Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models

11 Pages Posted: 29 Nov 2010

See all articles by Panayiotis Theodossiou

Panayiotis Theodossiou

Ball State University

James McDonald

Brigham Young University

Christian Hansen

University of Chicago - Booth School of Business - Econometrics and Statistics

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Date Written: 2007

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.

Keywords: Partially Adaptive Estimation, Econometric Models

JEL Classification: C13, C14, C15

Suggested Citation

Theodossiou, Panayiotis and McDonald, James B. and Hansen, Christian, Some Flexible Parametric Models for Partially Adaptive Estimators of Econometric Models (2007). Economics Discussion Paper No. 2007-13, Available at SSRN: https://ssrn.com/abstract=1716353 or http://dx.doi.org/10.2139/ssrn.1716353

Panayiotis Theodossiou (Contact Author)

Ball State University ( email )

2000 W. University Ave
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United States

James B. McDonald

Brigham Young University ( email )

130 Faculty Office Bldg.
Provo, UT 84602-2363
United States
801-378-3463 (Phone)

Christian Hansen

University of Chicago - Booth School of Business - Econometrics and Statistics ( email )

Chicago, IL 60637
United States
773-834-1702 (Phone)