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on Technology and Industrial Dynamics |
| By: | D'Alessandro, Francesco; Santarelli, Enrico; Vivarelli, Marco |
| Abstract: | This study examines how regional technological relatedness and local AI knowledge influence regional innovative activity, as measured by patenting activity. Using a novel three-way longitudinal dataset (670 four-digit CPC classes × 302 NUTS-2 regions × nine four-year periods, 1986-2021) and leveraging a deep learning-based identification of AI patents, we show that two broad mechanisms operate in parallel. First, in accordance with the extant literature, technologies that are cognitively close to a region's existing patent portfolio enjoy higher patenting activity, confirming that relatedness remains a strong and persistent predictor of innovative output. Second, local AI endowments are positively associated with patenting across technological fields, even after conditioning on relatedness, indicating that AI plays an enabling and cross-cutting role in a given regional innovation system. Moreover, the interaction between relatedness and AI turns out to be negative and statistically significant, implying that AI attenuates the extent to which local innovative efforts depend on the technology's proximity to the regional portfolio. In sum, AI appears to enhance overall local innovative activity while reducing its reliance on pre-existing regional knowledge structures. |
| Keywords: | Artificial intelligence, AI, technological change, regional innovation, relatedness |
| JEL: | O31 R11 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1792 |
| By: | Ina Ganguli; Jeffrey Lin; Vitaly Meursault; Nicholas Reynolds |
| Abstract: | Over nearly two centuries, U.S. inventions have become increasingly dissimilar: not just fewer head-to-head collisions between inventors, but growing distance between neighboring inventions. We document this secular decline in similarity using validated neural language models applied to the full text of claims in over 11 million U.S. patents (1836–2023), corroborated by a 98 percent decline in patent interference rates, a measure of independent simultaneous invention. Measuring this correctly requires validation, since different representations of the same patent text can yield opposite conclusions about whether inventions are converging or spreading out. Our validation framework, the first systematic comparison for patent text, selects among these locations in idea space. The model explains spreading out and connects it to several independently documented patterns — rising R&D investment per inventor, increasing patent values, weakening knowledge spillovers, and declining research productivity. The mechanism is spatial; as inventors spread out to capture new territory, inventions become more valuable but also more costly for others to absorb. In doing so, the model turns spillover intensity, innovation step size, and research productivity from fixed primitives into outcomes of inventor positioning. A calibrated decomposition attributes roughly 40 percent of the long-run decline in U.S. research productivity to these spatial forces, alongside traditional explanations such as fishing out and the burden of knowledge. Where inventors stand relative to each other in idea space matters as much for growth as how many of them there are. |
| Keywords: | Idea Space; Knowledge Spillovers; Research Productivity; Endogenous Growth; Technological Distance; Patent Embeddings |
| JEL: | O31 O41 O47 C55 |
| Date: | 2026–08–05 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedpwp:103607 |
| By: | Tiago Neves Sequeira (University of Coimbra, Faculty of Economics and CeBER) |
| Abstract: | Many frontier technologies generate both civilian and military applications, raising the question of how policies targeting one application influence innovation when knowledge is shared across sectors. This paper develops a Schumpeterian model of directed technical change in which civilian, military and dual-use technologies coexist as endogenous innovation ladders. The key innovation is to distinguish between a non-rival stock of knowledge generated by dual-use research and rival intermediate goods supplying civilian and military markets. Consequently, policy interventions in one sector redirect research incentives throughout the economy. The model admits a stable balanced-growth path with an interior allocation of research effort. A calibration based on U.S. patent stocks, aggregate R&D intensity and defence R&D expenditure illustrates the transition dynamics. Modest policy interventions substantially redirect innovation towards dual-use technologies, generating civilian knowledge spillovers while leaving long-run aggregate growth largely unchanged. |
| Keywords: | Directed technical change, dual-use innovation, endogenous growth, defense R&D, Schumpeterian growth, industrial policy |
| JEL: | O31 O32 O33 O40 H56 L16 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:gmf:papers:2026-06 |
| By: | Alice Albonico; Marco Guerzoni |
| Abstract: | Is the aggregate productivity slowdown in the U.S. driven by a decline in successful innovation? This paper addresses this question using a medium-scale DSGE model with endogenous technology growth. The model distinguishes between two innovation channels: a spillover channel, which governs the efficiency with which aggregate R&D advances the technological frontier, and a difficulty channel, which governs the probability that sectoral R&D efforts successfully generate innovation. We estimate the model on U.S. macroeconomic and R&D data over the period 1984-2019, using macroeconomic observables and incorporating a patent-text-based measure of technological creativity that is informative about innovation probability. The results show that spillover shocks are the main drivers of short and medium run fluctuations in TFP growth, while R&D difficulty shocks mainly explain the probability of successful innovation. Once creativity data are included, the estimated difficulty shock becomes less volatile and more persistent, suggesting that innovation difficulty is a slow moving force shaping successful innovation. However, its quantitative contribution to TFP fluctuations remains substantially smaller than that of spillover shocks, although it matters in specific episodes. |
| Keywords: | Innovation Difficulty, Endogenous growth, R&D investments, Bayesian estimation |
| JEL: | E3 O3 O4 C11 C13 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:mib:wpaper:580 |
| By: | Colin Caines; Florian Hoffmann; Gueorgui Kambourov |
| Abstract: | We document a strong, positive relationship between occupational problem complexity, measured from US data on problem-solving requirements, and occupational wage growth since 1980. In contrast, employment shifts toward more complex occupations have been modest, suggesting a race between the demand for and supply of complex skills. We rationalize these findings by formulating and structurally estimating a quantitative general equilibrium model on the granular occupational level. In our model, workers have heterogeneous comparative advantages in solving complex problems and physical capital admits capital-skill complementarity in occupation space. The equilibrium features Positive Assortative Matching of worker skills to occupational problem complexity, and the model quantitatively explains the evolution of the occupational wage- and employment structure over the last four decades. The model estimates uncover two distinct periods of technological change. Until around 2000, rising complexity premia were driven by capital-skill complementarity and declining equipment capital prices. Post-2000 patterns reflect supply-side technological change whereby occupations became more efficient in utilizing worker skills for complex problem-solving. Our framework helps unify distinct approaches to studying task automation and task augmentation on the one hand and skill-biased technological change on the other. |
| Keywords: | Occupational Task Content; Complex Tasks; Wage Polarization; Skills |
| JEL: | E24 J21 J23 J24 J31 |
| Date: | 2026–07–24 |
| URL: | https://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-825 |
| By: | Franziska Tinnefeld (Università Cattolica del Sacro Cuore and Fondazione Eni Enrico Mattei); Florian Wagener (Universiteit van Amsterdam) |
| Abstract: | We develop a multi-region, multi-sector Romer-type dynamic partial equilibrium model of endogenous growth. We calibrate on equally sized regions North, East, and South, based on data from Germany, Poland, and China. We compare the effect of trade block formation on innovation outcomes. Integration leads to aggregate increase in both product and process innovation, resulting in aggregate welfare gains. These are concentrated in North: the research sectors of East and South collapse. Our findings explain data from eastern European countries, as well as current R&D policies in China that are designed to avoid downstream lock-in. |
| Keywords: | product innovation, process innovation, integration |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:fem:femwpa:2026.20 |
| By: | Krieger, Bastian; Steines, Leon; Bangert, Hendrik Hermann; Glas, Andreas; Eßig, Michael |
| Abstract: | Public organizations rely on open innovation to maintain and improve public service performance. Suppliers are a key source of such innovation. Public contracting authorities act as the interface between public organizations and supply markets, shaping whether supplier innovations are identified, rewarded, and selected. Combining representative firm-level data from the German Community Innovation Survey with official tender-level data from the Tenders Electronic Daily database, we construct firms' public procurement award histories between 2006 and 2023. We distinguish between four tender categories that differ by geographic scope (domestic versus international) and award mechanism (price-based versus criteria-based). We further differentiate between "real outsiders" and "pseudo-outsiders" based on experience supplying public markets. Using multivariate probit models, we examine how different degrees of innovation novelty are associated with supplier selection across tender categories and outsider status. Three findings emerge. i) Suppliers' category-specific procurement experience increases the likelihood of subsequent selection, indicating rigidity in public procurement markets. ii) Price-based tenders are associated with firm-level novelties, whereas criteria-based tenders are associated with market-specific novelties. iii) These innovation advantages are concentrated among "real outsiders" and largely disappear for "pseudo-outsiders", for whom prior category-specific procurement experience becomes the main predictor of subsequent selection. |
| Keywords: | Public procurement, open innovation, supply markets, tender design, competition |
| JEL: | H57 O36 D40 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:zewdip:341998 |
| By: | Francesco Crespi; Dario Guarascio; Jelena Reljic |
| Abstract: | This article reassesses the concept of technological sovereignty and its policy implications in light of the close relationships between US- and China-based digital monopolies, or Big Tech, and their respective military apparatuses. First, we empirically examine the growing influence of the private sector in R&D activities, the increasing centrality of digital technologies within sectoral and technological hierarchies, the emergence of Big Tech firms and their dominance over knowledge, infrastructures, and key technologies such as cloud computing and AI. Second, building on Coveri et al. (2025a), we analyse the mutual dependence between Big Tech and the military apparatus, showing how it reinforces the economic power of the private actors involved, weakens the state's capacity to act autonomously, and intensifies the subordination of foreign governments dependent on US and Chinese digital platforms. Third, we propose a typology of technological sovereignty that takes into account the degree of technological dependence on Big Tech, the nature of the relationship between states and digital companies, and, consequently, the state's capacity to align the activities of these companies with its own strategic objectives. |
| Keywords: | technological sovereignty, Big Tech, R&D, military apparatus |
| JEL: | F5 F52 F55 O33 O34 O38 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ter:wpaper:00209 |
| By: | Matt Clancy |
| Abstract: | This paper develops a novel estimates of annual private sector agricultural R&D at the level of US states for the period 1976-2014. For each of five different agricultural subsectors, I allocate estimates of national private sector R&D across the 50 states by using the geographic distribution of inventors listed on contemporaneous US patents in the same agricultural subsector. These five subsectors comprise a large majority of total private sector agricultural R&D. I then use this new dataset to document three stylized facts about private sector agricultural R&D: it is highly correlated with the size of the state's agricultural economy (including over time, as well as in cross section), it is highly persistent, and is has become increasingly less concentrated over 1976-2014, though this last trend shows signs of reversing. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.04956 |
| By: | Radoslaw Stefanski (University of St Andrews; University of Stavanger) |
| Abstract: | Long-run growth is driven by new ideas, yet the cultural environment shaping their production is difficult to measure over time. We use large language models to read 23, 000 books from the Western canon and score whether each endorses, rejects, or merely depicts six dimensions of culture. We accumulate the scores into inherited stocks and summarize them with an Innovation Wedge measuring cultural resistance to new ideas. Between 1000 and 1920 the wedge falls by 51 percent. Blinded expert readings and modern surveys validate the measure. An independent 5, 000-book archive reproduces the decline. In a calibrated semi-endogenous growth model, the falling wedge raises 1920 productivity to 1.78 times its counterfactual level, explains two-thirds of the first sustained acceleration in productivity growth between 1500 and 1700, and accounts for 38.7 percent of productivity growth in 1920. |
| Keywords: | culture and growth; ideas production; growth accounting; innovation barriers; text as data |
| JEL: | O41 O31 N13 Z10 |
| Date: | 2026–07–23 |
| URL: | https://d.repec.org/n?u=RePEc:san:econdp:2602 |
| By: | Karen Dynan; Douglas Elmendorf; Louise Sheiner |
| Abstract: | Artificial intelligence will probably generate major changes in the US economy, although the nature, timing, and magnitude of those changes are highly uncertain. We analyze a set of long-term scenarios involving different combinations of faster productivity growth, greater income inequality, job displacement, and a higher capital share of income. For each scenario, we assess the implications for federal debt and potential policy responses related to faster economic growth, the distribution of income, support for workers who are laid off, and taxation and ownership of capital. Given the uncertainty surrounding AI’s economic effects, policies that are robust to different scenarios would be especially valuable. |
| JEL: | E62 H20 H60 H68 J24 O30 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35437 |
| By: | Mahlberg, Bernhard; Mara, Isilda; Prskawetz, Alexia; Gerstner, Isabel |
| Abstract: | The aim of this study is to estimate the age–productivity profile of Austrian firms using a linked employer–employee dataset for the years 2013–2022. The OLS and FE estimates indicate a highly significant relationship between workforce age structure and labour productivity. Across both estimation methods, we find an inverted U-shaped age–productivity profile. We also account for capital intensity and the share of automation-related assets (ADRA). The estimation results show that firms with greater capital intensity and higher levels of automation consistently exhibit higher productivity across the distribution. In addition, the marginal effect of the share of ADRA-related capital is greater than that of the agerelated variables. These findings have important implications for both firm strategy and public policy, highlighting the role of technology diffusion, education, and potentially organisational change in sustaining productivity in ageing societies. The empirical strategy is complemented by panel data methods and robustness checks to account for persistence, unobserved heterogeneity, and potential reverse causality. |
| Keywords: | Age-productivity profile, Labour productivity, Automation-related assets, Principal component analysis |
| JEL: | D24 J14 J24 J82 O33 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:tuweco:342377 |