Publication: Further evidence on forecasting international GNP growth rates using unobserved components transfer function models
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1993
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Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
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Abstract
Forecast of international GNP growth rates are computed using a novel, onobserved components model that allows for estimating the trend and the perturbational components in GNPdata. The model is formulated in state space terms, and estimating using recursive methods of filtering and fixed interval smoothing, The decomposition crucially hinges on the choice of the Noise-Variance Ratio parameter. As any other signal extraction method, the choice of the relevants parameters affects the statistical characteristics of the estimated components. Here, we incororate a priori beliefs on the values of the NVR parameter leading to a decomposition with reasonable business cycle properties. Throughout the paper, forecast comparisons are made with other Bayesian and non-Bayesian alternatives.
En este trabajo se presentan predicciones de las tasas de crecimiento del PIB/PNB de un conjunto de países, utilizando un modelo de componentes no observables que permite la estimación de componentes de tendencia y perturbación de dichas variables. El modelo se formula en espacio de los estados y se estima mediante procedimientos recursivos de filtrado y de suavizado con la muestra completa. La descomposición se basa en la opción del parámetro Noise-Variance Ratio (NVR). Como en cualquier procedimiento de extracción de señales, la elección de los parámetros relevantes afecta a las características estadísticas de los componentes estimados. En este artículo, se incorporan supuestos apriorísticos sobre los valores del NRV que generan una descomposición fácilmente interpretable en términos del ciclo económico. A través del artículo se establecen comparaciones predictivas con otras alternativas Bayerianas y no Bayerianas.
En este trabajo se presentan predicciones de las tasas de crecimiento del PIB/PNB de un conjunto de países, utilizando un modelo de componentes no observables que permite la estimación de componentes de tendencia y perturbación de dichas variables. El modelo se formula en espacio de los estados y se estima mediante procedimientos recursivos de filtrado y de suavizado con la muestra completa. La descomposición se basa en la opción del parámetro Noise-Variance Ratio (NVR). Como en cualquier procedimiento de extracción de señales, la elección de los parámetros relevantes afecta a las características estadísticas de los componentes estimados. En este artículo, se incorporan supuestos apriorísticos sobre los valores del NRV que generan una descomposición fácilmente interpretable en términos del ciclo económico. A través del artículo se establecen comparaciones predictivas con otras alternativas Bayerianas y no Bayerianas.
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