electricsheepafrica/african-cross-border-logistics-costs

---
license: cc-by-4.0
tags:
- trade
- logistics
- corridors
- afcfta
- sub-saharan-africa
- synthetic
- supply-chain
size_categories:
- 10K<n<100K
task_categories:
- tabular-regression
- tabular-classification
language:
- en
pretty_name: African Cross-Border Logistics Costs
---

# African Cross-Border Logistics Costs

Synthetic dataset of cross-border logistics costs across 10 major African trade corridors under 3 policy scenarios.

## Dataset Summary

- **30,000 records** (10,000 per scenario)
- **10 corridors** spanning East, West, Southern, and Central Africa
- **3 scenarios**: baseline, AfCFTA-facilitated, political disruption
- **2018–2026** temporal coverage

## Corridors

| Corridor | Origin | Destination |
|---|---|---|
| Mombasa-Kampala | Kenya | Uganda |
| Dar es Salaam-Kigali | Tanzania | Rwanda |
| Lagos-Accra | Nigeria | Ghana |
| Durban-Johannesburg | South Africa | South Africa |
| Beira-Harare | Mozambique | Zimbabwe |
| Djibouti-Addis Ababa | Djibouti | Ethiopia |
| Dakar-Bamako | Senegal | Mali |
| Tema-Ouagadougou | Ghana | Burkina Faso |
| Maputo-Lilongwe | Mozambique | Malawi |
| Douala-N'Djamena | Cameroon | Chad |

## Scenarios

- **baseline**: Current operational conditions
- **afcfta_facilitated**: Reduced tariffs, streamlined customs, fewer informal payments
- **political_disruption**: Increased delays, higher informal costs, degraded infrastructure

## Variables

| Variable | Type | Description |
|---|---|---|
| record_id | string | Unique identifier (LGS-XXXXXX) |
| corridor | string | Trade corridor name |
| origin_country | string | Country of origin |
| destination_country | string | Country of destination |
| year | int | Year (2018–2026) |
| transport_mode | string | road, rail, or multimodal |
| distance_km | float | Distance in kilometers |
| cost_per_ton_usd | float | Cost per ton in USD |
| transit_time_days | float | Transit time in days |
| border_crossings_count | int | Number of border crossings |
| informal_payments_usd | float | Informal payments in USD |
| documentation_compliance_pct | float | Documentation compliance (0–100%) |
| fuel_cost_pct | float | Fuel cost as percentage of total |
| insurance_cost_pct | float | Insurance cost as percentage of total |
| driver_rest_delays_hours | float | Driver rest delays in hours |
| corridor_efficiency_score | float | Efficiency score (0–100) |
| cost_competitiveness_class | string | low, moderate, high, very_high |

## Usage

```python
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/african-cross-border-logistics-costs")
```

Or load directly:

```python
import json
with open("data/logistics_costs.json") as f:
records = json.load(f)
```

## Generation

```bash
python generate_dataset.py
python validate_dataset.py
```

## License

CC-BY-4.0

## Citation

```bibtex
@dataset{african_cross_border_logistics_2026,
title={African Cross-Border Logistics Costs},
author={Electric Sheep Africa},
year={2026},
license={CC-BY-4.0}
}
```