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    <dc:publisher>Economics: The Open-Access, Open Assessment E-Journal</dc:publisher>
    <dc:publisher>http://www.economics-ejournal.org</dc:publisher>
    <dc:language>en</dc:language>

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<dc:creator>Christian B. Hansen</dc:creator>
<dc:creator>James B. McDonald</dc:creator>
<dc:creator>Panayiotis Theodossiou</dc:creator>
<dc:title>Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models</dc:title>
<dc:date>2007-03-26</dc:date>
<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:description>
<dc:identifier>http://www.economics-ejournal.org/economics/discussionpapers/2007-13</dc:identifier>
<dc:subject>JEL C13</dc:subject>
<dc:subject>JEL C14</dc:subject>
<dc:subject>JEL C15</dc:subject>


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