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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.