Impact Of Agricultural Market Reforms On Smallholder Farmers In ...

that higher values of the independent variable is associated with more positive assessment of
changes in household well-being.
Households with a lower per capita expenditure were more likely to see improvements in
household welfare since 1992. Since cotton growing and location are already controlled,
this means that even among cotton growers (and non-cotton growers) and even within each
department, poor households are more likely to report improved conditions than non-poor
households.
Households that have had contact with an extension agent and those that own a television
also appear to be more likely to see improved economic conditions for their household.
These variables may reflect greater awareness of the economic reforms and how the
reforms might have influenced their own households. In addition, contact with an
extension agent may contribute to positive attitudes toward the government and its attempts
to improve rural living conditions.
Households living far from the sous-prefecture center are less likely to report
improvements in household well-being. The size of this effect is quite small, however: if a
farm is located 120 km from the center (the maximum in the sample) rather than 18 km (the
mean), the probability of seeing improved well-being falls by less than 2 percentage points.
Finally, residents in Atacora and Borgou were significantly more likely to report improved
economic conditions. For example, living in Atacora increases the probability of reporting
improved welfare by 33 percentage points. This result may suggest that the cotton revenue
has boosted general economic conditions in these departments, leading both cotton growers
and non-cotton growers to see gains.
It is somewhat surprising that cotton growers are no more likely to report improved living wellbeing
than non-cotton growers. It should be noted, however, that the statistical significance is only
slightly below the 5 percent threshold usually considered acceptable. Furthermore, alternative
regression models indicate that the cotton variable is highly significant when the departmental
variables are excluded. In other words, either growing cotton or living in a cotton-growing
department is associated with reports of improved well-being, but within each department cotton
growers give similar responses to non-cotton growers.
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