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on Information and Communication Technologies |
| By: | Mantej Pardesi; Frank Corvers; Harald Pfeifer |
| Abstract: | We study how investment spikes in technologies and complementary infrastructure influence firms' hiring and training strategies. While prior work emphasizes how technologies reallocate skill demand, few focus on how firms acquire the required skills. Using linked employer-employee data on German establishments, we identify spikes by their technological composition and capital vintages. Event study estimates show that investment spikes in ICT and production line technologies lead to an upscaling effect raising employment by external hiring followed by training of young apprentices. Combining technologies with factories and plants induces firms to use apprenticeship training without an increase in external hiring. Incumbent workers are trained when investment spikes renew the vintage of firm's capital. Our findings support a vintage human capital framework in which technology adoption induces firms to gradually adjust workforce through hiring and training while preserving expertise of incumbent workers. |
| Keywords: | investment spikes, technology adoption, technology vintages, training, skill formation |
| JEL: | J24 D22 O33 |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:iso:educat:0249 |
| By: | Halkos, George; Aslanidis, Panagiotis-Stavros |
| Abstract: | The present report assesses the Greek inclusive wealth over 1990–2020 using the Inclusive Wealth Index (IWI), decomposing human, produced, and natural capital and benchmarking against the EU-28. The results show that the produced capital expanded markedly but plateaued after the financial crisis of 2008. Furthermore, the human capital per capita remains ~46% below the EU average, reflecting gaps in education, ICT and managerial skills, labour productivity, and the effects of brain drain and regional disparities. Essentially, the natural capital has been pressured by biodiversity loss, deforestation, marine pollution, and limited circular-economy uptake. Overall, these dynamics place Greece in the lower-middle tier of EU countries for inclusive wealth, therefore, the report outlines priorities to close the gap. The proposed policies target, one the one hand on human capital, by strengthening tertiary and vocational pathways, fostering innovation and university and industry linkages, expanding female employment, enhancing ICT skills, and rebuilding institutional trust. On the other hand on natural capital, through strategies on sustainable forest and land management, marine ecosystem protection, circular-economy incentives, and recognition of socio-cultural ecosystem services to support conservation and eco-tourism. To conclude, the improvement of human and natural capitals is pivotal for long-term wellbeing, intergenerational equity, and alignment with the EU sustainability agenda. |
| Keywords: | Inclusive wealth; beyond GDP; sustainable development; Greece. |
| JEL: | E01 O44 Q01 Q50 Q56 |
| Date: | 2025–08–27 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125927 |
| By: | Joshua Magero |
| Abstract: | Using data from Kenya's 2016 Micro, Small and Medium Enterprises survey, the 2017 Census of Establishments, key informant interviews, and focus group discussions, this paper examines the patterns of structural transformation as well as its drivers and barriers in Nairobi. The findings show that the pattern for employment shares by sector over time suggest movements of labour into the service sector. While the movements are largely into non-business activities, business-related activities have also picked up, an indication of the rapid expansion of the ICT sub-sector. |
| Keywords: | Urbanization, Employment, Structural transformation, Political settlements, Kenya |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:unu:wpaper:wp-2025-54 |
| By: | Schnabel, Claus (University of Erlangen-Nuremberg); Abraham, Martin (University of Erlangen-Nuremberg); Wieser, Luisa (FAU, Erlangen Nuremberg); Niessen, Cornelia (University of Erlangen-Nuremberg); Bergmann, Sara (FAU Erlangen Nuremberg) |
| Abstract: | This paper investigates the digital gender divide (DGD) in Germany by analyzing gendered patterns of digital technology use in both private and professional contexts, and their consequences for wages. Using data from the GESIS Panel, we construct a Digital Involvement at Work index covering ten technologies to assess both active use and passive exposure. Our results reveal a significant DGD in the workplace: women are consistently less involved with digital technologies at work, even after controlling for education, occupational qualification, and digital affinity. In contrast, private digital use appears more balanced. This suggests that structural constraints—rather than individual preferences—play a key role in shaping the divide. Further, we find that digital involvement is positively associated with individual income, yet it does not close the gender pay gap (GPG). On the contrary, digital involvement yields greater wage returns for men than for women. These findings highlight how gendered patterns of digitalization in the workplace reinforce existing inequalities. We conclude with a discussion of the implications for policy and labor market equity, emphasizing the need for measures that promote equitable digital inclusion. |
| Keywords: | gender, digital involvement, digitalisation, wages, gender pay gap, Germany |
| JEL: | J31 J16 O15 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18097 |
| By: | Paloma Mar\'in; Sergio Ardanza-Trevijano; Javier Sabio |
| Abstract: | The digitalization of financial markets has shifted trading from voice to electronic channels, with Multi-Dealer-to-Client (MD2C) platforms now enabling clients to request quotes (RfQs) for financial instruments like bonds from multiple dealers simultaneously. In this competitive landscape, dealers cannot see each other's prices, making a rigorous analysis of the negotiation process crucial to ensure their profitability. This article introduces a novel general framework for analyzing the RfQ process using probabilistic graphical models and causal inference. Within this framework, we explore different inferential questions that are relevant for dealers participating in MD2C platforms, such as the computation of optimal prices, estimating potential revenues and the identification of clients that might be interested in trading the dealer's axes. We then move into analyzing two different approaches for model specification: a generative model built on the work of (Fermanian, Gu\'eant & Pu, 2017); and discriminative models utilizing machine learning techniques. We evaluate these methodologies using predictive metrics designed to assess their effectiveness in the context of optimal pricing, highlighting the relative benefits of using models that take into account the internal mechanisms of the negotiation process. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.18147 |