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on Technology and Industrial Dynamics |
| By: | Riku Watanabe |
| Abstract: | This study incorporates two heterogeneous industries into an endogenous growth model within the framework of a circular economy. In the model, industries are classified as either brown or green, and each can transition between states through R&D activities related to innovation and greening. Greening R&D is conducted exclusively by firms in the brown industry and enables the transition to the green industry. We analyze the effects of subsidies for greening R&D and show that such subsidies increases labor allocation to both innovation and greening R&D. As a result, the model yields win-win outcome: economic growth is promoted not only by productivity-driven growth acceleration but also by a decline in the share of brown industries that rely on exhaustible resources, which mitigates the negative impact of resource depletion on growth. These findings suggest that advancing a circular economy can be compatible with sustained economic growth. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:dpr:wpaper:1286r |
| By: | Ufuk Akcigit; Harun Alp; Jeremy Pearce; Marta Prato |
| Abstract: | Why do some entrepreneurs drive economic growth while others do not? This piece discusses new work that studies entrepreneurs using a comprehensive dataset from Denmark. We study who becomes an entrepreneur, along with their hiring and business decisions, and find that a distinct minority are “transformative.” These individuals, who generate disproportionate productivity gains, tend to have high IQ scores, be well-educated, and hire technical (R&D) workers. The data support the idea of productivity growth being driven by the symbiotic relationship between transformative entrepreneurs and R&D workers. For policymakers, the lesson is that when an economy has more R&D workers and transformative entrepreneurs, they sustain higher long-run productivity growth. |
| Keywords: | entrepreneurship; R&D; innovation; productivity growth |
| JEL: | O31 O38 |
| Date: | 2026–01–05 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednls:102298 |
| By: | Roth, Felix; Rammer, Christian |
| Abstract: | Intangible assets have increasingly been identified as a main source of productivity gains. Since the pioneering work by Corrado, Hulten, and Sichel (2005), empirical research has largely focused on macro and industry-level studies, while firm-level studies have often been confined to a limited set of intangible assets, especially Research and Development (R&D). This paper employs a unique firm-level panel database that contains information on four types of intangible assets: R&D, software & databases (S&D), firm-specific human capital (HC), and brand value (BV). For R&D, we find much lower productivity returns than for S&D and HC. R&D even loses significance once controlling for other intangibles, except for high-tech manufacturing. In contrast to R&D, we find that S&D and HC tend to be the primary drivers of productivity gains, particularly in services. Our findings have implications for research policy, suggesting a stronger focus on supporting investment in non-R&D intangibles, including S&D and HC. |
| Keywords: | Non-R&D intangibles, productivity, R&D, digitalisation, firm-specific human capital, brand value, firm-level panel data |
| JEL: | E22 O33 O38 D24 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:zewdip:333901 |
| By: | Zoë B. Cullen; Ester Faia; Elisa Guglielminetti; Ricardo Perez-Truglia; Concetta Rondinelli |
| Abstract: | We present the first large-scale field experiment test of strategic complementarities in firms’ technology adoption. Our experiment was embedded in a Bank of Italy survey covering around 3, 000 firms. We elicited firms’ beliefs about competitors’ adoption of two advanced technologies: Artificial Intelligence (AI) and robotics. We randomly provided half of the sample with accurate information about adoption rates. Most firms substantially underestimated competitors’ current adoption, and when provided with information, they updated their expectations about competitors’ future adoption. The information increased firms’ own intended future adoption of robotics, although we do not observe a significant effect on AI adoption. Our findings provide causal evidence on coordination in innovation and illustrate how information frictions shape technology diffusion. |
| JEL: | C93 D22 L21 O33 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34532 |
| By: | Krieger, Bastian; Scrofani, Stefania; Strecke, Linus |
| Abstract: | This paper explores a novel web-based indicator to examine how firms' disclosure of university ties on their websites shapes their innovation performance. First, using data from the German Community Innovation Survey 2023 and the Tenders Electronic Daily database, combined with firms' discloser of university ties on their website provided by ISTARI.AI, we investigate the indicator's properties by comparing the most frequently disclosed types of university ties: innovation collaborations, university customers, and employee education, with firms' survey responses and their procurement contracts. Second, we analyze how website disclosure of university ties relates to firms' revenues from new or significantly improved products or services, applying Ordinary Least Squares, a Control Function, and Lewbel Instrumental Variable approach. In sum, the website disclosure of ties with universities is significantly associated with its related survey items and procurement contracts. Moreover, website disclosures show no consistent association with revenues from innovations new-to-the-firm. A consistent statistically significant relationship emerges only for small firms, where website disclosures are associated with higher revenues from market novelties. These findings suggest that our web-based indicator captures ties between firms and universities and that disclosing these ties on firms' websites may influence the market success of their novel products. |
| Keywords: | University-Industry Transfer, Innovation Performance, Signaling |
| JEL: | O31 O32 O36 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:zewdip:333900 |
| By: | Georgios A. Tritsaris |
| Abstract: | The Fourth Industrial Revolution commonly refers to the accelerating technological transformation that has been taking place in the 21st century. Economic growth theories which treat the accumulation of knowledge and its effect on production endogenously remain relevant, yet they have been evolving to explain how the current wave of advancements in automation and artificial intelligence (AI) technology will affect productivity and different occupations. The work contributes to current economic discourse by developing an analytical task-based framework that endogenously integrates knowledge accumulation with frictions that describe technological lock-in and the burden of knowledge generation and validation. The interaction between production (or automation) and growth (or knowledge accumulation) is also described explicitly. To study how automation and AI shape economic outcomes, I rely on high-throughput calculations of the developed model. The effect of the model's structural parameters on key variables such as the production output, wages, and labor shares of output is quantified, and possible intervention strategies are briefly discussed. An important result is that wages and labor shares are not directly linked, instead they can be influenced independently through distinct policy levers. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.16261 |
| By: | Zhang, Zhi Min; Yu, Chengzheng; Deng, Yang |
| Abstract: | The low-carbon city pilot policy (LCCP) is an important measure for China toad-dress climate change and promote low-carbon transformation under the goals of carbon peaking and carbon neutrality. Based on the LCCP, this study uses the difference-in-differences method to explore the impact of the policy on the real carbon emissions, the carbon emissions transferred by enterprises along the industrial chain to down-stream enterprises (i.e., carbon out sourcing), and green invention and innovation of enterprises by quantifying the changes of enterprises’ comprehensive carbon emissions, carbon outsourcing, and green patent applications before and after the implementation of the low-carbon pilot policy. The results show that the pilot policy significantly inhibits the real carbon emissions (1.85%) and carbon outsourcing (44.46%) of enterprises and significantly enhance green invention and innovation of enterprises. The effect of the pilot policy on carbon emissions and the incentive effect on green invention and innovation both exhibit significant heterogeneity between heavily polluting and non-heavily polluting industries, as well as between the eastern and western regions. This paper provides a quantitative basis for the government to formulate incentive policies to strengthen green innovation, and regulate carbon emission. |
| Keywords: | Environmental Economics and Policy |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:360768 |
| By: | Stefan Leknes (Statistics Norway); Jorn Rattso (Department of Economics, Norwegian University of Science and Technology); Hildegunn E Stokke (Department of Economics, Norwegian University of Science and Technology) |
| Abstract: | Intangible capital, an asset class central to the knowledge economy, has been shown to contribute substantially to productivity growth. However, the importance for agglomeration economies has received limited attention. We examine how the agglomeration effect varies with industries’ intensity of intangible capital, combining international measures of industry-level intangible capital with rich Norwegian administrative employer–employee data. The analysis addresses methodological challenges related to endogenous intangible investment, unobserved worker characteristics, and correlation between worker moves and firm quality. We find that at mean intangible intensity, the elasticity of wages with respect to city size is 0.026, with each standard-deviation increase in intangible intensity raising the elasticity by 0.004. Dynamic wage returns to city-specific experience are also significantly higher in intangible-intensive industries. Employing the AKM framework and a complementary firm- based measure of local productivity, we show that our main results are robust to potential hierarchy effects arising from worker mobility. Moreover, we document that positive selection on unobserved ability into large cities is driven primarily by workers employed in intangible-intensive industries, irrespective of education level. We further document heterogeneity across intangible components, showing that agglomeration elasticities are strong for industries intensive in software and databases, and economic competencies. Taken together, these findings highlight the importance of intangible capital investments in shaping urban wage premia. |
| Keywords: | Agglomeration economies, knowledge spillover, intangible capital, AKM-model, sorting, worker experience |
| JEL: | J24 J31 J61 R12 R23 |
| Date: | 2025–12–19 |
| URL: | https://d.repec.org/n?u=RePEc:nst:samfok:20425 |
| By: | Julius Koschnick |
| Abstract: | What was the origin of modern economic growth? Joel Mokyr has argued that self-sustained modern economic growth originated from a feedback loop between propositional (theoretical) and prescriptive (applied) knowledge, which turned positive in the eighteenth century during the "Industrial Enlightenment". While influential, this thesis has never been directly tested. This paper provides the first quantitative evidence by estimating the impact of knowledge spillovers between propositional and prescriptive knowledge on innovation in England, 1600-1800. For this, it introduces two new text-based measures for 1) the innovativeness of publications and 2) knowledge spillovers. The paper finds strong evidence that a feedback loop between propositional and prescriptive knowledge became positive during the second half of the eighteenth century. It also documents that this process had positive effects on the real economy as measured through patents. Overall, the findings provide empirical support for Mokyr's original hypothesis. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.16587 |
| By: | Liu, Dan; Liu, Yaru; Jin, Yanhong; Deng, Haiyan |
| Abstract: | This paper examines how the private sector in a middle-income country like China adapts to extreme heat through seed breeding innovation. While most existing research has focused on abiotic stress, such as drought and heat, we extend the analytical framework to include biotic stresses, specifically crop pest and disease exposure, a critical but often overlooked dimension of climate adaptation. We construct novel firm-level, crop-specific exposure measures of extreme heat and crop pests/diseases to investigate how both climate-related abiotic and biotic stressors influence the development of heat/drought-tolerant (HDT) and pest/disease-resistant (PDR) varieties at the firm level. Our results show that Chinese seed firms actively respond to climate pressures, increasing HDT varieties by 2.6% and PDR varieties by 9% for an additional harmful extreme heat degree-day, with significant variations across crops. Maize exhibits comprehensive adaptation across both HDT and PDR, rice focuses on PDR traits, while wheat shows limited responsiveness due to biological complexity and weaker market incentives. Breeding innovation responsiveness is stronger among private firms compared to state-owned enterprises and is most pronounced under the independent innovation model relative to inter-firm collaboration and private-public partnership models. We identify three key pathways driving these responses: increased farmer demand for climate-resilient seeds, heightened pest and disease pressures induced by extreme heat, and government policy signals, proxied by official communications addressing climate- and pest/disease-related issues. Furthermore, the adoption of improved varieties significantly mitigates crop yield loss caused by extreme heat exposure and pest/disease prevalence--PDR varieties reduce pest-related yield losses by 363.72 tons in rice and by 1, 342.27 tons in maize. However, adoption and mitigation effects in wheat remain limited due to biological and market constraints. These findings offer valuable policy insights for enhancing agricultural climate resilience. |
| Keywords: | Productivity Analysis, Research and Development/Tech Change/Emerging Technologies |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:361183 |
| By: | Wagner, Joachim |
| Abstract: | The use of advanced technologies like artificial intelligence, robotics, or smart devices will go hand in hand with higher productivity, higher product quality, and lower trade costs. Therefore, it can be expected to be positively related to export activities. This paper uses firm level data for manufacturing enterprises from the 27 member countries of the European Union collected in 2025 to shed further light on this issue by investigating the link between the use of advanced technologies and extensive margins of exports. Applying a new machine-learning estimator, Kernel-Regularized Least Squares (KRLS), which does not impose any restrictive assumptions for the functional form of the relation between margins of exports, use of advanced technologies, and any control variables, we find that firms which use more advanced technologies do more often export and do export to more different destinations. |
| Keywords: | Advanced technologies, exports, firm level data, Flash Eurobarometer 559, kernel-regularized least squares (KRLS) |
| JEL: | D22 F14 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:kcgwps:334537 |
| By: | Alessandro Montanaro (Università degli studi di Ferrara); Massimiliano Mazzanti (Università degli studi di Ferrara); Marianna Gilli (Università degli studi di Ferrara); Elisa Chioatto (Università degli studi di Ferrara); Filippo Cicoli (Department of Economics, Society and Politics of Università di Urbino Carlo Bo) |
| Abstract: | This paper presents and applies a new Italian Regional Accounting Matrix of Environmental Accounts (RAMEA) panel (1995–2019) to demonstrate how hybrid environmental–economic accounting can inform regional assessments of eco-efficiency and structural change. Using Emilia-Romagna and Lazio as two contrasting regional economies, we implement a sequence of applications: (i) long-run sectoral economic–environmental profiles, (ii) emission-intensity measures for greenhouse gases (GHG) and PM10, and (iii) an employment-based decomposition of emission dynamics. The results point to broad improvements in eco-efficiency: PM10 abatement is predominantly explained by within-sector technique gains, whereas GHG reductions reflect a combination of compositional shifts and technique effects, with the latter becoming stronger after 2005. We further exploit RAMEA granularity by zooming into manufacturing sub-sectors and by estimating a targeted econometric specification linking emissions per worker to productivity, investment, and EU ETS exposure, illustrating how decomposition diagnostics can be complemented with econometric evidence on potential drivers. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:srt:wpaper:0925 |