Title: Testing normality for unconditionally heteroscedastic macroeconomic variables
Authors: Hamdi Raissi - PUCV (Chile) [presenting]
Abstract: Testing normality for unconditionally heteroscedastic macroeconomic time series is considered. It is underlined that the classical Jarque-Bera test for normality is inadequate in our framework. On the other hand, it is found that the approach which consists in correcting the heteroscedasticity by kernel smoothing for testing normality is justified asymptotically. Nevertheless, it appears from Monte Carlo experiments that such a methodology can noticeably suffer from size distortion for samples that are typical for macroeconomic variables. As a consequence, a bootstrap methodology for correcting the problem is proposed. The innovations distribution of a set of inflation measures for the U.S., Korea and Australia are analyzed.