Transmitting Fiscal Covid-19 Counterstrikes Effectively: Mind the Banks!
Reint E. Gropp, Michael Koetter, William McShane
IWH Online,
No. 2,
2020
Abstract
The German government launched an unprecedented range of support programmes to mitigate the economic fallout from the Covid-19 pandemic for employees, self-employed, and firms. Fiscal transfers and guarantees amount to approximately €1.2 billion by now and are supplemented by similarly impressive measures taken at the European level. We argue in this note that the pandemic poses, however, also important challenges to financial stability in general and bank resilience in particular. A stable banking system is, in turn, crucial to ensure that support measures are transmitted to the real economy and that credit markets function seamlessly. Our analysis shows that banks are exposed rather differently to deteriorated business outlooks due to marked differences in their lending specialisation to different economic sectors. Moreover, a number of the banks that were hit hardest by bleak growth prospects of their borrowers were already relatively thinly capitalised at the outset of the pandemic. This coincidence can impair the ability and willingness of selected banks to continue lending to their mostly small and medium sized entrepreneurial customers. Therefore, ensuring financial stability is an important pre-requisite to also ensure the effectiveness of fiscal support measures. We estimate that contracting business prospects during the first quarter of 2020 could lead to an additional volume of non-performing loans (NPL) among the 40 most stressed banks ‒ mostly small, regional relationship lenders ‒ on the order of around €200 million. Given an initial stock of NPL of €650 million, this estimate thus suggests a potential level of NPL at year-end of €1.45 billion for this fairly small group of banks already. We further show that 17 regional banking markets are particularly exposed to an undesirable coincidence of starkly deteriorating borrower prospects and weakly capitalised local banks. Since these regions are home to around 6.8% of total employment in Germany, we argue that ensuring financial stability in the form of healthy bank balance sheets should be an important element of the policy strategy to contain the adverse real economic effects of the pandemic.
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Banks’ Equity Performance and the Term Structure of Interest Rates
Elyas Elyasiani, Iftekhar Hasan, Elena Kalotychou, Panos K. Pouliasis, Sotiris Staikouras
Financial Markets, Institutions and Instruments,
No. 2,
2020
Abstract
Using an extensive global sample, this paper investigates the impact of the term structure of interest rates on bank equity returns. Decomposing the yield curve to its three constituents (level, slope and curvature), the paper evaluates the time-varying sensitivity of the bank’s equity returns to these constituents by using a diagonal dynamic conditional correlation multivariate GARCH framework. Evidence reveals that the empirical proxies for the three factors explain the variations in equity returns above and beyond the market-wide effect. More specifically, shocks to the long-term (level) and short-term (slope) factors have a statistically significant impact on equity returns, while those on the medium-term (curvature) factor are less clear-cut. Bank size plays an important role in the sense that exposures are higher for SIFIs and large banks compared to medium and small banks. Moreover, banks exhibit greater sensitivities to all risk factors during the crisis and postcrisis periods compared to the pre-crisis period; though these sensitivities do not differ for market-oriented and bank-oriented financial systems.
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How to Talk Down Your Stock Performance
Andreas Barth, Sasan Mansouri, Fabian Wöbbeking, Severin Zörgiebel
SSRN Discussion Papers,
2020
Abstract
We process the natural language of verbal firm disclosures in order to study the use of context specific language or jargon and its impact on financial performance. We observe that, within the Q&A of earnings conference calls, managers use less jargon in responses to tougher questions, and after a quarter of bad economic success. Moreover, markets interpret the lack of precise information as a bad signal: we find lower cumulative abnormal returns and a higher implied volatility following earnings calls where managers use less jargon. These results support the argument that context specific language or jargon helps to efficiently and precisely transfer information.
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Does Working at a Start-Up Pay Off?
Daniel Fackler, Lisa Hölscher, Claus Schnabel, Antje Weyh
Abstract
Using representative linked employer-employee data for Germany, this paper analyzes short- and long-run differences in labor market performance of workers joining startups instead of incumbent firms. Applying entropy balancing and following individuals over ten years, we find huge and long-lasting drawbacks from entering a start-up in terms of wages, yearly income, and (un)employment. These disadvantages hold for all groups of workers and types of start-ups analyzed. Although our analysis of different subsequent career paths highlights important heterogeneities, it does not reveal any strategy through which workers joining start-ups can catch up with the income of similar workers entering incumbent firms.
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Managerial Biases and Debt Contract Design: The Case of Syndicated Loans
Tim R. Adam, Valentin Burg, Tobias Scheinert, Daniel Streitz
Management Science,
No. 1,
2020
Abstract
We examine whether managerial overconfidence impacts the use of performance-pricing provisions in loan contracts (performance-sensitive debt [PSD]). Managers with biased views may issue PSD because they consider this form of debt to be mispriced. Our evidence shows that overconfident managers are more likely to issue rate-increasing PSD than regular debt. They choose PSD with steeper performance-pricing schedules than those chosen by rational managers. We reject the possibility that overconfident managers have (persistent) positive private information and use PSD for signaling. Finally, firms seem to benefit less from using PSD ex post if they are managed by overconfident rather than rational managers.
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Does Machine Learning Help us Predict Banking Crises?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Journal of Financial Stability,
December
2019
Abstract
This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance metric, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly efficiently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.
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Should Forecasters Use Real‐time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
Katja Heinisch, Rolf Scheufele
German Economic Review,
No. 4,
2019
Abstract
In this paper, we investigate whether differences exist among forecasts using real‐time or latest‐available data to predict gross domestic product (GDP). We employ mixed‐frequency models and real‐time data to reassess the role of surveys and financial data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real‐time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.
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Wage Delegation in the Field
Sabrina Jeworrek, Vanessa Mertins
Journal of Economics and Management Strategy,
No. 4,
2019
Abstract
By conducting a natural field experiment, we analyze the managerial policy of delegating the wage choice to employees. We find that this policy enhances performance significantly, which is remarkable since allocated wage premiums of the same size have no effect at all. Observed self‐imposed wage restraints and absence of negative peer effects speak in favor of wage delegation, although the chosen wage premium levels severely dampen its net value. Additional experimental and survey data provide important insights into employees' underlying motivations.
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02.10.2019 • 20/2019
Joint Economic Forecast Autumn 2019: Economy Cools Further – Industry in Recession
Berlin, October 2, 2019 – Germany’s leading economics research institutes have revised their economic forecast for Germany significantly downward. Whereas in the spring they still expected gross domestic product (GDP) to grow by 0.8% in 2019, they now expect GDP growth to be only 0.5%. Reasons for the poor performance are the falling worldwide demand for capital goods – in the exporting of which the Germany economy is specialised – as well as political uncertainty and structural changes in the automotive industry. By contrast, monetary policy is shoring up macroeconomic expansion. For the coming year, the economic researchers have also reduced their forecast of GDP growth to 1.1%, having predicted 1.8% in the spring.
Oliver Holtemöller
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The Value of Smarter Teachers: International Evidence on Teacher Cognitive Skills and Student Performance
Eric A. Hanushek, Marc Piopiunik, Simon Wiederhold
Journal of Human Resources,
No. 4,
2019
Abstract
We construct country-level measures of teacher cognitive skills using unique assessment data for 31 countries. We find substantial differences in teacher cognitive skills across countries that are strongly related to student performance. Results are supported by fixed-effects estimation exploiting within-country between-subject variation in teacher skills. A series of robustness and placebo tests indicate a systematic influence of teacher skills as distinct from overall differences among countries in the level of cognitive skills. Moreover, observed country variations in teacher cognitive skills are significantly related to differences in women’s access to high-skill occupations outside teaching and to salary premiums for teachers.
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