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Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models

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dc.creator Theodossiou, Panayiotis
dc.creator McDonald, James B.
dc.creator Hansen, Christian B.
dc.date 2007
dc.date.accessioned 2013-10-16T06:57:28Z
dc.date.available 2013-10-16T06:57:28Z
dc.date.issued 2013-10-16
dc.identifier http://hdl.handle.net/10419/17936
dc.identifier ppn:558074200
dc.identifier RePEc:zbw:ifwedp:5527
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/10419/17936
dc.description This paper discusses three families of flexible parametric probability density functions: the skewed generalized t, the exponential generalized beta of the second kind, and the inverse hyperbolic sin distributions. These families allow quite flexible modeling the first four moments of a distribution and could be considered in modeling a wide variety of economic problems. We illustrate their use in a simple regression model with a simulation study that demonstrates that the use of the flexible distributions may result in significant efficiency gains relative to more conventional regression procedures, such as ordinary least squares or least absolute deviations regression, without a suffering from a large efficiency loss when errors are Gaussian.
dc.language eng
dc.publisher Kiel Institute for the World Economy (IfW) Kiel
dc.relation Economics Discussion Papers / Institut für Weltwirtschaft 2007-13
dc.rights http://creativecommons.org/licenses/by-nc/2.0/de/deed.en
dc.subject C13
dc.subject C14
dc.subject C15
dc.subject ddc:330
dc.subject Partially Adaptive Estimation
dc.subject Econometric Models
dc.title Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models
dc.type doc-type:workingPaper


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