Essays on forward-looking indicators and the yield curve
Carregando...
Arquivos
Data
2017-04-19
Autores
Orientador(res)
Fernandes, Marcelo
Métricas
Título da Revista
ISSN da Revista
Título de Volume
Resumo
This thesis presents three chapters about forward-looking indicators. In the first two chapters, we propose a factor augmented VAR that combines Nelson and Siegel yield curve factors and principal components extracted from a large dataset. We find that the factor augmented VAR models do a very good job in fitting the level, slope and curvature of the yield curve. The out-of-sample forecasting using principal components beats consistently the predictions from autoregressive and extant literature models in the short- and long-term horizons. We apply this methodology for Brazilian and US economy in the first and second chapter, respectively. Despite the differences between these countries, the results are quite similar. Additionally, we show that forecasting improvement comes from the nature of our dataset that gather mainly forward-looking series. In the last chapter, we study the behavior of macroeconomic predictions made by professional forecasters, specifically, 1-year inflation expectation. We conclude that apart of biased and inefficient forecasting, forecasters misestimate the inflation seasonality. This conclusion is not a country specific. We find seasonality in 1-year inflation for Brazil, Chile, Israel, New Zealand, US and Euro Zone.