The Corona Recession and Bank Stress in Germany
Reint E. Gropp, Michael Koetter, William McShane
IWH Online,
No. 4,
2020
Abstract
We conduct stress tests for a large sample of German banks across different recoveries from the Corona recession. We find that, depending on how quickly the economy recovers, between 6% to 28% of banks could become distressed from defaulting corporate borrowers alone. Many of these banks are likely to require regulatory intervention or may even fail. Even in our most optimistic scenario, bank capital ratios decline by nearly 24%. The sum of total loans held by distressed banks could plausibly range from 127 to 624 billion Euros and it may take years before the full extent of this stress is observable. Hence, the current recession could result in an acute contraction in lending to the real economy, thereby worsening the current recession , decelerating the recovery, or perhaps even causing a “double dip” recession. Additionally, we show that the corporate portfolio of savings and cooperative banks is more than five times as exposed to small firms as that of commercial banks and Landesbanken. The preliminary evidence indicates small firms are particularly exposed to the current crisis, which implies that cooperative and savings banks are at especially high risk of becoming distressed. Given that the financial difficulties may seriously impair the recovery from the Covid-19 crisis, the pressure to bail out large parts of the banking system will be strong. Recent research suggests that the long run benefits of largely resisting these pressures may be high and could result in a more efficient economy.
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Firm Productivity Report
Johannes Amlung, Tommaso Bighelli, Roman Blyzniuk, Marco Christophori, Jonathan Deist, Filippo di Mauro, Annalisa Ferrando, Mirja Hälbig, Peter Haug, Sergio Inferrera, Tibor Lalinsky, Phillip Meinen, Marc Melitz, Matthias Mertens, Ottavia Papagalli, Verena Plümpe, Roberta Serafini
CompNet - The Competitive Research Network,
2020
Abstract
As we enter a second phase of the COVID-pandemic, in which we attempt to reopen economies and foster growth, investigating the efficiency and productivity of firms becomes essential if we wish to design the appropriate policies. The 2020 Flagship Firm Productivity report provides a comprehensive account of how productivity is changing –and what is driving those changes –in Europe, drawing from granular firm-level information.Although it was written before the crisis erupted, this report can therefore offer critical insights to current policymaking andprovides grounds for future research.
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Automation, Globalization and Vanishing Jobs: A Labor Market Sorting View
Ester Faia, Sébastien Laffitte, Maximilian Mayer, Gianmarco Ottaviano
IZA Discussion Paper,
No. 13267,
2020
Abstract
We show, theoretically and empirically, that the effects of technological change associated with automation and offshoring on the labor market can substantially deviate from standard neoclassical conclusions when search frictions hinder efficient assortative matching between firms with heterogeneous tasks and workers with heterogeneous skills. Our key hypothesis is that better matches enjoy a comparative advantage in exploiting automation and a comparative disadvantage in exploiting offshoring. It implies that automation (offshoring) may reduce (raise) employment by lengthening (shortening) unemployment duration due to higher (lower) match selectivity. We find empirical support for this implication in a dataset covering 92 occupations and 16 sectors in 13 European countries from 1995 to 2010.
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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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Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Empirical Economics,
No. 1,
2020
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
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Labor Market Power and the Distorting Effects of International Trade
Matthias Mertens
International Journal of Industrial Organization,
January
2020
Abstract
This article examines how final product trade with China shapes and interacts with labor market imperfections that create market power in labor markets and prevent an efficient market outcome. I develop a framework for measuring such labor market power distortions in monetary terms and document large degrees of these distortions in Germany's manufacturing sector. Import competition only exerts labor market disciplining effects if firms, rather than employees, possess labor market power. Otherwise, increasing export demand and import competition both fortify existing distortions, which decreases labor market efficiency. This widens the gap between potential and realized output and thus diminishes classical gains from trade.
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Nowcasting East German GDP Growth: a MIDAS Approach
João Carlos Claudio, Katja Heinisch, Oliver Holtemöller
Abstract
Economic forecasts are an important element of rational economic policy both on the federal and on the local or regional level. Solid budgetary plans for government expenditures and revenues rely on efficient macroeconomic projections. However, official data on quarterly regional GDP in Germany are not available, and hence, regional GDP forecasts do not play an important role in public budget planning. We provide a new quarterly time series for East German GDP and develop a forecasting approach for East German GDP that takes data availability in real time and regional economic indicators into account. Overall, we find that mixed-data sampling model forecasts for East German GDP in combination with model averaging outperform regional forecast models that only rely on aggregate national information.
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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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Managerial Ability and Value Relevance of Earnings
Bill Francis, Iftekhar Hasan, Ibrahim Siraj, Qiang Wu
China Accounting and Finance Review,
No. 4,
2019
Abstract
We examine how management ability affects the extent to which capital markets rely on earnings to value equity. Using a measure of ability that captures a management team’s capacity for generating revenues with a given level of resources compared to other industry peers, we find a strong positive association between managerial ability and the value relevance of earnings. Additional tests show that our results are robust to controlling for earnings attributes and investment efficiency. We use propensity score matching and the 2SLS instrumental variable approach to deal with the issue of endogeneity. For further identification, we examine CEO turnover and find that newly hired CEOs with better managerial abilities than the replaced CEOs increase the value relevance of earnings. We identify weak corporate governance and product market power as the two important channels through which superior management practices play an important role in the corporate decision-making process that positively influence the value relevance of earnings. Overall, our findings suggest that better managers make accounting information significantly more relevant in the market valuation of equity.
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Private Debt, Public Debt, and Capital Misallocation
Behzod Alimov
IWH-CompNet Discussion Papers,
No. 7,
2019
Abstract
Does finance facilitate efficient allocation of resources? Our aim in this paper is to find out whether increases in private and public indebtedness affect capital misallocation, which is measured as the dispersion in the return to capital across firms in different industries. For this, we use a novel dataset containing industrylevel data for 18 European countries and control for different macroeconomic indicators as potential determinants of capital misallocation. We exploit the within-country variation across industries in such indicators as external finance dependence, technological intensity, credit constraints and competitive structure, and find that private debt accumulation disproportionately increases capital misallocation in industries with higher financial dependence, higher R&D intensity, a larger share of credit-constrained firms and a lower level of competition. On the other hand, we fail to find any significant and robust effect of public debt on capital misallocation within our country-sector pairs. We believe the distortionary effects of private debt found in our analysis needs a deeper theoretical investigation.
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