Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Modeling the Co-Movement of Inflation and Exchange Rate

Version 1 : Received: 31 March 2020 / Approved: 31 March 2020 / Online: 31 March 2020 (22:45:00 CEST)

How to cite: Dzupire, N.C. Modeling the Co-Movement of Inflation and Exchange Rate. Preprints 2020, 2020030465. Dzupire, N.C. Modeling the Co-Movement of Inflation and Exchange Rate. Preprints 2020, 2020030465.


Inflation and exchange rates have great influence on consumer prices especially on imports and exports. Exchange rate fluctuations create inefficiency and distort world prices whereas changes in inflation rates have a direct impact on consumer goods prices which incidentally include exchange rates. There is a direct interdependence between inflation and exchange rates and this paper is aimed at investigating this relationship in dynamic context. It tries to find out how changes in inflation and exchange rates impact on another by adopting the econometric and copula approaches. Both inflation and exchange rates data are susceptible to volatility clustering, possess fat tails and are skewed coupled with conditional heteroskedasticity. Hence we model the univariate distributions by using ARMA$(p,q)$-GARCH$(x,y)$ so as to capture the most important stylized features of inflation and exchange rates. A bivariate model is then constructed by coupling the marginal distributions of inflation and exchange rates using the survival Clayton copula. Empirical results from monthly inflation and exchange rates data show positive correlation between the two based on Kendall $\tau$ test which confirms that a change in inflation results in change of exchange rates an vice versa hence there is co-movement. Furthermore, by the Granger causality test, exchange rates spikes cause changes in inflation rates. The results of the study have implications on economic policy design and hedging strategies for traders on imports and exports.


inflation; exchange rates; heteroskedasticity; Granger causality; copula, bivariate; volatility clustering


Computer Science and Mathematics, Probability and Statistics

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