Testing normality for unconditionally heteroscedastic macroeconomic variables

Abstract

In this paper the testing of normality for unconditionally heteroscedastic macroeconomic time series is studied. It is underlined that the classical Jarque-Bera test (JB hereafter) 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 methodology can noticeably suffer from size distortion for samples that are typical for macroeconomic variables. As a consequence a parametric 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.

Powers correlation analysis of non-stationary illiquid assets

“…Several authors have underlined that non-stationary behaviors can generate so-called, stylized effects in finance. See, e.g., Mikosch and Stărică (2004), Fryźlewicz (2005), Engle and Rangel (2008), Patilea and Raïssi (2014), Raïssi (2018). In some sense, this paper complements the above references in the framework of illiquid assets.…”

On the correlation analysis of illiquid stocks

“…For instance, Fryźlewicz (2005) and Raïssi (2018) showed that the unconditional heteroscedasticity produce a high kurtosis for financial returns (see Table 1 for the Chilean stocks presented above). Mikosch and Stărică (2004) suggested that serial correlations for absolute returns may be generated from the non constant unconditional variance.…”