Credit Allocation when Borrowers are Economically Linked: An Empirical Analysis of Bank Loans to Corporate Customers
Iftekhar Hasan, Kristina Minnick, Kartik Raman
Journal of Corporate Finance,
June
2020
Abstract
Using detailed loan level data, we examine bank lending to corporate customers relying on principal suppliers. Customers experience larger loan spreads, higher intensity of covenants and greater likelihood of requiring collateral when they depend more on the principal supplier for inputs. The positive association between the customer’s loan spread and its dependence on the principal supplier is less pronounced when the bank has a prior loan outstanding with the principal supplier, and when the bank has higher market share in the industry. Longer relationships between the customer and its principal supplier, and between the bank and the principal supplier, mitigate lending constraints. The evidence is consistent with corporate suppliers serving as an informational bridge between the lender and the customer.
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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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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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Bank Accounting Regulations, Enforcement Mechanisms, and Financial Statement Informativeness: Cross-country Evidence
Augustine Duru, Iftekhar Hasan, Liang Song, Yijiang Zhao
Accounting and Business Research,
No. 3,
2020
Abstract
We construct measures of accounting regulations and enforcement mechanisms that are specific to a country's banking industry. Using a sample of major banks in 37 economies, we find that the informativeness of banks’ financial statements, measured by the value relevance of earnings and common equity, is higher in countries with stricter bank accounting regulations and countries with stronger enforcement. These findings suggest that superior bank accounting and enforcement mechanisms enhance the informativeness of banks’ financial statements. In addition, we find that the effects of bank accounting regulations are more pronounced in countries with stronger enforcement in the banking industry, suggesting that enforcement is complementary to bank accounting regulations in achieving higher value relevance of financial statements. Our study has important policy implications for bank regulators.
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The Value of Firm Networks: A Natural Experiment on Board Connections
Ester Faia, Maximilian Mayer, Vincenzo Pezone
CEPR Discussion Papers,
No. 14591,
2020
Abstract
This paper presents causal evidence of the effects of boardroom networks on firm value and compensation policies. We exploit exogenous variation in network centrality arising from a ban on interlocking directorates of Italian financial and insurance companies. We leverage this shock to show that firms whose centrality in the network rises after the reform experience positive abnormal returns around the announcement date and are better hedged against shocks. Information dissemination plays a central role: results are driven by firms that have higher idiosyncratic volatility, low analyst coverage, and more uncertainty surrounding their earnings forecasts. Firms benefit more from boardroom centrality when they are more central in the input-output network, hence more susceptible to upstream shocks, when they are less central in the cross-ownership network, or when they have low profitability or low growth opportunities. Network centrality also results in higher directors' compensation, due to rent sharing and improved executives' outside option, and more similar compensation policies between connected 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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Comparing Financial Transparency between For-profit and Nonprofit Suppliers of Public Goods: Evidence from Microfinance
John W. Goodell, Abhinav Goyal, Iftekhar Hasan
Journal of International Financial Markets, Institutions and Money,
January
2020
Abstract
Previous research finds market financing is favored over relationship financing in environments of better governance, since the transaction costs to investors of vetting asymmetric information are thereby reduced. For industries supplying public goods, for-profits rely on market financing, while nonprofits rely on relationships with donors. This suggests that for-profits will be more inclined than nonprofits to improve financial transparency. We examine the impact of for-profit versus nonprofit status on the financial transparency of firms engaged with supplying public goods. There are relatively few industries that have large number of both for-profit and nonprofit firms across countries. However, the microfinance industry provides the opportunity of a large number of both for-profit and nonprofit firms in relatively equal numbers, across a wide array of countries. Consistent with our prediction, we find that financial transparency is positively associated with a for-profit status. Results will be of broad interest both to scholars interested in the roles of transparency and transaction costs on market versus relational financing; as well as to policy makers interested in the impact of for-profit on the supply of public goods, and on the microfinance industry in particular.
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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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Drawing Conclusions from Structural Vector Autoregressions Identified on the Basis of Sign Restrictions
Christiane Baumeister, James D. Hamilton
Abstract
This paper discusses the problems associated with using information about the signs of certain magnitudes as a basis for drawing structural conclusions in vector autoregressions. We also review available tools to solve these problems. For illustration we use Dahlhaus and Vasishtha's (2019) study of the effects of a U.S. monetary contraction on capital flows to emerging markets. We explain why sign restrictions alone are not enough to allow us to answer the question and suggest alternative approaches that could be used.
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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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