Presentation is loading. Please wait.

Presentation is loading. Please wait.

Poverty Traps, Resilience and Resource Dynamics Among the Extreme Rural Poor Chris Barrett Cornell University Seminar at James Cook University (Townsville,

Similar presentations

Presentation on theme: "Poverty Traps, Resilience and Resource Dynamics Among the Extreme Rural Poor Chris Barrett Cornell University Seminar at James Cook University (Townsville,"— Presentation transcript:

1 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

2 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. Motivation

3 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 Poverty trap = “any self-reinforcing mechanism which causes poverty to persist” (Azariadis & Stachurski).

4 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)

5 Pov. line W2W2 W2W2 Well-being t+1 Well-being t Case (i): Welfare Dynamics With Unique Stable Dynamic Equilibrium: Unconditional Convergence Implies unique, common path dynamics. In expectation, no one escapes poverty. (Empirical examples: rural highland Ethiopia) The Economics of Poverty Traps

6 Pov. line W2W2 W2W2 Low group High group Implies unique path dynamics with a single stable dynamic equilibrium that differs among distinct groups (Ex: SC/ST in rural India, social groups/rules) The Economics of Poverty Traps Case (ii): Welfare Dynamics With Distinct Stable Dynamic Equilibrium: Conditional Convergence Well-being t Well-being t+1

7 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.

8 Pov. line Chronic poverty region ` Transitory poverty region 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) The Economics of Poverty Traps Case (iii): Welfare Dynamics With Multiple Stable Dynamic Equilibria Non-poor region Well-being t Well-being t+1

9 Example In southern Ethiopia/ northern Kenya, pastoralists face nonlinear, bifurcated herd/wealth dynamics (Lybbert et al. 2004 Econ J.):

10 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.

11 Why such persistence? Another example 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). Cost of 1kg nitrogen Value of maize from 1 kg of nitrogen Above red line: fertilizer profitable Below red line: fertilizer unprofitable (Marenya and Barrett, Am.J. Agr.Econ. 2009; Stephens et al., Food Security 2012). Kenyan rural poverty line

12 The result is pockets of productive, seemingly sustainable agro-ecosystems punctuated by neighboring economic and ecological problems

13 “Resilience” has rapidly become a ubiquitous buzzword, but ill-defined concept within the development and humanitarian communities Poverty Traps and Resilience

14 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

15 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

16 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. Key features o Initial conditions drive dynamics o Transitory 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 o Condt’l transition distns reflect both natural and socioecon env’t factors ( Barrett and Constas 2013, submitted) Poverty Traps and Resilience

17 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. Simulated using parametric rainfall- conditional herd growth function estimates and mean-preserving changes of rainfall variance, defined by π= prob(rainfall<250 mm/yr) (Barrett and Santos 2013 submitted)

18 If we represent the preceding conditional transitions as: W t+1 =g(W t |R t,ε t ) 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.) R t+1 =h(R t |W t,ε t ) 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

19 Coupled human and natural systems dynamics Note:- Ecological resilience links to human resilience through reciprocal causality in coupled human/natural dynamics - Many candidate relationships make prediction difficult at best Coupled Dynamics

20 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.

21 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 insuranceIndex-based livestock insurance (Chantarat et al., J. Risk & Insurance 2013) ( Worked as planned in 2011. Scaled out to southern Ethiopia in 2012 and scaling to other areas of northern Kenya this year.

22 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. Summary

23 Thank you for your time and interest!

Download ppt "Poverty Traps, Resilience and Resource Dynamics Among the Extreme Rural Poor Chris Barrett Cornell University Seminar at James Cook University (Townsville,"

Similar presentations

Ads by Google