Measuring Resilience Evidence from Ethiopia Kenya Uganda Niger and Burkina Faso

1. Measuring Resilience:
Evidence from Ethiopia, Kenya,
Uganda, Niger and Burkina Faso
Tim Frankenberger
May 17, 2016
Core Group Global Health Practitioner Conference

2. Background
• The combined effect of climate changes,
economic forces and socio-political conditions
have increased the frequency and severity of
risk exposure among vulnerable populations.
• For this reason interest in resilience has
increased with an associated call for
measurement

3. Defining Resilience
UDAID Definition:
“The ability of people, households, communities, countries, and systems to
mitigate, adapt to, and recover from shocks and stresses in a manner that
reduces chronic vulnerability and facilitates inclusive growth”
• Definition used by the Resilience Technical working Group of FSIN:
“Resilience is defined as a capacity that ensures stressors and shocks do
not have long-lasting adverse development consequences”
• In this research, resilience is viewed as a set of capacities that enable
households and communities to effectively function in the face of shocks
and stresses and still meet a set of well-being outcomes.

4. Disturbance
e.g., natural
hazard, conflict,
food shortage,
fuel price increase
Vulnerability pathway
Resilience pathway
Shocks
Stresses
LivelihoodAssets
Structures/processes
LivelihoodStrategies
Exposure
Sensitivity
Context
Levelofaggregation
Bounce
back
better
Bounce
back
Recover but
worse than
before
Collapse
Food Security
Adequate
nutrition
Environmental
security
Food Insecurity
Malnutrition
Environmental
degradation
Adaptive
state to
shock
Reaction to disturbance
e.g., survive, cope, recover,
learn, transform
Well-being
Outcomes
Absorptive, adaptive
and transformative
capacities
Context
e.g., social,
ecosystems,
political,
religious, etc.
(-)
( + )
Resilience Conceptual Framework
Source: Frankenberger et al. 2014.

5. OPERATIONALIZING RESILIENCE PRINCIPLES
Threshold
A set of
capacities
Realized in
connection with
some
disturbance
Indexed to
an
outcome

6. Three Capacities of Resilience
• Absorptive capacity: The ability to minimize exposure
to shocks and stresses through preventative measures
and appropriate coping strategies to avoid permanent,
negative impacts
• Adaptive capacity: Making proactive and informed
choices about alternative livelihood strategies based on
an understanding of changing conditions
• Transformative capacity: The governance mechanisms,
policies/regulations, infrastructure, community
networks, and formal and informal social protection
mechanisms that constitute the enabling environment
for systemic change

7. Indicators of Resilience Capacity Employed
for the PRIME Project Impact Evaluation
Indicators of Resilience Capacity
Absorptive Capacity
• Household perceived
ability to recover from
shocks
• Social capital (bonding)
• Access to informal
community safety nets
• Asset ownership
• Cash savings
• Availability of hazard
insurance
• Availability of a disaster
preparedness and
mitigation program
Adaptive Capacity
• Household aspirations and
confidence to adapt
• Exposure to information
• Human capital
• Social capital (bridging and
linking)
• Diversity of livelihoods
• Access to financial
resources
• Asset ownership
Transformative Capacity
• Availability of formal
safety nets in communities
• Access to markets
• Access to infrastructure
• Access to basic services
• Access to livestock
services
• Access to communal
natural resources
• Social capital (bridging and
linking)

8. Specific Components of Resilience
Indices Examined in this Presentation
• Social Capital (Bonding, Bridging and Linking)
• Livelihood Diversification
• Psycho-social dimensions (e.g.,aspirations and
confidence to adapt)

9. Empirical Evidence
• This presentation examines empirical evidence
from studies focused on measuring resilience
– Pastoralist Areas Resilience Improvement and
Market Expansion (PRIME) program in Ethiopia
– Build the Resilience and Adaptation to Climate
Extremes and Disasters Program (BRACED)
– Resilience in the Sahel Enhanced (RISE) initiative

10. Studies: PRIME
• Pastoralist Areas Resilience
Improvement through Market
Expansion
– USAID Ethiopia Feed the Future
• Project goals:
– increase household incomes
– enhance resilience
– Improve climate change adaptive capacity
• Program beneficiaries
– pastoralists, ag-pastoralist, non-pastoralists
• Geographic location
– 2 areas in Ethiopia (Borena and Jijiga)
• Data
– Baseline (2013)
– Interim monitoring data (2014 – 2015, 6
months)

11. Studies: BRACED
• Build the Resilience and
Adaptation to Climate Extremes
and Disasters Program
– Mercy Corps
• Goals:
– enhance resilience
– improve climate change adaptive capacity
– public sector engagement & service delivery
• Program beneficiaries
– vulnerable groups, esp. women and girls
• Geographic location
– Karamoja, Uganda
– Wajir county, Kenya
• Data
– Baseline (quantitative)
Wajir county, Kenya
Karamoja, Uganda

12. Studies: RISE
• Resilience in the Sahel
Enhanced (RISE) initiative
• Goal: increase the resilience of
chronically vulnerable populations
in agro-pastoral and marginal
agriculture livelihood zones of the
Sahel.
• Program beneficiaries
– Agriculturalist, pastoralist , other
• Geographic location
– Burkina Faso (Eastern, Northern
Central, and Sahel)
– Niger (Zinder, Maradi and Tillabery)
• Data
– Baseline (quantitative)

13. Samples from Project areas
Project area
# of
households
# of
communities
PRIME
Jijiga 1398 32
Borena 1744 41
BRACED
Karamoja 553 24
Wajir 563 10
RISE
Burkina Faso
and Niger
2492 100

14. Shocks & resilience capacities analysis
• Hypothesis 1: each of the 3 resilience capacities
help mitigate adverse effects of shocks (drought,
food price spikes)
• Data: PRIME,BRACED and RISE baseline surveys
• Analysis
– regressions were run with reported recovery from shocks
as the dependent variable against the three types of
resilience capacity, along with explanatory variables (e.g.,
demographic characteristics and shock exposure)
– dependent variable is a ranked categorical variable (e.g.,
‘not recovered’ to ‘ fully recovered’)
• Separate regressions were run with each resilience
capacity to measure the impact of each capacity

15. The Effect of Resilience Capacities in
Mitigating Shocks
• All 3 resilience capacities (absorptive, adaptive
and transformative capacity) contributed in
some way to making households resilient to
shocks in PRIME, BRACED, and RISE program
areas

16. PRIME Impact Evaluation: Results
Community
Resilience
2
4
6
8
10
12
14
16
18
20
22
0 10 20 30 40 50 60
Householdfoodinsecurityaccessscale
(HFIAS)
Shock exposure index
RC=39.2
RC=49.2 (mean)
RC=59.2

17. Links between Resilience & FS (RISE
Baseline)
12
14
16
18
20
22
24
0 2 4 6 8 10 12 14
Household
food security
Number of months of agricultural drought
RC=36.4
Greater household resilience capacity reduces negative impacts
of agricultural drought on food security
Resilience capacity (RC)–mediated relationship between drought exposure (months
of agricultural drought) and food security

18. Social Capital
• Social capital can be described as
– the quantity and quality of social resources (networks,
membership in groups, social relations, and access to wider
institutions in society) upon which people draw in pursuit of
livelihoods
• Signs of well-developed social capital include:
– close interaction between people through tight-knit
communities
– the ability to rely on others in times of crisis
– open communication between stakeholder groups
• Previous research demonstrates that social capital
strongly influences community level resilience
– Communities with high social capital rally together

19. Types of Social capital
• Bonding social capital is seen in the bonds
between community or group members.
• Bridging social capital connects members of one
community or group to members of other
communities/groups
• Linking social capital is often conceived of as a
vertical link between a network and some form
of authority

20. Social capital hypotheses
• H1: Households with greater levels of social capital (bonding, bridging, and
linking) achieve greater levels of food security than those with less social
capital, all else equal.
• H2: Households with greater levels of social capital (bonding, bridging, and
linking) are able to recover better than those with less social capital, all
else equal
• H3: For a given level of exposure to shocks, households with more social
capital report fewer negative impacts of shocks than households with less
social capital, all else equal.
• H4: Wealthier households have greater levels of social capital (bonding,
bridging, and linking) and are better able to both receive and give
assistance (in the form of money or food) than those of poorer
households.

21. Social capital conclusions
• Social capital appears to have a positive effect on food
security, helps households recover, and mitigates the
effect of shocks across the different data sets
• Thus social capital appears to be critical to resilience
• Wealthier households appear to receive the benefits of
social capital more than poorer households
• Social capital can be used up in the early phases of a
prolonged covariate shock and its downstream effects

22. Effects of livelihood diversity on
recovery and shock impact
• Livelihood
– activities in which households engage their skills,
capacities, and physical resources to create
income or otherwise improve their way of life
• Rural livelihood diversification
– the process by which households construct an
increasingly varied portfolio of activities, social
support capabilities, and assets for survival or to
improve their standard of living
(Assan 2014; Ellis 2000a, 1999; Chambers and Conway 1992)

23. Livelihoods hypotheses
• H1: Households with greater levels of livelihood
diversity achieve greater levels of resilience than those
who have less diversification, all else equal
• H2: Wealthier households are able to diversify their
livelihood sources more than poorer households, all
else equal
• H3: Poorer households are pushed into livelihoods with
lower returns, and are less able to access livelihoods
with greater and less risky returns
• Data: PRIME & BRACED baselines

24. Livelihoods Results
• Livelihood diversification as a mechanism to
better cope with shocks and stresses needs to
be better understood in the context in which
programs are being implemented
– Diversification can work where there are
opportunities to engage in high return activities
and in areas where significant non-climate sensitive
options exist
– Livelihood diversification in areas where such
opportunities do not exist will not necessarily lead
to better adaptation

25. Subjective and psychosocial factors
• Psychosocial measures that are posited to
influence adaptive capacity
– risk perception
• perceived risk of experiencing a slow-onset or sudden shock
• perceived risk associated with employing certain strategies
to maintain or improve wellbeing after a shock
– self-efficacy
• "belief in one’s own ability to perform a task and to manage
prospective situations”
– aspirations
• Fatalism is “the sense of being powerless to enact change
and having no control over life’s events” (TANGO 2014;
Smith et al. 2015)

26. Conceptual framework representing
two components of resilience
past
Psycho-social factors
aspiration, risk aversion,
self-efficacy, etc.
Subjective
resilience
Household and
community
characteristics
age, education, assets,
infrastructures, social
capital, etc.
Programme interventions
livelihood diversification,
climate smart agriculture
etc.
Resilience capacities
absorptive, adaptive,
transformative
Effect of
shocks/stressors
Responses
coping, adaptive,
transformative
Impact
Change in food security,
nutrition status,
wellbeing
current

27. 4. Psychosocial Hypotheses
• Hypothesis 1: Subjective resilience influences
households' response to shocks/stressors
• Hypothesis 2: Psycho-social factors influence the
people’s ability to recover from shocks/stressors
• Data used:
(1) fishing communities in Ghana, Fiji, Vietnam and Sri
Lanka (Béné et al. 2016)
(2) rural households in 2 regions of Ethiopia (Smith et
al. 2015)

28. H1: Psychosocial Results
• We found negative correlations between
households' level of subjective resilience (i.e.,
self-efficacy score) and the propensity of those
households to engage in coping strategies
• The higher the sense of control people have over
their lives and the more positive the perception
about their own ability to handle (future)
shocks/stressors, the lower the likelihood that
these households will engage in detrimental
short term responses

29. H2: Psychosocial Results
• Ghana-Fiji-Vietnam-Sri-Lanka dataset:
– a correlation between the level of subjective resilience
and the household's resilience index was significant
and positive
• Ethiopian dataset
– a positive correlation between the self-efficacy score
and the recovery index for both Jijiga and Borena
• The perception that people have of their level of
control over their own life positively influences
their ability to recover from shocks/stressors

30. Summary of key findings
• Shocks, resilience & response trajectories
– All 3 resilience capacities contributed in some way to
making households resilient
– Ongoing monitoring is needed (6 months – 1 yr)
– Shocks measurement needs to include both objective
and subjective data
• Social capital
– Social capital appears to have a positive effect on food
security, helps households recover, and mitigates the
effect of shocks across the different data sets
– Social capital appears to be critical to resilience
– Social capital can mitigate early impacts of a shock but
may be used up by a prolonged shock and its
downstream effects

31. Summary of key findings
• Livelihood diversity, recovery & shock impact
– Livelihood diversification needs to be understood in the
program context (e.g., opportunities exist to engage in
high return activities and non-climate sensitive options)
• Psycho-social factors
– People’s perceived level of control over their own life
positively influences their ability to recover from
shocks/stressors
– The higher the sense of control people have over their
lives and the more positive the perception about their own
ability to handle (future) shocks/stressors, the lower the
likelihood that these households will engage in detrimental
short term responses

32. Thank You
Tim Frankenberger
tim@tangointernational.com

33. References
Papers available at
http://www.technicalconsortium.org/publications/
under Technical Briefs/Reports Technical Report Series No 2.
1. Woodson, L, Frankenberger, T., Smith, L., Langworthy, M. & Presnall, C. (2016). The
effects of social capital on resilience: Evidence from Ethiopia, Kenya, Uganda, Niger and
Burkina Faso. Nairobi, Kenya: A joint ILRI and TANGO International publication (in press).
2. Bower, T., Frankenberger, T., Nelson, S., Finan, T. & Langworthy, M. (2016). The effect of
livelihood diversity on recovery and shock impact in Ethiopia, Kenya and Uganda.
Nairobi, Kenya: A joint ILRI and TANGO International publication (in press).
3. Béné, C., Frankenberger, T., Langworthy, M., Mueller, M. & Martin, S. (2016). The
influence of subjective and psychosocial factors on people's resilience: conceptual
framework and empirical evidence. Nairobi, Kenya: A joint ILRI and TANGO International
publication.
4. Bower, T., Presnall, C., Frankenberger, T., Smith, L., Brown, V. & Langworthy, M. (2016).
Shocks, resilience capacities and response trajectories over time. Nairobi, Kenya: A
joint ILRI and TANGO International publication (in press).