This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying...

This paper presents a framework for empirical analysis of dynamic macroeconomic models using Bayesian filtering, with a specific focus on the state-space formulation of New Keynesian Dynamic Stochastic General Equilibrium (NK DSGE) models with multiple regimes. We outline the theoretical...

To date, only annual information on economic activity is published for the 16 German states. In this paper, we calculate quarterly regional GDP estimates for the period between 1995 to 2021, thereby improving the regional database for Germany. The new data set will regularly be updated when...

In this paper we augment the Bayesian unobserved components model of the EU Commission to estimate the cyclical component of total factor productivity (TFP gap) with a factor structure to include a wide array of business cycle indicators. We demonstrate that this model extension considerably...

Recent articles suggest that a Bayesian vector autoregression (BVAR) with shrinkage is a good forecast device even when the number of variables is large. In this paper we evaluate different variants of the BVAR with respect to their forecast accuracy for euro area real GDP growth and HICP...

We develop a non-linear forecast combination rule based on copulas that incorporate the dynamic interaction between individual predictors. This approach is optimal in the sense that the resulting combined forecast produces the highest discriminatory power as measured by the receiver operating...

What are the effects of beliefs, sentiment, and uncertainty, over the business cycle? To answer this question, we develop a behavioral New Keynesian macroeconomic model, in which we relax the assumption of rational expectations. Agents are, instead, boundedly rational: they have a...

We propose two novel methods to "bring ABMs to the data". First, we put forward a new Bayesian procedure to estimate the numerical values of ABM parameters that takes into account the time structure of simulated and observed time series. Second, we propose a method to forecast aggregate time...

Parsimony is a desirable feature of economic models but almost all human behaviors are characterized by vast individual variation that appears to defy parsimony. How much parsimony do we need to give up to capture the fundamental aspects of a population's distributional preferences and to...