TITLE:
Explaining Systemic Risk in Money Market Funds
AUTHORS:
Necmi K. Avkiran
KEYWORDS:
Systemic Risk, Institutional Prime Money Market Funds, Latent Variables, Partial Least Squares Structural Equation Modeling
JOURNAL NAME:
Theoretical Economics Letters,
Vol.8 No.9,
June
12,
2018
ABSTRACT: For the first time, this study evaluates the
contributions to systemic risk in the context
of U.S. institutional prime money market funds (MMFs) from different sources
using partial least squares structural equation
modeling (PLS-SEM). The primary motivation behind this study is to
trace systemic risk to its underlying sources and measure which types of
relationships provide significant explanation using PLS-SEM. I illustrate the
application of PLS-SEM and interpretation of results in a step-by-step manner
to empower those new to PLS-SEM, and undertake robustness testing. Findings
indicate that through crisis years, macroprudential indicators contribute to potential systemic risk more than prudential indicators. This suggests that macroprudential
indicators that can be traced to individual MMFs market positions are more
important in understanding systemic risk during crises, and further underlines
the interconnectedness of markets.
PLS-SEM can be used to test the explanatory power of new indicators as they
emerge in an exploratory environment.