nep-ino New Economics Papers
on Innovation
Issue of 2026–01–05
four papers chosen by
Uwe Cantner, University of Jena


  1. Artificial Intelligence Innovation by Financial Innovators: Evidence from US Patents By Jean Xiao Timmerman
  2. Decoding Regional Dynamics: Institutions, Innovation, and Regional Development in the EU By Kamila Borsekova; Samuel Korony; Andres Rodriguez-Pose
  3. Finding stars: mapping the geography of the world’s scientific elites By Rodríguez-Pose, Andrés; Lee, Neil; Xiang, Leiboyu
  4. Research Grants and Independent Scientific Contributions: Evidence from Authorship Position By Matej Bajgar; Suren Karapetyan

  1. 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
  2. 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
  3. 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
  4. By: Matej Bajgar (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic); Suren Karapetyan (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic)
    Abstract: We examine whether competitive research grants generate new research led by the supported principal investigators (PIs), distinguishing publications where the PI made a substantial intellectual contribution (first or last authorship) from all publications. Using data on Czech medical research grants awarded between 2015 and 2019, we apply augmented inverse probability weighting and regression discontinuity designs, comparing funded projects with unfunded projects just below the funding cutoff. Both methods find that grants increase total publications over five years by approximately 2 papers, or 17%. Regression discontinuity estimates further indicate that grants have disproportionately large effects on publications involving substantial intellectual contribution from the PI, increasing first/last-author publications by 1.8 papers, or 40%. Standard outcome measures that ignore authorship position may significantly understate the impact of grants on independent, PI-led scientific output.
    Keywords: Regression discontinuity design, Research funding, Scientific productivity
    JEL: O38 O30 I23
    Date: 2025–12
    URL: https://d.repec.org/n?u=RePEc:fau:wpaper:wp2025_30

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