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on Technology and Industrial Dynamics |
| By: | Fort, Teresa; Goldschlag, Nathan; Liang, Jack; Schott, Peter; Zolas, Nikolas |
| Abstract: | Relatively flat US productivity growth versus rising R&D expenditures is often interpreted as evidence that ideas are getting harder to find. We build a new 45-year panel tracking the universe of US firms' patenting to investigate the micro underpinnings of this conclusion, separately examining the relationships between research inputs and ideas (patents) versus ideas and growth. We find that average patents per R&D input are increasing, the elasticity of patents to R\&D inputs is flat or rising, and there is not systematic evidence of a secular decline in patenting after controlling for research inputs. We then document a positive, significant, and fairly steady relationship between firms' patent and labor productivity growth rates. Average firm growth after controlling for patent growth, however, declines. Together, these results suggest that firms' innovative efforts play a key role in sustaining growth that has not diminished over the last four decades. |
| Keywords: | Innovation; Productivity; Patents |
| JEL: | O31 O32 O33 O47 D24 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21555 |
| By: | Bilgin, Nuriye Melisa; Ottaviano, Gianmarco |
| Abstract: | Do the determinants of technology adoption depend on technological architecture? Using administrative data on Turkish firms from 2021 to 2024, we compare the adoption of traditional and generative artificial intelligence (GenAI). We show that GenAI adoption is driven by workforce skill intensity and is not positively associated with firm size, whereas traditional AI depends on both scale and skills. Firms that adopt both technologies are distinct and represent the most persistent adoption mode. Conditional on adoption, the skill-to-size ratio governs technology choice, and transition dynamics indicate a sequential process in which firms adopt GenAI before expanding to hybrid use. Exploiting the release of ChatGPT as a quasi-experimental reduction in access costs, we find that high-skill firms differentially increased GenAI adoption, while firm size played a limited role. These results suggest that the canonical size-based diffusion pattern is not universal but depends on the cost structure of technologies, with implications for innovation policy and productivity dispersion. |
| Keywords: | Artificial intelligence |
| JEL: | O33 L25 D22 O14 J3 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21506 |
| By: | Bernardo Ribeiro (Einaudi Institute for Economics and Finance (EIEF)) |
| Abstract: | This paper proposes a semi-endogenous growth theory that incorporates technology vintages and the endogenous evolution of multiple technological paradigms through innovation. It provides a characterization of both balanced growth equilibrium and transitional dynamics in an environment where new technologies continuously emerge. From a positive perspective, the model rationalizes two distinct empirical patterns. Using two centuries of US patent data, I first document that the age profile of patents has a pronounced hump shape: most contemporary patents build upon technologies that are between 50 and 100 years old. Second, this age profile has remained stable throughout the past century. From a normative standpoint, the theory underscores a misallocation of research effort induced by the tendency among profit-maximizing firms to overinvest in further developing mature technologies. This yields a suboptimally slow development of emerging technologies. According to a calibrated version of the model, correcting such misallocation could generate welfare gains of 7%. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:cwl:cwldpp:2515r2 |
| By: | Masayuki Morikawa |
| Abstract: | This study documents the adoption of AI in the workplace and its impact on productivity among workers in the Japanese machinery industry. At the end of 2025, 34% of workers use AI in their jobs, with R&D accounting for the largest proportion of AI-utilized jobs. Among AI users, the mean share of tasks using AI, efficiency gains, and resulting productivity effects are 12%, 20%, and 4%, respectively. Most workers use AI for only a small fraction of their overall job tasks. The productivity effect is larger for continuous AI users than for new AI users, suggesting selection and learning effects of AI adoption. The use of AI at work is projected to increase labor productivity in the industry by 0.3-0.4 percentage points annually over the next several years. If the use of AI in R&D activities improves the efficiency of R&D investment, it is likely to generate productivity gains that extend beyond simple labor-saving effects. Finally, more than 80% of workers hold positive views toward expanding the use of AI in the workplace, with stronger support among those already using AI and those facing severe labor shortages. |
| Keywords: | artificial intelligence, machinery industry, productivity |
| JEL: | J24 L60 O33 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:een:camaaa:2026-49 |
| By: | Bedre Defolie, Ozlem; Biglaiser, Gary; Jullien, Bruno |
| Abstract: | We study a startup’s choice of its "direction of innovation, " how well the technology fits alternative acquirers, and the effects on acquisition outcomes and market dominance. Two horizontally differentiated firms bid to acquire the innovation and then compete in the product market. Firms differ in initial quality stock and in "absorption capabilities, " how effectively the acquired innovation is integrated into their stock. The innovator designs the innovation to intensify bidding by putting firms on a more equal footing, thereby favoring the initially lower-quality firm. As a result, "increasing dominance" is less likely than under exogenous fit. The winner of the innovation is driven primarily by relative absorption capabilities rather than initial quality: the firm with higher absorption capability is more likely to win. The equilibrium innovation direction minimizes industry profit and consumer surplus. In a two-period model, decreasing dominance becomes more likely when the low-quality firm has stronger absorption capabilities. |
| Keywords: | Startup Acquisitions; Direction of Innovation; Decreasing Dominance |
| JEL: | L13 L15 L24 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21361 |
| By: | Caprettini, Bruno |
| Abstract: | Can state-sponsored industrial espionage promote innovation and lead to self-sustained growth? I study the effect of 18th-century French industrial espionage on French innovation and industrial activity in the 19th century. Between 1730 and 1800 the French Bureau of Commerce promoted an ambitious plan aimed at stealing from Britain the new technologies of the Industrial Revolution, bribing British entrepreneurs and inventors to leave England and bring their expertise to France. I assemble a novel database with a comprehensive list of French espionage and combine it with newly digitized 17th- and 18th-century industrial surveys, 1800s industrial censuses, and the full list of early French patents. I find large, positive, and persistent effects of industrial espionage on industrial activity and innovation. |
| Keywords: | France |
| JEL: | O33 O14 N73 F63 O38 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21551 |
| By: | Paolo Castelnovo (University of Insubria and Fondazione Eni Enrico Mattei); Cinzia Lombardo (PTSCLAS); Valentina Morretta (University of Milan) |
| Abstract: | This paper evaluates the effectiveness of a public policy intervention introduced by the Italian government to support the economic valorization of patents held by small and medium-sized enterprises (SMEs). Using original survey data collected in 2025, the analysis compares firms that benefited from the measure during the 2020-2021 calls with a control group of comparable non beneficiary firms. The study examines patenting behavior, strategies for patent valorization, perceived obstacles, and innovation-related outcomes beyond traditional financial indicators. The results show that the measure effectively increases patenting activity and supports technological maturation, particularly for smaller, younger, and more resource-constrained firms, without crowding out private investment. Rather than directly boosting short-term financial performance, the measure acts as an enabling instrument by strengthening internal capabilities, know-how, and innovation processes, helping firms bridge the gap between invention and market readiness. While impacts on internationalization and market-based patent valorization remain limited, the intervention represents an effective component of a broader SME-oriented innovation policy mix. |
| Keywords: | Patents, Patents valorization, Public Policy, Business performance |
| JEL: | O30 O31 O34 O38 L38 P14 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:fem:femwpa:2026.18 |
| By: | Li, Yang; Ahuja, Ketan; Daryanani, Karan; Hausmann, Ricardo; Yıldırım, Muhammed A. |
| Abstract: | The energy transition offers countries that can manufacture clean energy technologies substantial opportunities for sustainable economic growth. This paper provides a framework for context-aware industrial policy by applying economic complexity theory to a newly constructed dataset of twelve key clean energy supply chains (CESCs). We find that CESCs are diverse but highly interdependent; they are also growing faster and are more concentrated than other industries. CESCs exhibit substantial entry, exit and competitive churn, and countries are more likely to enter CESC industries that are related to their existing productive capabilities. We also explore changing global competitiveness and country positioning in these industries, and draw out implications of these patterns for industrial policymakers. |
| Keywords: | Industrial policy |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21561 |
| By: | Arnarson, Björn Thor; Buus, Magnus Tolum; Moxnes, Andreas; Munch, Jakob Roland; Xiang, Chong |
| Abstract: | We study how firm growth reorganizes the division of labor across firms in global value chains. Using a novel dataset linking cross-border firm-to-firm transactions to matched employer–employee data, we show that demand shocks increase trade between firms while reducing occupational similarity, implying greater specialization. We develop and estimate a model of task outsourcing in which firms expand by reallocating tasks to suppliers. The model matches the data and implies endogenous scale economies. Eliminating outsourcing reduces average labor productivity by 25 percent and increases input costs by 10 percent, highlighting the central role of specialization in shaping firm performance. |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21543 |
| By: | Barwick, Panle; Xia, Hongyuan; Xia, Tianli |
| Abstract: | This paper examines China's transition from pharmaceutical ``free rider'' to global innovator over the last decade. In 2010, China accounted for less than 8% of global clinical trials; by 2020, it had surpassed the US in annual registered clinical trial volume. To study this transformation, we compile a comprehensive, synchronized database spanning the pharmaceutical drug development supply chain, covering scientific publications, clinical trials, drug development milestones for China, the U.S., and Europe, alongside drug sales and government policies over the same period. We provide strong evidence that China's rise was primarily driven by the National Reimbursement Drug List (NRDL) reform, which dramatically expanded the effective market size for innovative drugs. We document a sharp rise in both the quantity (86% increase) and novelty of drug trials post reform, with growth concentrated in reform-exposed disease categories, first- or best-in-class drugs, and among domestic firms. A decomposition exercise reveals that the NRDL reform accounts for 43% of the growth in oncology trial activity, nearly doubling the combined contribution of upstream knowledge accumulation and talent flows (24%), while other government policies play a minor role. Finally, dynamic gains from induced innovation exceed the reform's static gains in consumer access to innovative drugs by threefold, underscoring the importance of accounting for the reform's long-run effects on innovation incentives in addition to near-term improvements in drug affordability. |
| Keywords: | China |
| JEL: | O38 I18 O31 L65 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21286 |
| By: | Franziska Tinnefeld; Florian Wagener; Florian O.O. Wagener |
| 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, economic integration |
| JEL: | F15 O31 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12774 |
| By: | Fassio, Claudio (University of Pisa); Mattsson, Pauline (CIRCLE, Lund University); Geuna, Aldo (University of Torino); Igna, Ioana (Copenhagen Business School) |
| Abstract: | International university-industry collaboration expands access to heterogeneous knowledge environments but simultaneously raises coordination costs that may impede the deep, exploratory exchange needed to produce genuinely novel science. This paper examines the relational conditions under which geographically dispersed firm-academia collaborations generate knowledge novelty. We argue that social proximity, operationalized as prior shared institutional affiliation between AstraZeneca researchers and their academic collaborators, serves as a critical enabling mechanism, particularly under geographic distance, where institutional and cultural frictions are highest. Using a longitudinal dataset of 17, 522 co-authored publications by AstraZeneca scientists from 2000 to 2020, we measure novelty through word-embedding indicators capturing both recombination novelty and element novelty. Exploiting the within-firm variation across AstraZeneca's globally distributed R&D network, we test whether the novelty-enhancing effect of social ties is stronger in international than in domestic academic collaborations. Results support an asymmetric substitution mechanism: prior social ties are positively associated with novelty specifically in international collaborations, where they compensate for the absence of spatial and institutional proximity, but not in domestic ones. These findings refine the proximity literature's substitution hypothesis and contribute to the understanding of how multinational firms organize knowledge recombination across geographically dispersed innovation networks. |
| Keywords: | International university-industry collaborations; Novelty; Social proximity; Geographic proximity; R&D sites |
| JEL: | D83 F23 I23 L24 L65 O32 |
| Date: | 2026–07–02 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:lucirc:2026_007 |
| By: | Garicano, Luis; Li, Jin; Wu, Yanhui |
| Abstract: | This paper studies how the effect of AI on an occupation depends not just on which tasks AI can perform but also on how costly it is to unbundle those tasks from the job. Much of the discussion of AI and labor markets starts from task exposure: if AI can perform more tasks in an occupation, that occupation should lose employment or earnings. This is incomplete because labor markets price jobs, not tasks. Jobs bundle tasks together, and the effect of AI depends on how costly it is to break the bundle. We build a two-task model in which AI can either assist one task inside a bundled job or supply that task autonomously while a human supplies the residual task. We show that, in weak-bundle occupations, AI automates some tasks and narrows the boundary of the job, activating the standard task-substitution channel once product demand is sufficiently inelastic. In strong-bundle occupations where tasks are not independently reallocable, AI improves performance inside the job, but does not remove the human from the bundle. Thus, bundling provides a force that protects jobs and workers' share of downstream revenue. |
| JEL: | J24 J23 O33 L23 D20 J31 |
| Date: | 2026–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21453 |
| By: | Baslandze, Salomé; Edwards, Zachary; Graham, John; McClure, Ty; Sparks, Michael; Meyer, Brent; Waddell, Sonya; Weitz, Daniel |
| Abstract: | We use novel data from a survey of nearly 750 corporate executives to study the effects of artificial intelligence (AI) on productivity and the workforce. We document substantial heterogeneity in AI adoption across firms, with more than half having already invested, though many smaller firms are only beginning to do so. Labor productivity gains are positive, vary across sectors, and are expected to strengthen in 2026, with the largest effects concentrated in high-skill services and finance. These gains are not primarily driven by firms’ capital deepening but instead reflect increases in revenue-based total factor productivity, closely associated with innovation- and demand-oriented channels. We document a productivity paradox, in which perceived productivity gains are larger than measured productivity gains, likely reflecting a delay in revenue realizations. In labor markets, we find little evidence of near-term aggregate employment declines due to AI, though larger companies anticipate AI-driven workforce reductions, while smaller firms expect modest gains. We also find evidence of compositional reallocation of labor both within and across firms, with routine clerical roles declining and a relative demand for skilled technical roles increasing. We develop an index that ranks job functions most negatively affected by AI. |
| Keywords: | Artificial intelligence; Productivity; Technological change; Labor markets; Occupations |
| JEL: | O33 D22 J24 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:21313 |
| By: | Murillo Campello; Guilherme Junqueira |
| Abstract: | Do tax subsidies prompt investors to take on risk? We address this question by looking at investors' responses to changes to the Qualified Small Business Stock (QSBS) program, which reduces capital gains taxes on startup investing. We do so under a framework in which some startup investors — venture capitalists (VCs) — combine outside funding with incentive-based compensation, while others invest their own funds. Using bunching, triple-differences, and matching designs that exploit industry eligibility, investment vintage, and holding-period requirements, we analyze data from 158 thousand investor–firm pairings over two decades. We identify strategic investment timing, with subsidies prompting bunching at tax-eligible holding-period thresholds. Most notably, when and where tax subsidies apply, VCs shift their project selection toward riskier ventures: they invest more in pre-commercial stage startups, become more likely to provide startups with their initial capital, and invest more in startups with pre-existing debt, while becoming less likely to co-syndicate their investments. Tax-subsidized VC-backed ventures show higher failure rates, but on the flip side, attain higher valuations at exit and are more likely to reach "unicorn status." None of these patterns are observed for comparable non-VC investors in startups exposed to the same tax subsidies. Our tests further show that tax incentives lead to reallocation toward more innovative industries, yielding more impactful patents. Our study is the first to show that tax policy can shift entrepreneurial financing toward riskier, more innovative, and valuable startups. |
| Keywords: | tax policy, venture capital, risk-taking, entrepreneurial financing, innovation |
| JEL: | G24 G23 H25 O31 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12776 |