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on Small Business Management |
| By: | Kamila Borsekova; Samuel Korony; Andres Rodriguez-Pose |
| Abstract: | The importance of institutions and innovation for regional development is well established. How these two factors interact under different historical legacies and urban-regional contexts remains, however, insufficiently understood. This paper identifies which combinations of institutional and innovation indicators most effectively classify regions into distinct developmental archetypes, revealing critical thresholds that redirect regional trajectories. Employing decision-tree analysis on 233 EU NUTS-2 regions, we analyse 15 indicators spanning institutional quality, technological readiness, business sophistication, and innovation. This methodology uncovers non-linear relationships that traditional approaches cannot capture. The findings demonstrate that institutional quality acts as a necessary condition for innovation-led growth. High-performing regions, predominantly in Western and Northern Europe, benefit from robust institutions and strong innovation outputs. Many lower-performing regions, particularly in Central and Eastern Europe, exhibit innovation potential but are constrained by governance deficits. By integrating institutional and innovation indicators within a single analytical framework, we underscore how addressing governance and innovation in tandem can result in balanced and sustainable growth across Europe. |
| Keywords: | regional development, institutions, innovation, decision tree modelling, regional competitiveness |
| JEL: | O18 O43 R11 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2538 |
| By: | Ngoc-Sang Pham; Thi Kim Cuong Pham; Trong Tin Nguyen; Cuong Le Van |
| Abstract: | We develop a dynamic endogenous-growth model with an R&D sector in which the elasticity of innovation with respect to existing knowledge can be negative. We prove the existence and uniqueness of a balanced growth path (BGP) and derive closed-form growth factors, showing that productivity and output growth are semi-endogenous and population-driven. We also establish the global stability under general production function. Under testable parameter restrictions, the economy converges to the BGP. When the knowledge elasticity is sufficiently low, a Jacobian-based condition implies instability, and an N-period innovation cycle can emerge. Comparative statics are conducted to show the role of several factors, including research efficiency, elasticity of inputs and population growth. Calibrated simulations map out transitions and mark the points at which stability is lost. They make clear when innovation frictions endanger balanced growth and provide practical guidance for R&D and demographic policy. |
| Keywords: | endogenous growth, population-driven growth, balanced growth path, stability, instability, innovation, monotone dynamical system. |
| JEL: | C62 O31 O41 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:drm:wpaper:2025-46 |
| By: | Pierre-Louis Vézina; Cevat Giray Aksoy; Piotr Lewandowski |
| Abstract: | We examine business creation by Ukrainian refugees in Poland following the Russian invasion. We find that Ukrainians started 38, 833 firms in 2022–23, accounting for 7% of all registrations. Our survey shows that 58% of post-invasion Ukrainian founders are refugees, and cross-county regressions show that a 10% increase in adult male Ukrainian refugees is associated with a 2.7% increase in Ukrainian firm registrations. We then show that new Ukrainian businesses stimulate Polish entrepreneurship. Using a shift-share strategy based on refugee shocks and Ukrainians’ comparative advantage, we find that a 10% increase in Ukrainian registrations led to 2.3% more Polish firms. |
| Keywords: | migration, firms, entrepreneurship, multiplier |
| JEL: | F22 L26 O15 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:ibt:wpaper:wp072025 |
| By: | Jean Xiao Timmerman |
| Abstract: | This paper examines the evolution of artificial intelligence (AI) patent rates (i.e., the number of AI patents/number of firms of the same type) and concentration metrics (i.e., the Herfindahl-Hirschman Index (HHI) and Gini coefficient) among financial market participants from 2000 to 2020. It documents the historical trajectories of AI innovation for regulated banking entities and less-regulated firms, revealing that nonfinancial companies exhibit the highest baseline AI patent rate, while banks show the highest growth in AI patent rate over time. Banks have the highest HHI, and nonfinancial companies have the highest Gini coefficient, suggesting that a small number of banks dominate AI innovation and the distribution of AI innovation at nonfinancial firms � though higher in number � is highly skewed toward a subset of players. These findings indicate that the AI technological gap between small and large banks may be widening and the diversity of nonfinancial companies serving as third-party AI service providers may be limited. |
| Keywords: | Artificial intelligence; Banking; Financial innovation; Patents; Regulatory perimeter; Technological change |
| JEL: | G21 G23 G28 O31 O33 |
| Date: | 2025–12–12 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:2025-104 |
| By: | Andres Rodriguez-Pose; Leiboyu Xiang; Neil Lee |
| Abstract: | This paper presents the first systematic city-level mapping of global scientific talent, analysing the top 200, 000 star scientists across 3, 635 cities worldwide annually between 2019 and 2023. We use a novel Knowledge Generation Index (KGI) that combines researcher quantity with research impact to reveal extreme spatial concentration in knowledge production. Just four cities — New York, Boston, London and the San Francisco Bay Area — host 12% of the world's star scientists, while much of the Global South remains virtually excluded from frontier research. Beijing's ascent into the global top ten represents a rare challenge to established hierarchies. Our analysis uncovers striking disciplinary variations. Resource-intensive fields like clinical medicine cluster heavily and traditionally dispersed disciplines are increasingly gravitating toward major hubs. Despite these differences, concentration is intensifying across most scientific fields. Even the pandemic's remote collaboration experiment failed to level the playing field. Established innovation centres continued strengthening their advantages while peripheral regions fell further behind. Overall, we find that geography remains destiny, with profound implications for innovation policy confronting widening spatial inequalities in global scientific capacity. |
| Keywords: | Star scientists; geography of knowledge; innovation agglomeration; spatial inequality |
| JEL: | O25 O31 R12 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2540 |
| By: | Suleyman Faruk Gozen; David Hong; Mehmet Furkan Karaca |
| Abstract: | We study how non-rival intangible capital interacts with borrowing structure and financial frictions to shape firm dynamics over business cycles. We show: (i) the positive and significant association between intangible-capital growth and labor productivity growth becomes smaller in recessions; (ii) the non-rivalry of intangible capital is evident such that intangible growth predicts faster sales growth and broader firm scope, yet this relationship declines in recessions; (iii) intangible-intensive firms carry less total and secured debt, and substitute toward earnings-based covenant (EBC) borrowing over asset-based covenant (ABC) borrowing; and (iv) intangible-intensive firms with EBC have tightening financially constraints in recessions, which mitigates the productivity payoff of non-rival intangibles. We rationalize these patterns in a general-equilibrium model in which firms draw EBC/ABC constraints at entry and intangibles are non-rival in the firm production technology. The model yields a creditamplification mechanism with heterogeneous borrowing types, reconciling the productivity slowdown despite rising intangibles |
| Date: | 2025–04–02 |
| URL: | https://d.repec.org/n?u=RePEc:bri:uobdis:25/815 |
| By: | Rodríguez-Pose, Andrés; Lee, Neil; Xiang, Leiboyu |
| Abstract: | This paper presents the first systematic city‐level mapping of global scientific talent, analysing the top 200, 000 star scientists across 3635 cities worldwide annually between 2019 and 2023. We use a novel Knowledge Generation Index (KGI) that combines researcher quantity with research impact to reveal extreme spatial concentration in knowledge production. Just four cities—New York, Boston, London and the San Francisco Bay Area—host 12% of the world's star scientists, while much of the Global South remains virtually excluded from frontier research. Beijing's ascent into the global top 10 represents a rare challenge to established hierarchies. Our analysis uncovers striking disciplinary variations. Resource‐intensive fields like clinical medicine cluster heavily, and traditionally dispersed disciplines are increasingly gravitating towards major hubs. Despite these differences, concentration is intensifying across most scientific fields. Even the pandemic's remote collaboration experiment failed to level the playing field. Established innovation centres continued strengthening their advantages while peripheral regions fell further behind. Overall, we find that geography remains destiny, with profound implications for innovation policy confronting widening spatial inequalities in global scientific capacity. |
| Keywords: | geography of knowledge; innovation agglomeration; spatial inequality; star scientists |
| JEL: | N0 |
| Date: | 2025–12–17 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:130377 |
| By: | Maczulskij, Terhi |
| Abstract: | Abstract This paper examines how firms’ innovation activity responds to product- and destination-specific export demand shocks in their export markets. I draw on unique administrative data for Finnish manufacturing firms from 1999 onwards, matched with national customs records, patent data, and innovation and R&D surveys. The analysis reveals that positive export demand shocks significantly increase patenting activity and the likelihood of introducing new product innovations, while negative shocks reduce patenting and exports. The study finds that these innovation responses are dynamic, with patent applications rising in the short term and granted patents materializing over longer horizons. Heterogeneity analysis shows that more productive and financially stronger firms benefit disproportionately from export demand expansions. This pattern suggests that financial constraints may limit the ability of firms to adopt new innovations even as they expand production. |
| Keywords: | Export demand shock, Firm-level, Innovation, Manufacturing |
| JEL: | F14 O19 O30 |
| Date: | 2025–12–22 |
| URL: | https://d.repec.org/n?u=RePEc:rif:wpaper:134 |
| By: | M. Sadra Heydari; Zafer Kanik; Santiago Montoya-Bland\'on |
| Abstract: | We introduce heterogeneous R&D productivities into an endogenous R&D network formation model, generalizing the framework in Goyal and Moraga-Gonzalez (2001). Heterogeneous productivities endogenously create asymmetric gains for connecting firms: the less productive firm benefits disproportionately, while the more productive firm exerts greater R&D effort and incurs higher costs. For sufficiently large productivity gaps between two firms, the more productive firm experiences reduced profits from being connected to the less productive one. This overturns the benchmark results on pairwise stable networks: for sufficiently large productivity gaps, the complete network becomes unstable, whereas the Positive Assortative (PA) network -- where firms cluster by productivity levels -- emerges as stable. Simulations show that the PA structure delivers higher welfare than the complete network; nevertheless, welfare under PA formation follows an inverted U-shape in the fraction of high-productivity firms, reflecting crowding-out effects at high fractions. Altogether, a counterintuitive finding emerges: economies with higher average R&D productivity may exhibit lower welfare through (i) the formation of alternative stable R&D network structures or (ii) a crowding-out effect of high-productivity firms. Our findings highlight that productivity-enhancing policies should account for their impact on endogenous R&D alliances and effort, as such endogenous responses may offset or even reverse the intended welfare gains. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.23337 |
| By: | Inmaculada C. Alvarez; Javier Barbero; Luis Orea; Andres Rodriguez-Pose |
| Abstract: | Most studies of institutional quality and regional growth assume uniform effects across territories. However, this may mask crucial regional heterogeneity, with direct policy implications. We use a latent class framework applied to 230 EU regions over 2009-2017 to identify institution-driven regional parameter groups, and to examine both average effects and catching-up effects associated with changes in the institutional environment. We demonstrate that institutional quality generates highly variable returns to investment in physical capital and innovation. Nordic and Central European regions show highest returns to physical capital and R&D investment, whereas less-developed regions benefit most from education spending. Crucially, we find that improving government quality not only raises average returns but also promotes territorial cohesion. By contrast, regional autonomy shows limited impact on returns. Our findings challenge the one-size-fits-all approach to cohesion policy and indicate that cohesion policy should explicitly promote institutional improvements in addition to capital deployment. |
| Keywords: | Institutional quality, European funds, investment, regional development |
| JEL: | O43 E61 H54 R11 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2537 |