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Structural Breaks and interest rates forecast: a sequential approach

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The analysis of the future behaviour of economic variables can be biased if structural breaks are not considered. When these structural breaks are present, the in-sample fit of a model gives us a poor guide to ex-ante forecast performance. This problem is shared by univariate and multivariate analysis and can be extremely important when cointegration relationships are analysed. The main goal of this paper consists in analysing the impact of structural breaks on forecast accuracy evaluation. We are concerned in forecasting several interest rates from the Spanish interbank money market. In order to carry out the analysis, we perform two forecasting exercises: (1) without structural breaks and (2) when structural breaks are explicitly considered. We use new sequential methods in order to estimate change-points in an endogenous way. After which, we compare the out-of-sample forecast ability of these models. Our results may indicate scarce gains when the structural break is included in the models. El análisis del comportamiento futuro de las variables económicas puede estar sesgado si se ignora la presencia de cambios estructurales. Cuando se dan esos cambios, el ajuste de los modelos dentro de la muestra nos proporciona poca información ex-ante sobre el comportaiento en previsión. Este problema lo comparten el análisis univariante y multivariante y puede ser muy importante en el caso de que existan relaciones de cointegración. El objetivo principal de este trabajo consiste en analizar el impacto de los cambios estructurales en la evaluación de la capacidad predictiva. Estamos interesados en la previsión de los tipos de interés del mercado interbancario. Utilizamos nuevos métodos secuenciales para estimar los puntos de corte de manera endógena. Posteriormente, comparamos las previsiones hechas con los modelos que incorporan los cambios estructurales detectados con modelos en los que no se han tenido en cuenta. Nuestros resultados parecen indicar escasas ganancias cuando se incorpora la información sobre el cambio estructural.

Suggested Citation

  • José Luis Fernández Serrano & Mª Dolores Robles Fernández, 2001. "Structural Breaks and interest rates forecast: a sequential approach," Documentos de Trabajo del ICAE 0110, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  • Handle: RePEc:ucm:doicae:0110
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    5. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521632423, December.
    6. Perron, Pierre & Vogelsang, Timothy J, 1992. "Nonstationarity and Level Shifts with an Application to Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 301-320, July.
    7. Christiano, Lawrence J, 1992. "Searching for a Break in GNP," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 237-250, July.
    8. A. R. Pagan & J. C. Robertson, 1998. "Structural Models Of The Liquidity Effect," The Review of Economics and Statistics, MIT Press, pages 202-217.
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