Forecasting output growth tail risk using quantile regression framework

• Autor(a) principal: Quattrini, Filippo
• Data de Publicação: 2022
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10362/156104
• topic: Quantile regression; Growth at risk; Macro-financial linkages; Time series; Domínio/Área Científica::Ciências Sociais::Economia e Gestão

This thesis examines which financial indicator is the most accurate to model and predict the tail risk of output growth in the euro area. The CISS is more informative than other indicators that only focus on specific segment of the financial market. To capture the tail distribution information, the thesis implements quantile regression, capturing determined quantile of the output growth distribution. The forecast produced with the quantile regression for the 10th and the 5th quantile outperformed the standard OLS model in terms of forecasting evaluation metrics in predicting the 2008 output growth downfall, concluding that the quantile specification, combined with the CISS as financial indicator, improves the modeling and forecasting accuracy of tail risk output growth in the euro area.