Least Squares and Entropy: A Penalty Function Perspective
Mathematical measures of entropy as defined by Shannon and cross entropy as defined by Kullback and Leibler are currently in vogue in the field of econometrics, primarily due to the comprehensive work of Golan, Judge, and Miller. An alternative interpretation of the entropy measure as a penalty function over deviations is presented, and a number of parallels are drawn with least squares estimators. It is demonstrated that both approaches may be applied to the general linear model. The causes of differences in estimated parameter values are described, and some suggestions for the formulation of entropy-based econometric problems are presented. Copyright 2001, Oxford University Press.
Volume (Year): 83 (2001)
Issue (Month): 2 ()
|Contact details of provider:|| Postal: 555 East Wells Street, Suite 1100, Milwaukee, Wisconsin 53202|
Phone: (414) 918-3190
Fax: (414) 276-3349
Web page: http://www.aaea.org/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:oup:ajagec:v:83:y:2001:i:2:p:366-377. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.