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on Technology and Industrial Dynamics |
| By: | Adelia Fatikhova; Fabrizio Fusillo; Sandro Montresor; |
| Abstract: | This work investigates the role of external exchanges of green knowledge on the regional development of new green technological specializations. We extend the recombinant knowledge framework to commodity-embodied knowledge and posit that inter-industry inter-regional flows of commodities, in which new green knowledge gets incorporated, are a channel through which regions can increase their opportunities of specializing in new green technologies and diversify in a more exploratory manner. We further expect these dynamics to be stronger when foreign rather than domestic embodied flows are concerned. By combining the EUREGIO input-output database with patent data, we test our hypotheses on a sample of 237 EU (NUTS2) regions over the period 2000-2019. We measure the regions’ centrality in the network of inter-regional flows of embodied green knowledge (GreenFlowNet) and exploit regional network centrality in a model of related diversification for green technologies. Results show that the centrality of regions in the network is positively associated with green diversification, making this process more exploratory. We also find that the regional ability to acquire new green-techs is mainly associated with the centrality in outward flows of green knowledge towards other regions rather than inward ones. Lastly, we find that regions’ green-tech diversification seems to be enabled (at the extensive margin) primarily by their centrality in the foreign network and accelerated (at the intensive margin) by their centrality in the domestic one. Policy implications are drawn accordingly. |
| Keywords: | green technologies, diversification, relatedness, knowledge networks |
| JEL: | R11 R15 O52 O33 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2413&r= |
| By: | Valentin Laprie |
| Abstract: | Low-carbon technical change in the building sector is a promising solution to address the challenges of climate change, energy security, and public health. We aim to investigate the effects of various environmental policies on low-carbon innovation in the building sector where strong investment barriers transpire, focusing on France as a case study. Pollution taxes, subsidies, standards, which induce more low-carbon innovation? Using a quality index for patents and a Polynomial Distributed Lag Model, our results suggest a limited impact of a carbon tax on promoting low-carbon innovation within the building sector in France. Moreover, our findings indicate that subsidies targeting less polluting technologies emerge as a primary driver of qualitative innovation. Additionally, our study reveals that energy standards for buildings exert a significant albeit temporary influence on the number of patents in relevant technological domains. |
| Keywords: | Environmental Policy, Technical Change, Patents, Energy Efficiency, Buildings |
| JEL: | O33 O34 O38 Q54 Q55 Q58 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:drm:wpaper:2024-17&r= |
| By: | GRASSANO Nicola; NAPOLITANO Lorenzo (European Commission - JRC); M'BAREK Robert (European Commission - JRC); RODRIGUEZ CEREZO Emilio (European Commission - JRC); LASARTE LOPEZ Jesus (European Commission - JRC) |
| Abstract: | In this document, we focus on innovation in biotechnologies (biotech), as captured by patented invention worldwide. To this aim, we focus on international patents filed at multiple offices, at least one of which belonging to the IP5 consortium (see methodological box for more details). Moreover, we rely on expert knowledge collected by the OECD to select the inventions connected to biotech. The analysis aims to produce a bird’s eye view on the evolution of patenting in this technological area over time and its relevance across the geographical and technological dimensions. The key points emerging from this analysis are: Biotech patents represent around 5% of all the IP5 patents in the period 2001-2019. The US are by far the country with the highest share of biotech patents, the EU is lagging behind (with an increasing gap with the US) , while China seem to have started catching Up with the EU; The majority of the biotech patents are withe (industrials) and red (medical) biotechnologies. Japanese, Chinese, and EU applicants show relatively high specialization in white biotech patents, while UK and US applicants are relatively specialized in horizontal and red biotech patents. Germany and France have the highest number of biotech patent applicants in the EU, accounting for slightly over 50% of all EU biotech patents; The single biotechnology most patented is C12Q 1/66, "Measuring or testing processes involving luciferase", which alone represents 6.4% of all the biotech patents analysed; Preliminary analysis suggests that the competition among regions in biotech patents revolves around the number of patents in each of the main biotechnological domains, rather than the different types of biotechnologies patented. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc137266&r= |
| By: | Sylvain Leduc; Zheng Liu |
| Abstract: | We study the implications of trade uncertainty for reshoring, automation, and U.S. labor markets. Rising trade uncertainty creates incentive for firms to reduce exposures to foreign suppliers by moving production and distribution processes to domestic producers. However, we argue that reshoring does not necessarily bring jobs back to the home country or boost domestic wages, especially when firms have access to labor-substituting technologies such as automation. Automation improves labor productivity and facilitates reshoring, but it can also displace jobs. Furthermore, automation poses a threat that weakens the bargaining power of low-skilled workers in wage negotiations, depressing their wages and raising the skill premium and wage inequality. The model predictions are in line with industry-level empirical evidence. |
| Keywords: | offshoring; reshoring; automation; robots; uncertainty; unemployment; wages; productivity |
| JEL: | F41 E24 J64 O33 |
| Date: | 2024–05–05 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedfwp:98206&r= |
| By: | Christian Peukert; Florian Abeillon; J\'er\'emie Haese; Franziska Kaiser; Alexander Staub |
| Abstract: | Human-created works represent critical data inputs to artificial intelligence (AI). Strategic behavior can play a major role for AI training datasets, be it in limiting access to existing works or in deciding which types of new works to create or whether to create new works at all. We examine creators' behavioral change when their works become training data for AI. Specifically, we focus on contributors on Unsplash, a popular stock image platform with about 6 million high-quality photos and illustrations. In the summer of 2020, Unsplash launched an AI research program by releasing a dataset of 25, 000 images for commercial use. We study contributors' reactions, comparing contributors whose works were included in this dataset to contributors whose works were not included. Our results suggest that treated contributors left the platform at a higher-than-usual rate and substantially slowed down the rate of new uploads. Professional and more successful photographers react stronger than amateurs and less successful photographers. We also show that affected users changed the variety and novelty of contributions to the platform, with long-run implications for the stock of works potentially available for AI training. Taken together, our findings highlight the trade-off between interests of rightsholders and promoting innovation at the technological frontier. We discuss implications for copyright and AI policy. |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2404.18445&r= |
| By: | Spencer Bastani; Daniel Waldenström |
| Abstract: | This paper examines the implications of Artificial Intelligence (AI) and automation for the taxation of labor and capital in advanced economies. It synthesizes empirical evidence on worker displacement, productivity, and income inequality, as well as theoretical frameworks for optimal taxation. Implications for tax policy are discussed, focusing on the level of capital taxes and the progressivity of labor taxes. While there may be a need to adjust the level of capital taxes and the structure of labor income taxation, there are potential drawbacks of overly progressive taxation and universal basic income schemes that could undermine work incentives, economic growth, and long-term household welfare. Some of the challenges posed by AI and automation may also be better addressed through regulatory measures rather than tax policy. |
| Keywords: | AI, automation, inequality, labor share, optimal taxation, tax progressivity |
| JEL: | H21 H30 O33 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_11084&r= |
| By: | Fernanda Brollo |
| Abstract: | This paper investigates the impact of automation on the U.S. labor market from 2000 to 2007, specifically examining whether more generous social protection programs can mitigate negative effects. Following Acemoglu and Restrepo (2020), the study finds that areas with higher robot adoption reduced employment and wages, in particular for workers without collegue degree. Notably, the paper exploits differences in social protection generosity across states and finds that areas with more generous unemployment insurance (UI) alleviated the negative effects on wages, especially for less-skilled workers. The results suggest that UI allowed displaced workers to find better matches The findings emphasize the importance of robust social protection policies in addressing the challenges posed by automation, contributing valuable insights for policymakers. |
| Keywords: | Automation; Innovation; Gen-AI; Social Protection; Social Assistance; Social Safety Nets; Labor Market; Unemployment Insurance |
| Date: | 2024–05–03 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:2024/095&r= |
| By: | Franco, Chiara; Pietrovito, Filomena |
| Abstract: | The aim of the paper is to analyse the main internal drivers of the increase and adoption of online activities carried out by firms in reaction to the Covid-19 pandemic. While the impact of Covid-19 pandemic on several different measures of firm level performance has been debated in many papers, not enough effort has been devoted to investigating its digitalization impact, especially with respect to the drivers for firms operating in transition countries. To this end, we explore a very detailed firm-level dataset, drawn from the World Bank Enterprise Survey (WBES) combined with the Covid-19-ES Follow-up Survey, for 22 East European and Central-Eastern Asian countries. Our findings reveal that (i) higher online activity is associated with higher digital and technological endowment of the firm and (ii) this relationship is shaped by external factors, such as country-level digital infrastructure. |
| Keywords: | digitalization; technological endowment, transition countries, Covid-19. |
| JEL: | D22 L20 O30 |
| Date: | 2024–05–16 |
| URL: | http://d.repec.org/n?u=RePEc:mol:ecsdps:esdp24096&r= |
| By: | James Cloyne (University of California Davis, NBER and CEPR); Joseba Martinez (London Business School and CEPR); Haroon Mumtaz (School of Economics and Finance, Queen Mary, University of London); Paolo Surico (London Business School and CEPR) |
| Abstract: | Using a narrative identi cation of tax changes in the United States over the post-WWII period, we document that a temporary cut in corporate income tax rates leads to a long-lasting increase in innovation and productivity, whereas changes in personal income tax rates only have short-term e ects. We show that the results on corporate taxes are consistent with theories of endogenous growth that feature tax amortisation allowances on intellectual property purchases, as in the tax code of most countries in the world. In contrast, personal taxes work primarily through the response of labour supply, which is as transient as the tax change itself. |
| Keywords: | corporate taxes, narrative identi cation, TFP, R&D, technological adoption. |
| JEL: | E23 E62 O32 O34 O38 |
| Date: | 2024–04–22 |
| URL: | http://d.repec.org/n?u=RePEc:qmw:qmwecw:979&r= |
| By: | OECD |
| Abstract: | This paper details the methodology used to nowcast the growth rate of the information and communication technology (ICT) sector in the "The growth outlook of the ICT sector" chapter of the OECD Digital Economy Outlook 2024, Volume 1. In an era of rapid digital transformation, innovative data sources for economic measurement are crucial. Internet search data have gained prominence for tracking real-time economic activity. This paper details a nowcasting model that leverages Google Trends data to provide policymakers with timely, up-to-date and comparable data on the economic growth of the ICT sector. Having timely data on ICT sector performance is essential to evaluating the effectiveness of sector-related policies. By addressing data challenges and employing a data-driven approach, this paper advances economic measurement of the digitalisation of the economy and provides insights into ICT sector growth dynamics. |
| Keywords: | digital economy outlook, ICT sector, information and communication technology, nowcast, nowcasting |
| Date: | 2024–05–14 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stiaab:362-en&r= |
| By: | Pintu Parui (School of Economics, XIM University); Klaus Prettner (Department of Economics, Vienna University of Economics and Business) |
| Abstract: | We propose a generalized R&D-based economic growth model that incorporates i) endogenous human capital accumulation in terms of education and health, ii) endogenous population growth, and iii) the public provision of healthcare and basic science. The government taxes households to pay for healthcare personnel and basic scientists. Since these employees are not anymore available for applied science and for final goods production, important tradeoffs with respect to government spending emerge for economic growth and welfare. We show that increasing public spending, particularly on basic science, leads to faster economic growth in the medium run and tends to raise welfare when compared to actual levels of spending in Organisation for Economic Co-operation and Development (OECD) countries. Our results highlight the difficult tradeoffs associated with public expenditures for healthcare and basic science and emphasize the important role of policymakers in ensuring adequate overall public funding. |
| Keywords: | R&D-Based Growth, Basic Science, Public Healthcare, Children's Health, Education, Fertility, Intertemporal Tradeoffs |
| JEL: | H41 J24 O31 O32 O41 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwwuw:wuwp365&r= |
| By: | Bonvillian, William B. |
| Abstract: | Amid the backdrop of advanced technology competition from China, climate change and a global pandemic, the United States —traditionally averse to industrial policy— embraced major industrial policy programmes between 2020 and 2022. These programmes focused on fostering technology innovation and are prime examples of industrial innovation policy. The scale of these initiatives and their focus on non-defence sectors are unprecedented. This study reviews six major examples of new United States industrial innovation policies involving federal government interventions in post-research phases of innovation, from development to prototyping, testing, demonstration and production. These policies reflect different approaches, for example top-down strategies, whereby the government selects and supports specific companies, and bottom-up strategies, through which the government offers incentives for companies to meet government technology goals. However, gaps remain in areas such as scale-up financing, advanced manufacturing support and cross-agency coordination, although some efforts are under way to address them. While the United States has a highly developed economy, it has been experimenting with industrial policy models that may be relevant to developing nations in their efforts to meet the challenges of the twenty-first century. |
| Date: | 2024–04–29 |
| URL: | http://d.repec.org/n?u=RePEc:ecr:col022:69186&r= |