The Relationship between Crude Oil Price Fluctuations and Economic Growth in Tanzania

Abstract

This paper studies the relationship between crude oil price fluctuations and economic growth in Tanzania employing a Vector Error Correction Model (VECM) to capture both short-run and long-run relationships from annual secondary time series data from 1988 to 2022. The ADF and PP unit root tests were used to check for stationarity and the variables became stationary at first differencing (I(1)). Johansen cointegration tests revealed at least one cointegration vector, indicating a strong long-run relationship among variables. Long-run equations were estimated using least squares, short-run equations were estimated using error correction model, and Granger causality tests were conducted to analyze dynamic relationships. Model diagnostic tests included the Jarque-Bera test for normality, the Lagrange multiplier for autocorrelation, and the Eigenvalue stability condition for model stability. The findings revealed that in the short run, the relationship between crude oil price fluctuation and GDP is insignificant, indicating that immediate fluctuation in oil prices does not significantly impact economic growth. However, there is a negative relationship between crude oil prices and GDP in the long run, reflecting the adverse impact of prolonged increases in crude oil prices on economic growth. Granger causality tests provided compelling insights, as crude oil prices and interest rates unidirectionally drive GDP, while GDP exhibits a bidirectional causality with both inflation and exchange rates. Moreover, the joint influence of these variables has a significant impact on GDP. The study recommended that in the long run, the diversification of energy sources to reduce dependency on oil import while broadening the economic base. In the short run, strategic oil reserves and financial instruments are to be used in managing crude oil price fluctuations. Furthermore, the study recommends that policymakers consider complex interrelationships among the variables when analyzing economic growth and when making policy decisions.