Forecasting in ation with twitter
We use Twitter content to generate an indicator of the level of attention allocated to inflation in public discussions. The analysis corresponds to Argentina for the period 2012-2019. Estimated forecasting models show that the indicator provides valuable information regarding future levels of inflat...
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| Autores principales: | , |
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| Formato: | Artículo publishedVersion |
| Lenguaje: | Español |
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Instituto Interdisciplinario de Economía Política (IIEP UBA-CONICET)
2023
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| Acceso en línea: | https://ojs.economicas.uba.ar/DT-IIEP/article/view/2620 https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=dociiep&d=2620_oai |
| Aporte de: |
| Sumario: | We use Twitter content to generate an indicator of the level of attention allocated to inflation in public discussions. The analysis corresponds to Argentina for the period 2012-2019. Estimated forecasting models show that the indicator provides valuable information regarding future levels of inflation. Out-of-sample exercises confirm that social media content allows for gains in forecast accuracy. Beyond point forecasts, the index provides valuable information regarding inflation uncertainty, that is, the size of forecast errors confidence intervals. The proposed indicator compares favorably with other indicators such as media content, media tweets, google search intensity and consumer surveys. |
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