Macro Paper Warehouse Forthcoming macro & monetary research
Forthcoming [Quarterly Journal of Economics] doi:10.1093/qje/qjag005

Insuring Peace: Index-Based Livestock Insurance, Droughts, and Conflict

Kai Gehring

Paul Schaudt

What this paper finds — and why it matters

This paper provides quasi-experimental evidence that Index-Based Livestock Insurance (IBLI) — a remote-sensing-triggered, automated payout scheme for pastoralists — substantially reduces drought-induced conflict in Kenya over the 2001–2020 period.

The research question is whether a market-based financial instrument can mitigate the causal chain running from drought shocks to violent conflict between nomadic pastoralists and sedentary farmers and other land users. The authors motivate the study by documenting that droughts force pastoralists out of their traditional grazing grounds and into mixed-land-use areas (farms, ranches, urban settlements, nature reserves), where miscoordination with other land users escalates into violence. A case study of the Samburu-Laikipia-Isiolo-Meru region in central Kenya — drawing on georeferenced survey data from Lengoiboni et al. (2010) and ACLED conflict events — validates this spatial mechanism: during droughts, roughly 60–90% of non-pastoral land users report encounters with pastoralists, and conflicts accumulate precisely where drought migration routes cross into non-pastoral land.

The empirical design combines two sources of variation: (1) plausibly exogenous changes in rainfall deficits at the 0.1 × 0.1-degree grid-cell level (roughly 10 × 10 km), derived from NASA GPM satellite data; and (2) the staggered, five-wave rollout of IBLI across 146 insurance districts in Kenya from 2010 onward, which the authors argue was driven primarily by technical challenges rather than pre-existing conflict or drought patterns. The unit of observation is 94,300 cell-periods. Because conflicts due to pastoralist drought migration occur in the neighborhood of affected areas rather than within them, both drought and IBLI coverage are measured as inverse-distance-weighted averages over surrounding cells. The estimating equation is a linear probability model with cell and period fixed effects, interacting neighborhood rainfall deficit with neighborhood IBLI coverage; the coefficient on this interaction term (delta3) is the parameter of interest.

The main finding is that a one-standard-deviation increase in neighborhood IBLI coverage reduces the semi-elasticity of neighborhood rainfall deficit on conflict probability by approximately 23%. In absolute terms, a one-percentage-point increase in the rainfall deficit raises the probability of conflict by 6.92 percentage points at average IBLI coverage; with one additional standard deviation of neighborhood IBLI, that same deficit raises conflict probability by only 5.34 percentage points — a reduction of 1.58 percentage points against a baseline conflict probability of roughly 2.5%.

Scope conditions: the effect is estimated for Kenya specifically, over a pastoralist-heavy population of approximately 8.8 million out of 53 million Kenyans, during 2001–2020. The conflict-mitigating effect is approximately four times larger in mixed-land-use areas (nine times when rollout-cluster-times-period fixed effects are included), consistent with the theoretical expectation that IBLI matters most where pastoralists are most likely to encounter other land users during drought migration.

Two mechanisms are identified. First, IBLI reduces migratory pressure: when pastoral homelands have IBLI coverage, the distance between the ethnic homeland centroid and conflict events involving that group decreases, indicating reduced drought migration. Second, IBLI smooths incomes — corroborated with Afrobarometer geo-coded data — raising the opportunity cost of fighting. An instrumental-variable specification finds that actual IBLI payouts in the neighborhood reduce conflict probability by approximately 150% relative to the baseline risk.

A cost-effectiveness analysis finds that even using conservative World Health Organization or World Bank estimates of the value of statistical life, IBLI delivers fatality savings of between 10 and 22 cents per dollar spent on government subsidies for the program, making it a cost-effective complement to political and institutional conflict-mitigation approaches.

Q: What is the core causal mechanism linking droughts to conflict that IBLI interrupts?

A: Droughts deplete forage in pastoralists’ traditional grazing grounds, forcing them to migrate into mixed-land-use areas — farms, ranches, urban settlements, and nature reserves — where encounters with other land users are more likely to escalate into violence. Without insurance, pastoralists hold excess livestock as precautionary savings, amplifying the extent of necessary migration during dry periods. IBLI payouts allow pastoralists to purchase forage locally, reducing migration distance and intensity, and also smooth income, raising the opportunity cost of engaging in violence.

Q: How does IBLI work technically, and why does it overcome problems of traditional livestock insurance?

A: IBLI uses satellite remote sensing to calculate whether a district-specific drought threshold has been crossed; if so, automated payments are triggered immediately without requiring direct loss assessment or field inspections. This design eliminates moral hazard and adverse selection problems inherent in traditional indemnity insurance, reduces monitoring costs, and enables fast delivery via mobile payment platforms such as MPESA even to remote households. The Kenyan government rebranded the program as the Kenyan Livestock Insurance Program (KLIP) in 2015 and fully subsidizes coverage for up to five tropical livestock units per household.

Q: What is the magnitude of the main conflict-mitigation result?

A: A one-standard-deviation increase in neighborhood IBLI coverage reduces the semi-elasticity of the neighborhood rainfall deficit on conflict probability by approximately 23% (delta3/delta1 = -0.0158/0.0692). In absolute terms, this translates to a reduction from a 6.92 percentage-point increase in conflict probability per one-percentage-point rainfall deficit to a 5.34 percentage-point increase — a decline of 1.58 percentage points against a mean conflict probability of roughly 2.5%.

Q: Why do the authors use a neighborhood rather than cell-level treatment measure?

A: Drought-induced pastoralist conflicts occur primarily not in the pastoral home areas themselves but in neighboring regions where drought migration routes cross into non-pastoral land. The case study documents this pattern directly: ACLED conflict events accumulate where migration routes from Namelok, Lodungokwe, and Ngaremara communities intersect urban or agricultural areas, not within the pastoral zones. The neighborhood approach, using inverse-distance-weighted averages, captures both the probability of migration from surrounding cells and the declining probability of migration with distance.

Q: What is the main identification concern and how do the authors address it?

A: The main concern is that the timing of the IBLI rollout is endogenously determined — areas with a higher latent drought-conflict elasticity might receive coverage earlier or later, biasing the interaction coefficient. The authors show that the pre-treatment drought-conflict elasticity has no systematic correlation with either IBLI eligibility or the timing of coverage receipt. Placebo tests interacting the neighborhood rainfall deficit with pre-treatment eligibility or eventual coverage indicators yield positive, statistically insignificant coefficients, suggesting any bias would run in the direction of underestimating the mitigation effect. A permutation test randomly reassigning IBLI coverage across the six rollout clusters finds the actual point estimate is in the bottom 2.2% of the simulated distribution, indicating it is unlikely to arise from cluster-level confounders.

Q: How do the authors rule out that other programs — cash transfers or development aid — explain the result?

A: The authors control for cell-level and neighborhood-level coverage of Kenya’s Hunger Safety Net Programme (HSNP), which provides unconditional cash transfers to vulnerable households and covers most IBLI-eligible areas, as well as for World Bank agricultural aid projects. Across these specifications, the estimated conflict mitigation ranges from -19.16% to -42.24%, with the baseline estimate of -22.79% remaining robust, indicating neither HSNP nor development aid is a plausible alternative explanation.

Q: What is the alternative identification strategy using within-rollout-cluster variation?

A: The authors exploit pre-determined (1984 government land-use map) variation in mixed-land-use status across cells within the same IBLI rollout cluster-period, including rollout-cluster-times-period fixed effects that absorb any omitted variable related to the potentially endogenous rollout steps. The conflict-mitigating effect of IBLI is approximately four times larger in mixed-land-use cells, and approximately nine times larger in the most restrictive specification with rollout-cluster-times-period fixed effects, consistent with the prediction that IBLI matters most where pastoralists encounter other land users.

Q: How do the authors establish the migratory pressure mechanism?

A: Following Eberle et al. (2023), the authors match conflict actors to ethnic homelands using Murdock (1967) boundaries and test whether IBLI coverage in a homeland reduces the distance between the homeland centroid and conflict events involving that group. They find that it does, indicating that IBLI coverage reduces the spatial range of pastoralist drought migration and thus the probability of conflict-generating encounters with other land users.

Q: How do the authors establish the income-smoothing mechanism?

A: Using geo-coded Afrobarometer survey data, the authors show that IBLI coverage is associated with higher reported incomes among pastoralist households, consistent with Jensen et al. (2017). Higher incomes raise the opportunity cost of fighting (following Grossman, 1991), contributing to the overall conflict-mitigating effect alongside reduced migratory pressure.

Q: What does the instrumental variable specification find?

A: The authors instrument inverse-distance-weighted IBLI payouts in the neighborhood with the interaction of neighborhood rainfall deficit and neighborhood IBLI coverage. The first stage confirms that rainfall deficits trigger payouts conditional on coverage. The second stage finds that the occurrence of payouts in the neighborhood reduces the probability of conflict by approximately 150% relative to the baseline risk, corroborating the reduced-form results.

Q: How do the authors assess cost-effectiveness?

A: The authors predict plausible drought-induced conflict fatalities in Kenya over the pre-treatment period and calculate yearly lives saved from the main estimates, then compare the monetary value of saved lives to government subsidy expenditures on IBLI. Using conservative VSL estimates from the WHO and World Bank, IBLI delivers between 10 and 22 cents of pure fatality savings per dollar of public subsidy expenditure.

Q: How robust are the results to alternative drought and conflict measures?

A: Results are qualitatively similar using an Aridity Index or Dry Matter Productivity (DMP) as drought proxies instead of rainfall deficit. The estimated interaction effect maintains a t-statistic above two for spatial decay functions ranging from distance^-0.5 to distance^-1.5 and for Conley standard error cutoffs from 200 km up to 400 km. Results also hold when restricting to conflict events not involving the government, or to battles, riots, and violence against civilians only, and when excluding the pre-IBLI period (2000–2009) entirely.

Q: What are the policy implications regarding scalability?

A: Pastoralism covers 43% of the African landmass across 36 countries, supporting approximately 268 million people (FAO, 2018). The World Bank and private equity were planning to invest close to 900 million dollars in East African pastoralist programs over 2023–2027. The authors argue that IBLI’s cost structure — high fixed costs of technology and setup but low marginal costs of expansion — gives it a scalability advantage over cash transfer programs or public works schemes that require sustained state capacity. Market-based IBLI complements rather than substitutes for political and institutional reforms.

Index-Based Livestock Insurance (IBLI): A financial instrument that uses satellite remote sensing to automatically trigger preemptive cash payouts to pastoralists when a pre-determined district-specific drought threshold is crossed, bypassing direct loss assessment and thereby eliminating moral hazard and adverse selection problems inherent in traditional indemnity insurance.

Drought-conflict semi-elasticity: The percentage-point change in the probability of conflict associated with a one-percentage-point increase in the rainfall deficit; the paper’s main outcome quantity, estimated at 6.92 percentage points at mean IBLI coverage, reduced by 23% for a one-standard-deviation increase in neighborhood IBLI coverage.

Neighborhood approach: An empirical strategy that measures both drought severity and IBLI coverage as inverse-distance-weighted averages over all surrounding grid cells, reflecting the authors’ finding that pastoralist drought-migration generates conflicts not in the pastoral home area but in neighboring mixed-land-use zones where migration routes intersect other land users.

Migratory pressure: The mechanism by which drought forces pastoralists — who hold excess livestock as precautionary savings in the absence of insurance — to migrate farther from traditional grazing grounds into mixed-land-use areas, increasing the probability of encounters and violent miscoordination with farmers, urban dwellers, and protected-area managers.

Mixed land use: Areas, designated using a 1984 Kenyan government land-use map, where pastoral grazing zones are proximate to farms, ranches, urban settlements, or nature reserves; the paper identifies these as the locations with the highest expected treatment intensity, where IBLI coverage reduces drought-induced conflict approximately four to nine times more than elsewhere.

Tropical Livestock Unit (TLU): The standard unit of account for IBLI contracts in Kenya; one TLU corresponds to one head of cattle or ten goats or sheep; the Kenyan government fully subsidizes IBLI for up to five TLUs per household.

Rollout-cluster-times-period fixed effects: A restrictive set of fixed effects included in the alternative identification strategy that absorbs all omitted variables varying at the level of the six IBLI spatial rollout clusters over time, allowing the authors to identify the conflict-mitigating effect purely from within-cluster variation in mixed-land-use exposure.

How this summary was made. Bibliographic fields are pulled from Crossref and OpenAlex and are not model-generated. The summary was drafted from the open-access manuscript , checked by a claim-grounding and calibration review pass, and approved before publishing. Found an error or a misrepresentation? Flag it here — corrections are welcome, especially from the authors.