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on Information and Communication Technologies |
| By: | Alexander S. Kritikos (DIW Berlin, University of Potsdam, GLO Essen, IAB Nuremberg, CEPA); Mika Maliranta (University of Jyväskylä); Veera Nippala (University of Jyväskylä); Satu Nurmi (Statistics Finland) |
| Abstract: | We examine how the gender of business-owners is related to the wages paid to female relative to male employees working in their firms. Using Finnish register data and employing firm fixed effects, we find that the gender pay gap is – starting from a gender pay gap of 11 to 12 percent - two to three percentage-points lower for hourly wages in female-owned firms than in male-owned firms. Results are robust to how the wage is measured, as well as to various further robustness checks. More importantly, we find substantial differences between industries. While, for instance, in the manufacturing sector, the gender of the owner plays no role for the gender pay gap, in several service sector industries, like ICT or business services, no or a negligible gender pay gap can be found, but only when firms are led by female business owners. Businesses in male ownership maintain a gender pay gap of around 10 percent also in the latter industries. With increasing firm size, the influence of the gender of the owner, however, fades. In large firms, it seems that others – firm managers – determine wages and no differences in the pay gap are observed between male- and female-owned firms. |
| Keywords: | entrepreneurship, gender pay gap, discrimination, linked employer-employee data |
| JEL: | J16 J24 J31 J71 L26 M13 |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:pot:cepadp:76&r= |
| By: | Yulin Liu; Luyao Zhang |
| Abstract: | Decentralized Autonomous Organizations (DAOs), utilizing blockchain technology to enable collective governance, are a promising innovation. This research addresses the ongoing query in blockchain governance: How can DAOs optimize human cooperation? Focusing on the Network Nervous System (NNS), a comprehensive on-chain governance framework underpinned by the Internet Computer Protocol (ICP) and liquid democracy principles, we employ theoretical abstraction and simulations to evaluate its potential impact on cooperation and economic growth within DAOs. Our findings emphasize the significance of the NNS's staking mechanism, particularly the reward multiplier, in aligning individual short-term interests with the DAO's long-term prosperity. This study contributes to the understanding and effective design of blockchain-based governance systems. |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2404.13768&r= |
| By: | Shuochen Bi; Wenqing Bao; Jue Xiao; Jiangshan Wang; Tingting Deng |
| Abstract: | With the continuous development of artificial intelligence technology, using machine learning technology to predict market trends may no longer be out of reach. In recent years, artificial intelligence has become a research hotspot in the academic circle, and it has been widely used in image recognition, natural language processing and other fields, and also has a huge impact on the field of quantitative investment. As an investment method to obtain stable returns through data analysis, model construction and program trading, quantitative investment is deeply loved by financial institutions and investors. At the same time, as an important application field of quantitative investment, the quantitative investment strategy based on artificial intelligence technology arises at the historic moment.How to apply artificial intelligence to quantitative investment, so as to better achieve profit and risk control, has also become the focus and difficulty of the research. From a global perspective, inflation in the US and the Federal Reserve are the concerns of investors, which to some extent affects the direction of global assets, including the Chinese stock market. This paper studies the application of AI technology, quantitative investment, and AI technology in quantitative investment, aiming to provide investors with auxiliary decision-making, reduce the difficulty of investment analysis, and help them to obtain higher returns. |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2404.18184&r= |
| By: | Richiardi, Matteo; Leonie, Westhoff; Caterina, Astarita; Ekkehard, Ernst; Clare, Fenwick; Neysan, Khabirpour; Lorenzo, Pelizzari |
| Abstract: | We study the effects of digital transformation in the EU on individual employment outcomes, wage growth, and income inequality, during the decade 2010-2019. Our results allow us to formulate a “conveyor-belt†hypothesis, whereas digital skills are important for finding a job, but less so for retaining it. The ability of out-of-work individuals with higher digital skills to jump back on the labour market is reduced for those with higher education, suggesting a faster depreciation of their digital skills. A similar effect, although of limited size, is found for earning growth: out-of-work individuals with higher digital skills are not only more likely to find a job, but experience higher earning growth, compared to their peers with lower digital skills. Our results point to a vulnerability of workers “left behind†from the digital transformation and the labour market. The overall effects on inequality are, however, limited. |
| Date: | 2024–05–11 |
| URL: | http://d.repec.org/n?u=RePEc:ese:cempwp:cempa5-24&r= |
| By: | Janik Ole Wecks; Johannes Voshaar; Benedikt Jost Plate; Jochen Zimmermann |
| Abstract: | This study evaluates the impact of students' usage of generative artificial intelligence (GenAI) tools such as ChatGPT on their academic performance. We analyze student essays using GenAI detection systems to identify GenAI users among the cohort. Employing multivariate regression analysis, we find that students using GenAI tools score on average 6.71 (out of 100) points lower than non-users. While GenAI tools may offer benefits for learning and engagement, the way students actually use it correlates with diminished academic outcomes. Exploring the underlying mechanism, additional analyses show that the effect is particularly detrimental to students with high learning potential, suggesting an effect whereby GenAI tool usage hinders learning. Our findings provide important empirical evidence for the ongoing debate on the integration of GenAI in higher education and underscores the necessity for educators, institutions, and policymakers to carefully consider its implications for student performance. |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2404.19699&r= |
| By: | Maral Jamalova |
| Abstract: | The study uses bibliometric as well as content analysis to determine the current situation regarding the application of technology adoption models (i.e., the Technology Acceptance Model, Unified Theory of Acceptance and Use of Technology, and Innovation Diffusion Theory) to the smartphone market that also includes smart wearables. Hereby the author would like to determine the connection between smartphone usage and adoption models and enrich literature by defining state-of-the-art tendencies and approaches. To achieve the goal, the author applied a two-stage approach: in the first stage, 213 articles were analyzed using Citation and Bibliographic coupling tools in VOSviewer (1.6.20). The papers were selected from the Scopus database and the search of the papers was conducted in the fields of Economics, Business, and Computer technologies. In the second stage, the author conducted a brief literature review of the most influential papers. The results illustrate the situation regarding the implementation of different models in the case of smartphone adoption. Content analyses of the most influential papers were applied to explain and enrich the results of bibliometric analyses as well as determine research gaps and future research development. |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2405.01137&r= |