In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus on the estimation of their predictive distributions, with special attention being paid to the mean and the covariance matrix of h-step ahead forecasts. In the empirical...

Capital-labor substitution and total factor productivity (TFP) estimates are essential features of growth and income distribution models. In the context of a Monte Carlo exercise embodying balanced and near balanced growth, we demonstrate that the estimation of the substitution elasticity can be...

We forecast recession probabilities for the United States, Germany and Japan. The predictions are based on the widely-used probit approach, but the dynamics of regressors are endogenized using a VAR. The combined model is called a ‘ProbVAR’. At any point in time, the ProbVAR allows to...

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus on the estimation of their predictive distributions, with special attention being paid to the mean and the covariance matrix of h-step ahead forecasts. In the empirical...

We forecast recession probabilities for the United States, Germany and Japan. The predictions are based on the widely-used probit approach, but the dynamics of regressors are endogenized using a VAR. The combined model is called a 'ProbVAR'. At any point in time, the ProbVAR allows to generate...

We quantify the effects of wage bargaining shocks on macroeconomic aggregates using a structural vector auto-regression model for Germany. We identify exogenous variation in bargaining power from episodes of minimum wage introduction and industrial disputes. This narrative information...

We study state dependence in the impact of monetary policy shocks over the leverage cycle for a panel of 10 euro area countries. We use a Bayesian Threshold Panel SVAR with regime classifications based on credit and house prices cycles. We find that monetary policy shocks trigger a smaller...

This paper illustrates how to handle a sequence of extreme observations-such as those recorded during the COVID-19 pandemic-when estimating a Vector Autoregression, which is the most popular time-series model in macroeconomics. Our results show that the ad-hoc strategy of dropping these...

We study the macroeconomic consequences of financial shocks and increase in economic risk using a quantile vector autoregression. Financial shocks have a negative, but asymmetric impact on the real economy: they substantially increase growth at risk, but have limited impact on upside potential....

The role that the price of oil plays in economic analysis in central banks as well as in financial markets has evolved over time. Oil is not seen anymore just as a input to production but also as a barometer of global economic activity as well as a financial asset. A high frequency structural...