It can be shown that inflation expectations and associated forecast errors are characterized by a high degree of persistence. One reason may be that forecasters cannot directly observe the inflation target pursued by the central bank and, hence, face a complicated forecasting problem. In...

We investigate the international linkages of inflation uncertainty in the G7. In a first step, we document that inflation uncertainty in the G7 is intertwined. Moreover, the degree of synchronization has increased during the recent two decades. Second, based on a Factor-Structural Vector...

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...

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...

Uncertainty about the future course of the economy is a possible driver of aggregate fluctuations. To identify the different dimensions of uncertainty in the macroeconomy we construct a large dataset covering all types of economic uncertainty. We then identify two fundamental factors which...

In the current literature uncertainty about the future course of the economy is identified as a possible driver of business cycle fluctuations. In fact, uncertainty surrounds the movements of all economic variables which gives rise to a monitoring problem. We identify the different dimensions of...

Forecast models with large cross-sections are often subject to overparameterization leading to unstable parameter estimates and hence inaccurate forecasts. Recent articles suggest that a large Bayesian vector autoregression (BVAR) with sufficient prior information dominates competing approaches....

This paper presents a new methodology for the quantification of qualitative survey data. Traditional conversion methods, such as the probability approach of Carlson and Parkin (1975) or the time-varying parameters model of Seitz (1988), require very restrictive assumptions concerning the...