Google Trends Topic-Based Uncertainty: A Multi-National Approach
[EN] Several studies have shown that uncertainty among economic actorsinfluences business cycle dynamics. This paper uses Google Trends topic queries to construct an uncertainty proxy that can be applied to every country where Google is active. Using a VAR approach, this paper demonstrates that the...
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2020 |
| 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:10251/148765 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/148765 |
| Access Level: | acceso abierto |
| Palabra clave: | Web data Internet data Big data Qca Pls Sem Conference Google Trends Uncertainty Business Cycle Dynamics VAR |
| Sumario: | [EN] Several studies have shown that uncertainty among economic actorsinfluences business cycle dynamics. This paper uses Google Trends topic queries to construct an uncertainty proxy that can be applied to every country where Google is active. Using a VAR approach, this paper demonstrates that the obtained impulse-response functions of main economic indicators to a onestandard deviation shock to the constructed indicator, are similar to those from an already-existing uncertainty proxy, the EPU. This is true for the G7 countries and Russia. On average, the uncertainty indicator constructed for this paper leads to more statistically significant responses than does the EPU. Thus, this paper shows that Google Trends is a helpful tool for obtaining timely information about uncertainty among economic actors. The main improvement in this uncertainty proxy is in its language independence. Existing uncertaintymeasurement approaches, in contrast, rely on certain keywords that often vary across countries. |
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