Resilience to Avoid and Escape Chronic Poverty

Report
Resilience to Avoid and
Escape Chronic Poverty:
Theoretical Foundations
and Measurement Principles
Christopher B. Barrett and Mark A. Constas
Cornell University
December 11, 2012 presentation at CARE USA’s
Washington, DC, Roundtable on Resilience
Prologue
Activity – past few years
Three main reasons for increased activity around the
concept of development resilience
1. Pronounced Risks
Increasing exposure to risk related to natural disasters,
climate, food markets, macroeconomic shocks, political
violence, etc.
2. Bridging the Divide
Recurring crises have highlighted the importance of
aligning humanitarian and development objectives
3. Ecological/biophysical Factors
Growing consensus that development work must be
connected to pressing environmental concerns
Prologue
Activity – past few years
Work concerned with the poverty dynamics is not new,
but the recent activity in development has used
resilience as a common platform on which:
• A range of initiatives, strategic plans, and funded
program for humanitarian response and
development assistance have been based
• Broad participation from government agencies,
INGOs, multilateral organizations and foundations
has been structured and promoted
• Many white papers, reports, workshops, conferences,
newly established centers, working groups, high
profile events, articles, blogs, and tweet… have been
based
Prologue
Activity – past few years
Prologue
Activity – past ten days
December 3, 2012 USAID Press Release
Prologue
Activity – past ten days
December 3, 2012 World Vision Press Release
Prologue
Activity – past ten days
December 6, 2012 AGIR-Sahel, High Level Meeting in Burkina Faso
http://www.neurope.eu/article/eu-will-inject-500-million-help-food-crisis-sahel
Prologue
Hope
October 3, 2012
Prologue
Hope
November 7, 2012
http://ec.europa.eu/echo/policies/res
ilience/resilience_en.htm
Prologue
More Hope
November 19, 2012
Prologue
….and Creeping Doubt
http://www.irinnews.org/Report/96549/AID-POLICY-Resistingresilience-reassessing-the-new-mantra
http://blog.usaid.gov/2012/12/does-the-new-resilience-policy-havestaying-power/
Prologue
….and Creeping Doubt
October 25, 2012
http://www.irinnews.org/Report/96549/AID-POLICY-Resistingresilience-reassessing-the-new-mantra
November 14, 2012
http://www.ids.ac.uk/news/can-resilience-bring-something-newto-poverty-alleviation
I. Framing the Problem
What do we have and what is needed?
What we have:
• Much activity/enthusiasm around the resilience concept
• Some activity is rhetorical, some is strategic/policy
oriented, some is conceptual, and some is programmatic
• An opportunity to bridge between humanitarian response
and development assistance strategies
What we need:
• Theory to integrate programmatic efforts and analytical
approaches connected to mitigation, buffering, coping, and
adaptation
• Theory-driven measurement to evaluate progress
• Body of empirical results based on theory-driven measures
I. Framing the Problem
Call for Theory of Resilience
Theory is important because it:
• Serves as a conceptual tool to help build coherence for wide range of
variables and across a selection of programmatic approaches
• Directs attention to the importance of explanations that identify not just
if something worked but also why something worked –thereby pushing us
to identify causal mechanisms
Highlighting the need for explanatory knowledge of resilience , a
recent ODI Humanitarian Policy Brief offered the following:
“…the frameworks [of resilience cannot assist in answering critical
questions, such as what is it that makes people more or less sensitive to
crisis, because these dimensions are left as unexplained ‘black boxes’
”(Levine et al., 2012, p. 2).
from
Levine, S, Pain, A., Bailey, S., and Fan, L, 2012. The Relevance of
Resilience? ODI, Humanitarian Policy Brief 49
II. Toward a Theory
Resilience foregrounds risk in well-being dynamics:
Shocks that disrupt lives and livelihoods: the single
greatest cause of descents into chronic poverty (Krishna, etc.)
Uninsured risk of catastrophic loss (stressors): a key
structural reason for poverty traps/chronic poverty
We seek to bridge the ecological/engineering literatures on
resilience with the social science literatures on risk and poverty
traps in order to:
- advance a theory of resilience against chronic poverty
- tease out measurement principles appropriate to that theory
II. Toward a Theory
Resilience of whom to what?
Subject of interest – quality of life, roughly Sen’s ‘capabilities’.
This implies a focus on individuals’ (and groups’) well-being
within a system, not the state of a system itself. System has
instrumental rather than intrinsic importance.
Focus further on minimizing the human experience of
chronic poverty. We therefore focus on places with high
rates of chronic poverty and risk exposure.
Do not focus on a specific source of risk b/c problem is
uninsured exposure to a wide array of stressors (ex ante risk)
and shocks (ex post, adverse realizations) to which resilience
implies adaptability while staying non-poor.
II. Toward a Theory
We need to adapt ecological/engineering theory to the
development/humanitarian response context.
As used in ecology or engineering – e.g., “the ability of the
system to maintain its identity in the face of internal change
and external shocks and disturbances” (Cumming et al. 2005
Ecosystems, p. 976) – resilience is not necessarily desirable
for populations trapped in chronic poverty. Their objective
may be escape from – not persistence in -- their present state
of existence.
To be useful for development policy, we need resilience to be a
normative property, to be orderable – and preferably
decomposable (in FGT sense) – in order to offer a useful
metric to gauge performance and guide policy/programming.
II. Toward a Theory
Concept of Resilience for Development
Development resilience represents the likelihood over time of a
person, household or other unit not being poor in the face of
various stressors and in the wake of myriad shocks. If and only
if that likelihood is high, then the unit is resilient.
Key Elements:
Standards of living: Focus on avoiding/escaping poverty
Effects of stressors: Uninsured risk influences dynamic incentives
Response to shocks: Temporary setbacks vs. permanent descents
Dynamical system vs. static representations of standards of living
II. Toward a Theory
Well-Being Dynamics
Figure 1: Nonlinear expected well-being dynamics with multiple stable states
Humanitarian emergency zone
E[future]
capabilities
Death
Death T1
Chronic
poverty zone
Non-poor zone
T2
Current
capabilities
Noncontroversially: NPZ >> CPZ >> HEZ
Those in CPZ or HEZ are chronically poor in expectation
The CEF reflects indiv/collective behaviors (agency/power) w/n system
II. Toward a Theory
Well-Being Dynamics
Figure 1: Nonlinear expected well-being dynamics with multiple stable states
The humanitarian ambition is to
keep people from falling into HEZ
… offers foundation of a rightsbased approach to resilience.
E[future]
capabilities
Humanitarian emergency zone
The development ambition is to
move people into the non-poor
zone and keep them there.
Death
Death
Chronic
poverty zone
Non-poor zone
Current
capabilities
For the current non-poor, seek ‘resilience’ against shocks in the ecological
sense: no shift to either of the lower, less desirable zones.
But for the current poor, those in HEZ/CPZ, the objective is productive
disruption, to shift states.
Asymmetry is therefore a fundamental property of resilience against
chronic poverty. Thus stability ≠ resilience.
II. Toward a Theory
Well-Being Dynamics
A Utopian, asymmetric vision of well-being dynamics:
Figure 2: Desired expected well-being dynamics with multiple stable states
E[future]
capabilities
Humanitarian emergency zone
Egalitarian option
Death
Death
Chronic
poverty zone
Non-poor zone
Current
capabilities
‘Egalitarian option’: engineering concept applies - return to initial state.
‘Random walk w/safety net option’: implies perfect downward resilience
at NPZ/CPZ boundary … but zero resilience upward or w/n NPZ.
II. Toward a Theory
Well-Being Dynamics
Explicitly incorporate risk, move from CEF to CTD:
Figure 3: Nonlinear well-being dynamics with conditional transition distributions
Humanitarian emergency zone
Future
capabilities
Death
Death
Chronic
poverty zone
Non-poor zone
Current
capabilities
Note: The shape of the CTD affects the shape of the CEF
Transitory shocks (- or +) can have persistent effects
Risk may be partly endogenous to system state
II. Toward a Theory
Well-Being Dynamics
Feedback between sub-systems can be crucial
If we represent the preceding conditional transitions as:
Wt+1=g(Wt|Rt,εt)
where W is welfare, R is the state of the natural resource, and ε
is an exogenous stochastic driver
Then simply introducing feedback between R and W
(e.g., range conditions depend on herd size/stocking rate)
Rt+1=h(Rt|Wt,εt)
or allowing for drift in ε (e.g., due to climate change)
means the underlying CTD changes over time.
Then the resilience of the underlying resource base becomes
instrumentally important to resilience against chronic poverty.
II. Toward a Theory
Well-Being Dynamics
Coupled human and natural systems dynamics
E[future] capabilities
E[future]
natural
resource
state
?
Current
capabilities
Current natural resource state
Note:
- Ecological resilience links to human resilience through reciprocal
causality in coupled human/natural dynamics
- Many candidate relationships make prediction difficult at best
II. Toward a Theory
Programming implications
Objective: min likelihood people fall into HEZ/CPZ
Three options:
1) Shift people’s current state – i.e., move initial state
rightward. Ex: asset transfers: cash, education, land.
2) Alter CTDs directly (and thereby ∆ system too). Ex: social
protection - EGS, insurance, improved police protection,
drought-resistant animal/plant genetics.
3) Change the underlying system structure – institutions/
technologies – induces ∆ in behaviors and CTDs. Prob:
multi-scalar reinforcement – ‘fractal poverty traps’
Systems thinking becomes important to reveal the structure –
and possible intervention points – behind univariate dynamics.
II. Toward a Theory
Programming implications
The importance of social institutional arrangements
“A tale of two widows”
And would the widower’s
dynamic = the widow’s?
Mid-point summary
• We make no claim that this is THE definitive theory of
resilience against chronic poverty. We merely claim that such
theory(ies) is sorely needed to help shape the accelerating
programming around resilience. This is one candidate.
• Such theory needs to explicitly link risk, poverty and
supporting natural resources in an explicitly dynamic context.
• Theory becomes especially important as a bedrock for
measurement for M&E and prioritization.
III. Measurement
General Measurement Principles – not specific to
resilience but important across all measurement situations
1. Gender-based analysis/gender equity and focus on women and
mothers
2. Distinction between chronically poor and transiently poor
3. Measurement of non-market goods both subjective and
objective elements
4. Measurement of observables and latent variables, leading to
constructs/factors
5. Technical properties of measures –reliability and validity –
and rigorous analysis of the origins and effects of
measurement error
•
•
•
Ravallion, M. 1996. Issues in measuring and modeling poverty. Economic Journal, 106 (438), 1328-1343.
Krishnakamur, J. 2007. Going Beyond Functionings to capabilities: an econometric model to explain and estimate capabilities,
Journal of Human Development. 8 (1), 39-63
2010 UN Resolution 64/289 (49-50 ); HDR GDI, GEM; Guidance from various sources UNEGEEW, UNSD, DESA, ECOSOC
III. Measurement
Resilience Specific Measurement Principles
A set of theory-based measurement principles for
resilience that has operational merit should:
• Specify what needs to be measured to produce data needed to
test and advance interventions and policies
• Substantive functions of measurement
• Describe how data should be handled to draw inferences
about interventions and policies
• Analytical functions of measurement
III. Measurement
Principles for Resilience
Measurement
Substantive Principles
Focus on what needs to be
measured to understand
and predict resilience
Analytical Principles
Focus on the properties of
responses so that patterns
in resilience data may be
identified
Operational and
Procedural Details
•
•
•
•
Constructs
Mediators
Indicators/variables
Measurement tools
•
•
•
•
Sampling design
Causal structure
Modeling procedures
Types of inferences
III. Measurement
Substantive principles
1. Poverty Focus Principle
Importance of using poverty as the main indicator of the
resilience
• Population variation guideline
• Multidimensionality and weighting guideline
2. Intensive Risk Assessment Principle
Importance of detailed risk assessment that sensitive both
conspicuous and subtle stressors
• Multidimensionality-intertemporal guideline
• Cumulative and interactive guideline
III. Measurement
Substantive Principles
3. Response Heterogeneity Principle
Importance of response pattern variations and the impact of
institutional forces
• Intra/inter unit variations guideline
• Institutional variations guideline
4. Contextual Influences Principle
Importance of conditions and mediators that influence effects
of outcomes
• Socio-ecological guideline
• Causal-mediators guideline
III. Measurement
Substantive Principles
Summary of Substantive Principles
The substantive principles for measurement specify that
measurement tools should:
• Focus poverty in a manner that is sensitive to population
variations and reflect the multidimensionality of well being
• Measure stressors/shocks that reflect multidimensionalintertemporal (weighted) qualities with sensitivity to
cumulative and interactive effects
• Measure the range of responses that account for the ability or
inability to avoid remaining or falling into poverty and consider
variations within and between housholds/units
• Measure the impact of institutions and governance structures
that facilitate or hinder
• Measure the influence of socio-ecological contexts as mediators
III. Measurement
Analytical Principles
5. State Dependent Dynamics Principle
The importance of state dependence and measurement of
paths over time
• Initial-States Guideline
• Trajectories Guideline
6. Stochastic Processes Principles
The importance of distinguishing between stochastic and
structural risk factors
• Stochastic-structural differentiation guideline
• Structured conditional risk guideline
III. Measurement
Analytical Principles
7. Threshold Sensitivity Principle
Importance of measures that are sensitive to tipping points,
abrupt descents and impacts on well-being
• Hierarchical options guideline
• Indirect reflections guideline
8. Cross-Scale Interactions Principle
Importance of measures taken across scales with attention to
interactions across levels
• Multi-scalar assessment guideline
• Multi-level guideline
III. Measurement
Analytical Principles
Summary of Analytical Principles
The analytical principles for measurement specify that
measurement tools should:
• Be sensitive to initial conditions, not just as points but as
paths or trajectories
• Distinguish between stochastic and structural causes of
poverty
• Employ analytic approaches that are flexible so that the
capacity to detect effects will not be hindered by strong
assumptions (e.g., homoskedasticity)
• Be able to detect tipping points and multiple equlibria that
affect resilience
• Assess effects across scales and as nested interdependencies
(e.g., individuals, within households, within communities)
III. Measurement
Analytical Principles
Summary of Analytical Principles
The analytical principles for measurement specify that
measurement tools should:
• Be sensitive to initial conditions, not just as points but as
paths or trajectories
• Distinguish between stochastic and structural causes of
poverty
• Employ analytic approaches that are flexible so that the
capacity to detect effects will not be hindered by strong
assumptions (e.g., homoskedasticity)
• Be able to detect tipping points and multiple equlibria that
affect resilience
• Assess effects across scales and as nested interdependencies
(e.g., individuals, within households, within communities)
III. Measurement Summary
Measurement Principles for Development Resilience
Substantive Principles
Analytical Principles
1. Poverty Focus Principle
o Population variation guideline
o Multidimensionality and weighting
guideline
2. Intensive Risk Assessment Principle
o Multidimensional -intertemporal
guideline
o Cumulative and interaction guideline
3. Response Heterogeneity Principle
o Household variation guideline
o Institutional capacities guideline
4. Contextual Influences Principle
o Causal impacts guideline
o Multiple contexts guideline
5. State Dependent Dynamics Principle
o Initial states guideline
o Trajectories guideline
6. Stochastic Process Principle
o Stochastic dominance guideline
o Stochastic-Structural guideline
7. Threshold Sensitivity Principle
o Bifurcation threshold guideline
o Dynamic thresholds guideline
8. Cross-Scale Interactions
o Proximal-distal effects guideline
o Nested-effects guideline
IV.
Summary
Resilience is a popular buzzword now. But little precision in its
use, either theoretically, methodologically or empirically.
Aim to help facilitate rigorous, precise use of the concept to
help identify how best to avoid and escape chronic poverty.
This will require advances in theory, measurement and
empirical work in many different contexts and over time.
We start by advancing a conceptual theory of resilience and
measurement principles that derive from that theory.
Much to do in all areas … a massive research agenda, especially
as agencies begin using resilience as a programming principle.
Thank you
Thank you for your time, interest and comments!

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