When it comes to practical solutions, finding causal links is one of the holy grails in all disciplines of science. Although Granger-type causality doesn’t prove actual causality, it becomes a powerful tool for analyzing any system once it’s coupled with theoretical reasoning. Recent advances in wavelet analysis as a tool to unravel the patterns and coherence among different phenomena raise the question of whether such coherence can be used to indicate causality.
The 11th annual Austrian Stochastics Days were held on September 7 and 8, 2023, at the University of Klagenfurt. The Austrian Stochastics Days is a forum for researchers working on theoretical or practical topics in stochastic analysis. It covers any topic in stochastics, from insurance models to stochastic system analysis. The IIASA Cooperation and Transformative Governance (CAT) research group's research scholar, Mohammad Reza Yeganegi, shared their findings on the connection between wavelet analysis results and the Granger-type causality test in collaboration with Hossein Hassani, Senior Research Scholar in the IIASA CAT Research Group.
Granger-type causality tests are renowned for their ability to explore relationships between multiple time series. Theoretically, any causal relationship within a dynamic system’s variables will result in a phase difference among those variables. While Granger-type causality does not confirm actual causality, it provides a practical method for evaluating hypothesized causal links. In other words, once a hypothesis has been proposed within the scientific framework of a particular field, it can be empirically tested with observed data using Granger-type causality tests. However, such tests don’t shed light on the details of causal relationships. To address this, researchers have attempted to unify Granger-type causality tests with phase difference analysis. This unification of methods links the practical application of Granger-type causality tests with a deeper understanding of co-existing patterns over time.
In his talk, Yeganegi discussed a wavelet framework to merge these two concepts in stochastic systems, arguing that findings from one approach could enrich the results from the other. Findings from Yeganegi and Hassani's research showed a path to incorporating wavelet analysis and Granger-type causality tests for stochastic system analysis.
To read more on this matter click here.
To read more about the Austria Stochastic Days, click here.
News
15 October 2026
IIASA strengthens science diplomacy ties at UNGA in New York
IIASA Science Diplomacy Director and Head of Communications and External Relations Susie Kitchens represented the Institute at the United Nations General Assembly (UNGA) High-level Week and Science Summit in New York in September, contributing to discussions on how science and international cooperation can help address shared global challenges.
13 October 2026
Connecting disciplines and inspiring new ideas with the Environment and Climate Research Hub
IIASA Deputy Director General Karen Lips delivered a keynote at the University of Vienna's recent Environment and Climate Research Hub (ECH) Research Frontiers Workshop in Bad Vöslau, Austria, emphasizing the importance of interdisciplinary collaboration in addressing complex environmental and climate challenges.
12 October 2026
Connecting science across borders: IIASA Committee meets University of Salzburg
How can universities and international research organisations work together to address the complex challenges of a changing world? This question shaped a full day of scientific exchange at the University of Salzburg on 6 October, when the Austrian IIASA Committee met with members of the University community to discuss research, collaboration and opportunities for researchers and students.