This paper estimates a time-varying AR-GARCH model of inflation producing measures of inflation uncertainty for the euro area, and investigates their linkages in a VAR framework, also allowing for the possible impact of the policy regime change associated with the start of EMU in 1999. The main...

Markow switching models with time-varying means, variances and mixing weights are applied to characterise business cycle variation in the probability distribution and higher order moments of stock returns. This allows us to provide a comprehensive characterization of risk that goes well beyond...

It is widely known that significant in-sample evidence of predictability does not garantuee significant out-of-sample predictability. This is often interpreted as an indiciation that in-sample evidence is likely to be spurious and should be discounted. In this paper we question this conventional...

Conditional heteroskedasticity is an important feature of many macroeconomic and financial time series. Standard residual-based bootstrap procedures for dynamic regression models treat the regression eroor as i.i.d. These procedures are invalid in the presence of conditional heteroskedasticity....

It is standard in applied work to select forecasting models by ranking candidate models by their prediction mean square error (PMSE) in simulated ou-of-sample (SOOS) forecasts. Alternatively, forecast models may be selected using information criteria (IC). We compare the asymptotic and...

The paper presents an incomplete competition model (ICM), where inflation is determined jointly with unit labour cost growth. The ICM is estimated on data for the Euro area and evaluated against existing models, i.e. the implicit inflation equation of the Area Wide model (AWM) - cf. Fagan, Henry...

This paper derives forecasts for euro area real GDP growth based on a bottom up approach from the production side. That is, GDP is forecast via the forecasts of value added across the different branches of activity, which is quite new in the literature. Linear regression models in the form of...