About

roject Title: US Federal Reserve Policy as a Leading Indicator for Kenyan Inflation
What I Built:

A macro signal analysis project examining whether US Federal Reserve interest rate changes predict Kenyan inflation with a measurable time lag. The project pulls real Fed Funds Rate and US CPI data from the FRED API, constructs year-on-year inflation metrics, and runs a lagged Pearson correlation analysis across 0–12 month lags.
Workflow:

Fetched real FRED data (Fed Funds Rate, US CPI) via REST API; Kenya CPI and KES/USD modelled as simulated proxies
Cleaned and resampled all series to monthly frequency
Computed year-on-year inflation rates for both economies
Ran lagged correlation analysis (0–12 months) between US Fed Rate and Kenya inflation
Visualised time series, lag correlations, and KES/USD depreciation trend
Deployed chart and insight summary on Zerve
Key Insight:

The strongest correlation between US Fed Rate changes and Kenyan inflation occurs at an 8-month lag (r = 0.147, p = 0.055). While the result sits just outside conventional statistical significance — partly due to the use of simulated Kenya CPI data — the consistent positive correlation across all lags (0–12 months) supports the hypothesis that US monetary tightening transmits to Kenyan price levels with roughly a two-quarter delay, likely via the KES/USD exchange rate channel raising the cost of dollar-denominated imports such as fuel, wheat, and machinery.