Bayes' statistical rule remains the status quo for modeling belief updating in both normative and descriptive models of behavior under uncertainty. Recent research has questioned the use of Bayes' rule in descriptive models of behavior, presenting evidence that people overweight 'good news'...

This paper considers factor estimation from heterogenous data, where some of the variables are noisy and only weakly informative for the factors. To identify the irrelevant variables, we search for zero rows in the loadings matrix of the factor model. To sharply separate these irrelevant...

In this work, we consider modeling the past volatilities through an asymmetric generalised autoregressive conditional heteroskedasticity (Garch) model with heavy tailed sampling distributions. In particular, we consider the Student-t model with unknown degrees of freedom and indicate how it may...

We apply Bayesian Model Averaging and a frequentistic model space analysis to assess the pricing-determinants of credit default swaps (CDS). Our study focuses on the complete model space of plausible models covering most of the variables and specifications used elsewhere in the literature,...

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'...

We study cross-country differences in monetary policy transmission across the large four euro-area countries (France, Germany, Italy and Spain) using a large Bayesian vector autoregressive model with endogenous prior selection. Drawing both on the posterior distributions of the cross-country...

We propose a Bayesian approach to dynamic panel estimation in the presence of cross-sectional dependence and dynamic heterogeneity which is suitable for inference in short panels, unlike alternative estimators. Monte Carlo simulations indicate that our estimator produces less bias, and a lower...

This paper presents a novel Bayesian method for estimating dynamic stochastic general equilibrium (DSGE) models subject to a constrained posterior distribution of the implied Sharpe ratio. We apply our methodology to a DSGE model with habit formation in consumption and leisure, using an estimate...