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https://hdl.handle.net/1822/7059| Título: | Forecasting in data-rich environments |
| Autor(es): | Conraria, Luís Aguiar Hong, Yongmiao |
| Palavras-chave: | Combination of forecasts Factor analysis Forecasting Inflation Partial least squares Principal components |
| Data: | 2004 |
| Citação: | MIDWEST MACROECONOMICS MEETING, Ames, Estados Unidos da América , 2004 – “Midwest Macroeconomics Meeting : proceedings”. [S.l. : s.n., 2004]. |
| Resumo(s): | Stock and Watson (1998 and 1999) developed a factor-model approach which allows for big data sets to be systematically reduced to a few explanatory factors. In this paper two other methods are proposed. The first one, Partial Least Squares is imported from the Chemometrics literature. The second one, which is based on the Combination of Forecasts literature is a modification of Stock and Watson’s method. We will call this method Principal Components Combination. These methods are compared in an empirical application to inflation. We conclude that the method with the best overall performance is the Principal Components Combination. |
| Tipo: | Artigo em ata de conferência |
| URI: | https://hdl.handle.net/1822/7059 |
| Arbitragem científica: | yes |
| Acesso: | Acesso aberto |
| Aparece nas coleções: | NIPE - Comunicações a Conferências |
Ficheiros deste registo:
| Ficheiro | Descrição | Tamanho | Formato | |
|---|---|---|---|---|
| Conraria_Hong_2004_MMM.pdf | Documento principal | 331,66 kB | Adobe PDF | Ver/Abrir |
