Is Spain (still) different? This paper addresses this question from a macroeconomic perspective. After reporting differences in rates of output growth and inflation between Spain and the rest of the European Monetary Union (EMU) countries during last decade, the paper suggests three complementary explanations for those differences: • Different types of shock processes have hit the Spanish economy and the rest of the EMU. • Different structures leading to different price and wage nominal rigidities and different price and wage indexation mechanisms. • The common monetary policy may have exacerbated, rather than offsetting, the effects of shocks if they are different in Spain and in the rest of the EMU; and/or if their effects are transmitted differently due to different economic structures.

The paper provides a comprehensive description of the Spanish economy. The model (MEDEA) is built on recent developments of medium scale DSGE models, and it has been enriched by adding domestic and foreign sectors, several frictions on the real and nominal side of the economy. Moreover, MEDEA features important departures from the paradigm of DSGE models to closely mimic the evolution of the Spanish economy in the past 30 years. The main novelty with respect to the existing literature is the introduction of three sources of growth: neutral technological progress, investment-specific technological progress, and population growth. Immigration flows heavily influenced the Spanish economy in the recent past, and the attempt to model it is clearly an interesting idea. On top of that, the authors try to define a monetary policy rule that replicates closely the Spanish role in Europe Area and in the World economy, and they attempt to provide a better characterization of fiscal policy instruments. Finally, despite of its complexity the model description is very clear and the notation is easy to follow. MEDEA is estimated via Bayesian methods. The authors’ enterprise to estimate the model is fully aware of potential problems that likelihood based estimation of DSGE might carry, namely weak parameters identification and potential parameters instability. First, to reduce identification problems just a subset of structural parameters is estimated (47 parameters out of 59), and flat prior are used to let the data reveals fully the information about structural parameters. The model is treated analytically in such a way that it is feasible to implement II order approximation of the model solution; eventually, likelihood based estimation on II order approximation might be performed