The Use of Seemingly Unrelated Regression (SUR) to Predict the Carcass Composition of Lambs
AbstractThe aim of this study was to develop and evaluate models for predicting the carcass composition of lambs. Forty male lambs of two different breeds were included in our analysis. The lambs were slaughtered and their hot carcass weight was obtained. After cooling for 24 hours, the subcutaneous fat thickness was measured between the 12th and 13th rib and the total breast bone tissue thickness was taken in the middle of the second sternebrae. The left side of all carcasses was dissected into five components and the proportions of lean meat, subcutaneous fat, intermuscular fat, kidney and knob channel fat, and bone plus remainder were otained. Our models for carcass composition were fitted using the SUR estimator which is novel in this area. The results were compared to OLS estimates and evaluated by several statistical measures. As the models are intended to predict carcass composition, we particularly focussed on the PRESS statistic, because it assesses the precision of the model in predicting carcass composition. Our results showed that the SUR estimator performed better in predicting LMP and IFP than the OLS estimator. Although objective carcass classification systems could be improved by using the SUR estimator, it has never been used before for predicting carcass composition.
Download InfoIf 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.
Bibliographic InfoPaper provided by University of Copenhagen, Department of Food and Resource Economics in its series IFRO Working Paper with number 2011/12.
Length: 14 pages
Date of creation: Sep 2011
Date of revision:
Carcass; Quality; Ordinary least squares; Seemingly unrelated regression;
Find related papers by JEL classification:
- Q19 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Other
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
This paper has been announced in the following NEP Reports:
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Arne Henningsen & Jeff D. Hamann, . "systemfit: A Package for Estimating Systems of Simultaneous Equations in R," Journal of Statistical Software, American Statistical Association, American Statistical Association, vol. 23(i04).
Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:
- Seemingly unrelated regressions and lamb carcasses
by Economic Logician in Economic Logic on 2011-10-26 14:01:00
- Siwarat Kuson & Songsak Sriboonchitta & Peter Calkins, 2012. "Household determinants of poverty in Savannakhet, Laos: Binary choice model approach," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, Faculty of Economics, Chiang Mai University, vol. 1(3), pages 33-52, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Geir Tveit).
If references are entirely missing, you can add them using this form.