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 study loans from banking and non-banking lenders to different groups of borrowers in order to unveil significant differences on how those respond to a shock and evaluate possible alternative explanations for such differences. The objective is to gain insights useful to explain the loan...

We contribute to the empirical literature on the impact of non-performing loan (NPL) ratios on aggregate banking sector variables and the macroeconomy by estimating a panel Bayesian VAR model for twelve euro area countries. The model is estimated assuming a hierarchical prior that allows for...

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...

Longitudinal network data are increasingly available, allowing researchers to model how networks evolve over time and to make inference on their dependence structure. In this paper, a dynamic latent space approach is used to model directed networks of monthly interbank exposures. In this model,...

The amount of credit in the economy is a heterogeneous aggregate that can be analyzed across different dimensions. Considering such dimensions provides insights into the effect of monetary policy interventions because the credit components are observed to respond differently. Several possible...

I examine the relevance of contagion in explaining financial distress in the US banking system by identifying the component of bank level probabilities that is due to contagion. Identification is achieved after controlling for macrofinancial and bank specific shocks that have similar...

In this paper we study the impact of model uncertainty, which occurs when linking a stress scenario to default probabilities, on reduced-form credit risk stress testing. This type of uncertainty is omnipresent in most macroeconomic stress testing applications due to short time series for banks'...

This paper considers a linear panel data model with time varying heterogeneity. Bayesian inference techniques organized around Markov chain Monte Carlo (MCMC) are applied to implement new estimators that combine smoothness priors on unobserved heterogeneity and priors on the factor structure of...