Poverty Traps, Resilience and
Resource Dynamics
Among the Extreme Rural Poor
Chris Barrett
Cornell University
Seminar at James Cook University (Townsville, QLD Australia)
July 4, 2013
Motivation
Reducing poverty/hunger & conserving scarce
natural resources (biodiversity, water, forest,
etc.) are global challenges of the highest order.
These challenges are intrinsically linked:
Most (esp. extreme chronic) poverty/hunger
occurs in rural areas dependent on ag and s.t.
infectious disease, w/ bidirectional causality
and mutual causation by broader forces.
Yet most policy/research focuses on just one
or the other of these at a time.
The Economics of
Poverty Traps
Poverty trap = “any self-reinforcing mechanism which
causes poverty to persist” (Azariadis & Stachurski).
Reinforcing feedback:
Low productivity causes poverty.
Poverty causes hunger and
natural resource degradation.
But hunger and degraded
natural resources also cause
poverty and low productivity.
Hence the vicious cycle of
poverty traps, hunger and
natural resources degradation.
The Economics of
Poverty Traps
There are 3 distinct types of poverty trap dynamics:
(i) unique dynamic equilibrium systems (convergence
on misery) – distressing but empirically uninteresting
(ii) conditional convergence systems (unique equilibria
for distinct groups, only some below a poverty line)
(iii) multiple equilibrium systems (initial condition
guides resulting path dynamics)
(Carter and Barrett J. Dev’t Studies 2006; Barrett and Carter J. Dev’t Studies 2013)
The Economics of
Poverty Traps
Well-beingt+1
Case (i): Welfare Dynamics With
Unique Stable Dynamic Equilibrium:
Unconditional Convergence
Pov.
line
W2
W2
Well-beingt
Implies unique, common path dynamics. In expectation, no one
escapes poverty. (Empirical examples: rural highland Ethiopia)
The Economics of
Poverty Traps
Well-beingt+1
Case (ii): Welfare Dynamics With
Distinct Stable Dynamic Equilibrium:
Conditional Convergence High group
W2
Low group
Pov.
line
W2
Well-beingt
Implies unique path dynamics with a single stable dynamic equilibrium that
differs among distinct groups (Ex: SC/ST in rural India, social groups/rules)
Example
The importance of social institutional arrangements
“A tale of two widows”
Would the widower’s dynamic be the
same as the widow’s? Seems unlikely.
The Economics of
Poverty Traps
Well-beingt+1
Case (iii): Welfare Dynamics With
Multiple Stable Dynamic Equilibria
Pov.
line
Chronic
poverty
region
Transitory
poverty
region
Non-poor
region
`
Well-beingt
Implies nonlinear path dynamics with at least one unstable dynamic
equilibrium/threshold effect/tipping point (Ex: East African pastoralists;
infectious disease-poverty interactions; nutritional poverty traps; soils)
Example
In southern Ethiopia/ northern Kenya, pastoralists
face nonlinear, bifurcated herd/wealth dynamics
(Lybbert et al. 2004 Econ J.):
Those who maintain a herd remain mobile on a resilient
landscape, while those who lose their herd collapse into
destitution on a degrading local landscape.
Another example
Why such persistence?
Soil degradation poverty traps in Kenya
Marginal returns to fertilizer application low on degraded
soils; and poorest farmers cultivate the most degraded soils.
So the poor optimally don’t apply fertilizer, but stay poor.
Soil degradation also feeds a striga weed problem ($7bn/yr in
crop losses), mycotoxin contamination of >25% of food, and
serious micronutrient deficiencies (e.g., Fe, Zn, I, Se).
Above red line: fertilizer profitable
Value of maize
from 1 kg of
nitrogen
Cost of 1kg
nitrogen
Kenyan rural
poverty line
Below red line: fertilizer unprofitable
(Marenya and Barrett, Am.J. Agr.Econ. 2009; Stephens et al., Food Security 2012).
The result is pockets of productive, seemingly
sustainable agro-ecosystems punctuated by
neighboring economic and ecological problems
Poverty Traps and
Resilience
“Resilience” has rapidly become a ubiquitous
buzzword, but ill-defined concept within the
development and humanitarian communities
Poverty Traps and
Resilience
Why development and humanitarian communities’
current fascination with “resilience”?
1) Risk perceived increasing in both frequency and intensity
2) Recurring crises lay bare the longstanding difficulty of
reconciling humanitarian response to disasters with
longer-term development efforts.
3) Increasingly recognize interdependence of biophysical and
socioeconomic systems.. Tap ecological work on resilience
But we lack a theory-measurement-and-evidence-based
understanding of what resilience is with respect to poverty
and hunger, how to measure it, and how to effectively
promote it so as to reduce chronic poverty and hunger.
Big opportunity for ecologists - economists
Poverty Traps and
Resilience
Existing economic theories of
poverty traps closely parallel the
ecological literature on resilience
and resistance:
- similar ODE-based mathematics of
dynamical systems.
Considerable potential to
thoughtfully adapt ecological
thinking on resilience and
resistance to fit the current
development/humanitarian
community’s fascination
Poverty Traps and
Resilience
Humanitarian emergency zone
Chronic
poverty zone
Non-poor zone
Death
Key features
o Initial conditions
drive dynamics
oTransitory shocks can
have permanent effects
o Humanitarian
imperative (avoid HEZ)
merged w/development
ambition (reach NPZ)
o Critical thresholds
w/bifurcating dynamics
o Risk endogenous to
system state
oCondt’l transition distns
reflect both natural and
socioecon env’t factors
Future capabilities
Development resilience represents the likelihood over time of a person, household
or other unit being non-poor in the face of various stressors and in the wake of myriad
shocks. If and only if that likelihood is and remains high, then the unit is resilient.
Death
Current capabilities
(Barrett and Constas 2013, submitted)
Example
In southern Ethiopia, herd dynamics change with drought
risk (rainfall <250 mm/year). Halving current risk would
enhance resilience and eliminate apparent poverty trap.
Doubling drought risk would eliminate high-level
equilibiurm and yield unique, poor eqln in expectation.
60
Expected herd size 10 years ahead
Simulated using
parametric rainfallconditional herd growth
function estimates and
mean-preserving changes
of rainfall variance,
defined by π=
prob(rainfall<250 mm/yr)
(Barrett and Santos 2013
submitted)
Prob. = 0.03
50
Prob. = 0.06
40
30
Prob. = 0.12
20
10
0
0
10
20
30
Initial herd size
40
50
60
Coupled Dynamics
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,
disease reproduction depends on household incomes, soil
nutrients depend on fertilizer/manure use, etc.)
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.
Coupled 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
Policy Implications
Poverty traps imply a clear compulsion to intervene … only
reinforced by close coupling to environmental state
But how to intervene is much less clear because alternative
mechanisms imply different responses:
e.g., DeSoto vs. Sachs.
Most likely, face “fractal poverty traps” (Barrett and Swallow
WD 2006) – interlinked processes across different
scales, with micro-level market imperfections
reinforcing (and reinforced by) meso-level information
problems and macro-level institutional failures.
Implication: high returns to detailed empirical study to
identify proximate causes in a given setting.
Policy Implications
Example: In east African pastoralist setting, extensive
multi-year empirical research identified drought-related
herd loss with limited restocking capacity as the main
source of poverty traps.
Response: Index-based livestock insurance
(Chantarat et al., J. Risk & Insurance 2013)
(http://blip.tv/file/3757148)
Worked as planned in 2011. Scaled out to southern
Ethiopia in 2012 and scaling to other areas of northern
Kenya this year.
Summary
The economics of poverty traps links naturally to much
ecological research, especially that concerned with dynamics,
stability and resilience.
A prime opportunity for ecologists and economists to learn
from one another:
- Help identify how best to reduce chronic poverty and to
safeguard ecosystems vulnerable to anthropogenic disruptions.
This will require advances in theory, measurement, impact
evaluation and outreach in different contexts and over time.
Thank you for your time and interest!