PROPERTIES AND ESTIMATION OF ASYMMETRIC EXPONENTIAL POWER DISTRIBUTION
Victoria Zinde-Walsh and
Dongming Zhu ()
Departmental Working Papers from McGill University, Department of Economics
The new distribution class, Asymmetric Exponential Power Distribution (AEPD), proposed in this paper generalizes the class of Skewed Exponential Power Distributions (SEPD) in a way that in addition to skewness introduces di¤erent decay rates of density in the left and right tails. Our parametrization provides an interpretable role for each parameter. We derive moments and moment-based measures: skewness, kurtosis, expected shortfall. It is demonstrated that a maximum entropy property holds for the AEPD distributions. We establish consistency, asymptotic normality and e¢ ciency of the maximum likelihood estimators over a large part of the parameter space by dealing with the problems created by non-smooth likelihood function and derive explicit analytical expressions of the asymptotic covariance matrix; where the results apply to the SEPD class they enlarge on the current literature. Finally, we give a convenient stochastic representation of the distribution; our Monte Carlo study illustrates the theoretical results.
JEL-codes: C13 C16 (search for similar items in EconPapers)
Pages: 37 pages
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Journal Article: Properties and estimation of asymmetric exponential power distribution (2009)
Working Paper: Properties and Estimation of Asymmetric Exponential Power Distribution (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:mcl:mclwop:2007-11
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