The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting...

The uncertainty of U.S. core inflation, measured by the stochastic volatility of forecast errors, has soared to a level not seen in nearly five decades since the COVID-19 pandemic hit the global economy. Prices, consumption, and production increase after a positive shock to core inflation...

Most analyses of the U.S. Great Moderation have been based on VAR methods, and have consistently pointed toward good luck as the main explanation for the greater macroeconomic stability of recent years. Using data generated by a New-Keynesian model in which the only source of change is the move...

We present the estimated large-scale three-region DSGE model GEAR picturing Germany, the Euro Area and the Rest of the world. Compared to existing models of this type, GEAR incorporates a comprehensive fiscal block, involuntary unemployment and a complex international structure. We use the model...

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...

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'...

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,...

This paper contributes to the literature on early warning indicators by applying a Bayesian model averaging approach. Our analysis, based on Austrian data, is carried out in two steps: First, we construct a quarterly financial stress index (AFSI) quantifying the level of stress in the Austrian...

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...