Cross-Commodity Perspective on Contracting: Evidenc e from Mississippi
producers, for example, spend over twice the time gathering market information as compared
to livestock producers. Thus, while the absolute numbers appear to be inconsequential, the
relative differences may help explain some of the differences observed in contracting.
There appear to be differences in the level of income diversification as well. Cotton
producers have the lowest level of income diversification of the commodities analyzed. As
such, one would expect this group to have the highest level of contracting. Again, this
hypothesis appears to be supported by the data. In addition, the FNVO and L ivestock
groups have the highest levels of income diversification, and correspondingly have the lowest
levels of contracting activity.
Finally, the level of asset specificity appears fairly constant across crops, with the
exception of livestock. One would expect that higher levels of asset specificity would lead
to more use of contracting. However, for livestock, the data do not support this hypothesis.
It could be that other factors such as off-farm income are counteracting the effects of asset
specificity. It is interesting to note, however, that only FNVO or Livestock producers
responded as having participated in resource providing or production management contracts,
which are closer to vertical integration than spot markets. Thus, perhaps asset specificity is
important for these more complex forms of vertical integration. The regression model was
used to control for these potential counter-vailing effects.
4.2 Regression Results
A logistic regression model was used to analyze the impacts of the variables above on
the probability that a pro ducer is engaged in contract production:
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