We conduct a novel empirical analysis of the role of leverage of financial institutions for the transmission of financial shocks to the macroeconomy. For that purpose, we develop an endogenous regime-switching structural vector autoregressive model with time-varying transition probabilities that...

This paper exploits a recent and granular data set for 1,500 German LSIs to conduct a residential mortgage stress testing exercise. To account for model uncertainty when modeling PD dynamics we use a benchmark-constrained Bayesian model averaging approach that combines standard BMA with a...

This paper models the housing sector, mortgages and endogenous default in a DSGE setting with nominal and real rigidities. We use data for the period 1981-2006 to estimate our model using Bayesian techniques. We analyze how an increase in risk in the mortgage market raises the default rate and...

We contribute to the empirical literature on the impact of shocks to bank capital in the euro area by estimating a Bayesian VAR model identified with sign restrictions. The variables included in the VAR are those typically used in monetary policy analysis, extended to include aggregate banking...

We augment a standard monetary DSGE model to include a banking sector and financial markets. We fit the model to Euro Area and US data. We find that agency problems in financial contracts, liquidity constraints facing banks and shocks that alter the perception of market risk and hit financial...

The theoretical literature gives conflicting predictions on how bank competition should affect financial stability, and dozens of researchers have attempted to evaluate the relationship empirically. We collect 598 estimates of the competitionstability nexus reported in 31 studies and analyze the...

This paper introduces a new parametric measure of productivity change using the hyperbolic distance function. More specifically, the paper first estimates a stochastic translog hyperbolic distance function, which satisfies regularity conditions, using the Bayesian approach. Then it derives an...

Time series of financial asset values exhibit well known statistical features such as heavy tails and volatility clustering. Strongly present in some series, nonstationarity is a feature that has been somewhat overlooked. This may however be a highly relevant feature when estimating extreme...

This paper analyses the evolution of systematic risk of banking industries in eight advanced countries using weekly data from 1990 to 2012. The estimation of time-varying betas is done by means of a Bayesian state space model with stochastic volatility, whose results are contrasted with those of...

I use micro data to quantify key features of U.S. firm financing. In particular, I establish that a substantial 35% of firms' investment is funded using financial markets. I then construct a dynamic equilibrium model that matches these features and fit the model to business cycle data using...