electricsheepafrica/african-crop-insurance-payouts
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---
license: cc-by-4.0
language:
- en
tags:
- insurance
- agriculture
- crop
- climate
- sub-saharan-africa
- synthetic
- agritech
- index-insurance
- drought
- food-security
pretty_name: African Crop Insurance Payouts
size_categories:
- 10K<n<100K
task_categories:
- tabular-regression
- tabular-classification
---
# African Crop Insurance Payouts
Synthetic dataset of agricultural index-insurance payouts across **12 Sub-Saharan African countries** (30,000 records). Parameters are calibrated from real-world programs including IBLI (Kenya/Ethiopia), WFP R4 Rural Resilience Initiative, and ACRE Africa.
## Dataset Description
### Scenarios
| Scenario | Description |
|---|---|
| **baseline** | Current-state parameters reflecting existing IBLI/R4/ACRE enrollment and payout patterns |
| **expanded_index_insurance** | 2.5× enrollment scaling via premium subsidy and mobile distribution (ACRE model) |
| **climate_shock** | +15 percentage point drought probability shift reflecting IPCC AR6 projections for SSA |
Each scenario contains ~10,000 records.
### Countries
Kenya, Ethiopia, Tanzania, Malawi, Zambia, Zimbabwe, Mozambique, Senegal, Ghana, Nigeria, Rwanda, Uganda
### Variables
| Variable | Type | Description |
|---|---|---|
| record_id | int | Unique identifier |
| country | str | Country name |
| year | int | Calendar year (2015–2024) |
| season | str | Growing season (`long_rains` / `short_rains`) |
| crop_type | str | `maize` / `wheat` / `sorghum` / `rice` / `cassava` |
| insurance_type | str | `index_based` / `area_yield` / `weather_derivative` |
| scenario | str | Policy scenario |
| enrolled_hectares | float | Hectares covered (0.2–20) |
| premium_paid_usd | float | Premium in USD |
| ndvi_anomaly | float | NDVI z-score (negative = vegetation deficit) |
| rainfall_deficit_pct | float | Percentage below normal rainfall |
| yield_loss_pct | float | Estimated yield loss (0–100%) |
| payout_triggered | bool | Whether index triggered a payout |
| payout_amount_usd | float | Payout disbursement in USD |
| payout_ratio | float | Payout as fraction of insured value |
| farmer_count | int | Farmers in the micro-cohort |
| enrollment_rate | float | Regional enrollment rate (0–1) |
| lapse_rate | float | Policy non-renewal rate (0–1) |
| basis_risk_score | float | Residual unhedged risk (0 = perfect, 1 = none) |
## Parameter Calibration
Key parameters are drawn from published literature and program reports:
- **Premium rates**: IBLI charges 5.5%/3.25% of insured value for upper/lower Marsabit; R4 farmers contribute 10–15% of premium in cash or labor (WFP 2019)
- **Payout trigger**: IBLI indemnifies when cumulative NDVI deviation falls below the 15th percentile of historical conditions (ILRI 2013); ACRE triggers when area yield falls below 80% of historical average
- **Basis risk**: Jensen et al. (2016, AJAE) find IBLI reduces covariate risk by 63% but leaves policyholders with 69% of original risk from high-loss events
- **Enrollment**: R4 reached ~180,000 insured households in 2020 across 10 countries (WFP 2020); ACRE reached ~400,000 farmers by 2015 (GIIF 2016)
- **Climate projections**: IPCC AR6 WGII projects increased drought frequency across the Sahel and East Africa through 2050
## Sources
1. Jensen, N.D. & Barrett, C.B. (2016). "Index Insurance Quality and Basis Risk." *American Journal of Agricultural Economics*, 98(5), 1450–1469.
2. WFP (2023). R4 Rural Resilience Initiative Annual Report.
3. ACRE Africa / GIIF (2016). Scaling agricultural insurance in East Africa.
4. Ntukamazina, N. et al. (2017). "Index-based agricultural insurance products in SSA." *J. Agr. Rural Develop. Trop. Subtrop.*, 118(2), 171–185.
5. IPCC (2022). AR6 WGII, Chapter 9: Africa.
## Usage
```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/african-crop-insurance-payouts")
```
## License
CC-BY-4.0
许可证:CC-BY-4.0
语言:
- 英语
标签:
- 保险
- 农业
- 作物
- 气候
- 撒哈拉以南非洲
- 合成数据集
- 农业科技
- 指数保险
- 干旱
- 粮食安全
美观名称:非洲作物保险赔付数据集
样本量范围:
- 10000 < 样本量 < 100000
任务类别:
- 表格回归
- 表格分类
# 非洲作物保险赔付数据集
本数据集为覆盖**12个撒哈拉以南非洲国家**的农业指数保险(agricultural index-insurance)合成数据集,共计30000条记录。其参数基于真实项目校准而来,涵盖IBLI(肯尼亚/埃塞俄比亚)、世界粮食计划署(World Food Programme, WFP)R4农村韧性倡议(R4 Rural Resilience Initiative)以及ACRE Africa等项目。
## 数据集说明
### 场景设置
| 场景名称 | 场景描述 |
|---|---|
| 基准场景(baseline) | 反映IBLI、R4与ACRE当前参保及赔付模式的现有状态参数 |
| 扩面指数保险场景(expanded_index_insurance) | 通过保费补贴与移动推广实现参保规模2.5倍扩容(采用ACRE模型) |
| 气候冲击场景(climate_shock) | 干旱发生概率提升15个百分点,契合IPCC AR6针对撒哈拉以南非洲的预测 |
每个场景包含约10000条记录。
### 覆盖国家
肯尼亚、埃塞俄比亚、坦桑尼亚、马拉维、赞比亚、津巴布韦、莫桑比克、塞内加尔、加纳、尼日利亚、卢旺达、乌干达
### 变量说明
| 变量名 | 数据类型 | 变量说明 |
|---|---|---|
| record_id | 整数型 | 唯一标识符 |
| country | 字符串型 | 国家名称 |
| year | 整数型 | 日历年(2015–2024) |
| season | 字符串型 | 种植季(`长雨季` / `短雨季`) |
| crop_type | 字符串型 | 玉米、小麦、高粱、水稻、木薯 |
| insurance_type | 字符串型 | 基于指数保险、区域产量保险、天气衍生品保险 |
| scenario | 字符串型 | 政策场景 |
| enrolled_hectares | 浮点型 | 参保公顷数(0.2–20) |
| premium_paid_usd | 浮点型 | 以美元计价的保费金额 |
| ndvi_anomaly | 浮点型 | 归一化植被指数(Normalized Difference Vegetation Index, NDVI)Z得分(负值表示植被不足) |
| rainfall_deficit_pct | 浮点型 | 较正常降雨量的亏缺百分比 |
| yield_loss_pct | 浮点型 | 预估产量损失率(0–100%) |
| payout_triggered | 布尔型 | 指数是否触发赔付 |
| payout_amount_usd | 浮点型 | 以美元计价的赔付金额 |
| payout_ratio | 浮点型 | 赔付金额占投保保额的比例 |
| farmer_count | 整数型 | 微型队列中的农户总数 |
| enrollment_rate | 浮点型 | 区域参保率(0–1) |
| lapse_rate | 浮点型 | 保单不续保率(0–1) |
| basis_risk_score | 浮点型 | 剩余未对冲风险(0代表完全对冲,1代表无对冲效果) |
## 参数校准
核心参数均来自已发表文献与项目报告:
- **保费费率**:IBLI针对马萨比特北部/南部地区的投保额分别收取5.5%/3.25%的保费;R4项目农户需以现金或劳务形式缴纳保费总额的10–15%(WFP 2019)
- **赔付触发条件**:当累积NDVI偏差低于历史序列的15%分位数时,IBLI将启动赔付(国际畜牧研究所,ILRI 2013);ACRE项目则在区域产量低于历史均值的80%时触发赔付
- **基差风险**:Jensen等人(2016,《美国农业经济学杂志(American Journal of Agricultural Economics, AJAE)》)的研究表明,IBLI可降低63%的协变量风险,但仍使参保农户面临原始高损失事件风险的69%
- **参保规模**:R4项目于2020年在10个国家覆盖约18万户参保家庭(WFP 2020);截至2015年,ACRE项目已服务约40万农户(全球保险基础设施基金,GIIF 2016)
- **气候预测**:IPCC第六次评估报告第二工作组(AR6 WGII)预测,截至2050年,萨赫勒地区与东非的干旱发生频率将持续上升
## 参考文献
1. Jensen, N.D. 与 Barrett, C.B. (2016). 《指数保险质量与基差风险》,*American Journal of Agricultural Economics*, 98(5), 1450–1469.
2. 世界粮食计划署(WFP)(2023). 《R4农村韧性倡议年度报告》
3. ACRE Africa / 全球保险基础设施基金(GIIF)(2016). 《东非农业保险扩面实践》
4. Ntukamazina, N. 等人 (2017). 《撒哈拉以南非洲地区的基于指数的农业保险产品》,*J. Agr. Rural Develop. Trop. Subtrop.*, 118(2), 171–185.
5. 政府间气候变化专门委员会(IPCC)(2022). 《AR6 WGII 第九章:非洲》
## 使用方式
python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/african-crop-insurance-payouts")
## 许可证
CC-BY-4.0
提供机构:
electricsheepafrica



