The Value of Firm Networks: A Natural Experiment on Board Connections
Ester Faia, Maximilian Mayer, Vincenzo Pezone
CEPR Discussion Papers,
Nr. 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,
Nr. 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,
Nr. 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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Managerial Ability and Value Relevance of Earnings
Bill Francis, Iftekhar Hasan, Ibrahim Siraj, Qiang Wu
China Accounting and Finance Review,
Nr. 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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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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Foreign Ownership, Bank Information Environments, and the International Mobility of Corporate Governance
Yiwei Fang, Iftekhar Hasan, Woon Sau Leung, Qingwei Wang
Journal of International Business Studies,
Nr. 9,
2019
Abstract
This paper investigates how foreign ownership shapes bank information environments. Using a sample of listed banks from 60 countries over 1997–2012, we show that foreign ownership is significantly associated with greater (lower) informativeness (synchronicity) in bank stock prices. We also find that stock returns of foreign-owned banks reflect more information about future earnings. In addition, the positive association between price informativeness and foreign ownership is stronger for foreign-owned banks in countries with stronger governance, stronger banking supervision, and lower monitoring costs. Overall, our evidence suggests that foreign ownership reduces bank opacity by exporting governance, yielding important implications for regulators and governments.
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01.11.2019 • 23/2019
Presseeinladung zur Verleihung des Max-Planck-Humboldt-Forschungspreises und der Max-Planck-Humboldt-Medaille 2019 in Berlin, Akademie der Künste, 5. November 2019 um 17:00 Uhr mit anschließendem Empfang
Zum zweiten Mal wird der neugestaltete Max-Planck-Humboldt-Forschungspreis von der Max-Planck-Gesellschaft und der Alexander von Humboldt-Stiftung in Berlin verliehen. Der diesjährige Träger des Preises ist Ufuk Akcigit von der Universität Chicago mit dem Thema: Warum besteht zwischen Ost- und Westdeutschland weiterhin eine wirtschaftliche Kluft?
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