This dissertation consists of three papers analyzing the effect of Index-Based Livestock Insurance (IBLI) on pastoral communities in northern Kenya. The first paper investigates the effect of coverage level for IBLI on pastoral livestock production. The paper builds a model for a risk-averse pastoral producer to assess the effect of the IBLI policy. Using the output and vegetation data the study applies numerical optimization to the model and simulates the effect of coverage level on input use, output, premiums, and certainty equivalents. The simulation results suggest an optimal coverage of 70% based on a higher level of certainty equivalent. Results indicate as the coverage level increases, premium and certainty equivalent increases while input and production decrease. The findings of this paper imply that moral hazard is controlled for and IBLI is coupled to production through wealth and insurance effects.

The second paper empirically examines the potential effect of output and input prices, vegetation, and subscription to index-based insurance on pastoral livestock productivity for 924 households between the period 2009-2015. The paper applied Random effects to estimate production and productivity elasticities. Estimation results offer support for the hypothesis of a negative relationship between past output prices and pastoral livestock productivity, with an estimate of 1.1%. The result indicates past wages have a positive effect on productivity, with an estimate of 1.6%-2%, whereas material input price has a negative effect and an estimate of -2%. Lagged vegetation for the Long Rain Long Dry Season (LRLDS) has a positive effect on productivity with an estimate of 15%-16% while current vegetation has a negative effect. There is no evidence that subscription to IBLI increases productivity.

The third paper analyzes the historical profile of animal (camel, cattle, and shoats) deaths and the timing of compensation for IBLI asset protection contract using vegetation and precipitation data available from 2001-2017 and 1982-2017 respectively. Results of the nonparametric analysis indicate about 5 to 15 shoats (goats and sheep),     4 cattle, and 2-3 camels are lost during January-February (the short dry season) and May-September (the long dry season), and some more shoats die during the rainy season. Mortality is strongly linked to the long dry season (May-September) for all species. IBLI Subscribers can be compensated 2-3 months earlier for the LRLDS contract for all animal types while 3-4 (1-2) months earlier for shoats and camel (cattle) than the current timing for the Short Rain Short Dry Season (SRSDS) contract. Index-based livestock insurance programs should investigate the possibility of adjusting the timing of compensation for each animal type.

Also, the third paper empirically examines the factors that determine the incidence of animal deaths in Mountain, North, and South of Marsabit County. The results for random effects negative binomial revealed that the incidence of animal deaths is greater by more than 85% for poorer households in all the regions and specifically in the satellite camp. Level of lagged precipitation and vegetation are negative and strongly associated with the extent of death incidence in the North for all animal types and shoats in the South. The current vegetation is positive and strongly significant in the North for camel, cattle, and shoats. The result suggests that other than drought, high incidences of animal deaths occur during the rainy seasons. Disease risks increase immediately post-drought period which magnifies mortality events during the short rain season. The main distinction between North and South is livelihood variables. The number of animal death incidence is 19% more in large herds, 1.8% less for households headed by the aged, and 51% less for male-headed households for shoats, whereas for camel is 16%, 1.3%, and 29% respectively in the South. Policymakers and development agencies should target the vulnerable poor, the partially settled, and the female-headed households for productive investment support and index-based livestock insurance interventions.