Flight from Safety: How a Change to the Deposit Insurance Limit Affects Households‘ Portfolio Allocation
H. Evren Damar, Reint E. Gropp, Adi Mordel
IWH Discussion Papers,
No. 19,
2019
Abstract
We study how an increase to the deposit insurance limit affects households‘ portfolio allocation by exogenously reducing uninsured deposit balances. Using unique data that identifies insured versus uninsured deposits, along with detailed information on Canadian households‘ portfolio holdings, we show that households respond by drawing down deposits and shifting towards mutual funds and stocks. These outflows amount to 2.8% of outstanding bank deposits. The empirical evidence, consistent with a standard portfolio choice model that is modified to accommodate uninsured deposits, indicates that more generous deposit insurance coverage results in nontrivial adjustments to household portfolios.
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An Evaluation of Early Warning Models for Systemic Banking Crises: Does Machine Learning Improve Predictions?
Johannes Beutel, Sophia List, Gregor von Schweinitz
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 measure, 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 effciently, 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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Housing Consumption and Macroprudential Policies in Europe: An Ex Ante Evaluation
Antonios Mavropoulos, Qizhou Xiong
IWH Discussion Papers,
No. 17,
2018
Abstract
In this paper, we use the panel of the first two waves of the Household Finance and Consumption Survey by the European Central Bank to study housing demand of European households and evaluate potential housing market regulations in the post-crisis era. We provide a comprehensive account of the housing decisions of European households between 2010 and 2014, and structurally estimate the housing preference of a simple life-cycle housing choice model. We then evaluate the effect of a tighter LTV/LTI regulation via counter-factual simulations. We find that those regulations limit homeownership and wealth accumulation, reduces housing consumption but may be welfare improving for the young households.
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State Enforceability of Noncompete Agreements: Regulations that Stifle Productivity!
S. Anand, Iftekhar Hasan, P. Sharma, Haizhi Wang
Human Resource Management,
No. 1,
2018
Abstract
Noncompete agreements (also known as covenants not to compete [CNCs]) are frequently used by many businesses in an attempt to maintain their competitive advantage by safeguarding their human capital and the associated business secrets. Although the choice of whether to include CNCs in employment contracts is made by firms, the real extent of their restrictiveness is determined by the state laws. In this article, we explore the effect of state‐level CNC enforceability on firm productivity. We assert that an increase in state level CNC enforceability is detrimental to firm productivity, and this relationship becomes stronger as comparable job opportunities become more concentrated in a firm's home state. On the other hand, this negative relationship is weakened as employee compensation tends to become more long‐term oriented. Results based on hierarchical linear modeling analysis of 21,134 firm‐year observations for 3,027 unique firms supported all three hypotheses.
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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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Tail-risk Protection Trading Strategies
Natalie Packham, Jochen Papenbrock, Peter Schwendner, Fabian Wöbbeking
Quantitative Finance,
No. 5,
2017
Abstract
Starting from well-known empirical stylized facts of financial time series, we develop dynamic portfolio protection trading strategies based on econometric methods. As a criterion for riskiness, we consider the evolution of the value-at-risk spread from a GARCH model with normal innovations relative to a GARCH model with generalized innovations. These generalized innovations may for example follow a Student t, a generalized hyperbolic, an alpha-stable or a Generalized Pareto distribution (GPD). Our results indicate that the GPD distribution provides the strongest signals for avoiding tail risks. This is not surprising as the GPD distribution arises as a limit of tail behaviour in extreme value theory and therefore is especially suited to deal with tail risks. Out-of-sample backtests on 11 years of DAX futures data, indicate that the dynamic tail-risk protection strategy effectively reduces the tail risk while outperforming traditional portfolio protection strategies. The results are further validated by calculating the statistical significance of the results obtained using bootstrap methods. A number of robustness tests including application to other assets further underline the effectiveness of the strategy. Finally, by empirically testing for second-order stochastic dominance, we find that risk averse investors would be willing to pay a positive premium to move from a static buy-and-hold investment in the DAX future to the tail-risk protection strategy.
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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 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,
No. 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 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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