The importance of common cyclical features in VAR analysisa Monte-Carlo study

Resumo

Despite the commonly held belief that aggregate data display short-run comovement, there has been little discussion about the econometric consequences of this feature of the data. We use exhaustive Monte-Carlo simulations to investigate the importance of restrictions implied by common-cyclical features for estimates and forecasts based on vector autoregressive models. First, we show that the ìbestî empirical model developed without common cycle restrictions need not nest the ìbestî model developed with those restrictions. This is due to possible differences in the lag-lengths chosen by model selection criteria for the two alternative models. Second, we show that the costs of ignoring common cyclical features in vector autoregressive modelling can be high, both in terms of forecast accuracy and efficient estimation of variance decomposition coefficients. Third, we find that the Hannan-Quinn criterion performs best among model selection criteria in simultaneously selecting the lag-length and rank of vector autoregressions.

Ficha do documento

Tipo

Estudo

Ano

2001

Instituição

Escola de Pós-Graduação em Economia da FGV

Fonte

Repositório da FGV

Idioma

Inglês

Acesso

Não informado

Identificador

oai:repositorio.fgv.br:10438/554

Temas

Economia

Palavras-chave

Reduced rank modelsModel selection criteriaForecastingVariance decompositionEconomiaCiclos econômicosMonte Carlo, Método de