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Testing for conditional heteroscedasticity in the components of inflation

Listed author(s):
  • Carmen Broto

    ()

    (Banco de España)

  • Esther Ruiz

    ()

    (Universidad Carlos III de Madrid)

In this paper we propose a model for monthly inflation with stochastic trend, seasonal and transitory components with QGARCH disturbances. This model distinguishes whether the long-run or short-run components are heteroscedastic. Furthermore, the uncertainty associated with these components may increase with the level of inflation as postulated by Friedman. We propose to use the differences between the autocorrelations of squares and the squared autocorrelations of the auxiliary residuals to identify heteroscedastic components. We show that conditional heteroscedasticity truly present in the data can be rejected when looking at the correlations of standardized residuals while the autocorrelations of auxiliary residuals have more power to detect conditional heteroscedasticity. Furthermore, the proposed statistics can help to decide which component is heteroscedastic. Their finite sample performance is compared with that of a Lagrange Multiplier test by means of Monte Carlo experiments. Finally, we use auxiliary residuals to detect conditional heteroscedasticity in monthly inflation series of eight OECD countries.

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File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/08/Fic/dt0812e.pdf
File Function: First version, June 2008
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Paper provided by Banco de España & Working Papers Homepage in its series Working Papers with number 0812.

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Length: 36 pages
Date of creation: Jun 2008
Handle: RePEc:bde:wpaper:0812
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