-tier market, especially in the non-strata segment. The top-tier non-strata housing markets, Sydney and Melbourne, are largely driven by investor activity, while middle-tier markets, Brisbane and Adelaide, are influenced by net population movement between cities. The bottom tier, Perth and Hobart, is affected solely by housing lending rates. Second, at the local level, rent and price are key factors influencing building starts in Greater Sydney and Melbourne for the non-strata market. This drives investor activity in these top-tier markets, indicating that local factors reinforce external influences. In the strata market, the vacancy rate, combined with rent and price, determines housing starts. Third, the macro-micro framework for both non-strata and strata dwellings illustrates how various market and property variables influence the flow of housing stock. These findings could aid the decisions of several housing stakeholders, including policymakers, developers, homebuyers and investors.
Balancing health and economic outcomes has been central to pandemic policy debates, yet differentiating the impacts of various intervention intensities remains challenging. To manage COVID-19 outbreaks, China implemented an area-based risk-rating system that classified small areas within cities as low-, medium- or high-risk based on local case counts. This paper examines the effects of medium- versus high-risk designations on travel behaviour during the Zero-COVID period, using a dynamic difference-in-differences approach. It further analyses the weekly travel trajectories of 368 Chinese cities during both pandemic and reopening periods within a non-linear time-varying latent factor framework. Leveraging the latest Baidu mobility data and national risk level information, our findings demonstrate that high-risk designations significantly drive shifts toward work-related trips, and the impact tends to extend beyond the affected localities. People began reacting to high-risk eight days before extensive lockdowns, and the effects persisted for approximately four weeks afterward, longer than the typical lockdown duration. Additionally, our results reveal stratified mobility dynamics, highlighting that (a) cities in western China exhibited lower resilience during the Zero-COVID period and (b) regional disparities widened during this period but gradually diminished with reopening. This study offers transferable lessons for future pandemic preparedness, demonstrating how tiered risk designations can generate responses that extend beyond targeted zones and how regional disparities in mobility evolve through crisis and recovery periods.
The Republic of Croatia benefited from the IPA Rural Development Programme (IPARD) until its accession to the EU on 1 July 2013. Funds from the IPARD programme supported 691 projects in Croatian counties by the end of 2016. Measure 301 of the IPARD programme aimed at improving and developing rural infrastructure. This article examines the geographical distribution of IPARD projects across Croatian counties and the implications of Measure 301 on transport and communal infrastructure in Istrian County. The research relies on primary and secondary data from scientific articles, studies and dissertations. Original analysis results show that Istria and Osijek-Baranja counties were the most successful, with 114 and 81 projects, respectively, while Lika-Senj and Sibenik-Knin counties implemented only nine projects in total. In Istria County, 14.9% of projects were in less developed municipalities, and 85.1% were in more developed ones. These projects improved transport connections and municipal water infrastructure, enhancing the quality of life in Istrian municipalities and cities. These findings have broader implications for EU pre-accession assistance currently being implemented in western Balkan countries and Turkey. The Croatian experience demonstrates that pre-accession instruments, despite intentions to support convergence, may inadvertently reinforce territorial disparities when programme design fails to account for differential regional absorption capacity. The article contributes to debates on territorial cohesion by providing empirical evidence of how administrative complexity, co-financing requirements and reimbursement mechanisms systematically disadvantage less developed regions insights applicable to pre-accession instrument design across candidate countries.
This study examines how national mission-oriented innovation policies are translated into territorially embedded strategies through regioning processes. Using Zhongguancun Science Park - China's first state-sanctioned science park - as a longitudinal case study, the research traces four development phases (1988-2024) and compares three sub-park models to reveal how cognitive, relational and structural mechanisms shape differentiated local pathways under shared national policy frameworks. The findings suggest that policy translation constitutes an iterative process characterised by path-dependent dynamics and influenced by feedback interactions between local experimentation and national priorities. Haidian Park developed a knowledge-driven translation model, Changping Park evolved into an industry driven approach, while Fengtai Park exhibited integration-driven characteristics. These differentiated models demonstrate that the successful implementation of mission-oriented policies requires careful consideration of local institutional contexts, industrial foundations and governance traditions. The study extends the regioning concept beyond its original European federal contexts to China's tiao-kuai (vertical-horizontal) governance system, thereby enriching the theoretical framework of mission-oriented innovation policy. The empirical analysis confirms that effective policy translation necessitates coordinated efforts across meaning reconstruction (cognitive dimension), network formation (relational dimension) and institutional adaptation (structural dimension). The research offers policy insights for enhancing spatial sensitivity in mission governance, emphasising the importance of establishing multi-level feedback architectures and adaptive regulatory infrastructures.
This paper investigates the structural foundations of regional productivity divergence in Italy through the lens of economic complexity. Leveraging a newly constructed complexity index for Italian provinces, I examine how the sophistication and diversity of local productive structures shape productivity trajectories over the period 2000-2021. Empirical approach combines panel data models with instrumental variable techniques, spatial econometrics, and simultaneous equation systems to capture the direct, spatial and cumulative relationships between complexity and productivity. The findings reveal that economic complexity is a robust and consistent predictor of regional labour productivity. This association is particularly strong in northern provinces, where spatial spillovers from neighbouring territories enhance local outcomes. In contrast, southern regions experience lower returns and limited externalities. Crucially, I provide the first integrated empirical evidence of a cumulative, self-reinforcing loop between complexity and productivity: more complex regions become more productive, and more productive regions are better equipped to diversify into complex activities. Instead, lagging territories - trapped in traditional activities - face structural barriers to undertake dynamic growth trajectories.
This paper investigates the diversity of territorial representations resulting from different methods used to identify urban, rural and intermediate territories in European countries. The current debate about territorial delimitation revolves around two contrasting approaches: sophisticated techniques that capture local territorial nuances or harmonised methods that prioritise international comparability. Using Lombardy as a case study, this paper demonstrates how different classification methods produce different territorial representations. Discrepancies stem from the selection of variables, spatial unit delineation and the number of territories identified. Such variations can significantly impact the proportion of local population included in each territorial class and consequently affect eligibility for place-based policies. Moreover, differences also exist between locally relevant and harmonised methods. The former reveal greater territorial complexity, while the latter provide broader, less detailed territorial classifications, bringing significant implications for both policy design and spatial planning. The adoption of one method over another requires reflection on contemporary spatial and functional disparities, as well as on distinct institutional configurations.
The rapid expansion of the digital economy in Africa over the past few decades has drawn the attention of this paper, which aims to analyse its spillover effects on the economic growth of African countries. Using the spatial Durbin model (SDM) on data from 46 African countries spanning the period 2010-2021, the estimation results indicate a positive spatial interdependence between countries in terms of the diffusion of the digital economy and economic growth. An improvement in the level of the digital economy in one country has a positive and significant influence on economic growth in that country and its neighbouring countries. For this reason, an improvement in the level of digital infrastructure and a strengthening of the level of integration of African countries are necessary for more sustained economic growth in Africa.
Small- and medium-sized technology enterprises (SMTEs) are fundamental drivers of regional innovation. Understanding their spatial distribution is crucial for optimising resource allocation. This study analyses 4334 gazelle and 283 unicorn enterprises across 110 cities in China's Yangtze River Economic Belt (2016-2022). Using the Dagum Gini coefficient, hotspot analysis and spatial econometric models, we systematically characterise their spatiotemporal patterns and determinants, contextualised by comparison with the Rhine and Mississippi River economic belts. The findings reveal a composite spatial pattern of 'gradient differentiation, core anchoring and corridor diffusion'. Inter-regional disparities account for 47.3% of the total variation, with core zones concentrating 65.68% of enterprises. Diffusion along key corridors (e.g., G42 Highway, elasticity 0.8) is significantly stronger than in comparator basins. Mechanism analysis identifies foreign capital, R&D investment and talent as key drivers, while fiscal expenditure exhibits a complex dual effect. Critically, gazelle and unicorn enterprises show divergent locational responses, revealing a 'dual divergence' logic shaped by innovation factor prioritisation and ecological embeddedness. This study extends location theory within the innovation economy and provides an evidence base for differentiated SMTE policies in transitional economies.
The rapid expansion of work-from-home (WFH) during the COVID-19 pandemic accelerated the decoupling of residence from the workplace and created a natural experiment for examining the link between job and population growth across US cities and regions. This study uses descriptive statistics and spatial autoregression modelling to examine inter-regional shifts and intra-metropolitan redistribution, and the role of WFH in these changes. The results show that long-standing growth trajectories largely persisted: population growth continued in affordable Sunbelt regions and suburban areas, while slowing in several coastal superstar metropolitan areas. Within metropolitan areas, central counties grew more slowly than suburban and smaller counties, regardless of their regional location. Regarding employment, WFH intensity was positively associated with post-pandemic growth at the metropolitan scale. Intra-metropolitan redistribution linked to WFH followed a doughnut-type pattern, with higher remote work intensity associated with relative population losses in large central counties and gains in suburban and smaller counties. Structural factors such as housing affordability, industrial base and demographic composition were more consistently associated with growth than WFH alone. Overall, the findings suggest that remote work reinforced and reconfigured existing spatial patterns rather than overturning national hierarchies.
This study introduces a dual, data-driven framework for mapping organised crime in Italy by constructing and cross-validating two complementary, per-capita indices aggregated through a non-compensatory composite methodology. The municipal index mines more than a decade of ANSA (Agenzia Nazionale Stampa Associata) news (2012-2023) using Natural Language Processing to extract and geolocate mafia-related events at the municipality level, and complements these signals with computer-vision/optical character recognition (OCR) extraction of clan presence from DIA (Direzione Investigativa Antimafia) investigative maps. The provincial index relies on official records of mafia-related offenses, the dissolution of local administrations due to mafia infiltration and the number of clans, all normalised by population. Across provinces, the composite indices align strongly (a correlation approximate to 0.75). Moreover, for the two offenses unambiguously linked to mafia activity (Type I offenses), news-based counts correlate closely with official records (0.92 for mafia association and 0.88 for mafia-type murders/attempted murders), supporting the use of media narratives as a proxy for underreported activity.
Over the past two decades, China’s urban house market has experienced significant price appreciation, driven by a sustained influx of population. However, as population shrinkage has become an increasingly notable urban phenomenon, its interaction with house prices remains inadequately understood, particularly within the institutional context of China’s household registration (hukou) system. This paper examines the effect of population change on house prices by incorporating the role of a city’s hukou value, using Dongguan as a case study. By disaggregating the population by two hukou-based categories (i.e., hukou location and hukou type), this study presents three main findings: (1) The hukou influences the relationship between house prices and population change, with house price appreciation closely linked to increases in both the household population and the urban hukou population. (2) While house prices respond synchronously to the growth in these population groups, their response to the shrinkage of temporary residents and rural hukou population exhibits a distinct temporal hysteresis. (3) The effect of population change on house prices remains confined within towns, even though there are broader spatial spillovers across Dongguan’s towns in the house market.
We apply the synthetic control method (SCM) to evaluate the impact of the 2017-2020 New South Wales drought, one of the most severe in Australia's recorded history, on regional agricultural labour markets. Using 25 years of quarterly employment data, we construct region-specific counterfactuals for 14 non-metropolitan Statistical Area Level 4 (SA4) regions. Most regions exhibit limited long-term effects on agricultural employment. However, the Hunter Valley region experienced a sharp and persistent decline in agricultural employment, with levels up to 75% below those of its synthetic control and no sign of recovery years after the drought ended. This divergence reflects a place-specific adjustment path in which drought disruptions were compounded by subsequent climatic and market shocks, including bushfires, flooding and trade disruptions, resulting in persistent labour-market effects rather than a transitory response. Complementary evidence on the employment structure indicates widespread short-term shifts from full-time to part-time agricultural work, suggesting that drought impacts affect not only employment levels but also job quality and income stability. By providing a within-country, multi-region application of SCM to drought impacts on labour markets, the study contributes to understanding regional economic resilience and demonstrates the value of spatially disaggregated causal methods for identifying persistent vulnerability and informing targeted adaptation strategies.
Using invention patent data for 286 Chinese cities between 1991 and 2020, this study examines how urban technological diversity shapes the creation and diffusion of new knowledge combinations. First, urban scaling analyses reveal a strongly super-linear relationship between technological diversity and the number of new combinations, with the scaling exponent rising from just above 1.0 in the early 1990s to over 2.2 by 2020, indicating increasing returns to technological diversity in urban innovation systems. Cities with broader technological portfolios therefore generate disproportionately more new knowledge combinations. The analysis also distinguishes between types of recombination. Atypical combinations that connect cognitively distant technologies show stronger scaling effects than typical combinations, underscoring the importance of diverse cities in generating novel and potentially breakthrough innovations. Second, the paper examines how newly generated combinations diffuse across cities using event-history models. Results show that diffusion is strongly shaped by multi-dimensional proximity: geographic distance reduces the likelihood of adoption, while cognitive proximity and social proximity significantly accelerate diffusion. Overall, the findings demonstrate how urban technological diversity drives knowledge recombination and how multiple forms of proximity structure the spatial diffusion of new technological combinations across Chinese cities.
This study investigates how intra- and extra-regional collaborations affect regional technological diversification in Chinese urban regions (URs), using a continuous indicator that places diversification along a spectrum from related to unrelated. Based on patent co-application data from 2001 to 2020, we analyse the intensity, technological diversity and the correlation of intra- and extra-regional collaborations. Our results show that the effects of (1) intra-regional collaboration intensity on related diversification and (2) extra-regional collaboration diversity on unrelated diversification are both curvilinear. In addition, extra-regional intensity and the correlation between intra- and extra-regional collaborations foster related diversification. Moreover, economic disparities within URs reinforce, rather than weaken, the positive influence of intra-regional intensity and intra-extra technological correlation on related diversification. These results challenge conventional assumptions and highlight the importance of coordinated collaboration structures in promoting regional diversification, especially under uneven regional development conditions.
