Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?
Peter Sarlin, Gregor von Schweinitz
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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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 dif-ferent 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. We show that credit spreads are increasing in equity incentives. This relation becomes stronger as the seniority of inside debt increases. Using a sample of U.S. public firms with traded credit default swap (CDS) contracts, we provide evidence supportive of the model’s predictions.
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Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?
Peter Sarlin, Gregor von Schweinitz
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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Executive Compensation Structure and Credit Spreads
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 how inside debt features affect the relation between credit spreads and compensation components. First, inside debt reduces credit spreads only if it is unsecured. Second, inside debt exerts important indirect effects on the role of equity incentives: When inside debt is large and unsecured, equity incentives increase credit spreads; When inside debt is small or secured, this effect is weakened or reversed. We test our model on a sample of U.S. public firms with traded CDS contracts, finding evidence supportive of our predictions. To alleviate endogeneity concerns, we also show that our results are robust to using an instrumental variable approach.
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Equity and Bond Market Signals as Leading Indicators of Bank Fragility
Reint E. Gropp, Jukka M. Vesala, Giuseppe Vulpes
Journal of Money, Credit and Banking,
Nr. 2,
2006
Abstract
We analyse the ability of the distance to default and subordinated bond spreads to signal bank fragility in a sample of EU banks. We find leading properties for both indicators. The distance to default exhibits lead times of 6-18 months. Spreads have signal value close to problems only. We also find that implicit safety nets weaken the predictive power of spreads. Further, the results suggest complementarity between both indicators. We also examine the interaction of the indicators with other information and find that their additional information content may be small but not insignificant. The results suggest that market indicators reduce type II errors relative to predictions based on accounting information only.
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