A detailed presentation of differences in the incidence of
poverty for adopters and nonadopters in the two regions is given
in Table 4. As is evident from the table, three poverty measures
are employed in the analysis. The poverty measures
include the headcount index, the poverty gap, and the squared
poverty gap. The headcount index is the percentage of the
population living in households with income per capita below
the poverty line. However, the headcount index ignores the
amounts by which the expenditures of the poor fall short of
the poverty line. Hence, the poverty gap index which gives
the mean distance below the poverty line as a proportion of
the poverty line is also computed. The squared poverty gap index
which indicates the severity of poverty is computed by
weighting the individual poverty gaps by the gaps themselves,
so as to reflect inequality among the poor. 9 All three poverty
measures indicate that poverty is more prevalent and severe
among nonadopters compared to adopters.
The results from comparing mean differences in per capita
expenditure, poverty rates, and other household characteristics
between adopters and nonadopters appear to indicate that
adopters are better off than nonadopters. However, these comparisons
of mean differences do not account for the effect of
other characteristics of the households and thus may confound
the impact of technology adoption on expenditure and poverty
status with the influence of other characteristics. To investigate
the impact of the adoption of maize technologies on per
capita expenditure and poverty levels, multivariate approaches
that account for selection bias arising from the fact that adopters
and nonadopters may be systematically different are essential.