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Purpose - This article aims to investigate the effect of energy consumption on economic growth in Tanzania. It is a quantitative investigation that is structured by the time series data from the World Bank (WB) database which started from 1990 to 2019. The article uses variables of Energy consumption (EC) and Economic growth (GDP). The variables are measured in GDP (Constant US$) and EC (MTOE). Methodology – To obtain the significant estimated results, this study uses econometric tools for both theoretical and empirical analysis such Augmented Dickey-Fuller (ADF) test for identifying stationary and nonstationary time series data, Engel and Granger test for determination of the existence or absence of cointegration relationship, Vector Error Correction Model (VECM) for determining the speed of adjustment (ECT) and Classical Granger-causality test for a causal relationship between economic growth and consumption. Findings- The core findings from the study are; the cointegration relationship between Energy consumption (EC) and Economic growth (GDP), a bidirectional causal relationship between energy consumption (EC) and Economic growth (GDP) in Tanzania. Therefore, the study accepts the energy feedback hypothesis that revealed to exist both a long-run effect and short-run effect between the energy consumption and economic growth in Tanzania. Conclusion- The estimated results of this study provide the information to Tanzanian policymakers with a new dimensional approach to Tanzanian economic growth through an increase in energy consumption use. Although Tanzanian government has a huge and long term sustainable project of increasing energy power by adding 2115megawatts to Tanzanian national grid using the Stigler gorge or Julius Nyerere Hydroelectric power at Rufiji River but also Tanzania should invest to the short energy projects consumptions that can facilitate and improve the economic development of domestic hoods.

Empirical analysis of energy consumption and economic growth in Tanzania: based on Engel and Granger tests