O13 | Macro Paper Warehouse

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

Mon, 01 Jan 0001 00:00:00 +0000

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.

Praying for Rain

Mon, 01 Jan 0001 00:00:00 +0000

This paper studies rainmaking as an instrumental religious belief. The central research question is: why do people believe that prayer can bring rain, even though it does not work? The authors develop a model of cultural evolution in which a religious leader prays for rain at an arbitrary time, and people update their beliefs about whether the leader can cause rainfall based on whether rain follows. The key mechanism is the local rainfall hazard function — the probability of rain conditional on how many days have passed since the last rainfall. In environments where the hazard is increasing (rain becomes more likely the longer a drought continues), a leader who prays during a drought will tend to be followed by rain, creating the illusion of efficacy. In environments with a flat or declining hazard, prayer cannot be systematically followed by rain in a persuasive way. The model yields five predictions: rain ritual traditions will select for prayers correlated with rainfall; the level of average rainfall does not determine persuasiveness; constant-hazard environments cannot support persuasive prayer; increasing-hazard environments are more likely to adopt rainmaking; and higher net benefits of rainfall (e.g., settled agriculture) further increase the likelihood of ritual.

The authors test these predictions with two empirical strategies. First, they use daily data from the Catholic church in Murcia, Spain, covering 1600 to 1836. Church records provide the daily timing of pro pluvia rogations (prayers for rain), while municipal council records — kept independently of the church — record notable rainfall events. Murcia’s rainfall hazard is estimated to be increasing after long dry spells: the hazard rate after a long drought is roughly double the hazard rate two months after the last rainfall. The main finding is that a prayer for rain in the last 30 days predicts a 0.144 percentage-point higher daily probability of notable rainfall (standard error 0.057 pp), relative to a baseline mean daily rainfall probability of 0.203 pp — a 71% increase in the predicted probability. Prayer also Granger-causes rainfall conditional on lags of recent rainfall, and the predictive power holds within a given calendar month, ruling out a purely seasonal coincidence.

Second, the authors construct an original dataset covering rainmaking practice for 1,208 ethnic groups drawn from the Ethnographic Atlas (Murdock, 1967), coded from 370 anthropological sources. They match each ethnic group to its nearest weather station and estimate the rainfall hazard function each group faces in its ancestral location. Of the 1,208 groups, 33% face an increasing rainfall hazard, and 39% of all groups practice rain ritual. The main global finding is that ethnic groups facing an increasing rainfall hazard are 14 percentage points more likely to practice rainmaking (standard error 3.7 pp), relative to a base rate of 30% among groups facing a non-increasing hazard — a 47% increase. This result is robust to continent fixed effects, geographic and climatic controls (longitude, latitude, elevation, distance to coast, ruggedness, mean temperature, mean rainfall, coefficient of variation of rainfall, maximum dry spell length, and the Giuliano-Nunn 2021 climatic variability measure), alternative hazard estimation methods, and linguistic family fixed effects. Crucially, lower average rainfall, longer droughts, and greater climatic variability are not associated with more rain ritual conditional on hazard shape — it is specifically the shape of the hazard function, not aridity or variability per se, that drives adoption.

A second global finding concerns demand: groups dependent on agriculture are 11 pp more likely to practice rainmaking; those dependent on intensive agriculture, 21 pp more likely; and those dependent on intensive irrigated agriculture, 32 pp more likely (on a base of 32%). The scope of the findings is the pre-modern or traditional period captured by the Atlas; the Murcia case covers 1600–1836. The authors conclude that some environments create an illusion of efficacy that sustains instrumental religious belief through cultural selection, without requiring that believers be irrational.

Q: What is the paper’s central theoretical claim about why rainmaking beliefs persist? A: The paper argues that in environments where the rainfall hazard is increasing during a drought, a leader who begins praying during a dry spell will tend to be followed by rain, because the probability of rain rises as the drought lengthens. People who cannot observe the counterfactual hazard (what rainfall would have been without prayer) interpret this coincidence as evidence that prayer works. Cultural selection then favors leaders whose prayer timing is more persuasive, causing the belief to persist across generations even though prayer does not actually cause rain.

Q: What is the rainfall hazard function, and why does its shape determine whether prayer can be persuasive? A: The hazard function h(t) gives the instantaneous probability of rain at time t days after the last rainfall. If the hazard is flat, the probability of rain is the same regardless of whether prayer was offered or not, so there is no systematic correlation between prayer and rainfall to exploit. If the hazard is declining, prayer during a drought will be followed by lower-than-average rainfall probability, undermining the leader. Only if the hazard is increasing does prayer during a long dry spell systematically coincide with a higher probability of rain, creating a persuasive correlation.

Q: What do Propositions 2 and 3 of the model establish? A: Proposition 2 establishes that if the hazard rate is constant and a person’s prior belief that prayer works is below 0.5, then no prayer start time can persuade them to support the leader. Proposition 3 establishes the converse: if the hazard rate is increasing and the prior is below 0.5, there exists a meaningful belief for which a person will support the leader for any prayer start time. Together these propositions identify the increasing hazard as the necessary and sufficient structural condition for persuasive prayer.

Q: What is the main quantitative finding from Murcia, and what identification strategy supports it? A: A prayer for rain in the last 30 days predicts a 0.144 percentage-point higher daily probability of notable rainfall (standard error 0.057 pp) relative to a baseline mean of 0.203 pp, a 71% increase. The authors additionally demonstrate that prayer Granger-causes rainfall conditional on lags of recent rainfall, and that the effect holds within a given calendar month, ruling out the explanation that prayer simply tracks the rainy season. The prayer and rainfall records are kept by independent institutions (church and municipal council), reducing the risk of strategic recording.

Q: How does the hazard rate in Murcia behave, and does it satisfy the model’s key condition? A: The hazard of rainfall in Murcia is initially high just after rain, declines to a minimum roughly two months after the last rainfall, and then increases significantly thereafter, reaching or exceeding its initial level after a long drought. The fluctuations are large: the hazard after a long dry spell is roughly double the hazard two months after rainfall. This U-shaped pattern means the hazard is increasing during a prolonged drought, satisfying the model’s key condition for persuasive prayer.

Q: How was the global rainmaking dataset constructed, and what is its coverage? A: The authors used the Ethnographic Atlas (Murdock, 1967) as a template, covering 1,290 ethnic groups, and combed 370 anthropological sources — primarily group-specific ethnographic monographs — to code rainmaking practice for 1,208 groups. A group is coded as practicing rain ritual only if there is clear evidence of a practice specifically intended to bring rain through supernatural means. The authors treat their measure as a lower bound. They find that 39% of the 1,208 groups practice rainmaking, across every settled continent.

Q: What is the main global regression result and how robust is it? A: Ethnic groups facing an increasing rainfall hazard are 14 percentage points more likely to practice rain ritual (standard error 3.7 pp) relative to a base rate of 30%, a 47% proportional increase. This coefficient is positive and statistically significant across all specifications, including those adding continent fixed effects, a full battery of geographic and climatic controls (longitude, latitude, elevation, distance to coast, ruggedness, mean temperature, mean rainfall, coefficient of variation of rainfall, maximum dry spell length, and the Giuliano-Nunn 2021 climatic variability measure), alternative hazard estimation methods, linguistic family fixed effects, and restrictions to groups with high-quality rainfall data.

Q: Does aridity or climatic variability explain rainmaking adoption? A: No. Lower average rainfall, longer droughts, and greater climatic variability (measured using the Giuliano-Nunn 2021 index) are not associated with more rain ritual practice, conditional on the shape of the hazard function. This rules out the naive hypothesis that people pray for rain simply because they do not get enough, or because their rainfall is unreliable. It is specifically the shape of the hazard — whether it is increasing during a drought — that drives adoption, not the level or volatility of rainfall.

Q: How does demand for rainfall, proxied by agricultural subsistence, affect rainmaking adoption? A: Groups dependent on agriculture are 11 percentage points more likely to practice rainmaking relative to other subsistence modes. Groups dependent on intensive agriculture are 21 percentage points more likely, and groups dependent on intensive irrigated agriculture are 32 percentage points more likely, all on a base of 32%. This gradient is consistent with Proposition 5 and 6 of the model: settled, location-specific agricultural investment raises the net benefit of rainfall control, increasing support for rain ritual independently of the persuasion channel.

Q: What does the model’s cultural evolution mechanism (Proposition 4) predict about how prayer timing changes over generations? A: Proposition 4 states that rituals with high support are more likely to persist. In increasing-hazard environments, random variation in prayer timing means some leaders gain more support than others; those with more persuasive timing are more likely to persist. Each generation then adopts a policy at least as persuasive as the prior generation, so support rises over time and prayers gradually converge toward the timing that maximizes persuasiveness. This mechanism does not require deliberate optimization by any individual leader.

Q: How does the paper’s finding relate to the long-standing anthropological debate between the traditional and revisionist schools on rainmaking? A: The traditional school (following Frazer 1890) holds that belief is instrumental — people engage in rainmaking to make rain, and belief responds to empirical evidence. The revisionist school (Wittgenstein, Durkheim) argues that religious belief and rationality are fundamentally separate, and religious practice is performative rather than evidence-responsive. The paper’s finding that rainmaking is more prevalent precisely where it is more persuasive — i.e., where the environment makes prayer appear to work — supports the traditional, instrumental interpretation that belief responds to evidence of efficacy.

Q: What are the scope conditions for the paper’s conclusions? A: The Murcia case study covers the period 1600–1836, ending when the abolition of tithes reduced the church’s funding and influence; it applies to a sophisticated Catholic institutional context. The global analysis covers traditional practices of pre-modern ethnic groups as recorded in the Ethnographic Atlas and anthropological literature; it does not speak to modern religious practice or to religions after substantial modernization. The persuasion mechanism requires that people cannot directly observe what rainfall would have been without prayer, a condition satisfied in pre-scientific contexts.

Rainfall hazard function: In this paper’s usage, the function h(t) = f(t)/(1-F(t)) giving the instantaneous probability of rainfall at time t days since the last rainfall. Its shape — whether flat, declining, or increasing during a drought — determines whether prayer can be persuasive, not the overall level of rainfall.

Increasing hazard: A hazard rate that rises as the length of a dry spell increases, so that rain becomes more likely the longer the drought has continued. The paper defines this specifically as the derivative of the hazard function evaluated at the 99th percentile of spell length. This is the necessary structural condition for prayer to seem efficacious.

Instrumental religious belief: Belief directed at achieving a worldly outcome (here, rainfall), as opposed to purely expressive or social belief. The paper treats belief as instrumental if it responds to perceived evidence of efficacy and is adopted where it appears to work.

Persuasion (in the model): The process by which a leader’s prayer timing causes people to update their belief that prayer works, by generating a correlation between prayer and subsequent rainfall that exceeds what people expect from the background hazard rate. Persuasion is possible only when the hazard is increasing.

Pro pluvia rogations: The Catholic church’s formal prayers for rain, practiced in Murcia since at least the 14th century. In the paper’s data, these prayers follow a pattern of escalation — increasing in number and intensity — during prolonged droughts, consistent with the model’s prediction about prayer timing.

Cultural evolution: The paper’s framework (drawing on Henrich 2015) in which religious leaders act as cultural entrepreneurs; leaders whose prayer timing happens to be more persuasive gain greater support and are more likely to survive across generations, so prayer traditions drift toward more persuasive timing without deliberate design.

Rain ritual (global measure): A binary indicator coded as one for an ethnic group if the anthropological literature contains clear evidence of a practice specifically intended to bring rain through supernatural means, including dances, sacrifices, prayers, and petitioning of rain deities. Treated by the authors as a lower bound on actual prevalence.