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on Innovation |
| By: | Federico Moscatelli; Julio Raffo; Shreyas Gadgin Matha; Christian Chacua; Matté Hartog; Eduardo Hernandez Rodriguez; Muhammed A. Yildirim |
| Abstract: | In developing countries' innovation activities, limited patenting suggests structural gaps that hinder technological progress. This paper investigates whether countries can leverage their scientific and productive capabilities to realize untapped technological potential. We analyze connections between trade, science, and technology across global innovation ecosystems and introduce an indicator to assess where countries are positioned to expand their technological capabilities. Our results show that the indicator predicts technological output growth, though growth slows when countries exceed their predicted potential, indicating diminishing returns. The indicator performs better in more complex ecosystems. These findings provide valuable insights for policymakers, offering a framework to address weaknesses in innovation ecosystems and foster balanced, sustainable technological development. |
| Keywords: | Innovation capabilities, complexity metrics, innovation ecosystems, science and technology policies, industrial policy, economic development, smart specialization |
| JEL: | O25 O31 O33 O11 O14 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:wip:wpaper:90 |
| By: | Antonin Bergeaud; Ruveyda Nur Gozen; John Van Reenen |
| Abstract: | We introduce a methodology to measure cross-country trends in innovation capability - "technological trajectories" and implement this on a new rich dataset covering patents between 1836 and 2016 across multiple countries. Intuitively, trajectories are revealed by a country's sustained increases in patenting across multiple patent offices. We first describe the data patterns, showing the relative decline of the UK, and the rise first of the US and Germany, and then later of Japan and China. We then econometrically estimate trajectories on (i) the post-1902 period for France, Germany, Japan, the UK and US, and (ii) the post-1960 period for a wider sample of 40 countries. Our trajectories are strongly positively correlated with Total Factor Productivity growth, and also (but less strongly) associated with the growth of labour productivity and capital intensity. We show that future trajectories are predicted by a country’s initial levels of R&D, education and defence spending, classic drivers of innovation in modern growth theory. |
| Keywords: | patents, technical progress, economic history, innovation |
| Date: | 2026–01–22 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2146 |
| By: | Diego Sancho-Bosch (Department of Economic Analysis, Universidad Complutense de Madrid (Spain)); Elena Huergo (ICAE – Department of Economic Analysis, Universidad Complutense de Madrid (Spain)) |
| Abstract: | This paper examines how the level of public R&D subsidies and firm size jointly influence firms’ net R&D investment. Using data on Spanish manufacturing firms from 2008 to 2018, we estimate parametric and non-parametric dose–response functions after applying entropy weighting to balance covariate distributions across treatment levels. The results reveal an inverted U-shaped relationship between subsidy intensity and net R&D expenditure for small, medium-sized, and large firms, but not for very large firms, which display a negative linear pattern. We also find substantial heterogeneity in subsidy effects within both the SME and large-firm categories, and show that the public funding share of R&D expenditure at which the positive impact of subsidies peaks declines markedly with firm size. These findings suggest that support schemes should implement progressively lower maximum subsidy rates, rather than relying on only two distinct caps for SMEs and larger firms. Overall, the results underscore firm size as a critical determinant of innovation policy effectiveness and provide practical guidance for optimizing subsidy design. |
| Keywords: | R&D support, policy evaluation, dose-response, entropy balancing. |
| JEL: | L24 L25 O32 R11 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ucm:doicae:2509 |
| By: | Jos\'e M. Gaspar; Minoru Osawa |
| Abstract: | We develop a Schumpeterian quality-ladder spatial model in which innovation arrivals depend on regional knowledge spillovers. A parsimonious reduced-form diffusion mechanism induces the convergence of regions' average distance to the global frontier quality. As a result, regional differences in knowledge levels stem residually from asymmetries in the spatial distribution of researchers and firms. We analytically characterize the processes of innovation and knowledge diffusion. We then explore how the weight of intra-relative to inter-regional knowledge spillovers interacts with freer trade to shape the spatial distribution of economic activities. If intra-regional spillovers are relatively stronger, a higher economic integration leads to progressive agglomeration. If inter-regional spillovers dominate, researchers and firms may re-disperse after an initial phase of agglomeration as integration increases. This happens because firms and researchers have incentives to relocate to the smaller region, where they can leverage the concentrated knowledge base of the larger region while avoiding congestion in innovation. The smoothness of the dispersion process depends on the particular weight of intra-regional spillovers. If inter-regional spillovers become stronger as trade becomes freer, then the latter induces a monotone dispersion process. When integration is high enough, stable long-run equilibria always maximize the growth rate of the global frontier quality and the average distance to the frontier, irrespective of whether spillovers are mainly local or global. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.06402 |
| By: | Kartiki Verma (Department of Economics, Delhi School of Economics, University of Delhi); Sunil Kanwar (Department of Economics, Delhi School of Economics, University of Delhi) |
| Abstract: | This paper examines the impact of the strengthening of intellectual property rights (IPR) on industry-level outcomes such as sales, innovation, and profitability in India, for the period 1990-2020. We first construct a novel industry-specific IPR implementation index that reflects de facto enforcement across 27 two-digit industries. Industry outcomes are then modelled using industry data at the two-digit level. The empirical results reveal significant heterogeneity in the effects of IPR regimes. Stronger IPR protection disproportionately benefits firms with higher R&D intensity, amplifying both R&D investment and profitability, with robustness checks confirming consistency across alternative specifications. However, the gains from IPR protection are less pronounced for firms heavily engaged in innovation. This interaction may also reflect a strategic shift in firm behavior rather than a decline in performance. IPR reform positively affect R&D and profitability, particularly in pharmaceuticals and advanced manufacturing. The strengthening of IPR is a powerful driver of performance when paired with internal innovation capacity, highlighting the critical role of absorptive capacity |
| Keywords: | Intellectual property rights, enforcement, de facto index, industry JEL codes: O34, C43, K11, L16 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:cde:cdewps:360 |
| By: | Lorenzo Emer; Anna Gallo; Mattia Marzi; Andrea Mina; Tiziano Squartini; Andrea Vandin |
| Abstract: | Innovation emerges from complex collaboration patterns - among inventors, firms, or institutions. However, not much is known about the overall mesoscopic structure around which inventive activity self-organizes. Here, we tackle this problem by employing patent data to analyze both individual (co-inventorship) and organization (co-ownership) networks in three strategic domains (artificial intelligence, biotechnology and semiconductors). We characterize the mesoscale structure (in terms of clusters) of each domain by comparing two alternative methods: a standard baseline - modularity maximization - and one based on the minimization of the Bayesian Information Criterion, within the Stochastic Block Model and its degree-corrected variant. We find that, across sectors, inventor networks are denser and more clustered than organization ones - consistent with the presence of small recurrent teams embedded into broader institutional hierarchies - whereas organization networks have neater hierarchical role-based structures, with few bridging firms coordinating the most peripheral ones. We also find that the discovered meso-structures are connected to innovation output. In particular, Lorenz curves of forward citations show a pervasive inequality in technological influence: across sectors and methods, both inventor (especially) and organization networks consistently show high levels of concentration of citations in a few of the discovered clusters. Our results demonstrate that the baseline modularity-based method may not be capable of fully capturing the way collaborations drive the spreading of inventive impact across technological domains. This is due to the presence of local hierarchies that call for more refined tools based on Bayesian inference. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.10224 |
| By: | Zoltan Elekes; Gergo Toth; Rikard Eriksson; Dieter Kogler |
| Abstract: | This paper examines how labour market segmentation shapes inter-occupational labour flows and the related diversification of regions, contributing new evidence to the evolutionary economic geography (EEG) literature. Using Swedish matched employer- employee data (2002-2012), we construct segment-specific occupation networks by sex, education, and country of origin to uncover heterogeneity in revealed skill-relatedness. Applying a novel measure based on normalized mutual information, we compare the structural similarity of these networks and demonstrate that while occupations may appear related on average, the underlying connections are often segment-specific. Regional diversification processes may therefore unevenly align with the redeployment potential of different worker groups. This unevenness implies that policies promoting related diversification, central to frameworks such as Smart Specialisation, may inadvertently reproduce labour market segmentation by privileging capabilities concentrated in certain groups (e.g., men, Nordic-born, or medium-educated workers). Conceptually, the paper advances the EEG agenda by integrating network science with labour segmentation theory, revealing that relatedness is not uniform but socially embedded. Regarding policy, it calls for diversification strategies that explicitly assess (i) how local skill-related activities are distributed across worker segments and (ii) whether new specialisations reinforce or mitigate local segmentation. Doing so would allow regional innovation and industrial policies to better balance efficiency and inclusiveness. This is particularly relevant in the context of “just†and “green†transitions, where aligning emerging activities with the capabilities of diverse local workforces is critical to ensuring broad-based opportunity creation rather than deepening existing divides |
| Keywords: | inter-occupation labour flows; skill-relatedness; labour market segments; regional diversification |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:egu:wpaper:2601 |
| By: | Elie Gray (TBS - Toulouse Business School); André Grimaud (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement) |
| Abstract: | We formalize inter-sectoral knowledge diffusion in a standard fully endogenous Schumpeterian growth model. Each sector is simultaneously sending and receiving knowledge; thereby, to produce new knowledge, the research and development activity of each sector draws from a pool of knowledge which stems from this diffusion. This enables us to revisit the scale effects issue by revealing how this property (inconsistent with empirical evidence) relates with knowledge diffusion (the importance of which is empirically highlighted). Weshow that suppressing knowledge diffusion across sectors is a sufficient but not necessary condition for obtaining scale-invariancy. Then, we identify several sets of assumptions which enable us to obtain models which are reasonably consistent with empirical evidence both on scale effects and how knowledge diffuses in the economy. Specifically, these models do not exhibit scale effects (or at least not significant ones) while considering various scope of knowledge diffusion (including possible occurrence of general-purpose technologies). |
| Keywords: | Schumpeterian growth theory, Scale effects, Knowledge diffusion, Knowledge, spillovers, Non rivalry, Technological distance |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04723727 |