The Swiss Journal of Economics and Statistics (SJES) is blind peer-reviewed open access journal published under the brand SpringerOpen.
We welcome original research papers using textual analysis in economics and finance. Potential areas include, but are not limited to, macroeconomics (measurement and identification), forecasting, political economy, law and economics, economics of regulation, economics of innovation, public economics, media economics, health economics, economics of contracts, and education.
Digitalization, availability of online texts, and advances in computing power have made it possible to leverage vast amounts of text for economic analysis. The Swiss Journal of Economics and Statistics invites papers that apply textual analysis to economics and finance to uncover novel insights.
Submit your manuscript to this collection through the participating journal.
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Daniel Kaufmann, University of Neuchâtel, Switzerland
Daniel holds the Chair of Applied Macroeconomics at the University of Neuchâtel, and is director of the MSc in Applied Economics, as well as Research Fellow at the KOF Swiss Economic Institute, ETH Zurich. His research focuses on inflation, output, interest rate, and exchange rate dynamics over long historical episodes. He is also interested in the role of monetary policy and nominal rigidities. His recent work uses novel methods and data sources to analyze Swiss business cycle fluctuations since the 19th century. -
Elliott Ash, ETH Zurich, Switzerland
Elliott Ash is Associate Professor of Law, Economics, and Data Science at ETH Zurich's Center for Law & Economics. His interdisciplinary research takes an empirical approach to understanding laws, judges, and institutions, combining AI tools for measurement with econometrics for causal analysis. His work has been published in top venues in economics, law, political science, and computer science. He has held previous appointments at University of Warwick and Princeton University. He earned a PhD in economics and JD from Columbia University and an LLM in international criminal law from University of Amsterdam. -
Markus Leippold, University of Zurich, Switzerland
Markus Leippold is a professor at the Swiss Finance Institute (SFI) and the University of Zurich (UZH), where he holds the Chair in Financial Engineering. He is also a research scientist at Google DeepMind. Before joining the University of Zurich in 2009, Markus was an associate professor in quantitative finance at Imperial College Business School, London. In 2005, he was a visiting professor at the Federal Reserve Bank in New York. Markus obtained his Ph.D. in economics from the University of St.Gallen, Switzerland, in 1999. After some years in the financial industry, he started his academic career as an assistant professor at UZH in 2002. -
Leif Anders Thorsrud, BI Norwegian Business School, Norway
Leif Anders Thorsrud is a Professor at BI Norwegian Business School and serves as Associate Dean for the MSc Data Science for Business program at BI. Thorsrud obtained his Ph.D. in 2014. His research has been published in top field international journals, and his area of expertise includes time series analysis, machine learning and applied macroeconomics and natural language processing. Thorsrud has previously worked as a Senior Researcher in Norges Bank and the Reserve Bank of New Zealand. Thorsrud is also the co-author of the book: "Applied Time Series for Macroeconomics".
