In this paper, using the MCMC method, we derive the conditional distribution of "mean variance" variable. This random variable appears in the option pricing problem under the stochastic volatility assumption. Two real data sets are considered. -- conditional distribution ; equity returns ; MCMC...

We estimate a DSGE model where rare large shocks can occur, but replace the commonly used Gaussian assumption with a Student's t-distribution. Results from the Smets and Wouters (2007) model estimated on the usual set of macroeconomic time series over the 1964-2011 period indicate that 1) the...

The integrated provision of energy among various energy sectors plays an important role in the process of decarbonisation of large energy systems. An important pillar is thereby the decarbonisation of the heat sector, where nowadays still a large percentage of heat supply originates from...

With the COVID-19 pandemic, the intense debate about secular stagnation will become even more important. Empirical estimates of equilibrium real interest rates are so far mostly limited to advanced economies, since no statistical procedure suitable for a large set of countries is available. This...

We relax the standard assumption in the dynamic stochastic general equilibrium (DSGE) literature that exogenous processes are governed by AR(1) processes and estimate ARMA (p,q) orders and parameters of exogenous processes. Methodologically, we contribute to the Bayesian DSGE literature by using...

This paper analyzes the forecasting performance of an open economy DSGE model, estimated with Bayesian methods, for the Euro area during 1994Q1-2002Q4. We compare the DSGE model and a few variants of this model to various reduced form forecasting models such as vector autoregressions (VAR) and...

We investigate how a macroeconomic uncertainty shock affects the labor market. We focus on the uncertainty transmission mechanism, for which we employ a set of worker flow indicators in addition to labor stock variables. We incorporate common factors from such indicators into a framework that...

We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...

To simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural changes, we introduce a time-varying parameter mixed-frequency VAR. To keep our approach from becoming too complex, we implement time variation parsimoniously: only the intercepts and a common...