Abstract
Most of the shadow banks (SBs) in India are not listed in stock exchanges; hence, it is a challenge to capture their systemic risk (SR) exposure, which could be quite different from those that are listed. This study aims to find the distinct features of SR of listed and non-listed banks by ascertaining that the quantum of risk emanates from both the groups and to identify the distinct drivers of such risk, which would help policymakers to manage risk with a different perspective. The SR of listed SBs is identified by the Conditional Value at Risk (CoVaR) approach, and the risk of non-listed SBs is identified following the Leave-One-Out (LOO) approach. The bank-specific and macro-factors that influence their SR exposure are identified through the random effect panel regression model with robust check. Over the years, there has been a heightened risk in both categories. The size of the risky segment of SBs in each category is quite different. Distinct firm-specific factors are found responsible for risk build-up. Identifying the risk exposure of the non-listed SBs is an important original contribution that has not been attempted by earlier researchers. Macro-variables as the contributors to the build-up of SR have augmented the existing literature. Further, in the context of any emerging economy, to the best of the authors’ knowledge, this is the first comprehensive work covering both the listed and non-listed SBs.
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