Welfare Dynamics in Rural Kenya and Madagascar:

1
Welfare Dynamics in Rural Kenya and
Madagascar Preliminary Quantitative Findings
Chris Barrett Cornell University    March 15,
2004 BASIS CRSP Project Annual Team
Meeting Nyeri, Kenya
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 cargo nets.
some people can be trapped in perpetually
(poverty traps due to multiple equilibria)?
implies need for safety nets and cargo
nets.
3
Outline

• Theory and Its Implications
• Economic Mobility and Poverty Dynamics
• Why Economic Immobility?
• Conclusions and Policy Implications

4
Brief theoretical background The slow
convergence possibility
Welfare Dynamics With Unconditional Convergence
Welfare Dynamics With Conditional Convergence
Welfare Dynamics With Multiple Dynamic Equilibria

High group
Chronic poverty region

Transitory poverty region
Low group
Key unique, common path dynamics with a single
stable dynamic equilibrium
Key unique path dynamics with a single stable
dynamic equilibrium for distinct groups or
individuals
Key nonlinear path dynamics with multiple stable
dynamic equilibria and at least one unstable
dynamic equilibrium (threshold effect)
5
Why bother with the theory?

• These three alternative theoretical foundations
  for understanding persistent poverty carry very
  different policy implications.
• - need for/design of safety nets for asset
  protection
• - need for/methods of targeting cargo nets
• - need for patience
• So need to get a firmer handle on
• (i) the nature of persistent poverty.
• (ii) what causes observed poverty traps?
• (iii) how can we move thresholds and/or path
  dynamics?
• Those are the objectives of this project.

6
Economic Mobility and Poverty Dynamics
Ultra-Poverty Transition Matrices As measured
against 0.50/day per capita income poverty line
Kenya rural poverty line 0.53 Madagascar
poverty line 0.43
Poverty deepest where agroecology and markets
least favorable (remote rural areas or less
favored lands)
7
Economic Mobility and Poverty Dynamics
Estimated annual gross (net) poverty exit rates
Estimate using mobility transition probability
PRt mt PR0 Site Gross Net Dirib Gombo
0.0 (0.0) Madzuu 2.2
(1.0) Fianarantsoa 2.3 (0.7) Vakinanka
ratra 2.4 (-4.2) Ngambo 5.2 (4.1)
Considerable persistence of ultra-poverty with
low rates of net exit from poverty
8
Moving beyond headcount measures
Economic Mobility and Poverty Dynamics

• 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.
9
Economic Mobility and Poverty Dynamics
Filtered vs. unfiltered income change regressions
Unfiltered Y Ar eR U eT eM
(2) dY dA r eR Adr deR deT deM
(4) includes measurement error negative
bias Filtered EY Ar U
(3) EdY EdAr AEdr (5) omits
true stochastic component of income positive
bias Regress dY on Y, EdY on EY, or both to
bracket?
10
Economic Mobility and Poverty Dynamics
Site-specific filtered and unfiltered income
change regressions It clearly makes a difference

11
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
• Not at all clear whether the conditional
  convergence or poverty traps hypotheses, or
  both, best explain these data.

12
Why Economic Immobility?

• Explanation 1
• Risk-taking and asset/consumption smoothing

Wealth-dependent risk management among northern
Kenya pastoralists
Consumption smoothing a luxury enjoyed by the
wealthiest third.
13
Why Economic Immobility?

• If income variability increases with wealth,
  so should returns on assets. Indeed, the
  income-herd size relation exhibits increasing
  returns, consistent with risk-based poverty traps

14
Why Economic Immobility?

• Explanation 2
• Barriers to entry into higher-return activities
• - educational attainment and rationing (social
  networks)
• - lack of credit and liquid savings (negligible
  credit access) limited capacity to enter
  higher-return businesses or even to buy livestock
  
• - pastoralist mobility depends on herd size
• expected result is nonlinear asset dynamics,
  with rapid accumulation beyond key thresholds

15
Why Economic Immobility?
The asset data appear consistent in the Kenya
sites with multiple equilibria, but in the
Madagascar sites, low-level conditional
convergence seems to fit better.
Asset Index Dynamics Highland Kenya/Madagascar
Herd Dynamics in Southern Ethiopia
16
Why Economic Immobility?
Same with the income data. Multi-modal income
distribution in Madzuu.
2002 Income Distribution in Madzuu

• Consistent with qualitative evidence
• Importance of non-farm salaried employment,
  incl. to agricultural intensification
• Fragility of non-poor status, esp. to health
  shocks

17
Why Economic Immobility?
But unimodal distribution in Madagascar
reflective more of conditional convergence with
significant geographic grouping.
Implied dynamic real income equilibria Vakinankar
atra 0.61 Fianarantsoa 0.33 Latter
seems a geographic poverty trap
18
Conclusions and Policy Implications
1) Reject the unconditional convergence
hypothesis. 2) Qualitative and quantitative
evidence most consistent with poverty traps
hypothesis in rural Kenya. Need safety nets for
asset protection critical for (i) risk management
and (ii) to prevent collapse into poverty (for
health shocks, natural disasters such as
drought/floods, etc.). 3) 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. 4)
Conditional convergence apparent at community
level in both countries. Cargo nets needed for
asset building among poor and for remote
communities (i.e., indicator and geographic
targeting). 5) Transition technologies, improved
market access, etc. key.
19
Misaotra! Asante! Thank you!