CONCLUSIONES

Northern Kenya’s climate is generally characterized by bimodal rainfall that disaggregates the agricultural calendar in this region into two seasons, each with a pair of rainy and dry periods. A year starts with long rain (falling March-May)-long dry (June-September) season, which we henceforth refer to as LRLD, and follows by short rain (falling October-December)-short dry (January-February) season, hereafter referred to as SRSD. Pastoralists rely on both rains for water and pasture for their animals. Pastoralism in the arid and semi-arid areas of northern Kenya is nomadic in nature, where herders commonly adapt to spatiotemporal variability in forage and water availability through herd migration.

Livestock represent the key source of livelihood across most households in this environment, but face considerable mortality risk largely related to drought, rendering pastoral households vulnerable to herd mortality shocks. As part of the IBLI pilot

Survey Sites in Marsabit, Northern Kenya

Survey Sites in Marsabit, Northern Kenya

Survey Sites in Marsabit, Northern Kenya

Chalbi

Laisamis

Survey Sites in Marsabit, Northern Kenya

Survey Sites in Marsabit, Northern Kenya

Survey Sites in Marsabit, Northern Kenya

Chalbi

Laisamis

Chalbi

Laisamis

project in Marsabit District in northern Kenya, this study investigates the performance of IBLI in four locations in the district: Dirib Gombo, Logologo, Kargi and North Horr. These four study locations marked in Figure 5.1

These four locations are the overlapping survey locations of the two complementary household-level data sets. First is the household-level panel data collected quarterly by the USAID Global Livestock Collaborative Research Support Program (GL-CRSP) “Improving Pastoral Risk Management on East African Rangelands” (PARIMA) in these locations from 2000-2002 (Barrett et al. 2008). Thirty households were randomly selected in each of the survey location and the household heads were interviewed. In each location, a baseline survey was conducted in March 2000. Repeated surveys were conducted quarterly for an additional nine periods through June 2002. Data on household’s seasonal livestock losses, mortality, growth and offtake were then reconstructed to match the agricultural calendar by combining two quarters into the season system. And so these main variables are available for four seasons: LRLD 2000, SRSD 2000, LRLD 2001 and SRSD 2001, which also cover a major drought that affected much of the areas in 2000.

We complement the current set with the household surveys fielded specifically in these locations during May-August 2008. The main objectives of this survey were to gain insights of pastoralists risk experience, their historical herd dynamics, their risk appetite, their perceptions of climactic variability and also to gather household level information that is likely to be correlated to these variables.48 The sample was stratified by wealth class: low, medium and high, based on owned herd size classified by community standards.49 For the sample size of 42 households in each location, approximately 14 households were randomly drawn from these location-wealth strata. The survey was conducted in June-July 2008, though many key questions gathered

48 _{In addition we aimed to introduce potential clients to the concept of IBLI, and to investigate patterns}

and determinants of willingness to pay for IBLI. Chantarat et al. 2009c describes this data set in more detail).

49 _{Wealth classification standards vary by location. The boundaries in TLU for (L,M,H) wealth class for}

the five locations are Dirib( <3,3-8,>8), Kargi(<15, 15-25,>25), Karare(<15,15-30,>30), Logologo( <10,10-25,>25) and North Horr( <15,15-35,>35).

recalled information over the season for the preceding year. This allows us to construct the main variables on seasonal mortality, growth and offtake for two seasons: LRLD 2007 and SRSD 2007. This data set also includes pastoralist’s risk perception estimates elicited from a simple 50-50 lottery game with real monetary payoff described in Section 5.5.

Table 5.1 summarizes the key characteristics50 of the pastoral economy in the four study locations representing diversity in ethnicity, pastoral production system, climate and geographical resources. They range from the least arid location of Dirib Gombo occupied mostly by cattle- and smallstock-based pastoralists, who also rely on town-based livelihood opportunities to complement there meager livestock resource; to Logologo with relatively more arid climate and relatively larger number of large- scaled, cattle- and smallstock-based and migratory pastoralism; to the very arid locations at the opposite edge of the Chalbi dessert, Kargi and North Horr, with many large-scaled, camel- and smallstock-based pastoralists with extensive migratory patterns due to harsher spatiotemporal variability in forage and water availability.

Mean herd sizes range from the lowest of 2 TLU per household in Dirib Gombo to the highest of 25 TLU in North Horr. Livestock is considered the main component of pastoralist’s asset. Livestock also represents the key source of livelihood with households relying on livestock and livestock products for 44-87% of their income. The location with the lowest mean herd size, Dirib Gombo, exhibits the highest income poverty (with respect to $0.5/day poverty line) as well as asset poverty (with respect to 10 TLU livestock unit), while these poverty incidences are the lowest in the location with the highest mean herd size, North Horr. This evidence thus further emphasizes the significance of livestock as a component of livelihoods among pastoralists and agro-pastoralists in northern Kenya.

Variables/Location

Climate Mean S.D. Mean S.D. Mean S.D. Mean S.D. Annual Rainfall (mm) 366 173 297 137 270 115 227 86 NDVI 0.30 0.11 0.24 0.12 0.15 0.05 0.11 0.03 Livestock Composition Mean S.D. Mean S.D. Mean S.D. Mean S.D. % Camel 0% 4% 3% 9% 10% 5% 9% 8% % Cattle 28% 34% 26% 18% 2% 3% 2% 3% % Small stock 72% 34% 71% 19% 88% 6% 89% 9% % Migration 6% 21% 87% 21% 88% 16% 88% 17% Asset (per household) Median S.D. Median S.D. Median S.D. Median S.D. Livestock (TLU) 2 4 16 22 17 10 25 19 Nonlivestock (1,000 Ksh) 31 53 0 3,553 0 46 10 60 Income (per capita) Mean S.D. Mean S.D. Mean S.D. Mean S.D. Annual income (1,000 KSh) 3 6 12 11 6 10 27 58 % Livestock share 29% 39% 70% 40% 90% 27% 77% 39% % Salary/business 41% 43% 26% 40% 5% 21% 20% 39% Seasonal livestock loss (%) Mean S.D. Mean S.D. Mean S.D. Mean S.D. In 2000-02 (drought in 2000) 21% 29% 15% 19% 11% 12% 7% 10% Poverty Incedence % Headcount (0.5$/day) % Headcount (10 TLU) 97% Dirib Gombo 52% 91% 30% 63% 18% 73% 98%

Kargi North Horr Logologo

Livestock mortality is considered the main threat to the livelihood of pastoralists in this environment. Households’ overall seasonal livestock loss experiences during 2000-2002 (covering bad drought in 2000) varied within and across locations range from the lowest averaged seasonal rate of 7% in North Horr to 21% in Dirib Gombo. Extreme herd losses occurred in high frequency in these regions with greater-than-20% seasonal losses occurred with probability of around 20% (10- 15%) in Dirib Gombo and Logologo (in Kargi and North Horr). Strikingly, there were at least 10% probabilities of greater-than-50% seasonal losses in Dirib Gombo.

Table 5.1 Descriptive Statistics of Supportive Variables, 2007-2008

Note: % Migration represents percentage of herd that moves at least once over the year. An average value of 1 TLU is approximately 12,000 Ksh, an equivalent of $150 based on November 2008 exchange rates (79.2Ksh/US$).

Investigating the composition of historical herd loss from 2000-02 and 2007- 08 in the observed data sets also implies that catastrophic herd losses tend to result from covariate shocks over the rangeland – e.g., water and forage availability – in contrast to the small-scaled herd losses, which tend to result from other seemingly idiosyncratic shocks, e.g., accident or conflict. This evidence thus naturally provides logic behind the design and development of vegetation index based insurance to provide cost-effective coverage for a specific (but major) component of livestock asset risk in this region.