Agriculture Reference
In-Depth Information
F(-β
'
x
i
) = ∫
-β'xi/σ
∞
1 / (2π)
1/2
exp(-t
2
/2)dt
(6)
The econometric software Stata-10 is able to calculate the probit coefficients and estimate
maximum likelihood ratios based on which model validity can be ascertained. Marginal
effects of the independent variables were also calculated and interpreted.
8.5 Results and discussion
The summary statistics of the variables comprising demographic and some production/
marketing data are presented in Table 8.2. In terms of the demographic characteristics of
the sample, the summary statistics suggest that the majority of the farmers were male, aged
about 60 years on average (ranging from 38 to 82 years). All surveyed household heads had
had some education, with average years of schooling of 5.7 years (the raw data showing that
years of schooling ranged from 1-15 years). Household size averaged about 8.02 persons,
surprisingly large although the skewness suggests that more households had fewer than the
average household size.
It was deemed necessary to summarize data relating to productive asset ownership and
perceptions about production and marketing activities of the households. The indication
from the results is that farm sizes are generally small, property rights are limited and
that few persons that had access to land actually owned them (based on the possession
Table 8.2. Descriptive statistics of sample households in Lesotho.
Variable
Mean
Std. deviation
Skewness
Gender
0.61
0.490
-0.458
Age
60.7
8.794
-0.500
Education
5.7
2.561
1.279
Household size
8.02
2.365
-0.118
Land holding
3.2
1.234
0.525
Property rights
0.35
0.479
0.639
Title deeds to land
0.39
0.490
0.458
Satisfied with production
0.28
0.451
0.995
Non-farm employment
0.42
0.496
0.329
Revenue per ha
4,870
>2 million
1.295
Land access
0.48
0.502
0.081
Market distance
3.9
1.713
1.215
Transport problems
0.49
0.502
0.041
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