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...

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...

This paper examines the issue of the impact of aggregation in the empirical analysis of euro area labour markets. A Phillips Curve describing the adjustment of unit labour costs is estimated at the national and aggregate level for the 5 largest euro area countries. Potential sources of...

We propose a new method for multivariate forecasting which combines Dynamic Factor and multivariate GARCH models. The information contained in large datasets is captured by few dynamic common factors, which we assume being conditionally heteroskedastic. After presenting the model, we propose a...

We propose a new method for medium-term forecasting using exogenous information. We first show how a shifting-mean autoregressive model can be used to describe characteristic features in inflation series. This implies that we decompose the inflation process into a slowly moving nonstationary...

To forecast an aggregate, we propose adding disaggregate variables, instead of combining forecasts of those disaggregates or forecasting by a univariate aggregate model. New analytical results show the effects of changing coefficients, mis-specification, estimation uncertainty and...

A small labour market model for the six largest euro area countries (Germany, France, Italy, Spain, the Netherlands, Belgium) is estimated in a state -space framework. The model entails, in the long run, four driving forces: a trend labour force component, a trend labour productivity component,...

The rank of the spectral density matrix conveys relevant information in a variety of statistical modelling scenarios. This note shows how to estimate the rank of the spectral density matrix at any given frequency. The method presented is valid for any hermitian positive definite matrix estimate...

We propose a method for estimating a subset of the parameters of a structural rational expectations model by exploiting changes in policy. We define a class of models, midway between a vector autoregression and a structural model, that we call the recoverable structure. As an application of our...