Given that machinery costs are a significant part of crop production, one might ask, how
much do they affect profitability, and are they manageable? Albright used three years of data to
sort farms into high, middle, and low profitability groups. Across seven different enterprises
(non-irrigated wheat, irrigated wheat, non-irrigated grain sorghum, non-irrigated corn, sprinkler
irrigated corn, non-irrigated soybeans, and non-irrigated alfalfa) there was an average $97.91 per
acre difference in profit between the high and low profitability groups. Of this difference, 84%
was due to costs. The difference between high and low profitability farms due to machinery
costs (including repairs, machine hire, depreciation, gas, fuel and oil) ranged from $14.91 per
acre for non-irrigated soybeans to $45.04 per acre for sprinkler irrigated corn. As a percentage
of the total cost difference between high and low profit groups, machinery costs accounted for
28% to 44% of the total cost difference depending on the crop. These results show that a
majority of the difference in profitability between farms comes from cost management, with a
large part of the cost differences being machinery related.
Knowing that machinery costs are important and impact farm profitability, it is logical for
producers to determine their machinery costs, but more importantly to determine their costs
relative to others. These costs can be determined from actual farm records or cost estimators
using sources like the American Society of Agricultural Engineers and Bowers. Unfortunately,
the cost estimators are based on averages or generalizations that do not take into account the
individual management abilities of a farm (Reid and Bradford; Cross and Perry). Furthermore,
assumptions must be made about the field efficiency of the operations to derive per unit
machinery costs from actual aggregate or estimated machinery costs. Hunt mentions that with
inflation and technological changes, machinery cost estimators become inaccurate within a few
years after they are estimated. A method of avoiding the downfalls of generalized assumptions