Upload
reece-moon
View
34
Download
1
Tags:
Embed Size (px)
DESCRIPTION
APPLICATIONS OF SYSTEM DYNAMICS TO MODELING POVERTY TRAPS AND LAND DEGRADATION IN EAST AFRICA. Investigators C. BARRETT - CORNELL A. PELL- CORNELL B. OKUMU- CORNELL F. MURITHI - KARI F. PLACE - ICRAF - PowerPoint PPT Presentation
Citation preview
APPLICATIONS OF SYSTEM DYNAMICS TO APPLICATIONS OF SYSTEM DYNAMICS TO MODELING POVERTY TRAPS AND LAND MODELING POVERTY TRAPS AND LAND
DEGRADATION IN EAST AFRICADEGRADATION IN EAST AFRICA
InvestigatorsInvestigatorsC. BARRETT C. BARRETT - CORNELL- CORNELL
A. PELLA. PELL - CORNELL- CORNELL
B. OKUMUB. OKUMU - CORNELL- CORNELL
F. MURITHI F. MURITHI - KARI - KARI
F. PLACE F. PLACE - ICRAF- ICRAF
J. RASAMBAINARIVO J. RASAMBAINARIVO - FOFIFA- FOFIFA
Problem StatementProblem StatementAgrarian poverty may create incentives to follow land and
livestock management practices which further reduce agricultural labor productivity by depleting natural capital:
resource degradation poverty traps (RDPTs).
Key Sources of RDPTs (threshold effects):
- missing/imperfect factor, product and asset markets - biologically-induced non-convex technologies
Study ObjectivesStudy Objectives
Examine empirically how biological processes and market conditions interact to create or extend dynamic poverty traps
Simulate policy experiments that might sustainably reduce poverty and/or improve resource management
Build capacity with local partners to carry out such analysis and simulations locally
Research DesignResearch DesignM
AR
KE
T A
CC
ES
S
Drier
Wor
se B
ette
r
Wetter
1. North Central Kenya (Baringo)
AGRO-ECOLOGICAL CONDITIONS
1.Central highlands, Kenya (Embu)
2. Central highlands, Madagascar (Vakinankaratra)
1. Northern Kenya(Marsabit)
1. Western Kenya (Siaya /Vihiga)
2. Southern highlands, Madagascar (Fianarantsoa)
SOIL
-Biology (microbes, micro-fauna and flora)-Chemistry (N, P, K) - Physics (structure, texture, moisture content)
HUMAN
LIVESTOCK
PLANT BIOMASS- Natural vegetation- crops
MilkmeattractionSavingsManure
Herd size + specieshusbandry,feedingpractices
Foragefeed
crops, green manure
cropproductionpracticesland usepatterns
MODEL FRAMEWORKMODEL FRAMEWORK
Soil/waterconservation, fertilizer, brown & green manure application
ENVIRONMENTAL & POLICY FACTORS - rainfall, - temperature - slope- prices - land tenure - land use restrictions
State or decision variables
Excreta,litter,
- Soil cover- Soil organic matter (SOM)
-Soil nutrients,
- moisture
Geographicaleffects
Study MethodologyStudy Methodology SD approach is chosen because it is consistent with
traditional economic approaches towards modeling dynamic systems i.e. use of ordinary differential or difference equations
It employs a very simplified structure of feedback and causal loops that are either balancing (stable equilibrium) or reinforcing (unstable equilibrium)
It is possible to integrate or nest micro-economic models in the SD framework
Study Methodology... Cont’dStudy Methodology... Cont’d SD yields numerical estimates of the paths taken by
key policy variables over time and space as well as any equilibrium to which they might converge (diverge)
Simulate policy experiments that might sustainably reduce poverty and/or improve resource management
Uses both quantitative and qualitative information
Graph for rainfall ratio
2
1.5
1
0.5
0
1977 1981 1985 1989 1993 1997
Time (Year)
Rainfall ratio : Normalized rainfall for Embu 1977-1999
Mean: 1270 Max: 1885 Min: 499
Simulation of ICRAF/KARI technologies on Soil depth levels
100
95
90
85
801977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999
Time (Year)
Soil depth : without technology interventions cm
Soil depth : with technology interventions cm
Sensitivity analysis of soil depth Sensitivity analysis of soil depth declinedecline
50% 75% 95% 100%
Soil depth100
95
90
85
801977 1983 1988 1994 1999
Time (Year)
Policy RelevancePolicy Relevance Models such as this one could be used to simulate
policy experiments, allowing for differences according to market and agroecological conditions. For example- What are the consequences of improving market
access on poverty and soils over time?
- How might biological interventions (e.g., liming soils, extending improved fallows) change labor allocation and income trajectories?
- What targeting mechanisms and transfer forms (e.g., livestock species) are likely to prove most effective in sustainably reducing agrarian poverty?