We develop a Bayesian Structural VAR (SVAR) model to study the relationship between different kinds of energy shocks and inflation dynamics in Europe. Specifically, we include in our specification two separate energy markets (oil and natural gas) and two target macroeconomic variables, measuring...

We develop a Bayesian Structural VAR (SVAR) model to study the relationship between different kinds of energy shocks and inflation dynamics in Europe. Specifically, we include in our specification two separate energy markets (oil and natural gas) and two target macroeconomic variables, measuring...

This paper analyses energy efficiency in the EU, both in terms of reductions in energy intensity and in terms of physical indicators, looking at the differences among sectors and among Member States. We test econometrically the existence of convergence in energy intensity across Europe. We find...

The empirical literature is very far from any consensus about the appropriate model for oil price forecasting that should be implemented. Relative to the previous literature, this paper is novel in several respects. First of all, we test and systematically evaluate the ability of several...

Although there is much interest in the future retail price of gasoline among consumers, industry analysts, and policymakers, it is widely believed that changes in the price of gasoline are essentially unforecastable given publicly available information. We explore a range of new forecasting...

This article examines how the shale oil revolution has shaped the evolution of U.S. crude oil and gasoline prices. It puts the evolution of shale oil production into historical perspective, highlights uncertainties about future shale oil production, and cautions against the view that the U.S....

Recently, there has been increased interest in real-time forecasts of the real price of crude oil. Standard oil price forecasts based on reduced-form regressions or based on oil futures prices do not allow consumers of forecasts to explore how much the forecast would change relative to the...

We address some of the key questions that arise in forecasting the price of crude oil. What do applied forecasters need to know about the choice of sample period and about the tradeoffs between alternative oil price series and model specifications? Are real or nominal oil prices predictable...

We construct a monthly real-time data set consisting of vintages for 1991.1-2010.12 that is suitable for generating forecasts of the real price of oil from a variety of models. We document that revisions of the data typically represent news, and we introduce backcasting and nowcasting techniques...

The U.S. Energy Information Administration regularly publishes short-term forecasts of the price of crude oil. Traditionally, such out-of-sample forecasts have been largely judgmental, making them difficult to replicate and justify, and not particularly successful when compared with naïve...