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Economic limits of bitcoin’s environmental promises: pathway or pitfall for the green transformation?
Jona Stinner, Maximilian Gill, Marcel Tyrell
Witten/Herdecke University, Germany
Discussant: Thomas Walther (Utrecht University)
The Bitcoin network imposes significant external costs, including CO₂ emissions and electronic waste, comparable to those of entire nations. Some studies argue these externalities are justifiable, claiming that cryptocurrency mining fosters sustainable energy by monetizing surplus power. We examine this trade-off from an economic perspective, asking: Does surplus energy use mitigate Bitcoin’s externalities? Are carbon credits effective? And does mining ultimately benefit or harm society? Our model shows that while surplus energy reduces CO₂ emissions, it also incentivizes more mining, increasing e-waste and potentially offsetting gains. We find that carbon credits, if implemented multilaterally, effectively lower total externalities. Our study concludes by highlighting the dual role of Bitcoin mining in facilitating the short-term energy transition while hindering long-term decarbonization.
2:30pm - 3:00pm
Banking for boomers - A field experiment on technology adoption in financial services
Katharina Hartinger1, Erik Sarrazin1, David Jia-Hui Streich2
1Johannes Gutenberg University Mainz, Germany; 2Catholic University Eichstaett-Ingolstadt, Germany
Discussant: Maximilian Gill (University of Witten/Herdecke)
We develop and evaluate a training intervention to foster internet banking adoption in a field experiment with more than 25,000 elderly customers of a large German bank, of whom we randomize 333 into training. We find that the share of internet banking users increases by 26 percentage points relative to a matched control group. In terms of sustainable usage, the share of online transactions increases by 14 percentage points and remains elevated four months after the intervention. Our data allows us to estimate intent-to-treat effects and predict drop-out along the multi-stage adoption process, shedding light on practical roll-out considerations. We show that the type of training (self-guided versus social training) impacts drop-out differentially despite similar treatment effects.
3:00pm - 3:30pm
Certainly! Generative AI and its Impact on Academic Writing (in Finance)
Thomas Walther1,2, Marie Dutordoir3,1
1Utrecht University School of Economics, The Netherlands; 2Faculty of Business and Economics, Technische Universität Dresden, Germany; 3University of Manchester Alliance Manchester Business School, United Kingdom
Discussant: David Jia-Hui Streich (Catholic University Eichstaett-Ingolstadt)
This paper investigates how the introduction of Large Language Models (LLMs) has shaped academic writing in finance journals. Analyzing over 40,000 finance articles from 34 different journals, we find that readability declined while the use of LLM-associated terms increased following ChatGPT’s release at the end of 2022. These trends are more pronounced among authors from non-English-speaking countries and in lower-ranked journals. Moreover, the effects are strongest in countries that place less emphasis on creativity and technology and exhibit higher levels of moral confusion. Author-level analyses suggest that while LLM adoption boosts publication quantity, it does not enhance publication quality or scholarly impact.
