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Research Activities Under the Project

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Title: Research Activities Under the Project


1
  • Research Activities Under the Project
  • Rural Markets, Natural Capital and Dynamic
    Poverty Traps in East Africa
  • Presentation to BASIS CRSP Technical Committee
  • October 11, 2002
  • College Park, MD
  • Chris Barrett, Cornell University
  • and
  • Festus Murithi, Kenya Agricultural Research
    Institute
  • on behalf of the project team

2
Contemporary Poverty Reduction Strategies in East
Africa
  • The PRSP process is focusing government, donor
    and civil society efforts on poverty persistence.
  • Efforts particularly directed at chronic poverty
    and vulnerability in rural areas. Thus, PRSP in
    Kenya based heavily on KRDS (Kenya Rural
    Development Strategy) and new Malagasy government
    has made rural poverty reduction is top priority.
  • Soils degradation and market access widely viewed
    as most important limiting factors in improving
    agricultural productivity and rural incomes

3
Contemporary Poverty Reduction Strategies in East
Africa
  • Effective, policy-relevant research must
    therefore target the core question of poverty
    persistence in rural areas, with special
    attention to market access and soils
    degradation/rehabilitation.
  • Our BASIS CRSP project aims to integrate
    research, training and outreach activities to
    address this need.

4
Toward A Theory of Poverty Traps
  • Existing, largely macro-level theories of poverty
    traps (new growth theory)
  • The multidisciplinary literatures on livelihoods
    and on technology adoption point toward an
    alternative approach that seems especially
    well-suited to rural Africa and our cases in
    Kenya and Madagascar.

5
Toward A Theory of Poverty Traps
  • Opportunity set mappings/ density plots
  • (conditional on quality-adjusted productive
    assets)

Labor
T3
T4
T2
T1
Land
6
Toward A Theory of Poverty Traps
  • Activity choice and productivity/income
    differences

Output/Income
T4
T3
T2
T1
Ex Ante Assets
7
Toward A Theory of Poverty Traps
  • Implied wealth dynamics distinct classes emerge

Dynamic eqln
Wealthti
Non-Poor
T4
W3
Chronically Vulnerable
Chronically Poor
T3
T2
W2
T1
W1
Wealtht
Poverty line
8
Implied causality of poverty traps
  • Four key sources of poverty traps
  • Meager stocks of productive assets
  • Rudimentary production/processing technologies
    and nonfarm opportunities
  • Weak markets and nonmarket institutions
  • Risk exposure and limited risk management
  • Research design implication Need household-level
    data to establish asset/income/productivity
    dynamics, measures of shocks, livelihood strategy
    choice, and market access

9
Empirical Tasks
  • Project objective 1
  • Describe welfare and resource dynamics
    empirically
  • What is happening over time to the poor? Who
    climbs out of poverty? Who is trapped in poverty?
  • What is happening to the natural resource base on
    which the poor in particular depend for rural
    livelihoods?

10
Empirical Tasks
  • Project objective 2
  • Test four hypotheses about poverty traps in East
    Africa
  • (i) High return production strategies (e.g.,
    livestock) exhibit increasing returns at low
    production levels, with a minimum efficient scale
    of production beyond the means of the poor
    lacking adequate financing.
  • (ii) Poor market access creates significant
    fixed costs to market participation, giving
    larger producers net price advantages and
    inducing poorer producers in areas of weak market
    access to opt out of markets in favor of
    low-return self-sufficiency.

11
Empirical Tasks
  • Project objective 2 (continued)
  • (iii) Poorer households lacking access to capital
    to finance productive investments may be unable
    to undertake lumpy investments, regardless of
    their expected returns
  • (iv) Risk and subsistence constraints impede
    long-term investment for asset accumulation and
    productivity growth among poorer, more risk
    averse households.

12
Empirical Tasks
  • Project objective 3
  • Use dynamic process modeling methods to replicate
    observed patterns and then to explore how the
    existence of poverty traps conditions natural
    resource conservation, particularly soil quality
    dynamics that affect future agricultural and
    labor productivity and food security.       
  • The soil said to man, take good care of me,
    else when I get hold of you I wont let your soul
    go free.
  • -Kipsigis proverb

13
Empirical Tasks
  • Project objective 4
  • Through bioeconomic model simulations and both
    qualitative and quantitative empirical work,
    identify and document effective policies,
    technologies and programs to combat dynamic
    poverty traps in this setting.
  • Examples
  • - new agroforestry technologies
  • - restocking herds after droughts
  • - contract farming schemes that address multiple
  • factor market failures

14
Preliminary evidence
  • Objective 1 Describing welfare/resource dynamics
  • Examples herd dynamics in northern Kenya
  • land transitions in western Kenya

15
Preliminary evidence
  • Objective 2 Explaining observed poverty traps
  • Increasing returns and minimum efficient scales
    of adoption
  • i) SRI adoption in Madagascar
  • ii) Education and nonfarm
  • earnings in C/W Kenya
  • iii) Herd mobility in N Kenya

16
Preliminary evidence
  • Objective 2 Explaining observed poverty traps
  • Market access
  • Market access comparisons from
  • - central-western Kenya
  • - south-central highlands Madagascar
  • (education, nonfarm, dairy cattle,
  • market access, vertical integration
  • of input/output marketing systems)

17
Preliminary evidence
  • Objective 2 Explaining observed poverty traps
  • Access to finance
  • SRI adoption in Madagascar
  • Education in rural Kenya
  • (N/W Kenya in particular)
  • Microfinance in northern Kenya
  • Irrigation investments

18
Preliminary evidence
  • Objective 3 Bioeconomic modeling tool
  • CLASSES model prototype near completion. Short
    course begun in Kenya in June and will complete
    this month in Ithaca.
  • NSF Biocomplexity project will enrich and extend
    CLASSES significantly in the Kenya sites

19
Thank you!We welcome your comments and
suggestions on this project
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