PROPERTIES AND ESTIMATION OF ASYMMETRIC EXPONENTIAL POWER DISTRIBUTION

Victoria Zinde-Walsh and Dongming Zhu ()

Departmental Working Papers from McGill University, Department of Economics

Abstract: 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
Date: 2007-10
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (3)

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Related works:
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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