GRAS versus minimizing absolute and squared differences: a comment
Junius and Oosterhaven (2003) developed the GRAS algorithm that minimizes the information gain when updating input-output tables with both positive and negative signs. Jackson and Murray (2004), however, claim that minimizing squared differences in coefficients produces a smaller information gain, which is theoretically impossible. In this comment, calculation errors are sorted out from differences in measures, and it is shown that the information gain needs to be taken in absolute terms when increasing and decreasing cell values occur together. The numerical results show that GRAS outperforms both sign-preserving alternatives in all but one comparison of lesser economic importance. Moreover, as opposed to the result of Jackson and Murray, they show that minimizing absolute differences consistently outperforms minimizing squared differences, which overweighs large errors in small coefficients.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 17 (2005)
Issue (Month): 3 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/CESR20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/CESR20|
When requesting a correction, please mention this item's handle: RePEc:taf:ecsysr:v:17:y:2005:i:3:p:327-331. 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: (Michael McNulty)
If references are entirely missing, you can add them using this form.