Before revision: We analyse whether, and when, a large set of Google search data can be useful to increase euro area GDP nowcasting accuracy once we control for information contained in official variables. To deal with these data we propose an estimator that combines variable pre-selection and Ridge regularization and study its theoretical properties.
After revision: Alternative data sets are nowadays widely used for macroeconomic nowcasting together with new Machine Learning-based tools which often are applied without having a complete picture of their theoretical nowcasting properties. Against this background, this paper proposes a theoretically-funded nowcasting methodology allowing to incorporate alternative Google Search Data (GSD) among the predictors and combining targeted preselection, Ridge regularization and study its theoretical properties.