Analysis of the Impact of Crude Oil Price Changes on Economic Growth in Tanzania: ARDL Econometric Model

Authors

DOI:

https://doi.org/10.51867/scimundi.4.2.2

Keywords:

ARDL, Crude Oil Price, Economic Growth, Tanzania

Abstract

Crude oil is a valuable resource for boosting global economic growth. In this regard, this study examined the effect of crude oil price fluctuations on Tanzania’s economic growth from 1989 to 2022. Empirically this study utilized time-series data extracted from World Bank in particular, GDP per capital from World Development Indicators (WDI) as proxy of economic growth and Statistical Review of World Energy for Crude Oil prices. In this study, Renaissance growth theory, Autoregressive distributed lag model (ARDL), Dickey and Fuller tests, The Johansen test for cointegration, Breusch- Godfrey test for Serial correlation LM, Breusch-Pagan heteroscedasticity test, Jarque-Bera normality test, Error Correction Model (ECM), Granger Causality test, CUSUM and CUSUMSQ curves tests were used to analyse the data. This study revealed that crude oil price changes have positive and significant impact on Tanzania’s economic growth. A dollar increase in crude oil prices brings about 0.232791unit increase Tanzania’s economic upturn in the short run. The ARDL results also shows that error correction model (ECM) of -0.1000 (p= 0.0025) is significant with its value, suggesting a moderate speed of convergence to equilibrium after shock. Thus, this study recommends to policy maker and the government to ensure that they use fiscal policies that will reduce the adverse impact of the world crude oil prices hikes, finding other sources of energy and promoting research and development to explore and harness the oil fossils to produce oil and reduce oil importations and increase oil exportations to further increase economic growth.

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Published

2024-07-03

How to Cite

Mbwambo, S. K., Mchukwa, E. W., & Mchomvu, Z. B. (2024). Analysis of the Impact of Crude Oil Price Changes on Economic Growth in Tanzania: ARDL Econometric Model. SCIENCE MUNDI, 4(2), 11–20. https://doi.org/10.51867/scimundi.4.2.2