An Economic Assessment of Banana Genetic Improvement and ...

82 CHAPTER 6
tion. More frequent visits of extension
agents appear to increase cultivar demand,
perhaps due to better knowledge associated
with each cultivar and related management
practices. Wealthier households appear to
have lower demand, suggesting that income
effects drive substitution away from home
production of cooking bananas.
Banana area is positively related to cultivar
demand, as expected. Greater availability
of different planting materials reduces
demand for any single cultivar. This
finding likely reflects complementarities in
the bundles of consumption and production
attributes provided by different banana cultivars,
which motivates farmers to plant
smaller numbers of more cultivars on the
available land. Cultivar demand is also
greater for households in low-elevation
areas, the historical locus of banana production
in Uganda, by a large magnitude.
Households located farther from markets
have greater cultivar demand, meeting
their immediate household consumption
needs through own production. A positive
supply response is evident, however, with a
higher farm-gate price inducing farmers to
plant more mats and hence sell more banana
bunches. Because all households sell bananas
at the farm gate, the variable “distance
to market” captures the behavior of
buyers. The farm-gate price is related to the
behavior of sellers. 7
The statistical importance of consumption
and production attributes in understanding
cultivar demand is clear. Perceived
yield losses caused by either black Sigatoka
or weevils reduce cultivar demand significantly,
evidence that farmer demand for
planting material is responsive to improving
resistance through effective gene insertion
for targeted traits. Perceived cooking quality
in a cooking-type cultivar raises demand
significantly and by a large magnitude,
highlighting the importance of consumption
attributes when host-plant material is selected
for gene insertion.
Sensitivity Analysis
Postestimation, we use the fitted model to
illustrate several policy messages concerning
the potential demand of Ugandan farmers
for genetically engineered planting material
ex ante. First, “client” prototypes are
developed by comparing the characteristics
of households at the upper and lower tails
(20 percent) of the distribution of predicted
demands. Industry clients are the households
with the highest predicted demand for
host planting material with the genetically
engineered traits. Examining the mean
characteristics of households located at the
upper and lower tails of the distribution of
predicted demands provides insights that
are not readily apparent in the regression
relationship, which depicts marginal changes
on average. This exercise demonstrates that
scientists’ choice to transform one host cultivar
rather than another can have social
consequences, favoring one rural population
over another. Such choices are often
necessary, however, because of technical
constraints and the costs of transformation,
particularly in a vegetatively propagated
crop, such as banana.
Second, the total farmer demand for
planting material of a genetically transformed
host cultivar is calculated as an
indicator of the size of the banana industry
demand. Given the vegetatively propagated
nature of the crop, some public investments
in the planting material industry
will probably be necessary, perhaps in
conjunction with private investments in
biotechnology tools and the investments
7
The bulky nature of banana bunches constrains their transportation to local trading centers or urban markets.
Thus, the point of sale is generally the farm gate. In our survey, only a small fraction of the farmers
also sold bunches at local trading centers. At the farm gate, transactions costs are typically borne by buyers
(middlemen, other farmers), and they are reflected in the level of farm-gate prices received by selling
households.