Forecasting EMU macroeconomic variables

After the creation of the European Monetary Union (EMU), both the European Commission (EC) and the European Central Bank (ECB) are focusing more and more on the evolution of the EMU as a whole, rather than on single member countries. A particularly relevant issue from a policy point of view is the availability of reliable forecasts for the key macroeconomic variables. Hence, both the fiscal and the monetary authorities have developed aggregate forecasting models, along the lines previously adopted for the analysis of single countries. A similar approach will be likely followed in empirical analyses on, e.g., the existence of an aggregate Taylor rule or the evaluation of the aggregate impact of monetary policy shocks, where linear specifications are usually adopted. Yet, it is uncertain whether standard linear models provide the proper statistical framework to address these issues. The process of aggregation across countries can produce smoother series, better suited for the analysis with linear models, by averaging out country specific shocks. But the method of construction of the aggregate series, which often involves time-varying weights, and the presence of common shocks across the countries, such as the deflation in the early 1980s and the convergence process in the early 1990s, can introduce substantial non-linearity into the generating process of the aggregate series. To evaluate whether this is the case, we fit a variety of non-linear and time-varying models to aggregate EMU macroeconomic variables, and compare them with linear specifications. Since non-linear models often over-fit in sample, we assess their performance in a real time forecasting framework. It turns out that for several variables linear models are beaten by non-linear specifications, a result that questions the use of standard linear methods for forecasting and modeling EMU variables.