This study evaluates oil price forecasts based on their economic significance for macroeconomic predictions. More specifically, we first use the current state-of-the-art frameworks to forecast monthly oil prices and subsequently we use these forecasts, as oil price assumptions, to predict...

This paper applies Markov-switching multifractal (MSM) processes to model and forecast carbon dioxide (CO2) emission price volatility, and compares their forecasting performance to the standard GARCH, fractionally integrated GARCH (FIGARCH) and the two-state Markov-switching GARCH (MS-GARCH)...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

This study evaluates potential migration flows to the European Union from its eastern neighbors and Croatia. We perform out-of-sample forecasts using an adaption of the model of Hatton (1995) to time series cross-sectional data about post-enlargement migration flows following the EU's 2004...

Most macroeconomic data is continuously revised as additional information becomes available. We suggest that revisions of data is an important source of uncertainty about the state of the economy. This paper evaluates the quality of major real macroeconomic Euro area variables, published by...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

Inflation is a monetary phenomenon. While this statement is widely accepted in terms of a long-run relationship, the quantity theory has been made operational also for the short-run dynamics of inflation by so-called Pstar models. An error correction model with quarterly data for the Euro Area...

This paper reinterprets Maganelli's (2009) idea of "Forecasting with Judgment" to obtain a dynamic algorithm for combining survey data and time series models for macroeconomic forecasting. Unlike existing combination approaches which typically assign weights to alternative forecasts, the...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

Recent general equilibrium models prescribe predictable dynamics in the volatility surfaces that are implied by observed option prices. In this paper we investigate the predictability of surfaces, using extensive time series of implied volatilities from over-the-counter options on eight...