Vol 7 No 2 (2020)
Articles

Does the Oil Price Influence the Exchange Rates in Nigeria? Empirical Evidence from Wavelet and Causality Approaches

Tomiwa Sunday Adebayo
Cyprus International University, Nicosia Mersin 10- Turkey, Faculty of Economic and Administrative Science, Department of Business Administration, Turkey.
Published June 10, 2020
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155 Views | 69 Downloads
Keywords
  • Exchange rate, Oil price, Wavelet tools, Granger causality, Toda Yamamoto causality, Variance decomposition.
Citations
How to Cite
Adebayo, T. S. (2020). Does the Oil Price Influence the Exchange Rates in Nigeria? Empirical Evidence from Wavelet and Causality Approaches. Asian Journal of Economics and Empirical Research, 7(2), 126-135. https://doi.org/10.20448/journal.501.2020.72.126.135

Abstract

This study explores the connection between the exchange rate and oil price within the framework of time and frequency utilizing monthly data between January 2007 and March 2020. The study deployed the wavelet tools to investigate this relationship. Furthermore, Granger and Toda Yamamoto causality tests were employed as a robustness check for the wavelet coherence techniques. Findings from the wavelet power spectrum shows; (a) a significant vulnerability in the exchange rate between 2014M6 and 201412, between 2017M1 and 2017M12 2016M1; and (b) a significant vulnerability was found in oil price between 2008M1 and 2008M12, between 2014M1 and 2014M12. The wavelet coherence technique reveals; (a) negative co-movement between the exchange rate and oil price between 2009M10 and 2011M3, between 2012M1 and 2012M3, between 2014M2, 2015M6 and between 2019M2 and 2019M11. The Granger and Toda Yamamoto causality tests reveal a bidirectional interaction between oil price and exchange rate. The variance decomposition shows that as the months dwindle, 40.2% and 40.5% of discrepancy in the exchange rate can be explained by oil price in the twenty-third and twenty-fourth month respectively. This signifies that oil price is a good predictor of the exchange rate in the long term. Also, the variance decomposition and causality tests provide a piece of supportive evidence for the wavelet coherence technique. Key recommendations are suggested based on these findings.

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