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Multivariate Normality Tests for Serially Correlated Data
Pruebas de normalidad multivariadas para datos correlacionados en serie
DOI:
https://doi.org/10.15446/rce.v47n2.111979Keywords:
Macroeconomic Data, Monte Carlo, Multivariate normality, Orthogonalization, Time series, χ2-distribution. (en)Datos macroeconómicos, Monte Carlo, Normalidad multivariada, Ortogonalización, χ2-distribución, Series de tiempo. (es)
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We extend univariate normality tests for time-dependent observations to their multivariate versions using orthogonalization or empirical standardization of the data. This extension allows us to assess the multivariate normality of serially correlated data. The proposed test statistics asymptotically follow the χ2 distribution, which allows for readily applicable tests. A comprehensive Monte Carlo study indicates that the proposed tests exhibit good size control and high empirical power. Furthermore, we provide empirical illustrations of all the extended tests using West German macroeconomic data (Lütkepohl, 2005).
Extendemos las pruebas de normalidad univariadas para observaciones dependientes del tiempo a sus versiones multivariadas usando ortogonalización o estandarización empírica de los datos. Esta extensión nos permite evaluar la normalidad multivariada. de datos correlacionados en serie. Las estadísticas de prueba propuestas siguen asintóticamente la distribución χ2, que permite pruebas fácilmente aplicables. Un comprensivo Estudio de Montecarlo indica que las pruebas propuestas presentan buen tamaño control y alto poder empírico. Además, proporcionamos ilustraciones empíricas. De todas las pruebas ampliadas utilizando datos macroeconómicos de Alemania Occidental (Lütkepohl, 2005).
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