|Abstract or Summary
- This study expresses the hypothesis that historical patterns of national beef cow herd accumulation and liquidations (the cattle cycle) have been related to investment incentive differences across cow ages through time, resulting each year in changes in herd age structure,
performance and potentials for adjustment in subsequent years. A review of national cattle cycle literature reveals the common assumption of variable heifer recruitment levels through time to the
mature cow herd. A review of firm level cattle cycle stategy studies shows that most which considered heterogeneous herds (distinguishing performance by cow age) ironically assumed constant recruitment in proportion to cow numbers. Farmer interviews indicated that heifer recruitment may vary widely in proportion to cow numbers from year to year and that there
are strong tendencies to cull non-pregnant and unsound cows from the herd at any age. The present study assumes both variable recruitment and age heterogenity. A search and synthesis of the biological literature allowed expression of economically important attributes as point estimates
from continuous functions of cow age. These attributes are conception rates, health rates, cow survival rates, cull cow body weights, calf survival rates and weaning weights. Based on these biological parameters, and on the assumption that non-pregnant and unsound cows would be culled, retainment and culling rates are defined as management expectation parameters. These biological and expectation parameters are the building blocks of a simulation model designed to make value
comparisons between cows of different ages and pregnancy status and to trace out changes in the national cow herd age structure through time. A budget generator produces estimates of expected net annual revenues for each of the 26 discrete age and pregnancy classes of heifers and cows, in each year from 1950 through 1978, based on exogenous price and cost series. These estimates are used to project the present values of expected future net revenues for each class of breeding animals. The ratio of future breeding value to present cull slaughter value is calculated for each of the 26 classes, each year. These V-ratios, in turn, are decision variables for determining
the proportions of animals in each class to be retained in the herd, simulated by a national beef cow demography model. Annual summations from the demography model are compared with objective historical series of January 1 inventories of beef cows and replacement heifers, and annual numbers of cull cows slaughtered and beef calves born. The model's simplicity, ignoring related livestock sectors, is one of its significant features. With its few exogenous price and cost variables, simple biological relationships and management assumptions, the model is able to track the historical numbers of beef cows and calves born quite well. Mean proportional absolute deviations (MPAD) of the simulated series from the objective historical series were computed in addition to simple correlation coefficients and Theil's coefficients of inequality. In a display run, the tracking behavior of the model was best for cow inventories and calves born, and worst for heifer recruitment and cull cows, with MPAD's of .029, .036, .172, and .261, respectively. Theil's coefficients of inequality were .405, .587, .962, and .842, respectively. In an alternative run, with parameters set to reflect the assumption that all cows have the same performance characteristics across ages, the tracking behavior of the model was in several
aspects about as good as the display run. Thus, the null hypothesis that performance differences across cow ages are of no importance in explaining investment behavior could not be rejected.
Simulated national beef cow herd age structure changes through cattle cycles are shown from 1950 through 1978.