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on Technology and Industrial Dynamics |
| By: | Jesus Fernandez-Villaverde; Yang Yu; Francesco Zanetti |
| Abstract: | Defensive hiring of researchers by incumbent firms with monopsony power reduces creative destruction. This mechanism helps explain the simultaneous rise in R&D spending and decline in TFP growth in the US economy over recent decades. We develop a simple model highlighting the critical role of the inelastic supply of research labor in enabling this effect. Empirical evidence confirms that the research labor supply in the US is indeed inelastic and supports other model predictions: incumbent R&D spending is negatively correlated with creative destruction and sectoral TFP growth while extending incumbents’ lifespan. All these effects are amplified when ideas are harder to find. An extended version of the model quantifies these mechanisms’ implications for productivity, innovation, and policy. |
| Keywords: | productivity growth, innovation, R&D, patents, creative destruction |
| JEL: | E22 L11 O31 O33 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:een:camaaa:2025-15 |
| By: | Wagenaar, Homer; Colvin, Christopher L. |
| Abstract: | We examine the accessibility and functioning of the patent system in the United Kingdom of the Netherlands, a state that existed between 1815 and 1830. The country's patent law combined an examination process with significant government discretion over a patent's duration and cost. Using our hand-collected database of all patent applications-granted, withdrawn, and rejected-we analyse the determinants of success, and the conditions imposed on applicants by the system's administrators. We find that discretion optimised patent terms rather than causing bias. The system was accessible despite high fees. Our analysis suggests that social class, skills, and market orientation drove the demand for patents. Our research contributes to understanding the history of European patent institutions by adding high-quality patent data for the second economy in the world to experience an Industrial Revolution. |
| Keywords: | patents, innovation, industrialisation, discretion, Low Countries |
| JEL: | L51 N44 N74 O31 O34 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:qucehw:315206 |
| By: | Colin Davis; Ken-ichi Hashimoto |
| Abstract: | This paper investigates how the cash-in-advance (CIA) constraints that firms face in production and innovation decisions affect the long-run relationship between monetary policy and innovation-based economic growth. Firms produce differentiated product varieties and invest in process innovation to reduce production costs. With imperfect knowledge diffusion across countries, the country with the greater share of industry has relatively productive firms. We find that when innovation has a stricter CIA requirement than production, an increase in the nominal interest rate in the country with the larger (smaller) share of industry reduces the industrial share of that country, thereby decreasing (increasing) the rate of productivity growth. We also examine the implications of improvements in knowledge diffusion for the optimal nominal interest rate policy of each country. |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:dpr:wpaper:1278 |
| By: | Siddharth, L. |
| Abstract: | Technological evolution depends not only on the invention of new artefacts but also on how their knowledge is structured, represented, and propagated. In this study, we examine how the modularity of artefact knowledge influences technological impact. We utilize a dataset of 33, 803 patents from the United States Patent & Trademark Office (USPTO) and their knowledge graphs constructed using the facts extracted from patent descriptions. Using a regression analysis controlling for several structural properties of the knowledge graphs, we establish a significant positive relationship between modularity of the graph structures—measured using the Louvain method and the technological impact, as quantified by normalized forward citations. To further examine this relationship, we develop a predictive framework integrating Graph Neural Networks (GNNs) and regression models to estimate normalized citation scores from patent knowledge graphs. We then apply this framework to conduct a counterfactual analysis, wherein, we tune the modularity of knowledge graphs and assess the enhancement in expected citations. The analysis reveals that patents with less or no citations could benefit the most from modularization of their knowledge, as a citation gain could help initiate their knowledge propagation. We also discuss with a few examples as to how re-representation of artefact knowledge is necessary in addition to re-designing artefacts for modularity. |
| Date: | 2025–03–24 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:fd36m_v1 |
| By: | Moritz Kuhn; Iourii Manovskii; Xincheng Qiu |
| Abstract: | Spatial differences in labor market performance are large and highly persistent. Using data from the United States, Germany, and the United Kingdom, we document striking similarities across these countries in the spatial differences in unemployment, vacancies, and job filling, finding, and separation rates. The novel facts on the geography of vacancies and job filling are instrumental in guiding and disciplining the development of a theory of local labor market performance. We find that a spatial version of a Diamond-Mortensen-Pissarides model with endogenous separations and on-the-job search quantitatively accounts for all the documented empirical regularities. The model also quanitatively rationalizes why differences in job-separation rates have primary importance in inducing differences in unemployment across space while changes in the job-finding rate are the main driver in unemployment fluctuations over the business cycle. |
| Keywords: | Local Labor Markets, Unemployment, Vacancies, Search and Matching |
| JEL: | J63 J64 E24 E32 R13 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2024_609 |
| By: | Lodefalk, Magnus (Örebro University School of Business); Engberg, Erik (Örebro University School of Business); Lidskog, Rolf (School of Humanities, Education and Social Sciences); Tang, Aili (Örebro University School of Business) |
| Abstract: | This paper investigates the economic and societal impacts of Artificial Intelligence (AI) in the public sector, focusing on its potential to enhance productivity and mitigate labour shortages. Employing detailed administrative data and novel occupational exposure measures, we simulate future scenarios over a 20-year horizon, using Sweden as an illustrative case. Our findings indicate that advances in AI development and uptake could significantly alleviate projected labour shortages and enhance productivity. However, outcomes vary substantially across sectors and organisational types, driven by differing workforce compositions. Complementing the economic analysis, we identify key challenges that hinder AI’s effective deployment, including technical limitations, organisational barriers, regulatory ambiguity, and ethical risks such as algorithmic bias and lack of transparency. Drawing from an interdisciplinary conceptual framework, we argue that AI’s integration in the public sector must address these socio-technical and institutional factors comprehensively. To unlock AI’s full potential, substantial investments in technological infrastructure, human capital development, regulatory clarity, and robust governance mechanisms are essential. Our study thus contributes both novel economic evidence and an integrated societal perspective, informing strategies for sustainable and equitable public-sector digitalisation. |
| Keywords: | Artificial intelligence; Implementation of technology; Productivity; Labour demand |
| JEL: | E24 J23 J24 N34 O33 |
| Date: | 2025–04–02 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:oruesi:2025_006 |
| By: | Delera, Michele; Mathew, Nanditha (Maastricht Graduate School of Governance, RS: GSBE MORSE, RS: GSBE MGSoG); Treibich, Tania (RS: GSBE MORSE, Macro, International & Labour Economics) |
| Abstract: | The global fragmentation of production has important implications for the environment. As emerging economies increase their participation in trade, scale effects increase environmental impacts worldwide. Yet at the same time, access to international markets might help offset these impacts by increasing the efficiency of production. Existing literature suggests that trading firms tend to be more energy efficient than non-traders. However, this literature does not take into account the effect of firms’ product baskets. In this paper, we leverage a rich plantand product-level database from India to investigate the effects of importing on plant-level environmental outcomes. We first construct a measure of energy efficiency that is net of effects arising from plants’ product baskets. We then use an event study set up to compare outcomes between importers and future importers at the time of their entry into import markets. Our design takes advantage of plants’ staggered entry into importing to address issues of selection. Our findings suggest that after they start importing, plants experience increases in their energy intensity. Plants which start importing also grow larger and more productive, and diversify their product baskets. Our results suggest that access to international markets leads to gains in scale and productivity, but not in environmental performance. This finding suggests that there is an environmental cost to learning and product diversification. |
| JEL: | D22 F10 F14 F18 O11 O33 |
| Date: | 2025–03–31 |
| URL: | https://d.repec.org/n?u=RePEc:unm:unumer:2025009 |
| By: | Grimaud, André; Rougé, Luc |
| Abstract: | Technical progress is considered a key element in the ght against climate change. It may take the form of technological breakthroughs, that is, shocks that induce signicant leaps in the stock of knowledge. We use an endogenous growth framework with directed technical change to analyze the climate impact of such shocks. Two production subsectors coexist: one subsector is fossil-based, using a non-renewable resource, and yields carbon emissions; the other subsector uses a clean, renewable resource. At a given date, the economy benets from an exogenous technology shock. We fully characterize the general equilibrium and analyze how the shock modies the economys trajectory. The overall e¤ect on carbon emissions basically depends on the substitutability between the production subsectors, the initial state of the economy, and the nature and size of the shock. We notably show that green technology shocks induce higher short-term carbon emissions when the two subsectors are gross complements, but also in numerous cases when they are gross substitutes. |
| Keywords: | directed technical change; endogenous growth; technology shocks; climate; change |
| JEL: | O33 O44 Q32 Q54 Q55 |
| Date: | 2025–04–04 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130495 |