measuring resilience evidence from ethiopia kenya uganda niger and burkina faso tim frankenberger
TRANSCRIPT
Measuring Resilience: Evidence from Ethiopia, Kenya, Uganda, Niger and Burkina Faso
Tim Frankenberger May 17, 2016 Core Group Global Health Practitioner Conference
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
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.
Disturbance e.g., natural
hazard, conflict, food shortage,
fuel price increase
Vulnerability pathway
Resilience pathway
Shocks
Stresses
Live
lihoo
d As
sets
Stru
ctur
es/p
roce
sses
Live
lihoo
d St
rate
gies
Expo
sure
Sens
itivi
ty
Cont
ext
Leve
l of a
ggre
gatio
n
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.
OPERATIONALIZING RESILIENCE PRINCIPLES
Threshold
A set of capacities
Realized in connection with
some disturbance
Indexed to an
outcome
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
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)
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)
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
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)
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
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)
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
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
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
PRIME Impact Evaluation: Results
Community Resilience
2
4
6
8
10
12
14
16
18
20
22
0 10 20 30 40 50 60
Hou
seho
ld fo
od in
secu
rity
acc
ess
scal
e (H
FIA
S)
Shock exposure index
RC=39.2
RC=49.2 (mean)
RC=59.2
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
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
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
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.
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
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)
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
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
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)
Conceptual framework representing two components of resilience
past
Psycho-social factorsaspiration, risk aversion,
self-efficacy, etc.
Subjective resilience
Household and community
characteristicsage, education, assets, infrastructures, social
capital, etc.
Programme interventionslivelihood diversification, climate smart agriculture
etc.
Resilience capacitiesabsorptive, adaptive,
transformative
Effect of shocks/stressors
Responsescoping, adaptive, transformative
ImpactChange in food security,
nutrition status, wellbeing
current
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)
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
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
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
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
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).