Testing for conditional heteroscedasticity in the components of inflation

Carmen Broto () and Esther Ruiz ()
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Esther Ruiz: Universidad Carlos III de Madrid

No 812, Banco de España Working Papers from Banco de España

Abstract: 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.

Keywords: Leverage effect; QGARCH; seasonality; structural time series models; unobserved component (search for similar items in EconPapers)
JEL-codes: C22 C52 E31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-mac and nep-ore
Date: 2008-06
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Related works:
Journal Article: Testing for Conditional Heteroscedasticity in the Components of Inflation (2009)
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Persistent link: http://EconPapers.repec.org/RePEc:bde:wpaper:0812

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