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
16 May 2025
Roman Hoffmann honored with awards and Academy membership
IIASA researcher Roman Hoffmann has been honored with two prestigious awards and elected as a member of the Young Academy of the Austrian Academy of Sciences, recognizing his contributions to climate change research and environmental social sciences.
08 May 2025
OJERI-IIASA Symposium 2025 Wraps Up with Significant Exchanges on Wildfire and Sustainable Land-Water Management
The OJEong Resilience Institute at Korea University (OJERI) and the International Institute for Applied Systems Analysis (IIASA) successfully held the OJERI–IIASA Symposium 2025 on April 28–29 at IIASA in Laxenburg, Austria. With the theme “Forest Fire and Water-Land Management under the Carbon (Emission) Cycle”, the symposium aimed to continue the strong partnership between IIASA and OJERI@KU in advancing cross-disciplinary research for sustainable forest and land-water management.
08 April 2025
IIASA Director General supports ambitious Austrian tree-planting initiative
A new climate initiative launched in Vorarlberg, Austria, aims to plant 50 trees for every child born in the region. The initiative, which will run under the patronage of IIASA Director General Hans Joachim (John) Schellnhuber, was introduced on 3 April in Rankweil.