Summary: This table is part of the Rwanda Labour Force Survey (LFS) 2025 aggregated schema, which compiles quarterly labour market data from 2019 to 2025 to provide a continuous and longitudinal view of workforce dynamics. It presents key labour force indicators disaggregated by age group, comparing youth (16–30 years) and adults (31 years and above). The table shows differences in labour market outcomes between younger and older populations over time.
Geographic Coverage: National coverage across Rwanda.
Time Period: Quarterly data from 2019 Q1 to 2025 Q4.
Frequency: Quarterly
Population/Units: Individuals aged 16 years and above in the labour force, grouped into youth (16–30) and adults (31+).
Key Variables: Age group (youth/adult), labour force participation rate, employment rate, unemployment rate, labour underutilization indicators, and other labour market metrics.
Purpose: To support analysis of generational differences in labour market outcomes and inform policies on youth employment, workforce transition, and labour market inclusion.
Data Quality Notes: Data are derived from nationally representative Quarterly Labour Force Surveys conducted by the National Institute of Statistics of Rwanda (NISR). Estimates are weighted and subject to sampling variability, reflecting labour market conditions at the time of each survey round.
","databaseName":"datasharing_platform","schemaDescription":"Summary: This schema contains aggregated data from Rwanda’s Quarterly Labour Force Survey (LFS) covering the period from 2019 to 2025. It provides a continuous and high-frequency view of labour market dynamics, capturing trends in employment, unemployment, and labour underutilization among the working-age population. The dataset compiles quarterly survey results into a unified structure to enable longitudinal analysis of workforce patterns over time.
Geographic Coverage: National coverage across Rwanda, with disaggregation by districts, provinces, and area of residence (urban and rural).
Time Period: 2019–2025, based on quarterly data collection rounds conducted throughout each year.
Frequency: Quarterly (four rounds per year), aggregated for longitudinal analysis.
Population/Units: Individuals aged 16 years and above living in private households in Rwanda.
Key Variables: Employment status, unemployment rate, labour force participation rate, underutilization indicators (LU1–LU4), NEET rate, median earnings, occupation, industry (economic activity), and status in employment (ICLS-93 and ICSE-18 classifications), with breakdowns by sex, age, education level, and residence.
Purpose: To support labour market monitoring, employment policy design, workforce planning, and evaluation of national development strategies through consistent and internationally comparable labour statistics.
Data Quality Notes: Data are derived from nationally representative quarterly household surveys using standardized methodologies. Aggregated indicators are subject to sampling and non-sampling errors, and estimates may vary across subpopulations and time periods.
","ownerName":"Norbert","ownerEmail":"norbert.habimana@statistics.gov.rw","tags":null,"customTags":["Aggregated data"],"datasetType":"TABLE","datasetFileId":null,"queryDefinition":null,"periodBegin":"2025-01-01","periodEnd":"2025-12-31","createdAt":"2026-03-26T14:19:12.736Z","updatedAt":"2026-08-18T09:44:55.008Z","columns":[{"id":"3e8769e1-562d-4094-b198-02c06be279c1","columnName":"youth_adult","description":"Age category: \"Youth (Age: 16-30 years)\" or \"Adult (Age: 31 and over)\"","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"5146e7b5-95b7-427b-8aee-5839789e0253","columnName":"year","description":"Survey year (2019 to 2025)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"67456355-e2c9-417b-a55a-d40f111a91e3","columnName":"quarter","description":"Survey quarter (Q1, Q2, Q3, Q4)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"effa5334-792f-437b-a13e-d013dd04f517","columnName":"employment_to_population_ratio","description":"Employment-to-population ratio for this age category (%)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"4cbf2842-105c-4471-8f97-c8d9a2abc3b1","columnName":"labour_force_participation_rate","description":"Participation rate for this age category (%)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"55f9187d-9a71-4103-8799-0c2b94bcd064","columnName":"lu1_unemployment_rate","description":"Unemployment rate for this age category (%)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"7f501422-8f82-4860-a660-fca9024f9bed","columnName":"lu2_combined_rate_of_unemployment_and_time_related_underempl","description":"Combined unemployment and underemployment rate (%)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"41dff6e1-afbd-49c0-a6a2-6aafc79de725","columnName":"lu3_combined_rate_of_unemployment_and_potential_labour_force","description":"Combined unemployment and potential labour force rate (%)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"e8d9ce38-0841-4c76-ac15-82e679517197","columnName":"lu4_composite_measure_of_labour_underutilization","description":"Composite labour underutilization (%)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"a6fa52c8-b9f5-407f-8c7c-73be018f6456","columnName":"median_monthly_earnings_at_main_job","description":"Median monthly earnings at main job (RWF)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"770c1810-618b-4bc6-8af3-56c330da3999","columnName":"neet_rate_youth_not_in_employment_nor_currently_in_education","description":"Youth NEET rate (%)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"847ccbe2-95cb-4b59-b9b4-38da4ff10a07","columnName":"out_of_labour_force_inactivity_rate","description":"Inactivity rate (%)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"},{"id":"73212c12-226b-4349-ba26-2f671f713783","columnName":"time_related_underemployment_rate","description":"Time-related underemployment rate (%)","dataType":"TEXT","tags":null,"createdAt":"2026-07-09T22:22:35.210Z","updatedAt":"2026-07-09T22:22:35.210Z"}],"organization":{"id":"8998f38d-c75b-4861-9a0c-5ed451f7c88b","name":"NISR","infoEmail":null},"downloadCount":12,"downloadFormats":[{"format":"csv","label":"CSV"},{"format":"json","label":"JSON"},{"format":"xlsx","label":"Excel"}]},"timestamp":1787046744189}