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Discussion Papers
Discussion Papers
Abstract
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.
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Assessment
Comments and Questions
Referee Report - anonymous - April 25, 2007 - 10:13
The paper is relevant to current concerns and issues in econometrics, especially in finance where data and regression errors have a tendency to have thick-tailed and skewed distributions. The topic of the paper is very
timely and well-written, but there is little in the paper by way of examples
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in economics and finance that frame the value of the contribution of the paper. The paper includes a simulation that demonstrates the improvement in
estimation efficiency from specifying the flexible distributions that they review for the likelihood functions of the regressions. Since the paper seems to be structured as a note, I would not expect them to do an empirical
analysis with a dataset, but it would be helpful to cite and discuss an application or two that is already in the literature.
Referee Report - anonymous - April 23, 2007 - 16:17
see attached file