Modeling the COVID-19 effects on the Austrian economy and banking system

Martin Guth (), Christian Lipp (), Claus Puhr () and Martin Schneider ()
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Martin Guth: Oesterreichische Nationalbank, Supervision Policy, Regulation and Strategy Division
Christian Lipp: Oesterreichische Nationalbank, Supervision Policy, Regulation and Strategy Division
Claus Puhr: Oesterreichische Nationalbank, Financial Markets Analysis and Surveillance Division

Financial Stability Report, 2020, issue 40, 63-86

Abstract: In response to the COVID-19 pandemic, many governments around the globe have imposed strict containment measures to prevent the further spreading of the virus. While saving lives, such lockdowns have also led to the largest peacetime economic shock since the Great Depression of the 1930s. To lessen the blow, governments have been complementing containment measures with mitigating measures. The latter serve to cushion both companies’ and households’ loss of revenue and income suffered during lockdowns, when nonessential economic activity has been suspended or cut to a minimum. In this paper, we only consider mitigating measures addressed to incorporated firms and banks. To assess the vulnerabilities of the Austrian economy and banking system, we follow a two-step approach. First, we have developed a novel model to assess the impact of both containment and mitigating measures on the real economy. This approach combines firm-level micro data from two different databases. To close remaining data gaps, we employ a Monte Carlo simulation to assess the effects of two scenarios based on the current OeNB economic forecast for Austria. We combine these scenarios capturing various policy reactions, i.e. mitigating measures, with firms’ solvency and liquidity positions and ultimately derive sectoral insolvency rates. Second, we use the OeNB’s top-down stress testing framework ARNIE to assess the COVID-19 impact on the banking system. Rather than employing large-scale regression models to derive risk parameters for credit risk, we infer default probabilities of banks’ credit exposure from the Austrian insolvency rates described above. Then, we extrapolate insolvency rates for domestic retail exposures and nondomestic exposures of the Austrian banking system. Here, we assume that individual industry sectors face similar challenges across countries and that country-specific GDP forecasts reflect the overall severity with which individual countries are affected by the pandemic. To this end, we draw on GDP forecasts by the ECB for countries other than Austria as well as country aggregates to calculate scaling factors based on the relative GDP-level deviation. We find that the mitigating measures up to end-August 2020, while effective, only partly offset the COVID-19-induced shock to Austrian firms and banks. They do, however, play an important role in lowering insolvency rates both on aggregate and in the hardest-hit sectors. As a side effect, the mitigating measures taken by the Austrian government and other institutions help improve the outlook for the Austrian banking system, which may benefit indirectly. Moreover, the top-down solvency stress test results show that the Austrian banking system – not only on an aggregate, but also on a disaggregate level – remains well capitalized despite the expected increase in insolvencies. At the time of publication, both COVID-19 containment and mitigating measures will have been extended, which calls into question some of the results of the paper. However, the main conclusion will nevertheless hold: only a substantial further deterioration of the COVID-19 pandemic could put the banking system in a difficult position.

Keywords: COVID-19; corporate insolvency; bank stress testing; quantitative policy modeling (search for similar items in EconPapers)
JEL-codes: C54 G21 G33 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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