This study empirically investigates the impact of foreign direct investment (FDI) on GDP growth in East Africa.The study employs annual panel data, obtained from the United Nations aggregate database for the selected countries in the region over the period 1970-2015. Unlike time series and cross-sectional, panel dataset reduces the identification problems in the presence of endogenous variables and estimates more robust and efficient parameters.This study uses methods of panel autoregressive distributed lag and random effect models combined with time scaling wavelet decomposition analysis in order to show a panel of short-, medium-, and long-run effects for the entire region and individual countries. Flowing FDI into developing countries is one of the most dynamic resources which play an important role in economic development by supplementing domestic savings in capital accumulation, creating innovation and income growth, transferring modern technology and employment generation, and providing a means for creating stable and long-lasting economic growth. Examining the correlation between FDI and economic growth, cannot identify the direction of causation using traditional approaches such as dynamic panel ARDL. However, the time scaling wavelet decomposition method can help to recognize the dynamic causality in time horizons. The Granger causality of wavelet analysis in a panel indicates that there are bi-directional dynamic relationships between real GDP and FDI in the short, medium, and long run. According to the empirical evidence, the long-run estimated coefficients reveal that a one percentage increase in FDI significantly increases the real GDP by approximately 0.16 percent in a panel of seven East African countries.