Logo Lanfrica

DavidSamah/Kenya-Economics-Statistical-Report

Domain:

socioeconomic
Creator:
Dav
Host:
# Kenya Quarterly GDP Statistical Analysis **2021 Q1 – 2026 Q1** A reproducible economic-data analysis of Kenya's quarterly GDP growth, sector performance, momentum, acceleration/deceleration, direction changes, and extreme observations. ## What this project demonstrates This project turns publicly available Kenyan economic statistics into a structured analytical workflow. The analysis examines: * GDP growth trajectory * Sector-level growth * Sector acceleration and deceleration * Sector direction * Seasonally adjusted momentum * Extreme observations and anomalies * Potential structural changes requiring further investigation * Contribution analysis where validated level/weight data are available ## Key findings Across the validated 21-quarter growth dataset: * Manufacturing recorded positive growth in all 21 observations. * Information & Communication recorded positive growth in all 21 observations. * Financial & Insurance recorded positive growth in all 21 observations. * Agriculture showed greater variability, with 13 positive and 8 negative observations. * Mining & Quarrying also showed substantial variation, with 14 positive and 7 negative observations. * Accommodation & Food recorded exceptionally large growth observations during the post-disruption period, illustrating the importance of base effects when interpreting economic statistics. * Kenya's real GDP growth was **5.3% in 2026 Q1** in the validated dataset. ## Analytical approach The workflow separates: **Observation → Measurement → Pattern → Interpretation → Limitation** This is deliberate. The project does **not** treat statistical correlation or unusual movements as proof of causation. ### Important limitations The extracted quarterly level table contained structural extraction problems affecting later observations. Those incomplete observations were not fabricated or inferred. The validated growth dataset was therefore retained as the authoritative analytical dataset. Consequently: …