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on Technology and Industrial Dynamics |
| By: | Matteo Romagnoli (Department of Economics, Management and Statistics, Università degli Studi di Milano-Bicocca) |
| Abstract: | The paper investigates the effect of electricity liberalisation on the variety of clean energy patent’ search space to asses whether a more competitive electricity market can foster the development of radical clean-energy technologies. This idea is tested using a cross-section of patents filed in the period 1990-2017, a set of patent-level indicators and an instrumental variable approach. Results show that electricity liberalisation pushes clean-energy patents to cite knowledge from technological fields other than their own. However, the reform does not significantly affect the overall breath of the knowledge base of these patents. Additional insights are drawn by looking at the correlation between electricity liberalisation and an indicator of novelty in patents’ search space. The results are consistent with the claim that electricity liberalisation has a positive effect on the development of radical clean-energy technologies. At the same time, by describing how the reform changes clean-energy patents’ search space, they define this effect more precisely. |
| Keywords: | Clean-energy Technologies, Electricity Liberalisation, Climate Change, Patent Data |
| JEL: | L94 O31 Q42 Q55 |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:fem:femwpa:2022.44&r=tid |
| By: | Shai Bernstein; Rebecca Diamond; Abhisit Jiranaphawiboon; Timothy McQuade; Beatriz Pousada |
| Abstract: | We characterize the contribution of immigrants to US innovation, both through their direct productivity as well as through their indirect spillover effects on their native collaborators. To do so, we link patent records to a database containing the first five digits of more than 230 million of Social Security Numbers (SSN). By combining this part of the SSN together with year of birth, we identify whether individuals are immigrants based on the age at which their Social Security Number is assigned. We find immigrants represent 16 percent of all US inventors, but produced 23 percent of total innovation output, as measured by number of patents, patent citations, and the economic value of these patents. Immigrant inventors are more likely to rely on foreign technologies, to collaborate with foreign inventors, and to be cited in foreign markets, thus contributing to the importation and diffusion of ideas across borders. Using an identification strategy that exploits premature inventor deaths, we find that immigrant inventors create especially strong positive externalities on the innovation production of their collaborators, while natives have a much weaker impact. A simple decomposition illustrates that immigrants are responsible for 36% of aggregate innovation, two-thirds of which is due to their innovation externalities on their native-born collaborators. |
| JEL: | J6 O31 |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:30797&r=tid |
| By: | Gabriele Pellegrino (Università Cattolica del Sacro Cuore); Orion Penner (Ecole polytechnique federale de Lausanne); Etienne Piguet (University of Neuchatel); Gaetan de Rassenfosse (Ecole polytechnique federale de Lausanne) |
| Abstract: | This paper studies the relationship between migration and the productivity of high-skilled workers, as captured by inventors listed in patent applications. Using machine learning techniques to identify inventors across patents uniquely, we are able to track the worldwide migration patterns of nearly one million individual inventors. Migrant inventors account for more than ten percent of inventors worldwide. The econometric analysis seeks to explain the recurring finding in the literature that migrant inventors are more productive than non-migrant inventors. We find that migrant inventors become about thirty-percent more productive after having migrated. The disambiguated inventor data are openly available. |
| Keywords: | inventor; productivity; skilled migration |
| JEL: | F22 J61 O30 |
| Date: | 2023–01 |
| URL: | http://d.repec.org/n?u=RePEc:iip:wpaper:20&r=tid |
| By: | Link, Albert (University of North Carolina at Greensboro, Department of Economics); Sardar, Rashedur (University of North Carolina at Greensboro, Department of Economics) |
| Abstract: | We quantify, using data from the World Bank’s Enterprise Surveys and the World Economic Forum’s Global Competitiveness Index, the empirical relationship between global competitiveness and R&D investment activity as well as the independent relationship between global competitiveness and R&D investments across geographic regions of economic development. We also explore alternative measures of the effectiveness of R&D investments. Our findings suggest that R&D investments are a possible policy target variable in high-income regions for policy makers to consider for increasing firms’ global competitiveness. |
| Keywords: | R&D; global competitiveness; entrepreneurship; regional growth; program management; |
| JEL: | H11 L26 O32 O38 |
| Date: | 2023–01–04 |
| URL: | http://d.repec.org/n?u=RePEc:ris:uncgec:2023_001&r=tid |
| By: | Heinrich, Torsten; Yang, Jangho |
| Abstract: | Did the Covid-19 pandemic have an impact on innovation? Past economic disruptions, anecdotal evidence, and the previous literature suggest a decline with substantial differences between industries. We leverage USPTO patent application data to investigate and quantify the disturbance. We assess differences by field of technology (at the CPC subclass level) as well as the impact of direct and indirect relevance for the management of the pandemic. Direct Covid-19 relevance is identified from a keyword search of the patent application fulltexts; indirect Covid-19 relevance is derived from past CPC subclass to subclass citation patterns. We find that direct Covid-19 relevance is associated with a strong boost to the growth of the number of patent applications in the first year of the pandemic at the same order of magnitude (in percentage points) as the percentage of patents referencing Covid-19. We find no effect for indirect Covid-19 relevance, indicating a focus on applied research at the expense of more basic research. Fields of technology (CPC mainsections) have an additional significant impact, with, e.g., mainsections A (human necessities) and C (chemistry, metallurgy) having a strong performance. |
| Keywords: | Innovation; Covid-19; Patent applications; Technological change |
| JEL: | I18 O31 O32 O33 |
| Date: | 2022–12–29 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:115809&r=tid |
| By: | NINDL Elisabeth (European Commission - JRC) |
| Abstract: | This report presents the results of the 2022 survey of the top 1 000 EU companies by R&D investment in 2020, conducted between June and September 2022. The survey is intended to provide insights into the research and development activities of the R&D investors listed in the 2021 EU Industrial R&D Investment Scoreboard (Scoreboard 2021). The objective of this survey is to gather future expectations for R&D investment and gain first-hand information on barriers and drivers and the role of various activities that influence the level and direction of R&D investment. The survey addresses financing and collaboration, technology transfer and open innovation, and the effects of COVID-19 and the war in Ukraine. The response rate stood at 12%. The number of responses increased by 31.5% compared to the previous year, and the respondents accounted for over 26% of the R&D investment of the top 1 000 EU corporate investors in R&D. The results show a strong recovery in R&D investment after the COVID-19 pandemic, and the respondents expect this positive development to continue in 2022 and 2023. The main drivers of R&D investment are environmental sustainability and digitalisation. The respondents’ capital investment is largely driven by technologies to reduce emissions and to adapt to Industry 4.0. The survey thus confirms that innovative EU companies are actively helping to meet the targets set out in the European Green Deal and the green and digital transformation (the Twin Transition). |
| Keywords: | R&D, Survey, EU Industrial R&D Scoreboard, Innovation, Growth |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc131984&r=tid |
| By: | Jos\'e M. Gaspar; Minoru Osawa |
| Abstract: | This paper analyses a two-region model with vertical innovations that enhance the quality of varieties of the horizontally differentiated manufactures produced in each of the two regions. We look at how the creation and diffusion of knowledge and increasing returns in manufacturing interact to shape the spatial economy. Innovations occur with a probability that depends on the inter-regional interaction between researchers (mobile workers). We find that, if the weight of interaction with foreign scientists is relatively more important for the success of innovation, the model accounts for re-dispersion of economic activities after an initial stage of progressive agglomeration as transport costs decrease from a high level. |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2212.14475&r=tid |
| By: | Golin, M.; Rauh, C. |
| Abstract: | In this paper, we establish a causal effect of workers’ perceived probability of losing one’s job due to automation on preferences for redistribution and intentions to join a union. In a representative sample of the US workforce, we elicit the perceived fear of losing one’s job to robots or artificial intelligence. We document a strong relationship between fear of automation and intentions to join a union, retrain and switch occupations, preferences for higher taxation, higher government handouts, populist attitudes, and voting intentions. We then show a causal effect of providing information about job loss probabilities on preferred levels of taxation and handouts. In contrast, our information treatment does not affect workers’ intentions to self-insure by retraining or switching occupations, but it increases workers’ self-reported likelihood of joining a union to seek more job protection. The treatment effects are mostly driven by workers who are informed about larger job loss probabilities than they perceived. |
| Keywords: | Automation, Inequality, information treatment, Political attitudes, Political preferences, Populism, Redistribution |
| Date: | 2022–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camjip:2229&r=tid |
| By: | Figiel, Szczepan |
| Abstract: | Artificial intelligence (AI) is one of the most striking recent technology developments. Potentially, it can significantly affect all areas of economic activities including agriculture. The paper addresses two issues such as the actual essence of AI and its most important current and expected future applications in agriculture and their potential impact on labor use and productivity of this sector. The research methods applied in the paper are critical analysis of selected literature sources and deductive reasoning regarding the likely influence of AI applications on labor use in agriculture and its total factor productivity. It was found out that applications of AI in agriculture are numerous and very diverse both in terms of technological solutions and managed processes. Moreover, the market for AI applications in agriculture is expected to grow quite rapidly due to an increasing tendency to automatize agricultural production and marketing processes. This inevitably leads to substitution of physical labor with sophisticated machinery and robots. Also, it generates demand for new labor competencies needed to manage increasingly capital intensive agricultural production and related processes driven by the use of AI. Based on mainly theoretical considerations, it can be surmised that widespread use of AI in agriculture should positively contribute to the growth in the total factor productivity (TFP) of the sector. Consequently, countries where agricultural producers adopt AI solutions faster can gain competitive advantage in food production. |
| Keywords: | Labor and Human Capital, Research and Development/Tech Change/Emerging Technologies |
| Date: | 2022–12–22 |
| URL: | http://d.repec.org/n?u=RePEc:ags:iafepa:329862&r=tid |
| By: | Gaetan de Rassenfosse (Ecole polytechnique federale de Lausanne); Emilio Raiteri (Eindhoven University of Technology); Rudi Bekkers (Eindhoven University of Technology) |
| Abstract: | This paper tests for traces of discrimination against foreigners in the patent system. It focuses on patent applications filed in China, and for which the owner has made a public disclosure that they are or may become essential to the implementation of a technical standard. Such potentially standard-essential patents are of particularly high importance to their owner. We use the timing of disclosure to a leading standard-setting organization as a source of econometric identification and carry out extensive tests to ensure the exogeneity of timing. We find that foreign patent applications are significantly less likely to be granted by the Chinese patent office if their owners disclose them to be potentially essential to a standard before the substantive examination starts. Furthermore, the patent office spends, on average, one more year on the examination of such patents, and the scope of the patents are also more extensively reduced. Our findings contribute to the emerging discussion on technology protectionism. |
| Keywords: | discrimination; indigenous innovation; national treatment principle; standard-essential patent; technology protectionism |
| JEL: | F53 F68 K39 L52 L63 |
| Date: | 2023–01 |
| URL: | http://d.repec.org/n?u=RePEc:iip:wpaper:21&r=tid |
| By: | Elvis D. Achuo (University of Dschang, Cameroon); Pilag B.C. Kakeu (University of Bamenda, Cameroon); Simplice A. Asongu (Yaoundé, Cameroon) |
| Abstract: | Despite the global resolves to curtail fossil fuel consumption in favour of clean energies, several countries continue to rely on carbon-intensive sources in meeting their energy demands. Financial constraints and limited knowledge with regard to green energy sources constitute major setbacks to the energy transition process. This study therefore examines the effects of financial development and human capital on energy consumption. The empirical analysis is based on the System Generalised Method of Moments (SGMM) for a panel of 134 countries from 1996-2019. The SGMM estimates conducted on the basis of three measures of energy consumption, notably fossil fuel, renewable energy as well as total energy consumption, provide divergent results. While financial development significantly reduces fossil fuel consumption, its effect is positive though non-significant with regard to renewable energy consumption. Conversely, financial development has a positive and significant effect on total energy consumption. Moreover, the results reveal that human capital development has an enhancing though non-significant effect on the energy transition process. Additionally, the results reveal that resource rents have an enhancing effect on the energy transition process. However, when natural resources rents are disaggregated into various components (oil, coal, mineral, natural gas, and forest rents), the effects on energy transition are divergent. Although our findings are consistent when the global panel is split into developed and developing economies, the results are divergent across geographical regions. Contingent on these findings, actionable policy implications are discussed. |
| Keywords: | Energy transition, Financial development, Fossil fuel, Human capital, Energy consumption, Eco-innovation |
| Date: | 2023–01 |
| URL: | http://d.repec.org/n?u=RePEc:exs:wpaper:23/005&r=tid |