ANALYSIS OF INFLATION DRIVERS ON ECONOMIC GROWTH IN THE EAST AFRICAN COMMUNITY COUNTRIES USING A FIXED EFFECTS PANEL MODEL CASE STUDY: KENYA, RWANDA, TANZANIA AND UGANDA (2000-2022)

Abstract

High inflation in developing economies has a wide-ranging impact, eroding purchasing power, impeding economic stability, competitiveness, and investment, and ultimately leading to decreased demand for goods and services. The primary goal of this study was to comprehensively evaluate the drivers of inflation and their impact on the economic growth of Kenya, Rwanda, Tanzania, and Uganda over a 22-year period spanning from 2000 to 2022. The study also sought to achieve specific objectives, including the exploration of the factors influencing inflation, an assessment of the extent of economic growth as influenced by these inflation drivers, and an analysis of the effects of these inflation determinants on the economic growth of the aforementioned East African nations. To achieve these objectives, the study harnessed secondary panel data and conducted rigorous data analysis through panel regression analysis, utilizing data curated from the World Bank. An econometric model was constructed to gain a more profound comprehension of the intricate relationship between inflation drivers and economic growth, measured by Gross Domestic Product (GDP), in the Rwandan, Kenyan, Tanzanian, and Ugandan economies. The results of this study underscore the significance of various variables, including Foreign Direct Investment, interest rates, the money base, population growth rate and exchange rate (all p-values < 0.05), in influencing inflation levels across the four countries. These variables also showed a nuanced relationship with GDP, with Foreign Direct Investment and exchange rate showing a negative impact and the money base, population growth rate and interest rate demonstrating a positive influence. The R-squared value of 0.927 suggests that 92.7% of the economic growth variations in the studied nations are explained by the independent variables. Furthermore, the F statistics result with a p-value less than 0.05 confirms the strong fit of the regression model, offering convincing evidence of its reliability.