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on Technology and Industrial Dynamics |
| By: | Yuan Gao (School of Economics, University of East Anglia); Emiliya Lazarova (School of Economics, University of East Anglia) |
| Abstract: | We propose the Knowledge Origin Re-Combination Index (KORCI) to measure the ex-ante technological novelty of inventions at the sectoral level. The index is developed through the intertemporal comparison of a sequence of networks, which represents the complex 10 connections between the technological components listed in subsequent cohorts of patent applications in the sector. Using patent data from three sectors, we are the first to document the cyclical nature of the evolution of ex-ante technological novelty. Further investigation into the correlation between KORCI and patent application growth rates suggests that this relation, however, is sector-specific. This suggests that the relation between the degree of ex-ante 15 technological novelty and invention activities depends on the specific drivers of innovation in the sector – whether it is process-based or application-based. |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:uea:ueaeco:2022-08&r=tid |
| By: | Nii-Aponsah, Hubert (RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn) |
| Abstract: | This paper addresses three main objectives. First, the analysis estimates and compares the average share of workers at risk of automation in advanced and developing regions. Second, the study investigates the possible structural implications of automation across the Gender, Age, and Skill labour market structures at the sectoral, country, and regional levels. Third, the paper extends the analysis of the Gender structure from possible job implications to potential wage consequences; in particular, the potential effect of automation on the gender wage gap at the regional level is studied and the sources of the differentials are identified. This study uses data from the PIAAC dataset, which comprises detailed task data for individual workers including novel data for developing countries. The results indicate that, from a purely technological feasibility viewpoint, advanced countries are more vulnerable than developing countries on average. Male and middle-aged workers are also likely to be more affected by automation, whereas high-skilled workers are likely to be the least affected by automation. The results also indicate that automation could reduce gender inequality not only through jobs but also through wages. |
| JEL: | J16 J21 J31 O30 O33 |
| Date: | 2022–06–16 |
| URL: | http://d.repec.org/n?u=RePEc:unm:unumer:2022021&r=tid |
| By: | Caravella, Serenella; Cirillo, Valeria; Crespi, Francesco; Guarascio, Dario; Menghini, Mirko |
| Abstract: | The digital transformation is an important driver of long-run productivity growth and, as such, it has the potential to promote a more inclusive and sustainable growth. However, digital capabilities, crucial to develop and govern new digital technologies, are unevenly distributed across European regions increasing the risk of divergence and polarization. By taking advantage of a set of original indicators capturing the level of digital skills in the regional workforce, this work analyzes the factors shaping the process of digital skill accumulation in the EU over the period 2011-2018. Relying on transition probability matrices and dynamic random effects probit models, we provide evidence of a strong and persistent regional polarization in the adoption and deployment of digital skills. Further, we investigate whether European Funds (European Regional Development Fund, Cohesion Funds, and European Social Funds) are capable to shape the digitalization process and to favor regional convergence. |
| Keywords: | Digital transition,Skills,Labour markets,Persistence,Regional development,EU policies |
| JEL: | O14 O30 O38 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:1188&r=tid |
| By: | Darke, Matthew James (University of Warwick) |
| Abstract: | Developments in Artificial Intelligence and Machine Learning technologies have had massive implications for labour automation. This paper builds on the task-based methodology first adopted by Frey and Osborne (2013) to predict how the risk of automation evolved in the UK labour between 2012 and 2017 using data from the UK Skills and Employment Survey. The analysis accounts for technological progress, making use of two sets of experts’ assessments for 70 occupations. The probability of automation is predicted for each individual using a set of self-reported job skills. It finds that the proportion of jobs at high-risk from automation has risen from 10.6% to 23.4%, and that this is largely due to better technology rather than changing job skill requirements. It also identifies sectors experiencing the greatest increase in automation risk between the two periods and, in contrast, those which appear complementary to technology, drawing on occupational case studies as evidence. |
| Keywords: | Employment ; Skills Demand ; Technology JEL Classification: J01 ; J21 ; J24 ; J62 ; O33 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:wrk:wrkesp:41&r=tid |
| By: | Semrau, Finn Ole |
| Abstract: | Industries that occupy upstream positions in global value chains (GVCs) - being positioned closer to the raw product - produce proportionately more CO2-intensive. However, firms are heterogeneous, even in narrowly defined industries. In this paper, I empirically investigate whether the relationship between upstreamness and CO2 emissions, measured in absolute and relative terms, holds within industries at the firm level. Using granular data of Indian manufacturing firms and controlling for established drivers of clean production, I reveal that firms producing products closer to final consumption produce less CO2-intensive. I corroborate the finding by using a 2-SLS instrumental variable approach. Interestingly, I find that exposure to importing countries with stringent environmental policies attenuates the link between upstreamness and dirty production. The latter finding suggests the imperative of technology upgrading for dirty upstream producers aiming to remain competitive in international markets. |
| Keywords: | Environment and trade,environment and development,CO2 intensity,global value chains,sustainable development |
| JEL: | F14 F18 O13 Q56 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:vfsc22:264178&r=tid |
| By: | Josef Taalbi |
| Abstract: | A long-standing discussion is to what extent patents can be used to monitor trends in innovation activity. This study quantifies the amount and quality of information about actual innovation contained in the patent system, based on 4,460 Swedish innovations (1970-2015) that have been matched to international patents. The results show that most innovations were not patented and that among those that were, 43.9% of all innovations, only a fraction can be identified with patent quality data. The best-performing models identify 17% of all information about innovations, equivalent to an information loss of at least 83%. Econometric tests also show that the fraction of innovations responding to strengthened patent laws during the period were on average 8% percent. The overlap between the patent and innovation systems is hence more modest than often assumed. This accentuates the need to, alongside patents, develop versatile approaches in order to induce and monitor various aspects of innovation. |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2210.04102&r=tid |
| By: | Burlina, Chiara; Casadei, Patrizia; Crociata, Alessandro |
| Abstract: | Several studies have detected a positive relationship between the spatial dynamics of cultural and creative industries (CCIs) and their social and economic outcomes. In this article, we draw upon the Economic Complexity Index (ECI) as a proxy to capture the social interactive nature that characterises CCIs and the way this affects firm performance. Our assumption is that more complex locations, endowed with different types of more sophisticated production capabilities, allow CCI firms to perform more strongly. This can depend on the higher opportunities of complex knowledge sharing and cross-fertilisation processes among different types of CCI firms or with non-CCI firms. The focus is on Italy, a country with a long-standing historical tradition in culture and creativity. We draw upon an original panel database at firm and province level (for the period 2010–2016) to compute two different ECIs, one for the CCIs and another one for the rest of the economy. Moreover, we analyse the effects these two types of complexity on the performance of firms within sectors with different levels of cultural and commercial value. We find that economic complexity of CCIs but not economic complexity of the rest of the economy matters for CCI firm performance. However, the effect is relatively weak. The same finding applies to all CCI firms, irrespective of their type of sector. Policy implications and directions for future research are discussed. |
| Keywords: | clusters; cultural and creative industries; economic complexity; firm performance; Italy; provinces |
| JEL: | J1 R14 J01 |
| Date: | 2022–09–23 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:116979&r=tid |
| By: | Pöge, Felix (Boston University); Gaessler, Fabian (Max Planck Institute for Innovation and Competition); Hoisl, Karin (Max Planck Institute for Innovation and Competition); Harhoff, Dietmar (University of Munich); Dorner, Matthias (Institute for Employment Research (IAB), Nuremberg) |
| Abstract: | We examine how collaborator loss affects knowledge workers in corporate R&D. We argue that such a loss affects the remaining collaborators not only by reducing their team-specific capital (as argued in the prior literature) but also by increasing their bargaining power over the employer, who is in need of filling the gap left by the lost collaborator to ensure the continuation of R&D projects. This shift in bargaining power may, in turn, lead to benefits, such as additional resources or more attractive working conditions. These benefits can partially compensate for the negative effect of reduced team-specific capital on productivity and influence the career trajectories of the remaining collaborators. We empirically investigate the consequences of collaborator loss by exploiting 845 unexpected deaths of active inventors. We find that inventor death has a moderate negative effect on the productivity of the remaining collaborators. This negative effect disappears when we focus on the remaining collaborators who work for the same employer as the deceased inventor. Moreover, this group is more likely to be promoted and less likely to leave their current employer. |
| Keywords: | collaboration, mobility, innovation, inventors, patents, teams |
| JEL: | J62 O32 J24 |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp15618&r=tid |
| By: | Belloc, Filippo; Valentini, Edilio |
| Abstract: | We propose a mixture model approach to identify locally optimal technologies and to dissect environmental productivity (output produced per unit of emission) into a technological and a managerial component. For a large sample of plants covered by the EU ETS, we find that the share of plants adopting the frontier technology is about 21%. We also find that the average output gains that plants could reach by adopting optimal technologies and managerial practices are 75% and 80% respectively. These results remain qualitatively similar after addressing endogeneity of emissions. Finally, we match EU ETS data with balance-sheet data on parent companies and find that better environmental technologies tend to be adopted by larger, listed, multi-plant and international companies, while older firms and firms with higher intangibles assets intensity more commonly show improved environmental management. Our results suggest that existing technologies have large unexploited potentials and deliver important insights for policy. |
| Keywords: | Environmental Economics and Policy, Production Economics, Productivity Analysis |
| Date: | 2022–10–25 |
| URL: | http://d.repec.org/n?u=RePEc:ags:feemwp:328580&r=tid |