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BrianKarimi/Agrifood-System-Employment-Trends-in-East-Africa

Domaine:

agriculturesocioeconomic

Type de record:

dataset
Créateur:
Bri
Hôte:
This project analyses agricultural employment trends in East Africa (Kenya, Ethiopia, Uganda, Tanzania, Rwanda, Burundi) from 2000–2023 using ILO/FAO estimates and national surveys. It examines time trends in employment levels and shares, gender differences # East Africa Agricultural Employment Analysis (2000–2023) Analysis of employment indicators in agriculture across East African countries using ILO, FAO, labour force surveys, household surveys, and census data. **Dataset source**: [FAOSTAT] (fao.org) **File**: `Employment_Indicators_Agriculture_E_Africa_NOFLAG.csv` **Time period in focus**: 2000–2023 **Geographic focus**: East Africa (Kenya, Ethiopia, Uganda, Tanzania, Rwanda, Burundi) ## Objectives 1. **Trend Analysis Over Time** → Employment levels, shares (%), year-on-year changes, productivity trends 2. **Comparative Analysis Across Countries / Regions** 3. **Gender and Demographic Breakdowns** → Male vs Female shares over time → Age distribution in agriculture by gender (sparse survey data) ## Key Visuals & Insights Created ### 1. Time Trends (2000–2023) - Male agricultural employment (absolute, thousands) – line plots by country - Share of employment in agriculture (%) – Male only, with YoY % change (dual axis) - X-axis shows every year (rotated labels for readability) **Main observations**: - Absolute male employment generally rising slowly (population effect) - Share % declining across most countries (structural transformation) - YoY changes volatile; some years show sharp drops/recoveries ### 2. Gender Comparison - Male vs Female share % over time (faceted by country) - 2023 snapshot: bar chart comparing male/female shares per country **Main observations**: - Female shares often higher than male (especially Tanzania, Rwanda, Burundi) - Both genders show long-term decline in agricultural dependence - Gap (Female – Male) usually positive and relatively stable ### 3. Age Distribution by Gender **Data source**: Labour force surveys, household surveys, population censuses (not modelled estimates) **Limitation**: Very sparse – only a few snapshots per country, not annual series ## Tools & Technologies Used The analysis was performed using the following tools and …