Nowcasting GDP in Greece: The impact of data revisions and forecast origin on model selection and performance

In this paper we consider ways to forecast and nowcast the evolution of the growth rate of the Greek Real Gross Domestic Product (GDP). We explore information in more timely indicators that are available at a higher frequency to improve the forecast of quarterly output growth and, more importantly, examine the effect of data revisions in model selection. In our analysis we focus on three kinds of models, benchmarks, bridge models and factor analysis models trying to understand the effect that the crisis had on both data, informational content of explanatory variables and predictive ability of various models. Our results suggest that not only do we observed large changes in the informational content due to data revisions but the models with highest predictive ability are varying based on both the predictive variables being used and the point in time of the forecast origin. It is therefore important to consider an array of models when nowcasting, especially under periods of higher volatility and data revisions, as in the case of Greece.