PARIMA Research Highlights1997-2001

Regional Perspectives

Local Findings

Observations on Enabling Systems

Regional Level Risk Mapping

• Classify and order sources of risk faced by subject populations

• Enhance understanding of nature and variation in risks

• Results reveal variation in risk exposure and risk severity as affected by gender, wealth class, economic activity

Methods

• Six-month data collection period in 1998

• 120 group interviews where respondents were asked to rank sources of risk and mapped by GPS coordinates.

– 49 from Ethiopia and 71 from Kenya

– 59 groups of females and 61 of males

Sample Maps

Some Key Findings

• High local variation in risk exposure• Lack of food and water most common• Poor worry about human disease, conflict,

and crop failure; wealthier worry about resource access and livestock prices.

• Females worry about food and conflict, while males worry about resource access and livestock prices

Implications

• Local priorities for risk management intervention will vary, thus local priority solutions will vary

• Gender and wealth will also affect intervention priorities

Regional Diversification Patterns

• Respondents indicated 16 options to generate income outside of pastoralism.

• Proximity to town (<40 km) affects options• Poor diversify to firewood/charcoal prod.• Middle class women focus on dairy sales• Wealthier males may engage in retail or

wholesale business• Options greater in Kenya than Ethiopia

Local Case Studies

• Cattle dynamics and diversification: Boran

• Diversification and risk: Gugi

• Land use and envir. degradation: Gabbra

• Livestock marketing attitudes: Boran

• Resource use and conflict: Samburu

• Diversification and risk: Samburu

• Education and diversification: Il Chamus

General Findings

• Emergent agro-pastoralism in some areas as per capita livestock holdings drop

• Typically very low level of non-agricultural diversification (few formal links to towns), especially in Ethiopia

• Many populations in very precarious state• Samburu: Cattle raids most common form of

conflict, led to school closures, food insecurity, often ineffective official response

General Findings, cont’d

• High levels of adult illiteracy (>80%)

• Il Chamus: Improved access to education since 1980 had altered the society– 80% of 175 households had educated member

in labor market– 28% of households receive remittances from

wage earners– Education enhances diversification

Borana Cattle Dynamics1980-1999

• Determine scope of livestock losses• Determine effects of stocking rate and

rainfall on cattle mortality• Determine possible effects of improved

marketing and rural finance on risk/return features of system

• Characterize poverty traps, local variation in losses

0

10

20

30

40

50

60

70

80

90

100

1980

-119

81-2

1982

-319

83-4

1984

-5

1985

-619

86-7

1987

-819

88-9

1989

-90

1990

-119

91-2

1992

-3

1993

-419

94-5

1995

-619

96-7

Year (1981-1997)

Cattl

e nu

mbe

r (he

ad)

Mean cattleholding/householdMean mortality/household

Net sales

Findings

• Steady decline in per capita inventory • Loss of US 45 million for 7,000 households from

1980 to 1997; extrapolate to US 300 million • High local variation in losses• Poverty traps: <6 head likely to drop out in <10 yr• Cattle plus safe banking and improved marketing

(to cut death loss by 33%) would reduce risk for nearly the entire spectrum of returns.

0

200

400

600

800

1000

1200

Year

Rai

nfal

l (in

mm

) Herd size

Herd size

What Drives Cattle Losses?

• Losses of 37% in 1983-85 (major drought)• Losses of 42% in 1991-3 (minor dry year)• Losses of 62% in 1998-9 (major drought)• Stocking rate appears to be underlying cause

of crash; higher stocking rate plus drier year = larger crash

• Next crash most likely around 2004/05/06??

Enabling Systems

• Public services delivery

• Tenurial regimes

• Rural finance

• Marketing

Public Services Delivery

• Pastoralists marginalized in both countries• Pastoral populations have grown• Settlements have grown due to destitute

pastoralists and food-relief economy• Pastoral policy gaps in both countries• Education and health delivery poor—

decline in Kenya, but more commitment in Ethiopia?

Tenurial Regimes

• Danger of de facto privatization of formerly open-access resources such as forage and water

• Expansion of cultivation, annexation of fodder reserves, etc., can occupy some sites formerly used for dry season grazing and may limit traditional mobility patterns

Rural Finance

• Many pastoralists aware of formal banking services, but use appears sharply limited by poor physical access, lack of trust, and due banks not considering pastoralists as clientele.

• Potential demand for community-based financial systems may exist

• Some pastoral cultures may be conducive to community-based financial systems.

Marketing

• Our study area is a good model for examination of marketing issues

• Annual off-take rates may vary from 4-7% (Kenya) to 1-3% (Ethiopia)

• Analysis of secondary price data (n=63,000 transactions) for northern Kenya (Marsabit, Moyale) and Nairobi terminal markets for 1995-8

Some Findings

• Producer price risk is high• Sharp seasonal price swings that vary with

location and livestock species• Prices in northern Kenya often markedly vary with

Nairobi prices, contributing risk to trader profit margins as well.

• View that livestock prices rise when range conditions are favorable

• Quarantine contributes to market risks

0

5,000

10,000

15,000

20,000 K

Sh

93/11 94/1 94/6 94/12 96/4 96/6 97/1

Nairobi-Marsabit Marketing MarginsAdult Male Cattle,1993-97 (broken)

Some Development Implications

• Inter- and intra-community variation in risk exposure, and hence risk management interventions, can be local and also specific to gender/wealth class

• Opportunities for income diversification increase closer to towns, again interventions could be specific to location/gender/wealth class

Implications, cont’d.

• In some cases, access to education can lead to significant out-migration that contributes to household income diversification over longer term

• In some cases, losses of livestock wealth may be extremely high, and could be mitigated by improvements in markets and secure rural financial systems

Implications, cont’d.

• Evidence that livestock losses in drought-stricken areas are highly variable among localities and households points to a need for better understanding of local responses and locally targeted interventions

• In some cases, stocking rate dynamics may provide a locally based, and long-range predictor of drought-induced livestock crashes