Monitoring Transmission of Systemic Risk from Shadow Banking to Regulated Banking

Abstract

There is a need to introduce a statistical method to the toolkit of the regulators that is versatile, easy-to-use and can handle complex cause-effect phenomena that are not directly observable or measurable, i.e. latent constructs. In a first application of partial least squares structural equation modeling (PLS-SEM) in financial stress testing, we demonstrate how this technique can be used to explain transmission of systemic risk. We model transmission of systemic risk from shadow banking to the regulated banking sector by a set of indicators (directly measurable variables) that are causes of systemic risk in shadow banking and consequences of systemic risk observed in the regulated banking sector. Procedures followed for predictive model assessment using PLS-SEM are outlined in clear steps for the benefit of those unfamiliar with this technique. Results indicate that around 75% of the variation in systemic risk in the regulated banking sector can be explained by micro and macro-level linkages traced to shadow banking. The path coefficients between the two exogenous latent constructs (i.e. systemic risk in shadow banking separately sourced from micro and macro-level linkages) and the endogenous latent construct (i.e. systemic risk in the regulated banking sector) are statistically significant. Regulators can use the approach illustrated in this article to monitor transmission of systemic risk appreciative of the extent of contagion emanating from micro and macro-level linkages, thus guiding microprudential versus macroprudential regulatory decisions. Skills demonstrated in this article are transferable to any finance topic or discipline where latent constructs are found.

Keywords: PLS-SEM, structural equation modeling, contagion of systemic risk, shadow banking, regulated banking

JEL Classification: E5, F3, G2, L5