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  4. Monitoring transmission of systemic risk: Application of partial least squares structural equation modeling in financial stress testing
 
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Monitoring transmission of systemic risk: Application of partial least squares structural equation modeling in financial stress testing

Publikationstyp
Journal Article
Date Issued
2018-06
Sprache
English
Author(s)
Avkiran, Necmi K.  
Ringle, Christian M.  orcid-logo
Low, Rand  
Institut
Personalwirtschaft und Arbeitsorganisation W-9  
TORE-URI
http://hdl.handle.net/11420/2506
Journal
Journal of risk  
Volume
20
Issue
5
Start Page
83
End Page
115
Citation
Journal of Risk 20 (5): 83-115 (2018-06)
Publisher DOI
10.21314/JOR.2018.386
Scopus ID
2-s2.0-85052749443
Regulators need a method that is versatile, is easy to use and can handle complex path models with latent (not directly observable) variables. In a first application of partial least squares structural equation modeling (PLS-SEM) in financial stress testing, we demonstrate how PLS-SEM can be used to explain the transmission of systemic risk. We model this transmission of systemic risk from shadow banking to the regulated banking sector (RBS) using a set of indicators (directly observable variables) that are sources of systemic risk in shadow banking and consequences of systemic risk measured in the RBS. Procedures for predictive model assessment using PLS-SEM are outlined in clear steps. Statistically significant results based on predictive modeling indicate that around 75% of the variation in systemic risk in the RBS can be explained by microlevel and macrolevel linkages that can be traced to shadow banking (we use partially simulated data). The finding that microlevel linkages have a greater impact on the contagion of systemic risk highlights the type of significant insight that can be generated through PLS-SEM. Regulators can use PLS-SEM to monitor the transmission of systemic risk, and the demonstrated skills can be transferred to any topic with latent constructs.
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