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on Information and Communication Technologies |
| By: | Kyoji FUKAO; Kenta IKEUCHI; Yoshiaki NAGAYA; Cristiano PERUGINI; Fabrizio POMPEI |
| Abstract: | This study empirically examines the impact of advances in AI and robotics on employment, wages, and industrial structure in Japan. By constructing an original occupational-level Automation Risk Index (ARI) and combining it with industry-level panel data from 2009 to 2019, the analysis explores how investment in information and communications technology (ICT) capital affects labor market outcomes. A system of three simultaneous equations is used to account for the endogeneity of working hours, wages, and ICT capital intensity. The results indicate that increases in ICT capital tend to reduce working hours and exert a direct suppressive effect on wages. However, such negative effects are significantly mitigated in industries with lower ARI levels. Further analysis incorporating worker attributes reveals that highly educated, younger, and male workers are relatively less susceptible to the adverse effects of innovation. These findings underscore the importance of accounting for differences in automation risk when evaluating the impact of ICT investment on the labor market, and provide meaningful insights for the design of future employment and reskilling policies. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:eti:rpdpjp:25008 |
| By: | Ma, Shuang (Guangzhou University); Mu, Ren (Texas A&M University) |
| Abstract: | This study investigates broadband internet's impact on rural-urban migration in China, using the Universal Broadband and Telecommunication Services pilot program as a quasi-experimental setting. Analyzing China Household Finance Survey data (2013-2021) through difference-in-differences estimation, we find that improved internet access significantly increased rural-urban migration. Effects were strongest in villages with initially low migrant populations, locations closer to county centers, and those with better road infrastructure. At the individual level, impacts were most pronounced among females, younger people, the more educated, and those from higher-income households. Increased attention to economic information, rather than enhanced e-commerce opportunities, appears to drive these migration decisions. Our findings suggest broadband creates “digital routes” facilitating outmigration rather than “digital roots” anchoring residents to rural areas. |
| Keywords: | migration, urbanization, information and communications technology, China |
| JEL: | O15 R2 L86 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17752 |
| By: | Yarkin, Alexander |
| Abstract: | This paper documents the effects of home-country Internet expansion on immigrants' health and subjective well-being (SWB). Combining data on SWB and health from the European Social Survey (ESS) with data on 3G and overall Internet expansion (ITU and Collins Batholomew), I find that immigrants' SWB and health increase following home-country Internet expansion. This result is observed in both the TWFE, and event study frameworks. The effects are stronger for (i) first-generation immigrants, (ii) those less socially integrated at destination, and (iii) those with stronger family ties to the origins. Thus, while recent evidence points towards negative effects of the Internet and social media on user well-being, the effects are very different for immigrants. |
| Keywords: | subjective well-being, internet, immigration, health, social networks |
| JEL: | F22 I31 J15 J61 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17743 |
| By: | Egana-delSol, Pablo (Universidad Adolfo Ibañez); Bravo-Ortega, Claudio (Universidad Adolfo Ibañez) |
| Abstract: | This study examines the implications of artificial intelligence (AI) on employment, wages, and inequality in Latin America and the Caribbean (LAC). The paper identifies tasks and occupations most exposed to AI using comprehensive individual-level data alongside AI exposure indices. Unlike traditional automation, AI exposure correlates positively with higher education levels, ICT, and STEM skills. Notably, younger workers and women with high-level ICT and managerial skills face increased AI exposure, underscoring unique opportunities. A comparison of LAC with the OECD countries reveals greater impacts of AI in the former, with physical and customer-facing tasks showing divergent correlations to AI exposure. The findings indicate that while AI contributes to employment growth at the top and bottom of wage quintiles, its wage impact strongly depends on the movement of workers from the middle class to below the wage mean of the high-level quintile of wages, hence decreasing the average income of the top quintile. |
| Keywords: | artificial intelligence, automation, labor market, developing economies, AI exposure, inequality, non cognitive skills, cognitive skills |
| JEL: | J23 J24 J31 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17746 |
| By: | Athaya, Haura; Simatupang, Togar M |
| Abstract: | In this era, digital transformation become a key driver in enhancing the efficiency of the pharmaceutical supply chain. This study conducts a bibliometric literature review on digital transformation and pharmaceutical supply chains to identify research trends, literature gaps, and further development opportunities. The data are taken from Google Scholar and Scopus up to 2025, this research analyzes publications with the keywords “digital transformation” and “pharmaceutical supply chain” utilizing VOSviewer software. The findings indicate the adoption of technologies such as the Internet of Things (IoT), artificial intelligence (AI), and supply chain resilience. Furthermore, while there is extensive global research on digital transformation in supply chains, studies focusing on the pharmaceutical industry are limited in Indonesia. However, this study provides insights into the importance of digitalizati on in the pharmaceutical supply chain. It also encourages further research to understand the gap, regulatory implications, and collaborations, especially in the Indonesian context. |
| Date: | 2025–04–24 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:bm489_v1 |
| By: | McGuinness, Seamus (Economic and Social Research Institute, Dublin); Redmond, Paul (ESRI, Dublin); Pouliakas, Konstantinos (European Centre for the Development of Vocational Training (Cedefop)); Kelly, Lorcan (Economic and Social Research Institute, Dublin); Brosnan, Luke (Economic and Social Research Institute, Dublin) |
| Abstract: | Using the second wave of the European Skills and Jobs survey, this paper measures the relationship between technological change that automates or augments workers’ job tasks and their participation in work-related training. We find that 58 per cent of European employees experienced no change in the need to learn new technologies in their jobs during the 2020-21 period. Of those exposed to new digital technology, 14 per cent did not experience any change in job tasks, 10 per cent reported that new tasks had been created while 5 per cent only saw some of their tasks being displaced by new technology. The remaining 13 per cent simultaneously experienced both task displacement and task creation. Our analysis shows that employees in jobs impacted by new digital technologies are more likely to have to react to unpredictable situations, thus demonstrating a positive link between technologically driven task disruption and job complexity. We show a strong linear relationship between technologically driven job task disruption and the need for job-related training, with training requirements increasing the greater the impact of new technologies on task content. |
| Keywords: | upskilling, technological change, digitalisation, tasks, automation, training, complexity |
| JEL: | J24 O31 O33 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17753 |
| By: | Magaletti, Nicola; Leogrande, Angelo; Nortarnicola, Valeria; Mariani, Stefano; Di Molfetta, Mauro |
| Abstract: | This case study features Tecnomulipast, an SME from Southern Italy that specializes in machinery production for the food processing industry. The study is in fact centered on the company's digital transformation process, facilitated by investments in advanced production systems and innovation-driven managerial practices both facilitated by regional co-financing initiatives, including from Regione Puglia. At the center of it all is the integration between a new Industry 4.0-compliant laser welding system in the company's ERP system. Through Internet of Things (IoT) technologies, the system is inherently equipped to collect and transmit batch-level as well as real-time data, instantiating a cyber-physical system for advanced manufacturing. Easy to connect by standard interface (i.e. OPC-UA), the system is tied to an analytics data framework capable of working on structured data (e.g., KPIs, sensors' metrics) as well as on unstructured data (e.g., images), allowing for real-time monitoring, early anomaly signaling, and optimization of processes. Designed for scalability, the related technology architecture is future-proof to include artificial intelligence (AI) integration for augmenting decision-making with predictive and prescriptive analytics. Beyond the technological enhancement, however, the transformation was facilitated by an excellence managerial model that focuses on flexibility, data-driven governance, as well as on constant learning. Tecnomulipast's case offers an replicable template for SMEs—especially in low digital maturity areas—showing that targeted investment, innovation-driven management, and system-level integration might finally eliminate the gap between tech potential and operational performance in Industry 4.0 transitions. |
| Date: | 2025–04–23 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:g7qy2_v1 |
| By: | Melanie Arntz; Michael Böhm; Georg Graetz; Terry Gregory; Florian Lehmer; Cäcilia Lipowski |
| Abstract: | We investigate the diffusion of frontier technologies across German firms before and during the Covid-19 crisis. Our analysis tracks the nature, timing, and pandemic-related motivations behind technology investments, using tailor-made longitudinal survey data linked to administrative worker–firm records. Technologies adopted after the onset of the pandemic increasingly facilitated remote work and mitigated the negative employment effects of the crisis. Overall, however, investments in frontier technologies declined sharply, equivalent to a loss of 1.4 years of pre-pandemic investment activity. This procyclical adoption pattern is particularly striking since the pandemic created clear incentives to experiment with new technologies. Our findings highlight how short-run fluctuations may influence medium-run economic growth through their impact on technology diffusion. |
| Keywords: | frontier technology investments, firm-level survey data, cyclicality of technology adoption, Covid-19 crisis. |
| JEL: | O33 E22 E32 J23 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11825 |
| By: | Naudé, Wim (RWTH Aachen University) |
| Abstract: | This paper provides a primer on climate technology entrepreneurship, recognizing its limitations and potential adverse consequences. Climate technology entrepreneurship is needed to contribute to mitigation of and adaptation to climate change, and to help decouple economic growth from resource use. This paper identifies and describes three climate technology gaps: (i) an energy climate tech gap, an (ii) overshoot climate tech gap; and (iii) a resilience climate tech gap. The paper furthermore argues that policies for supporting climate technology entrepreneurship, including entrepreneurial ecosystems and mission-oriented approaches, have significant shortcomings. Furthermore, the paper concludes that Artificial Intelligence (AI) is unlikely to make a difference to the world’s climate change predicament. Hence, climate technology entrepreneurship is no panacea for climate change and ecological overshoot caused by human activity. On its own it will not save the world. |
| Keywords: | climate change, entrepreneurship, climate technology, sustainable development |
| JEL: | L26 Q54 O31 L53 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17794 |
| By: | Roxana Mihet (Swiss Finance Institute - HEC Lausanne); Kumar Rishabh (University of Lausanne - Faculty of Business and Economics (HEC Lausanne); University of Basel, Faculty of Business and Economics); Orlando Gomes (Lisbon Polytechnic Institute - Lisbon Accounting and Business School) |
| Abstract: | Artificial intelligence (AI) is transforming productivity and market structure, yet the roots of firm dominance in the modern economy remain unclear. Is market power driven by AI capabilities, access to data, or the interaction between them? We develop a dynamic model in which firms learn from data using AI, but face informational entropy: without sufficient AI, raw data has diminishing or even negative returns. The model predicts two key dynamics: (1) improvements in AI disproportionately benefit data-rich firms, reinforcing concentration; and (2) access to processed data substitutes for compute, allowing low-AI firms to compete and reducing concentration. We test these predictions using novel data from 2000–2023 and two exogenous shocks—the 2006 launch of Amazon Web Services (AWS) and the 2017 introduction of transformer-based architectures. The results confirm both mechanisms: compute access enhances the advantage of data-intensive firms, while access to processed data closes the performance gap between AI leaders and laggards. Our findings suggest that regulating data usability—not just AI models—is essential to preserving competition in the modern economy. |
| JEL: | L13 L41 O33 D83 E22 L86 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:chf:rpseri:rp2537 |