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on Technology and Industrial Dynamics |
| By: | Bernardo Caldarola; Dario Mazzilli; Aurelio Patelli; Angelica Sbardella |
| Abstract: | Structural change consists of industrial diversification towards more productive, knowledge intensive activities. However, changes in the productive structure bear inherent links with job creation and income distribution. In this paper, we investigate the consequences of structural change, defined in terms of labour shifts towards more complex industries, on employment growth, wage inequality, and functional distribution of income. The analysis is conducted for European countries using data on disaggregated industrial employment shares over the period 2010-2018. First, we identify patterns of industrial specialisation by validating a country-industry industrial employment matrix using a bipartite weighted configuration model (BiWCM). Secondly, we introduce a country-level measure of labour-weighted Fitness, which can be decomposed in such a way as to isolate a component that identifies the movement of labour towards more complex industries, which we define as structural change. Thirdly, we link structural change to i) employment growth, ii) wage inequality, and iii) labour share of the economy. The results indicate that our structural change measure is associated negatively with employment growth. However, it is also associated with lower income inequality. As countries move to more complex industries, they drop the least complex ones, so the (low-paid) jobs in the least complex sectors disappear. Finally, structural change predicts a higher labour ratio of the economy; however, this is likely to be due to the increase in salaries rather than by job creation. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.07906 |
| By: | Mirko Draca; Max Nathan; Viet Nguyen-Tien; Juliana Oliveira-Cunha; Anna Rosso; Anna Valero |
| Abstract: | Which types of human capital influence the adoption of advanced technologies? We study the skill biased adoption of information and communication technologies (ICT) across two waves in the UK. Specifically, we compare the 'new wave' of cloud and machine learning / AI technologies during the 2010s - pre-LLM - with the previous wave of personal computer adoption in the 1990s and early 2000s. At the area-level we see the emergence of a distinct STEM-biased adoption effect for the second wave of cloud and machine learning / AI technologies (ML/AI), alongside a general skill-biased effect. A one-standard deviation increase in the baseline share of STEM workers in areas is associated with around 0.3 of a standard deviation higher adoption of cloud and ML/AI. We find similar effects at the firm level where we are able to test for the influence of a wide range of skills. In turn, this STEM-biased adoption pattern has encouraged the concentration of these technologies, leading to more acute differences between high-tech and low-tech areas and firms. In contrast with classical technology diffusion, recent cloud and ML/AI adoption in the UK seems more likely to widen inequalities than reduce them. |
| Keywords: | Technology Diffusion, ICT, Human Capital, STEM, Technological change, AI |
| Date: | 2024–10–10 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2040 |
| By: | CONFRARIA Hugo (European Commission - JRC); GRASSANO Nicola; MONCADA PATERNO' CASTELLO Pietro (European Commission - JRC); NINDL Elisabeth (European Commission - JRC) |
| Abstract: | Understanding the flow of knowledge between scientific research and policymaking is increasingly important. This study examines the influence of the EU Industrial R&D Investment Scoreboard, which has been active at the science-policy interface since 2004. We analyse citation trends in scientific publications and policy documents to assess the Scoreboard’s usage, impact, and reach. Our findings indicate that the Scoreboard is cited more frequently in policy documents, though academic interest is growing. Policy documents cite the Scoreboard more quickly, reflecting its immediate relevance for policy actors, while scientific publications take longer to cite it and utilise its data. Papers citing the Scoreboard tend to have a higher citation impact than average, underscoring its significance in a broad set of research fields. In our citation content analysis, we find that "insight" citations are more common than "data" citations. However, papers combining patent data and Scoreboard tend to receive more citations, highlighting the value of integrating R&D data with other relevant variables to better understand the innovation process. Additionally, we show that the Scoreboard has influenced EU policy discourse to address the need for structural changes towards high R&D intensity sectors, and showing EU’s strengths in green innovation. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:ipt:wpaper:202403 |
| By: | Langinier, Corinne (University of Alberta, Department of Economics); Ray Chaudhuri, Amrita (University of Winnipeg) |
| Abstract: | We analyze the impact of patent policies and emission taxes on green innovation. We allow for strategic interactions of firms in a duopolistic market in the presence of green conscious consumers. We identify a paradoxical effect of increasing emission taxes beyond a certain threshold which results in an increase in emissions. Decreasing patenting costs mitigates this paradox, while the impact of tightening patentability requirements is more complex. Moreover, we show that the greater the proportion of green-conscious consumers, the less likely firms are to license a green patent, which results in higher emissions levels. With green consumers, the lowest emissions occur for an intermediate range of taxes for which licensing does occur. Finally, we find that while tax increases lead to a switch from overinvestment to underinvestment in the absence of green conscious consumers, they have the reverse effect in their presence. |
| Keywords: | Patent; Green Innovation; Pollution |
| JEL: | L13 O34 Q50 |
| Date: | 2024–10–10 |
| URL: | https://d.repec.org/n?u=RePEc:ris:albaec:2024_007 |
| By: | Langinier, Corinne (University of Alberta, Department of Economics); Martinez-Zarzoso, Inmaculada (University of Goettingen); Ray Chaudhuri, Amrita (University of Winnipeg) |
| Abstract: | Our theoretical model predicts that green innovation is an inverted U-shaped function of emission tax under free trade, while it is upward sloping under autarky. Our empirical analysis supports this finding by using the Environmental Policy Stringency Index (EPS) as a proxy for environmental regulations. Our theory also determines the conditions under which international technology transfers increase green innovation. The empirical results indicate that technology transfers increase green innovation at any given level of EPS, although the inverted U-shape persists. We observe that OECD and non-OECD countries lie on either side of the turning point. Implementing stricter environmental regulations in non-OECD countries increases green innovation, while the reverse is likely to hold for most OECD countries. Our findings also show that market-based regulations are more effective in non-OECD countries for fostering green innovation, while non-market-based regulations are more effective in OECD countries. |
| Keywords: | Green Innovation; Environmental Policy; International Trade; Technology Transfer |
| JEL: | O34 Q55 Q56 Q58 |
| Date: | 2024–10–10 |
| URL: | https://d.repec.org/n?u=RePEc:ris:albaec:2024_008 |
| By: | Langinier, Corinne (University of Alberta, Department of Economics) |
| Abstract: | Even after final rejection, patent applications are never completely rejected. In the U.S., a patent applicant can reapply after a final rejection by submitting amended applications called continuations. While patent applicants benefit from this procedure (a final rejection is never final), examiners are worse off when examining continuations than when reviewing new applications. We theoretically investigate the impact of continuation on the patenting process. We find that the continuation process introduces a trade-off for examiners: a reduction in the initial applications' examination intensity can compensate for the loss incurred due to continuation in the case of rejection. Thus, examiners reduce their examination efforts when uncertainty about the innovation's patentability is the highest. When innovations are more likely to be patentable, examiners tend to grant patents after little scrutiny, reducing the chance of encountering continuations later on. Abolishing continuing applications could restore examiners' incentives to perform thorough evaluations of patent applications. |
| Keywords: | Patents; Examiners; Continuation |
| JEL: | D23 D86 O34 |
| Date: | 2024–10–10 |
| URL: | https://d.repec.org/n?u=RePEc:ris:albaec:2024_006 |
| By: | Jacques Bughin |
| Abstract: | Generative Artificial Intelligence (genAI) is the latest evidence of the transformative value of AI in organizations. One promising avenue lies in software engineering, where genAI can contribute to coding by pairing with developers. Based on a sample of global firms, two main insights emerge on analyzing the productivity implications of genAI-pair coding. Coding quality is negatively correlated with productivity throughput gains, while quality-adjusted productivity gains depend on the extent to which organizations have deployed AI capabilities in the form of data, skills upgrade, and AI governance. As observed with other digital technologies, the success of using genAI is closely tied to complementary technical skills and organizational resources. |
| Keywords: | Generative AI, productivity, enterprise RBV, capabilities, machine learning |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:ict:wpaper:2013/378272 |
| By: | Cimini, Francesco; Kalantzis, Fotios |
| Abstract: | This study examines the impact of green and digital investments on the investment inefficiency level of European firms. We define investment inefficiency as the deviation from the optimal investment level, which depends on both the net present value (NPV) of the projects and the marginal benefit and cost of investment. Leveraging matched data from the European Investment Survey (EIBIS) and ORBIS, which results in a sample of 4, 892 firmyear observations from 27 European countries surveyed over the period 2021-2023, we employed a panel data regression model to estimate the effect of green and digital investments on investment inefficiency. Our analysis shows that both types of investments reduce investment inefficiency, particularly for under-investing firms. We also find evidence of a statistically significant interaction effect between green and digital investments for over-investing firms, suggesting that digital technologies can enhance the efficiency gains from green investments. Our results have important implications for policy makers and business managers who aim to foster the twin digital and green transition in Europe and improve their investment efficiency and competitiveness. |
| Keywords: | European Investment Bank Investment Survey, Investment Inefficiency, Green investment, Digital investment, Twin transition |
| JEL: | M41 G31 Q53 O33 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:eibwps:304395 |
| By: | Hampel, Tim |
| Abstract: | Mistakes at work can lead to learning and personal development or can massively harm one's professional career. How a mistake affects a professional career often depends on how it is perceived by involved individuals (e.g. supervisors). In the present study we investigate two different types of mistakes at work: mistakes in routine and complex work tasks. In two experiments with 192 alumni of a German university we tested whether mistakes in routine tasks are judged differently than mistakes in complex work tasks. Results revealed that mistakes are judged significantly more negative when occurring in a routine work task compared to a complex work task. The results of our study give rise to a dilemma of mistakes at work where on basis of dual process theories mistakes are more likely to happen in routinized tasks while at the same time these mistakes are judged more negatively. We discuss an intervention to resolve the dilemma and suggest avenues for future research alongside the limitations of our study. |
| Keywords: | mistakes at work, errors, failures, attitudes towards mistakes, career development |
| JEL: | M |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:iubhbm:304403 |
| By: | Neave O'Clery; Juan Chaparro; Andres Gomez-Lievano; Eduardo Lora |
| Abstract: | What drives formal employment creation in developing cities? We find that larger cities, home to an abundant set of complex industries, employ a larger share of their working age population in formal jobs. We propose a hypothesis to explain this pattern, arguing that it is the organised nature of formal firms, whereby workers with complementary skills are coordinated in teams, that enables larger cities to create more formal employment. From this perspective, the growth of formal employment is dependent on the ability of a city to build on existing skills to enter new complex industries. To test our hypothesis, we construct a variable which captures the skill-proximity of cities' current industrial base to new complex industries, termed 'complexity potential'. Our main result is that complexity potential is robustly associated with subsequent growth of the formal employment rate in Colombian cities. |
| Date: | 2024–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2410.06971 |
| By: | Chenyue Bai (Dept. of Geography, Kiel University, Germany); Han Chu (Dept. of Geography, Kiel University, Germany); Robert Hassink (Dept. of Geography, Kiel University, Germany) |
| Abstract: | The regional innovation systems (RIS) concept is mature and widely used in economic geography. However, in the face of grand societal challenges and global economic uncertainty, the traditional RIS concept has been questioned and requires further consideration and discussion, to which we want to contribute in this paper. Thus, this study explores the evolution of RIS research by analyzing RIS articles published from 1992 to April 2024 using the Latent Dirichlet Allocation (LDA) model. It identifies three phases of RIS development and summarize five classic and three upcoming topics of RIS. These topics underscore the dynamic nature of RIS research and its continued relevance in addressing contemporary challenges and opportunities in regional development. Finally, this paper points out directions for future research. |
| Keywords: | Regional Innovation Systems, Latent Dirichlet Allocation, Innovation Policy, Regional Transformation |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:aoe:wpaper:2404 |
| By: | Ricardo Chiapin Pechansky; Michel Lioussis |
| Abstract: | This guide presents the Trade in Employment by workforce characteristics (TiMBC) database developed by the OECD to help inform cross-country, cross-industry discussions of issues such as gender and trade, skills and global value chains (GVCs), and the economic effects of an ageing population. It is an extension of the Trade in Employment (TiM) database, whereby indicators that provide insights into the different relations between GVC integration and employment by industry are further decomposed by workforce characteristics - namely age, gender, occupation, and education. To achieve this, statistics on employment by workforce characteristics, mainly Labour Force Surveys (LFS), are combined with existing TiM indicators. These novel indicators by workforce characteristics cover 43 countries and 12 unique industries, for the period 2008 to 2018. This guide presents the database, the sources and methods used, and a brief analysis showcasing indicators. |
| Keywords: | Employment, Global Value Chains, Workforce |
| Date: | 2024–10–24 |
| URL: | https://d.repec.org/n?u=RePEc:oec:stiaaa:2024/08-en |