The Impact of Large Language Models on Knowledge Sharing: A 25% Decline in Stack Overflow Activity

by Johannes Wachs
Rethinking Trade Flows: What New Insights Do Gravity Models with TiVA Data Bring? – by Imre Fertő & Magdolna Sass

In an increasingly globalized economy, understanding international trade flows is critical for policymakers and economists alike. Traditional trade data have long been used to estimate and predict trade patterns between countries. However, as global value chains (GVCs) have evolved, there has been growing recognition that traditional trade data—based on gross exports—might not provide the […]
The Split Reality of Rural Gastro Tourism: Growth and Challenges in Hungary – by Gusztáv Nemes

Rural gastro tourism has emerged as a popular strategy for regional development, promising economic benefits and cultural revitalization in rural areas. Inspired by the success of destinations like Tuscany and Provence, many regions aim to replicate this model to boost local economies. However, the realities of rural tourism are often more complex than the […]
Large language models reduce public knowledge sharing on online Q&A platforms – by Johannes Wachs et al.

Large language models reduce public knowledge sharing on online Q&A platforms R. Maria del Rio-Chanona – Nadzeya Laurentsyeva – Johannes Wachs PNAS Nexus, Volume 3, Issue 9, September 2024, pgae400Published: 11 September 2024 Abstract Large language models (LLMs) are a potential substitute for human-generated data and knowledge resources. This substitution, however, can present a significant […]
The Transformative Power of Hungarian Local Food-Buying Clubs – by Zsófia Benedek

As the world shifts towards more sustainable and resilient food systems, local initiatives are gaining momentum. In Hungary, local food-buying clubs (BCs) are emerging as grassroots solutions to connect consumers directly with local food producers. Buying clubs not only promote sustainability but also offer a blueprint for alternative food networks (AFNs) that prioritize ethics, […]
Understanding Uncertainty in Agriculture: How State-Contingent Production Models Can Help Farmers Cope by Lajos Baráth

Agriculture has always been a risky business, with farmers constantly navigating uncertainties like weather, pests, and market fluctuations. These uncertainties have become even more pronounced with the growing impacts of climate change. To help farmers make better decisions in the face of uncertainty, agricultural economists are increasingly turning to a concept known as […]
What Drives Olympic Success? Insights from a New Study – by Imre Fertő and Gergely Csurilla

Why do some nations consistently top the Olympic medal tables while others struggle to secure a single podium finish? The pursuit of understanding the determinants of Olympic success has long intrigued economists and sports analysts alike. In a recent study published in Social Science Quarterly, we shed new light on this question by examining both […]
Captured green aims: The case of Hungary – new research article by Andrea Éltető & Judit Ricz

Captured green aims: The case of Hungary Andrea Éltető -Judit Ricz New Perspectives – Research article – First published online September 12, 2024 Abstract The article aims to shed light on the environmental risks of the Hungarian autocratic economic policy coupled with increased state interventionism and the revival of industrial policies. Green economic strategies proliferate […]
The effect of within-school sorting on the socioeconomic test score gap in Hungary – by Zoltán Hermann et al.

Are separate classrooms inherently unequal? The effect of within-school sorting on the socioeconomic test score gap in Hungary Zoltán Hermann, Hedvig Horváth, Dorottya Kisfalusi Economics of Education Review – Volume 103, December 2024 Highlights Within-school sorting on socioeconomic status is prevalent in Hungary. Within-school sorting widens socioeconomic test score inequalities. Sorting […]
Bid-Aggregation Based Clearing of Day-Ahead Electricity Markets

New research article by Dávid Csercsik et al.