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We examine the impact of so-called "Crisis Contracts" on bank managers' risk-taking incentives and on the probability of banking crises. Under a Crisis Contract, managers are required to contribute a pre-specified share of their past earnings to finance public rescue funds when a crisis occurs. This can be viewed as a retroactive tax that is levied only when a crisis occurs and that leads to a form of collective liability for bank managers. We develop a game-theoretic model of a banking sector whose shareholders have limited liability, so that society at large will suffer losses if a crisis occurs. Without Crisis Contracts, the managers' and shareholders' interests are aligned, and managers take more than the socially optimal level of risk. We investigate how the introduction of Crisis Contracts changes the equilibrium level of risk-taking and the remuneration of bank managers. We establish conditions under which the introduction of Crisis Contracts will reduce the probability of a banking crisis and improve social welfare. We explore how Crisis Contracts and capital requirements can supplement each other and we show that the efficacy of Crisis Contracts is not undermined by attempts to hedge.
Banks can deal with their liquidity risk by holding liquid assets (self-insurance), by participating in interbank markets (coinsurance), or by using flexible financing instruments, such as bank capital (risk-sharing). We use a simple model to show that undiversifiable liquidity risk, i.e. the liquidity risk that banks are unable to coinsure on interbank markets, represents an important risk factor affecting their capital structures. Banks facing higher undiversifiable liquidity risk hold more capital. We posit that empirically banks that are more exposed to undiversifiable liquidity risk are less active on interbank markets. Therefore, we test for the existence of a negative relationship between bank capital and interbank market activity and find support in a large sample of U.S. commercial banks.
I analyze a critical illness insurance in a consumption-investment model over the life cycle. I solve a model with stochastic mortality risk and health shock risk numerically. These shocks are interpreted as critical illness and can negatively affect the expected remaining lifetime, the health expenses, and the income. In order to hedge the health expense effect of a shock, the agent has the possibility to contract a critical illness insurance. My results highlight that the critical illness insurance is strongly desired by the agents. With an insurance profit of 20%, nearly all agents contract the insurance in the working stage of the life cycle and more than 50% of the agents contract the insurance during retirement. With an insurance profit of 200%, still nearly all working agents contract the insurance, whereas there is little demand in the retirement stage.
I numerically solve realistically calibrated life cycle consumption-investment problems in continuous time featuring stochastic mortality risk driven by jumps, unspanned labor income as well as short-sale and liquidity constraints and a simple insurance. I compare models with deterministic and stochastic hazard rate of death to a model without mortality risk. Mortality risk has only minor effects on the optimal controls early in the life cycle but it becomes crucial in later years. A diffusive component in the hazard rate of death has no significant impact, whereas a jump component is desired by the agent and influences optimal controls and wealth evolution. The insurance is used to ensure optimal bequest such that there is no accidental bequest. In the absence of the insurance, the biggest part of bequest is accidental.
We explore the sources of household balance sheet adjustment following the collapse of the housing market in 2006. First, we use microdata from the Federal Reserve Board’s Senior Loan Officer Opinion Survey to document that banks cumulatively tightened consumer lending standards more in counties that experienced a house price boom in the mid-2000s than in non-boom counties. We then use the idea that renters, unlike homeowners, did not experience an adverse wealth shock when the housing market collapsed to examine the relative importance of two explanations for the observed deleveraging and the sluggish pickup in consumption after 2008. First, households may have optimally adjusted to lower wealth by reducing their demand for debt and implicitly, their demand for consumption. Alternatively, banks may have been more reluctant to lend in areas with pronounced real estate declines. Our evidence is consistent with the second explanation. Renters with low risk scores, compared to homeowners in the same markets, reduced their levels of nonmortgage debt and credit card debt more in counties where house prices fell more. The contrast suggests that the observed reductions in aggregate borrowing were more driven by cutbacks in the provision of credit than by a demand-based response to lower housing wealth.
This paper solves a dynamic model of households' mortgage decisions incorporating labor income, house price, inflation, and interest rate risk. It uses a zero-profit condition for mortgage lenders to solve for equilibrium mortgage rates given borrower characteristics and optimal decisions. The model quantifies the effects of adjustable vs. fixed mortgage rates, loan-to-value ratios, and mortgage affordability measures on mortgage premia and default. Heterogeneity in borrowers' labor income risk is important for explaining the higher default rates on adjustable-rate mortgages during the recent US housing downturn, and the variation in mortgage premia with the level of interest rates.
SAFE Newsletter : 2014, Q1
(2014)
In this paper, we study the effect of proportional transaction costs on consumption-portfolio decisions and asset prices in a dynamic general equilibrium economy with a financial market that has a single-period bond and two risky stocks, one of which incurs the transaction cost. Our model has multiple investors with stochastic labor income, heterogeneous beliefs, and heterogeneous Epstein-Zin-Weil utility functions. The transaction cost gives rise to endogenous variations in liquidity. We show how equilibrium in this incomplete-markets economy can be characterized and solved for in a recursive fashion. We have three main findings. One, costs for trading a stock lead to a substantial reduction in the trading volume of that stock, but have only a small effect on the trading volume of the other stock and the bond. Two, even in the presence of stochastic labor income and heterogeneous beliefs, transaction costs have only a small effect on the consumption decisions of investors, and hence, on equity risk premia and the liquidity premium. Three, the effects of transaction costs on quantities such as the liquidity premium are overestimated in partial equilibrium relative to general equilibrium.
Inflation differentials in the euro area have been persistent since the adoption of the single currency. This paper analyzes the impact of product and labor market regulation on inflation in a sample of 11 countries. The results show that, after the adoption of the euro, product market deregulation has a relevant and significant effect on the level of inflation, while higher labor market regulation increases the responsiveness of inflation to the output gap.
We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the parameter vector, the procedure yields computationally tractable, consistent and asymptotic efficient estimates of all parameters. We show the asymptotic normality and derive the estimator's asymptotic covariance in dependence of the number of iteration steps. To mitigate the curse of dimensionality in high-parameterized models, we combine the procedure with a penalization approach yielding sparsity and reducing model complexity. Small sample properties of the estimator are illustrated for two time series models in a simulation study. In an empirical application, we use the proposed method to estimate the connectedness between companies by extending the approach by Diebold and Yilmaz (2014) to a high-dimensional non-Gaussian setting.
In this paper, we propose a novel approach on how to estimate systemic risk and identify its key determinants. For all US financial companies with publicly traded equity options, we extract their option-implied value-at-risks (VaRs) and measure the spillover effects between individual company VaRs and the option-implied VaR of an US financial index. First, we study the spillover effect of increasing company risks on the financial sector. Second, we analyze which companies are most affected if the tail risk of the financial sector increases. We find that key accounting and market valuation metrics such as size, leverage, balance sheet composition, market-to-book ratio and earnings have a significant influence on the systemic risk profile of a financial institution. In contrast to earlier studies, the employed panel vector autoregression (PVAR) estimator allows for a causal interpretation of the results.