Google trends forecasting of youth employment
[EN] The forecasting field has been using the surge in big data and advanced computational capabilities. This article discusses the methodological issues of Google Trends (GT) data reliability and forecasting validity for youth unemployment forecasts. We demonstrate the problems with static GT forec...
| Autores: | , , |
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/208678 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/208678 |
| Access Level: | acceso abierto |
| Palabra clave: | Forecasting accuracy Time series Rolling window Expanding window Unemployment Google trends Parameter instability |
| Sumario: | [EN] The forecasting field has been using the surge in big data and advanced computational capabilities. This article discusses the methodological issues of Google Trends (GT) data reliability and forecasting validity for youth unemployment forecasts. We demonstrate the problems with static GT forecasting procedures and show a 44% increase in forecasting accuracy by applying time-varying model respecification forecasting. |
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