LiveLihoods strategies and househoLd resiLience to Food insecurity ...

LIVELIHOODS STRATEGIES AND HOUSEHOLD RESILIENCE TO FOOD INSECURITY: AN EMPIRICAL ANALYSIS TO
KENYA
government, firms, and remittances. Then, we standardised it, in order to have a latent
variable with zero mean and variance equal to 1, before running the second stage factor
analysis to estimate resilience. In this case, wage-employees show the highest level of
SSN while pastoralists and small-holder farmers the lowest level (Table 10).
Table 10: Average values of the SSN component
Variables Kenya
Agropastoral
ists
Smallholder
farmers
Largeholder
farmers
Entrepr
e-neurs
Wage
employe
es
Pastorali
sts
SSN 1,117.6 985.0 660.1 944.2 1,197.9 2,055.4 242.6
Stability (S)
Stability is an important dimension of household’s resilience that captures the degree to
which household’s options vary over time. To estimate the value of this latent variable,
we used the value of losses due to shocks, namely:
• animal shock (ANS): the value-loss due to stolen or dead livestock;
• crop shock (CRS): this is the crop loss caused by droughts, floods, crop diseases,
pest outbreaks, fall in output prices, increase in input prices, and water shortages;
• other shocks (OTS): this variable summarises the value loss due to shocks other than
those considered in the previous two variables (for example, the illness, death, job
loss of a household member);
• shocks (SHK): this is a count variable constructed as the sum of the dummy
variables which indicate whether a household was hit or not by each shock typology
during the five years before the survey.
Clearly, a given monetary loss does not have the same meaning for all
households. Thus, we decided to normalise the first three variables by dividing each of
them for household per capita expenditure. Each observed shock variable is, indeed, an
indicator of instability. Thus, we multiplied each of them times -1 in order to make them
consistent with the meaning of the latent variable S.
Table 11 shows that the most stable livelihood groups are wage-employees and
large-holder farmers, while small-holder farmers are those who are relatively the least
stable.
Table 11: Factor loadings for the observed variable used to estimate the S
component
Variables Kenya
Agropastoral
ists
Smallholder
farmers
Largeholder
farmers
Entrepre
-neurs
Wage
employ
ees
Pastorali
sts
SHK 0.4009 0.7122 0.5641 0.3621 0.2500 0.4822 0.2540
ANS 0.6796 0.7134 0.2329 0.6662 0.1865 0.8528 0.8026
OTS 1.0069 0.9904 0.9337 1.0088 0.9706 1.0123 1.0102
CRS 0.7726 0.7588 0.9548 0.9117 0.9046 0.7913 0.8406
Adaptive Capacity (AC)
This is another important dimension of resilience, which measures the household’s ability
to adapt and react to shocks. The following observed variables are meant as the
determinants of the household adaptive capacity:
• diversity (DIV): this is a count variable that accounts for the number of household
sources of income; the idea is that the more diversified the sources of income, the
higher the ability of the household to adapt to a given shock;
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