Analyzing Uganda’s Hydro-power and Policy Nexus: Insights from a Structural Vector Auto-Regression Mode

Uganda’s transition to renewable energy is critical for achieving sustainable development, yet significant challenges persist in energy access, infrastructure expansion and policy effectiveness. This study utilizes a structural vector auto-regression SVAR modelling to forecast and analyze Uganda’s hydro-power on economic growth and to quantify interactions between policy shocks and macroeconomic outcomes, using time-series data (2026-2030) depending on history data from national energy reports and macroeconomic indicators. Endogenous variables (hydro-power capacity, electrification rates, industrial gross domestic product GDP and tariffs) and exogenous shocks (oil prices and climate finance) are evaluated through impulse response functions IRFs and variance decomposition VD. Results indicate that hydro-power investments generate effects with substantial time lags. A 120 MW capacity increase is associated with a 2.7% rise in electrification rates (peaking around 2029), a 0.6% increase in industrial GDP (peaking around 2027), and a cumulative reduction in electricity tariffs of 0.025 USD/kWh over a ten-year period. VD attributes 42% of electrification variability to hydro-power shocks. Oil price volatility significantly affects macroeconomic stability. A 15 USD/barrel increase reduces GDP growth by 0.8% within two years, though this effect can be mitigated by compensatory hydro-power investments of 30 USD M. Climate finance exhibits strong but diminishing marginal returns. A 100 USD M investment boost achieves a 2.7% increase in electrification rates by 2030, accounting for 35% of the observed variation in electrification access.