RT Generic
T1 Testing for conditional heteroscedasticity in the components of inflation
A1 Broto, Carmen
A1 Ruiz Ortega, Esther
A2 Banco de España, 
AB 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.
YR 2008
FD 2008
LK https://hdl.handle.net/10016/9025
UL https://hdl.handle.net/10016/9025
LA eng
DS e-Archivo
RD 17 jul. 2024