A SIMPLE TEST OF NORMALITY FOR TIME SERIES

By Ignacio N. Lobato, Carlos Velasco. Econometric Theory, 2004

60 citations recorded by the source corpus.

This paper considers testing for normality for correlated data. The proposed test procedure employs the skewness-kurtosis test statistic, but studentized by standard error estimators that are consistent under serial dependence of the observations. The standard error estimators are sample versions of the asymptotic quantities that do not incorporate any downweighting, and, hence, no smoothing parameter is needed. Therefore, the main feature of our proposed test is its simplicity, because it does not require the selection of any user-chosen parameter such as a smoothing number or the order of an approximating model.We are very grateful to Don Andrews and two referees for useful comments and suggestions. We are especially thankful to a referee who provided a FORTRAN code. Lobato acknowledges financial support from Asociación Mexicana de Cultura and from Consejo Nacional de Ciencia y Tecnologìa (CONACYT) under project grant 41893-S. Velasco acknowledges financial support from Spanish Dirección General de Enseñanza Superior, BEC 2001-1270.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/79fb8a1702d1756939241966d3e1cea75863d7f1

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In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Testing Distributional Assumptions: A GMM Approach (2007, methodology): “Using a HAC procedure in testing marginal distributions was already adopted by Richardson and Smith (1993), Lobato and Velasco (2004) , Bai and Ng (2005) and Bontemps and Meddahi (2005) for testing normality, and by A¨it-Sahalia (1996), Conley et al. (1997), and Corradi and Swanson (2005) for testi”