depends on the efficiency of the farms in the actual sample.
The farms were ranked by DEA-analysis according to
how high gross margin they produced given three different
inputs; acreage of land, cowshed capacity and milk
quota.
The ranking coefficient was used as the dependent
variable in a regression model with approximately 80
relevant biological and economic explanatory variables.
After finalising the analysis, the study resulted in a list
of approximately 13 variables that explain why some
farms are more efficient than others. A selection of the
variables (e.g., total roughage costs, milk delivered of
quota, heifers age) are provided as an example for one
farm in Table 2. The table shows the results for one
farm for the two last years together with a reference
group. The reference group is useful for benchmarking,
and represents an average of farms of similar size
localised in an area with comparable production conditions.
Heifers age is one of the variables that is important
in predicting economic efficiency. Heifers at the
actual farm calved when they were 27.8 months old in
2008, an increase from 25.0 months in 2007. Compared
to the reference group the current farm is worse
off, and should consider taking measures in order to
regain the position it had in 2007. Similarly, insemination
costs have increased from 0.10 in 2007 to 0.14 in
2008, which is well above the costs of the reference
group.
The fact that the study finds a combination of both
biological and economic key performance indicators
points to the importance of including both types of
data. An alternative model consisting of purely biological
data reached only half the explanatory power compared
to the model referred above. However, despite
having access to an enlarged dataset, many questions
are still left unanswered. For example, the farmer might
ask: “How do I reduce my veterinary costs per litre
milk?” Confronted with such questions the analysis of
cattle and economic databases offers very little, if any,
information on how farmers with low veterinary costs
manage their herd. In order to obtain a better understanding
there is a need to get behind the figures.
Hence, we need other perspectives.