Research Article Modelling the Dependency between Inflation and Exchange Rate Using Copula Charles Kwoﬁe , Isaac Akoto, and Kwaku Opoku-Ameyaw Department of Mathematics and Statistics, University of Energy and Natural Resources, Sunyani, Ghana Correspondence should be addressed to Charles Kwoﬁe; charles.kwoﬁe@uenr.edu.gh Received 26 March 2020; Revised 12 May 2020; Accepted 30 May 2020; Published 17 June 2020 Academic Editor: Aera avaneswaran Copyright©2020CharlesKwoﬁeetal.isisanopenaccessarticledistributedundertheCreativeCommonsAttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In this paper, we propose a copula approach in measuring the dependency between inﬂation and exchange rate. In unveiling this dependency, we ﬁrst estimated the best GARCH model for the two variables. en, we derived the marginal distributions of the standardised residuals from the GARCH. e Laplace and generalised t distributions best modelled the residuals of the GARCH(1,1) models, respectively, for inﬂation and exchange rate. ese marginals were then used to transform the standardised residuals into uniform random variables on a unit interval [0, 1] for estimating the copulas. Our results show that the dependency between inﬂation and exchange rate in Ghana is approximately 7%. 1. Introduction Macroeconomic variables such as inﬂation and exchange rate are very fundamental in any country’s economy. ey are the key indicators of performance of an economy as a whole. Several studies have focused on showing the dy- namics and dependencies between these macroeconomic variables. According to the literature, inﬂation is of high priority to central banks because it gives an indication of price stability in an economy. Many argue that having high inﬂation leads to lower savings of individuals and also downplays an economy’s international competitiveness. On the other hand, it is believed that a low inﬂation rate pro- motes economic growth. Some ways in which governments control inﬂation is by targeting exchange rates, interest rate dynamics, and others. e literature somehow provides diﬀerent results when it comes to the kind relationship between inﬂation and other macroeconomic variables such as the exchange rate. ese conﬂicting results in the relationship between inﬂation and exchange rate diﬀer with countries and data periods. Hence, the exchange rate can be said to be linked to inﬂation rate volatility through importation of goods and materials needed for production. e dependency of macroeconomic indicators has been shown in several papers to have some existing relationship [1–3]. However, this relationship has been unveiled using diﬀerent approaches and methods. For instance, Kwoﬁe and Ansah [4] used the autoregressive distributed lag (ARDL) model, while Arslaner et al. [1] used Markov switching regression and vector autoregression (VAR) methods in establishing some dynamics between inﬂation and exchange rate. We are motivated by the work of Barro and Gordon [5] who pioneered and proposed an inﬂation and exchange rate nexus in relation to credibility of the monetary policy. eir argument was that any economy with a stable or ﬁxed ex- change rate regime has the tendency of lowering the inﬂation by authorities’ increasing credibility. is assertion was echoed in [6, 7]. ey both stated that having a stable currency is not just a good step for maintaining inﬂation but also enhances monetary policy eﬃciency. Anthony and Nkegbe [8] studied the relationships be- tween several macroeconomic variables in Ghana using cointegration techniques. eir results showed a signiﬁcant relationship between inﬂation and exchange rate in Ghana. Similarly, Gyebi and Boafo [9] stated in their conclusion that the exchange rate and money supply are the main macro- economic variables responsible for inﬂation changes in the Ghanaian economy. Nortey et al. [10] stated that one of the main aims of Ghana’s central bank is to maintain stability in Hindawi Journal of Probability and Statistics Volume 2020, Article ID 2345746, 7 pages https://doi.org/10.1155/2020/2345746