Direct and Indirect Risk-taking Incentives of Inside Debt
Stefano Colonnello, Giuliano Curatola, Ngoc Giang Hoang
Journal of Corporate Finance,
August
2017
Abstract
We develop a model of compensation structure and asset risk choice, where a risk-averse manager is compensated with salary, equity and inside debt. We seek to understand the joint implications of this compensation package for managerial risk-taking incentives and credit spreads. We show that the size and seniority of inside debt not only are crucial for the relation between inside debt and credit spreads but also play an important role in shaping the relation between equity compensation and credit spreads. Using a sample of U.S. public firms with traded credit default swap contracts, we provide evidence supportive of the model's predictions.
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FDI-Mikrodatenbank
IWH-FDI-Mikrodatenbank Die IWH-FDI-Mikrodatenbank (FDI = Foreign Direct Investment)...
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Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?
Peter Sarlin, Gregor von Schweinitz
ECB Working Paper Series,
Nr. 2025,
2017
Abstract
Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The expost threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-of-sample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. Given probabilistic model output, it is intuitive that a decision rule is independent of the data or model specification, as thresholds on probabilities represent a willingness to issue a false alarm vis-à-vis missing a crisis. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.
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Qual VAR Revisited: Good Forecast, Bad Story
Makram El-Shagi, Gregor von Schweinitz
Journal of Applied Economics,
Nr. 2,
2016
Abstract
Due to the recent financial crisis, the interest in econometric models that allow to incorporate binary variables (such as the occurrence of a crisis) experienced a huge surge. This paper evaluates the performance of the Qual VAR, originally proposed by Dueker (2005). The Qual VAR is a VAR model including a latent variable that governs the behavior of an observable binary variable. While we find that the Qual VAR performs reasonable well in forecasting (outperforming a probit benchmark), there are substantial identification problems even in a simple VAR specification. Typically, identification in economic applications is far more difficult than in our simple benchmark. Therefore, when the economic interpretation of the dynamic behavior of the latent variable and the chain of causality matter, use of the Qual VAR is inadvisable.
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Direct and Indirect Risk-taking Incentives of Inside Debt
Stefano Colonnello, Giuliano Curatola, Ngoc Giang Hoang
Abstract
We develop a model of managerial compensation structure and asset risk choice. The model provides predictions about the relation between credit spreads and different compensation components. First, we show that credit spreads are decreasing in inside debt only if it is unsecured. Second, the relation between credit spreads and equity incentives varies depending on the features of inside debt.
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Arbeitspapiere
Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After? ...
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Nested Models and Model Uncertainty
Alexander Kriwoluzky, Christian A. Stoltenberg
Scandinavian Journal of Economics,
Nr. 2,
2016
Abstract
Uncertainty about the appropriate choice among nested models is a concern for optimal policy when policy prescriptions from those models differ. The standard procedure is to specify a prior over the parameter space, ignoring the special status of submodels (e.g., those resulting from zero restrictions). Following Sims (2008, Journal of Economic Dynamics and Control 32, 2460–2475), we treat nested submodels as probability models, and we formalize a procedure that ensures that submodels are not discarded too easily and do matter for optimal policy. For the United States, we find that optimal policy based on our procedure leads to substantial welfare gains compared to the standard procedure.
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Taking the First Step - What Determines German Laser Source Manufacturers' Entry into Innovation Networks?
Jutta Günther, Muhamed Kudic, Andreas Pyka
International Journal of Innovation Management,
Nr. 5,
2015
Abstract
Early access to technological knowledge embodied in the industry’s innovation network can provide an important competitive advantage to firms. While the literature provides much evidence on the positive effects of innovation networks on firms’ performance, not much is known about the determinants of firms’ initial entry into such networks. We analyze firms’ timing and propensity to enter the industry’s innovation network. More precisely, we seek to shed some light on the factors affecting the duration between firm founding and its first cooperation event. In doing so, we apply a unique longitudinal event history dataset based on the full population of German laser source manufacturers. Innovation network data stem from official databases providing detailed information on the organizations involved, subject of joint research and development (R&D) efforts as well as start and end times for all publically funded R&D projects between 1990 and 2010. Estimation results from a non-parametric event history model indicate that micro firms enter the network later than small-sized or large firms. An in-depth analysis of the size effects for medium-sized firms provides some unexpected findings. The choice of cooperation type makes no significant difference for the firms’ timing to enter the network. Finally, the analysis of geographical determinants shows that cluster membership can, but do not necessarily, affect a firm’s timing to cooperate.
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Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?
P. Sarlin, Gregor von Schweinitz
IWH Discussion Papers,
Nr. 6,
2015
Abstract
Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The ex-post threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-of-sample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.
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