Rodrigues, Paulo Manuel MarquesSistovaris, Nicholas2023-08-032023-08-032023-01-132022-12-16http://hdl.handle.net/10362/156222This work project contributes to the current literature on using Google search queries to predict economic activity. We demonstrate, using the two-step Error-Correction Model (ECM) by Engle and Granger (1987), that specific search queries, also known as Google Trends, are related to house prices in Portugal. For out-of-sample forecasts, our ECM model with the Google Trends variables performed significantly better predicting one year ahead, in which, the Mean Absolute Error was reduced by over 30% compared to our baseline model. Until now, conventional economics has not leveraged this highly accessible digital data in their models, we hope this will change.engEconometricsHousingGoogle trendsForecastingError-correction modelmaster thesis203312643