1. Welfare Dynamics in Rural Kenya and Madagascar Christopher B. Barrett, Paswel Marenya, John McPeak, Bart Minten, Festus Murithi, Willis Oluoch- Kosura, Frank Place, Jean Claude Randrianarisoa, Jhon Rasambainarivo and Justine Wangila November 15, 2004 USAID BASIS CRSP Policy Conference Combating Persistent Poverty in Africa Washington, DC

2. Why is poverty so persistent in rural Africa? The design of appropriate strategies to combat persistent poverty depend on its origins. Is poverty something … … all people naturally grow out of in time (unconditional convergence)? … implies laissez-faire /macro focus. … some people grow out of in time (conditional convergence)? … implies need for targeted productivity improvements. … some people can be trapped in perpetually (poverty traps due to multiple equilibria)? … implies need for safety nets and cargo nets.

3. Economic Mobility and Poverty Dynamics Ultra-Poverty Transition Matrices As measured against $0.50/day per capita income poverty line Poor in Subsequent PeriodNon-Poor in Subsequent Period Poor in Initial Period 2000-2002 Dirib Gombo 100.0% 70.8% 1989-2002 Madzuu 60.7% 1997-2002 Fianarantsoa 82.8% 2000-2002 Dirib Gombo 0.0% 11.2% 1989-2002 Madzuu 20.2% 1997-2002 Fianarantsoa 10.3% 2000-2002 Ng’ambo 86.5% 1997-2002 Vakinankaratra 58.5% 2000-2002 Ng’ambo 9.0% 1997-2002 Vakinankaratra 7.4% Non-Poor in Initial Period 2000-2002 Dirib Gombo 0.0% 11.3% 1989-2002 Madzuu 10.1% 1997-2002 Fianarantsoa 6.9% 2000-2002 Dirib Gombo 0.0% 6.8% 1989-2002 Madzuu 9.0% 1997-2002 Fianarantsoa 0.0% 2000-2002 Ng’ambo 0.0% 1997-2002 Vakinankaratra 22.3% 2000-2002 Ng’ambo 4.5% 1997-2002 Vakinankaratra 11.7% Kenya rural poverty line ~ $0.53 Madagascar poverty line ~ $0.43 Poverty deepest and most persistent where agroecology and markets least favorable (“remote rural areas” or “less favored lands”)

4. Moving beyond headcount measures We want to know the directions and magnitudes of welfare change, not just discrete movements relative to an arbitrary poverty line. Annual average percent change in income, by site and resurveying interval Key point: Short panels may exaggerate economic mobility. Much year- on-year change is random. When we look at longer-term transitions, a lot of stasis – look at structural determinants Economic Mobility and Poverty Dynamics

5. Raw data suggests convergence … But structural component suggests multiple equilibria Economic Mobility and Poverty Dynamics Blue (red) dashed lines are structural (stochastic) component of income change

6. Summary of Findings on Economic Mobility and Poverty Dynamics -Considerable persistence of ultra-poverty with low rates of net exit from poverty -Poverty deepest where agroecology and markets least favorable (“remote rural areas” or “less favored lands”) -Stochastic component of income appears substantial -Structural component consistent w/existence of multiple equilibria -Data consistent with both the conditional convergence and poverty traps hypotheses..

7. Why Economic Immobility? Explanation 1: Wealth-differentiated risk mgmt Asset and consumption smoothing among northern Kenya pastoralists … Consumption smoothing a luxury enjoyed by the wealthiest third. Associated with locally increasing income returns to herd size.

8. Why Economic Immobility? Explanation 2: Locally increasing returns Barriers to entry into higher-return activities - educational attainment and social network rationing (skilled off-farm employment) - labor and liquidity constraints and SRI … expected result is nonlinear asset dynamics, with rapid accumulation beyond key thresholds Marginal return to hh labor supply and rice area, Fianarantsoa

9. Asset Dynamics with Multiple Equilibria Asset Index Dynamics Highland Kenya/Madagascar Asset dynamics appear consistent in the Kenya sites with multiple equilibria, but low-level conditional convergence seems to fit the Madagascar sites better. Herd Dynamics Northern Kenya Rangelands

10. Conclusions and Policy Implications 1)Sound policy design and programming requires a clear idea of the causal mechanism behind persistent poverty. 2)No support for the unconditional convergence hypothesis. 3)Conditional convergence apparent at community level in both countries. In Madagascar, the evidence points to geographic poverty traps and the need for exogenous productivity improvements to create path out of poverty. 4)Qual-quant evidence most consistent with poverty traps hypothesis in rural Kenya. Also need multi-dimensional safety nets to protect assets to block pathways into poverty (due to health shocks, natural disasters, etc.). 5)Poverty traps seem to exist due to missing financial markets and (i) excessive risk exposure and/or (ii) significant barriers to entry to remunerative livelihoods.

11. Misaotra! Asante! Thank you!