The Role of Risk Management in Pastoral Policy Evaluation and Poverty Reduction
Presented byLeseeto Saidimu
16 August 2011
SupervisorsProf. Sally Brailsford (School of Management)
Prof. Terry Dawson (Dundee University)
2
24% of national milk production.
Over 90% Livelihood source for 1/3 for
national population.
Red meat comprise of 80% meat consumption
out of which 67% produced in ASAL
Supports tourism sector which
contributes 11% of the GDP
Role
of
Past
ora
l R
an
gela
nd
s
2
Agriculture forms 21% of GDP in Kenya and supports 75% of national population.
Livestock contributes 50% to Agriculture
Indigenous livestock comprise of 75%
Over 80% Of indigenous are
Located in ASAL
National Economy
Arid and Semi-Arid Land (ASAL) accounts for 80% of Kenyan land mass.
It is home to approximately:
•A third of human population,
•70% of national livestock,
•75% of Wildlife population.ASAL is exposed to
high frequency, high impact climate
variability
Poverty
Trap
ASAL
Primary Pastoral Economy
The Role of Pastoral Economy
The Role of Risk Management
Vulnerability Measurements
3
Vulnerability Framework
44
Drought as Asset driver in Pastoral SystemYear Impact Inter-drought
durationLivestock mortality & Area of
StudySource
1979-1980 Severe 4 (1974/6) 50-70%,Turkana district63% Cattle, 45% camels & 55% sheep and goats
Ellis and Swift (1988)McCabe (1978;2004)
1984 Severe 4 years 50% in Baringo district56%, Ethiopia (East African Country69% Kenya
Homewood & Lewis (1987);Angassa & Oba (2007); Oba (2001).
1987-1988 Mild 4 Years None established
1991-1992 Severe 4 years 50-60%,Garissa,Northern Kenya86% Northern Kenya
Angassa & Oba (2007);De Waal (1997);Oba(2001).
1997/8 Mild 5 years 40% Samburu, ILRI data, 2009.
1999-2000 Severe 2 years 50% cattle & 20% goats, Samburu district53%, Ethiopia (E.A Country)
Angassa & Oba (2007);McPeak & Little (2005).
5
Sources of Pastoral RisksSources of Pastoral Risks Proactive StrategiesProactive Strategies
Risk EventRisk
EventReactive
StrategiesReactive
StrategiesConsequences of
Pastoral RisksConsequences of
Pastoral Risks
Climate VariabilityClimate Variability
Human PopulationHuman Population
Land DegradationLand Degradation
Market VariabilityMarket Variability
Biodiversity ConservationBiodiversity
Conservation
Pastoral Risks (Threats, Opportunities
and Uncertainties)
Pastoral Risks (Threats, Opportunities
and Uncertainties)
1. Livestock losses2. Food insecurity3. School drop-outs4. Human-wildlife conflicts5. Increased poverty6. Malnutrition7. Reduced land productivity
1. Livestock losses2. Food insecurity3. School drop-outs4. Human-wildlife conflicts5. Increased poverty6. Malnutrition7. Reduced land productivity
Risk Management Framework
Maximize on opportunities and minimize frequency of
threats
Maximize on opportunities and minimize impact of
threats
The framework is adopted from Crerand (2005)
6
Literature Review Map-Summary
Drivers of market and livestock prices
1.Lybbert et al. (2004)2.Barrett & Luseno (2004)3.Fafchamps & Gavian (1996)4.Turner & Williams (2002)5.Oba,G.(2001)
Pastoral social setting and infrastructure
1.Aklilu and Wekesa (2002)2.Campbell D. (1999)3.Fratkin,E. (2004)4.Lesorogol,C. (2009)5.Carter,M. & Barrett C.(2006)
Drivers of rangeland productivity
1.Mude,A. et al (2009)2.Tucker, C. et al. (2005)3.Wittemyer G.B. et al. (2007)4.Abule, E. et al. (2007)5.Snelder,D Bryan (1995)
Research GapResearch Gap
77
Data
Research Dimension
Early Warning System (EWS) indicator Variables
Natural capital Environmental indicators Rainfall and NDVIPhysical capital Economic indicators Food and livestock prices
Financial capital
Livelihoods indicators
Livestock ownership, Lactation rates, Mortality rates
Human capital Human nutritional status & Livelihood sources
Social capitalWealth status
Mitigation strategies Relief supply, copying strategies & migration
• Source: Arid Lands Resource Management Project (ALRMP-II) under the office of the prime minister.
• Period: Jan 2006-March 2010 • n=7,650 households
88
Results: Pastoral Condition (Droughts)
Observations:
1. Three major droughts in the past 10 years,
2. 1999-2001 recorded prolonged negative pasture conditions,
3. The drought years 2006 and 2009 arose from deficiency in short rains (December rain) of the years 2005 and 2008 subsequently.
3-yr drought 2-yr drought 2-yr drought
3-year interval 2-year interval
9
Wellbeing Measure Comparable Target
Non-Drought Year Averages
Drought Year Averages
Financial Capital (Total Livestock Unit) ASAL TLU 10-16 TLU=9.52<Min TLU=8.04<Min
Human Capital (Malnutrition rate) WHO 16.5% MUAC=16.9%>Max MUAC=24%>Max
Physical Capital (Meat-Cereal Price Ratio) Equilibrium 100% MCPR=128%>E.C MCPR=88.9%<E.C
Natural Capital (Rainfall mm) Equilibrium 33 pm Rain=38.8mm>E.C Rain=19.3mm<E.C
Social Capital (Poverty Percentage) National Level 50% Poor=67.9%>Nat. Avg. Poor=73%>Nat. Avg.
Comparison of wellbeing risk indicators between normal and drought conditions.
Observation: There is 10-50% change on the indicators from normal condition during droughts.
Vulnerability Risk Indicators
1010
Model Estimation
k
itiitkit xy 0
ity
itx
ij
i
Where Represents dependent variable for regions i, and time t.Is observed variables (independent variables)
unobserved error term
Is the subject specific residual and represents unmeasured individual factors which affects y (unknown intercept for each entity.
NB: “If unobserved variable does not change over time, then any changes in the dependent variable must be due to influences other than these fixed characteristics” (Stock and Watson, 2003, p.289-290).
Is the coefficient for the independent variables (slopes)Intercept (Model constant)0
11
Forms of Pastoral Capitals
Financial (H2) Human (H3) Physical (H4) Social (H1) Natural
Dependent VariablesTotal Livestock
Units (TLU)
Malnutrition
(MUAC %age)Market Volatility
(MCP Ratio)Poor Households
(POOR)Pasture Condition
(NDVI)
Birth Rates-Cattle 0.004 (+) 0.267***(-) 0.869*** (+)
Small Stock 0.142***(+) 0.136 (-) 0.551 (+)
Mortality Rates- Cattle 0.062* (-) 0.297***(+) 2.057*** (-)
Small Stock 0.010 (-)
Camels 0.433 (-)
Sales Rates-Cattle 0.323 (-) 2.375*** (+) 12.035*** (-)
Small Stock 0.477***(-) 1.327*** (-) 2.919 (-)
Pasture Condition-NDVI Lag 0 5.265* (-) 36.678***(-) 133.561***(+) 9.349 (+)
NDVI-Lag 3 4.598 (+) 43.446***(-) 164.248***(+) 7.802 (-)
NDVI-Lag 6 9.262***(+) 18.470** (-) 115.326***(+) 35.677*** (-)
Livestock Asset Ownership-TLU 1.454***(-) 2.972** (+) 2.233*** (-)
Market Condition-MCP Ratio 0.108***(+) 0.014 (+)
Food Insecurity-MUAC %age 2.141*** (+) 0.194* (+)
Mitigation Strategies-Relief Supply 0.053***(+) 0.295*** (-)
Rainfall Variability- Rain Lag 0 0.0005*** (+)
Rain Lag 1 0.0007*** (+)
Rain Lag 2 0.0002** (+)
Rain Lag 3 0.0001 (-)
Constant 7.898 (+) 56.452 (+) 52.639 (-) 96.644 (+) 0.301 (+)
R-Squared 0.671 0.785 0.821 0.712 0.645
Pastoral Risks Decomposition
1212
Impact
Status
Change
Climate Wellbeing
Forms of Pastoral Capital
Financial Human Physical Natural Social
Indicator Variables
Integrated Impact Response strategies by
private and public sectors
Modelling and Management Mindset
ALRMP Data Analysis
System Dynamics Modelling
13
Baseline Simulation Results
Percentage of children at risk of malnutrition
Test for data representationThe actual data Versus simulation runs
Scenario Wellbeing
Livestock mortalities Financial-TLU
Stable market prices Physical-MCP
Destocking/Restocking Financial-TLU
Food supplements Human-MUAC
Education Human/Financial
Reclamations/irrigation Natural-Rangeland
Disease control Financial-TLU
Possible Mitigation Strategies
14
Conclusion• Drought is a threat magnifier and source of pastoral poverty.
• Pastoral condition is the most significant covariate in ASAL system but highly driven by climate.
• Livestock asset ownership (TLU) is declining and is likely to increase poverty and malnutrition.
• Government is expected to spend more funds in supporting the poor and malnourished.
• Risk management therefore bridges the gap between ASAL resource management and poverty reduction. This is achieved through SD model development and scenario runs.
Top Related