Inflation expectations are often found to depend on socioeconomic and demographic characteristics of households, such as age, income and education, however, the reasons for this systematic heterogeneity are not yet fully understood. Since accounting for these expectation differentials could help...

This paper surveys existing factor forecast applications for real economic activity and inflation by means of a meta-analysis and contributes to the current debate on the determinants of the forecast performance of large-scale dynamic factor models relative to other models. We find that, on...

This paper discusses a factor model for estimating monthly GDP using a large number of monthly and quarterly time series in real-time. To take into account the different periodicities of the data and missing observations at the end of the sample, the factors are estimated by applying an EM...

In this paper, we put DSGE forecasts in competition with factor forecasts. We focus on these two models since they represent nicely the two opposing forecasting philosophies. The DSGE model on the one hand has a strong theoretical economic background; the factor model on the other hand is mainly...

This paper discusses methods to quantify risk and uncertainty in macroeconomic forecasts. Both, parametric and non-parametric procedures are developed. The former are based on a class of asymmetrically weighted normal distributions whereas the latter employ asymmetric bootstrap simulations. Both...

This paper compares different ways to estimate the current state of the economy using factor models that can handle unbalanced datasets. Due to the different release lags of business cycle indicators, data unbalancedness often emerges at the end of multivariate samples, which is sometimes...

This paper is the first attempt to investigate the performance of different learning rules in fitting survey data of household and expert inflation expectations in five core European economies (France, Germany, Italy, Netherlands and Spain). Overall it is found that constant gain learning...

This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model speci…cation in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on exponential lag polynomials for the coe¢ cients,...

This paper addresses the relative importance of monetary indicators for forecasting inflation in the euro area in a Bayesian framework. Bayesian Model Averaging (BMA)based on predictive likelihoods provides a framework that allows for the estimation of inclusion probabilities of a particular...

The paper develops an oil price forecasting technique which is based on the present value model of rational commodity pricing. The approach suggests shifting the forecasting problem to the marginal convenience yield which can be derived from the cost-of-carry relationship. In a recursive...