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International Journal of Statistics and Applied Mathematics

2022, Vol. 7, Issue 2, Part A

The asymmetric relationship between oil price shocks and macroeconomic fluctuation in Tanzania: A multivariate time series model approach


Author(s): Twahil Hemed Shakiru and Xiaohui Liu

Abstract: As a developing oil importer, Tanzania relies heavily on crude oil imports for the majority of its industrial and socioeconomic operations. Hence, verifying the link between oil price shocks and macroeconomic variables is critical for effective policy formulation and investment decisions. This paper examines the asymmetric relationship between oil price shocks and macroeconomic fluctuations using the linear and nonlinear autoregressive distributed lag models for Tanzania from 1989 to 2020 data set. Oil price and macroeconomic indicators are not cointegrated according to the results of the asymmetric autoregressive distributed lag model (NARDL), which indicates a specification short-run relationship between oil price shocks and macroeconomic indicators. Meanwhile, the analysis shows that the fitted linear ARDL (1, 0, 0) and nonlinear ARDL (1, 0, 0, 0, 1) time series models are significant, which indicate that there is a linear and assymetric relationship between oil price shocks and macroeconomic variables. The linear model (ARDL) shows that the lag 1 of oil price has a positive significant effect while the asymmetric model (NARDL) shows that the negative change in the inflation rate of Tanzania has a negative significant effect on oil price shock.

DOI: 10.22271/maths.2022.v7.i2a.794

Pages: 44-50 | Views: 148 | Downloads: 7

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How to cite this article:
Twahil Hemed Shakiru, Xiaohui Liu. The asymmetric relationship between oil price shocks and macroeconomic fluctuation in Tanzania: A multivariate time series model approach. Int J Stat Appl Math 2022;7(2):44-50. DOI: 10.22271/maths.2022.v7.i2a.794
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