Financial Stability Report 40

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• Financial Stability Report 40 (PDF, 6,7 MB) November 2020

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• Call for applications: Klaus Liebscher Economic Research Scholarship (PDF, 78 kB) en 25.11.2020, 00:00:00

• Recent developments (PDF, 822 kB) en 25.11.2020, 00:00:00

• Nontechnical summaries in English and German (PDF, 144 kB) de en 25.11.2020, 00:00:00

• Austrian banks’ exposure to climate-related transition risk (PDF, 527 kB) Battiston, Guth, Monasterolo, Neudorfer, Pointner. Climate change poses several risks to the value of financial assets and to financial stability. In this study, we estimate the exposure of the Austrian banking sector to climate risks that might arise from a disorderly transition to a carbon-neutral economy. To this end, we identify climate policy-relevant sectors (CPRSs), i.e. sectors which are particularly sensitive to these transition risks, and match that information with granular data of outstanding credits and bonds held by Austrian banks. We find that the Austrian banking sector’s direct exposure to CPRSs is comparable with banks’ exposure in other countries and relevant to financial supervision. As some banks are particularly exposed to climate transition risk, both banks and supervisors should take this risk seriously and monitor it closely. en climate change, credit risk, risk management G18, G32, Q54 25.11.2020, 00:00:00

• Green finance – opportunities for the Austrian financial sector (PDF, 813 kB) Breitenfellner, Hasenhüttl, Lehmann, Tschulik. Climate change and the internationally agreed decarbonization of the global economy not only pose risks to the financial sector and the economy but also open up opportunities. While focusing on the risks, mandate-driven central banks and financial supervisors also need to understand the dynamics and potential of green or sustainable finance markets. The investment needs at the global, European and national level to fund the transition to a climate-neutral economy are mind-blowing. Earmarked public funds alone will not suffice. In addition, financial markets will have to channel (excess) resources above all into sustainable projects. In other words, breaking out of its niche, green finance will have to scale up. Though dynamic, the development of Austria’s green finance markets is still sobering. At the same time, customer surveys suggest that demand for sustainable finance products will grow. The absence of common definitions of sustainability may give rise to “greenwashing,” i.e. making misleading claims about the environ-mental sustainability of a financial product. To prevent this, regulators and supervisors should help overcome market barriers and dysfunction on the supply and demand side. Noteworthy efforts in this respect are the European Commission’s action plan on sustainable finance, the ECB’s paying greater attention to climate change issues as well as the Austrian government’s green finance agenda. Predefining a credible pathway for linking carbon pricing to greenhouse gas emission targets would be the most effective – and least distorting – way to foster green finance and a smooth transition. en climate change, financial market development, sustainable finance G2, O16, Q54 25.11.2020, 00:00:00

• Modeling the COVID-19 effects on the Austrian economy and banking system (PDF, 993 kB) Guth, Lipp, Puhr, Schneider. 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. en COVID-19, corporate insolvency, bank stress testing, quantitative policy modeling C54, G21, G33 25.11.2020, 00:00:00

• The Austrian bank branch network from 2000 to 2019 from a spatial perspective (PDF, 3,8 MB) Stix. This paper presents results of an analysis of the spatial distribution of bank branches in Austria over the period from January 2000 to December 2019 from two perspectives: First, we analyze the temporal development of bank branch availability at the municipality level. Second, we present estimates of travel distances to the nearest bank branch. At the end of 2019, 555 municipalities (27% of 2,096 Austrian municipalities) did not have a bank branch, which compares with 271 municipalities in January 2000. We show that the bulk of the increase in “branchless” municipalities occurred after 2014. The closure of the last branch in a municipality occurred predominantly in municipalities with fewer than 2,000 inhabitants, and, overall, only a relatively small share of the Austrian population live in municipalities that became branchless (4.6% or 410,000 inhabitants). Given this trend, which we also see at the international level, we study travel distances to bank branches (as of 2019). On average, Austrian residents have to travel 1.5 km from their homes to the nearest bank. This distance varies from 2.7 km in municipalities with fewer than 2,000 inhabitants to 0.7 km in larger cities. A total of 77% of the population resides within a 2 km travel distance to the nearest bank. Although our results suggest that, on average, Austrians have reasonable access to bank branches, a more disaggregated analysis allows us to identify municipalities where travel distances are longer. For example, about 433,000 residents (4.9% of the population) have to travel more than 5 km. Municipalities with a high share of residents who have to travel farther than 5 km have 1,000 inhabitants on average and are located in all provinces except Vienna. en retail banking, bank branch, spatial analysis, Austria G21, R12, O18, E40 25.11.2020, 00:00:00

• Annex: Key financial indicators (PDF, 231 kB) en 25.11.2020, 00:00:00

• Annex: Key financial indicators (XLSX, 96 kB) de