Impact of inflation threshold on economic growth in East African countries

Abstract

The study examined the impact of inflation threshold on economic growth in five East African Countries: Burundi, Kenya, Rwanda, Tanzania, and Uganda. The study specifically sought to examine the relationship between inflation and economic growth within East Africa for the period of 1994 to 2019, estimate the threshold level of inflation within East Africa and determine the impact of inflation threshold on economic growth of the East African Countries. To determine the long-run relationship between inflation and economic growth among East African countries, the panel datasets were tested for cointegration, and in the estimation of the inflation threshold and to test the effect of inflation threshold on economic growth in East Africa, a panel threshold regression model was estimated with GDP as the dependent variable and Inflation threshold as the independent variable. The panel threshold regression model used the bootstrap method by Hansen (1999) to find the number of thresholds according to the principle of the minimum residual sum of squares where the threshold estimator is the residual sum of squares (RSS). There was strong evidence that all panels in the data are cointegrated hence the existence of a long run relationship between the study variables inflation and GDP per capita growth. The value of the threshold variable in the threshold model was 7.1422; therefore, the threshold of inflation in East Africa is 7.14%. The direction of GDP per capita growth before and after the inflation threshold value changes significantly, when the threshold value is not reached, increase in inflation will cause GDP per capita to increase, while upon reaching the threshold, it will prompt the reduction in GDP per capita growth. The study recommended that East African monetary policymakers should set inflation targets below 7.4% to avoid the growth detrimental effects of high inflation, and also switch public expenditure from consumption to investment to promote growth and keep inflation low. Further research needs to be done to fill the gaps in this study by enlarging the data set and analyzing how the degrees of trade openness, capital accumulation and government expenditures can influence the nonlinearity of the inflation–growth relationship.