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Monetary model of exchange rate determination under floating and non-floating regimes

Author

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  • Oyakhilome Wallace Ibhagui

Abstract

Purpose - The purpose of this paper is to empirically analyse how different exchange rate regimes affect the links between monetary fundamentals and exchange rates in Sub-Saharan Africa. Design/methodology/approach - Using the Pedroni method for panel cointegration, mean group and pooled mean group and the panel vector autoregressive technique, this study empirically investigates whether monetary fundamentals impact exchange rates similarly in both regimes. Thus, the author acquires needed and credible empirical data. Findings - The result suggests that the impact is dissimilar. In the floating regime, an increase in relative money supply and relative real output depreciates and appreciates the nominal exchange rate in the long run whereas in the non-floating regime, the evidence is mixed. Thus, exchange rates bear a theoretically consistent relationship with monetary fundamentals across SSA countries with floating regimes but fails under non-floating regimes. This provides evidence that regime choice is important if the relationship between monetary fundamentals and exchange rates in SSA are to be theoretically consistent. Originality/value - This study empirically incorporates the dissimilarities in exchange rate regimes in a panel framework and study the links between exchange rates and monetary fundamentals. The focus on how exchange rate regimes might alter the equilibrium relationships between exchange rates and monetary fundamentals in SSA is a pioneering experiment.

Suggested Citation

  • Oyakhilome Wallace Ibhagui, 2018. "Monetary model of exchange rate determination under floating and non-floating regimes," China Finance Review International, Emerald Group Publishing Limited, vol. 9(2), pages 254-283, July.
  • Handle: RePEc:eme:cfripp:cfri-10-2017-0204
    DOI: 10.1108/CFRI-10-2017-0204
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    Cited by:

    1. Kenny S, Victoria, 2019. "The effect of real shocks on business cycle fluctuations. A Bayesian panel vector autoregressive approach," MPRA Paper 95716, University Library of Munich, Germany.
    2. Sushil Kumar Rai & Akhilesh Kumar Sharma, 2023. "Forecasting Exchange Rate Volatility In India Under Univariate And Multivariate Analysis," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 26(1), pages 175-190, March.

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