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http://hdl.handle.net/10362/156222| Title: | Leveraging google search queries to help predict house prices in Portugal |
| Author: | Sistovaris, Nicholas |
| Advisor: | Rodrigues, Paulo M.M. |
| Keywords: | Econometrics Housing Google trends Forecasting Error-correction model |
| Defense Date: | 13-Jan-2023 |
| Abstract: | This 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. |
| URI: | http://hdl.handle.net/10362/156222 |
| Designation: | A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics |
| Appears in Collections: | NSBE: Nova SBE - MA Dissertations |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 31149_Nicholas_Sistovaris_LEVERAGING_GOOGLE_SEARCH_QUERIES_TO_HELP_PREDICT_HOUSE_PRICES_IN_PORTUGAL_261147_1589310182.pdf | 1,7 MB | Adobe PDF | View/Open |
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