Effects of estimation accuracy on potential payment premiums for superior beef carcasses

Citation
Rw. Purchas et al., Effects of estimation accuracy on potential payment premiums for superior beef carcasses, NZ J AGR RE, 42(3), 1999, pp. 305-314
Citations number
13
Categorie Soggetti
Agriculture/Agronomy
Journal title
NEW ZEALAND JOURNAL OF AGRICULTURAL RESEARCH
ISSN journal
00288233 → ACNP
Volume
42
Issue
3
Year of publication
1999
Pages
305 - 314
Database
ISI
SICI code
0028-8233(199909)42:3<305:EOEAOP>2.0.ZU;2-Q
Abstract
Knowledge of saleable meat yield (SMY%) at the time of carcass classificati on enables payments to be made on the basis of carcass saleable meat conten t. This study determined the extent to which improved accuracy of estimatin g SMY% enabled larger premiums to be paid for better yielding carcasses. A population of 1000 carcasses was simulated for true SMY% values (275 kg car cass weight; mean SMY% of 66 with a standard deviation of 3.0) as well as e stimated SMY% values when accuracies in terms of residual standard deviatio n (RSDs) ranged from 0 to 2.5. A consequence of the requirement that estima tes of SMY% be unbiased was that variability of the estimates was less than that of the true SMY% when estimation was imperfect. Premiums that could b e paid to the top 5% of carcasses relative to the average increased by 5.8, 9.2, and 9.7 c kg(-1) as the RSD decreased from 2.5 to 1.0 for five-step, eight-step, and smooth payment systems, respectively. The rate at which pot ential premiums increased with decreases in RSD values was low at high leve ls of accuracy (RSD values below about 1.0). The potential premiums for the top 5% were highest for the smooth payment system with an advantage over t he five-step system of 24% at an RSD of 1.0 and 28% at an RSD of 2.0, but t he size of the advantage varied with the proportion of carcasses considered . It is concluded that the benefits that may be derived from using a smooth payment system rather than a stepwise system will often be more easily att ained than those from improving the accuracy of estimating SMY% and may be as great.