An empirical analysis of systemic and macroeconomic risk in South Africa: an application of the quantile regression

Joel Eita (), Sibusiso Blessing Ngobese and John Weirstrass Muteba Mwamba

MPRA Paper from University Library of Munich, Germany

Abstract: This study conducts an empirical analysis on how the build-up of systemic risk in the financial system affects downside macroeconomic risk of the South African economy. The study outlines and apply several systemic risk measures, namely the conditional value at risk, principal component analysis, average conditional volatility and interest rate spreads. Thereafter, the study employs the quantile regression to evaluate the predictive ability of each systemic risk measures to lower quantiles of economic activity. The study reveals that each of the systemic risk measures are significant predictors of macroeconomic risk. The results of this study serve as important tools that can help South African financial regulators and policymakers to foresee and prevent systemic risk. It enables regulators to identify the build-up of systemic vulnerabilities, systemically important financial and too connected to fail institutions. These are useful in the sense that they serve as early warning signals of financial systemic risk and the consequences of such on macroeconomic outcomes.

Keywords: systemic risk; macroeconomic risk; quantile regression; principal component analysis (search for similar items in EconPapers)
JEL-codes: C22 C58 G01 G21 (search for similar items in EconPapers)
Date: 2020-03-28
New Economics Papers: this item is included in nep-ban and nep-fdg
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:101493

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