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The impact of macroeconomic variables on exchange rate volatility in Ghana: The Partial Least Squares Structural Equation Modelling approach

https://doi.org/10.1016/j.ribaf.2017.07.081Get rights and content

Abstract

This paper employs the Partial Least Squares Structural Equation Modelling approach to analyse the impact of inflation, monetary policy rate, current account balance, money and quasi money supply per GDP, annual GDP growth rate and the total external debt on the Cedi to the US dollar exchange rate in Ghana with data spanning 1975–2014. The results show that the macroeconomic variables explain 82% of the adjusted variance in the cedi-dollar exchange rate with monetary policy rate, inflation and current account balance contributing 8.2%, 10.5% and 19.2% respectively. Money and quasi money supply per GDP, total external debt and annual GDP growth rate contribute 15%, 14.9% and 15.1% respectively to the explained variance in cedi-dollar exchange rate. Whereas monetary policy rate, inflation and current account balance have negative relationships with the cedi-dollar exchange rate, money and quasi money supply per GDP, total external debt and annual GDP growth rate have positive relationships with the cedi-dollar exchange rate. These results underpin the conclusion that inflation, monetary policy rate, current account balance, money and quasi money supply per GDP, annual GDP growth rate and the total external debt are significant predictors of the cedi-dollar exchange rate in Ghana.

Introduction

Exchange rate is defined as the value of a country’s currency in terms of another currency. In international trade, a country’s exchange rate could be used as the barometer of its international competitiveness. Consequently, volatility in exchange rate has serious far-reaching consequences for policymakers, investors, firms and consumers. For instance, exchange rate volatility negatively impacts investment decision making because it makes return on investment uncertain. Volatility of the exchange rate between the Ghana cedi and the international currencies especially the dollar has been a major concern to most Ghanaians especially entrepreneurs.

The adoption of the floating or flexible exchange rate system after the demise of the Bretton Woods institutions in 1973 has caused exchange rate fluctuations to be more violent than ever (Chang and Su, 2014). For instance, in the first quarter of 1986 after Ghana had adopted the managed exchange rate regime, about 0.01 Cedis exchanged for a dollar. However, by the end of April 2015, the rate had skyrocketed to 3.84, constituting a depreciation of 98.7% over the period (Adu et al., 2015). It is on record that the fluctuations in exchange rate could be influenced, in the short or long-run, by macroeconomic fundamentals, such as interest rate, output and price level. Consequently, the linkages between exchange rates and fundamentals are always given chary scrutiny by monetary authorities (Chang and Su, 2014). However, empirical studies on the relationship between exchange rate and macroeconomic fundamentals have yielded inconclusive results (Kwakye, 2015, Ray, 2008, Flood and Rose, 1999). Whereas some of the studies find a positive impact of macroeconomic fundamentals on exchange rate (Ray, 2008), some find that macroeconomic fundamentals play an insignificant role in understanding exchange rate volatility (Mark, 2009; Flood and Rose, 1999). Indeed, some studies argue that the relationship between macroeconomic variables and exchange rate is nonlinear (Yuan, 2011).

Pivotal to the debate on the determinants of exchange rate is the issue of the analytical technique adopted. The monetary model of exchange rates developed by MacDonald and Taylor (1994) applies the vector autoregressive (VAR) approach and utilizes the dollar-sterling exchange rate, as well as UK–US macroeconomic variables, in the period 1976–1990. The study concludes that the out-of-sample forecasting ability of an unrestricted monetary model achieves better results compared to the naïve random walk process. Mark (1995) conducts alternative bootstrap distributions under the null hypothesis that exchange rate is unpredictable. The study adopts a long-horizon regression and finds that monetary fundamentals have long-run forecasting ability to exchange rate changes. The Mark and Sul (2001)’s panel cointegration analysis of the interaction between nominal exchange rates and their fundamental values for a panel of 19 countries produces results to the effect that there is cointegration between exchange rates and fundamentals. However, the bivariate contingration tests performed by Engel and West (2005) fail to find cointegration between exchange rates and fundamentals. Similarly, Chang and Su (2014) analyse the dynamic relationship between exchange rates and macroeconomic variables data from Pacific Rim countries (monthly observations from 1986:01 to 2011:12 for Canada, Chile, Indonesia, Japan, S. Korea, Malaysia, the Philippines, Taiwan and the U.S., 1991:01 to 2012:07 for Singapore, and 1987:01 to 2006:12 for Thailand) and report that the conventional cointegration tests fail to find the long-run equilibrium for any country-pairs except Taiwan, but cointegration tests with structural breaks demonstrate the long-run connections between exchange rates and fundamentals for some country-pairs.

The above conflicting results have led some studies including Mark and Sul (2001) to posit that the elusive evidence of a long-run equilibrium relationship between exchange rates and fundamentals is attributable to the low power of conventional tests. Indeed, Evans and Lyons (2002) assert that the explanatory power of exchange rate determination models is essentially zero. Our motivation for this study is, thus, predicated on the argument that if the extant models are incompetent to establish any stable relationship between exchange rate and macroeconomic variables then the search for new models should go on unabated. It is our humble submission that the current study which applies the Partial Least Squares Structural Equation Modelling (PLS-SEM) approach to examine the effect of macroeconomic variables on exchange rate represents a contribution to the models for assessing the exchange rate-fundamentals nexus.

We apply the PLS-SEM approach to analyse data from Ghana which is one of the countries in Sub-Saharan Africa. Our choice of Ghana is influenced by two main reasons. First, Ghana is an import-dependent country with a tumbling currency relative to foreign currencies especially the dollar. Thus, unravelling the structural linkages between the cedi-dollar exchange rate and macroeconomic fundamentals should inform future policy interventions. Second, methodologically, it is our case that this study represents a marked departure from the extant literature in Ghana as far as the relationship between exchange rate and macroeconomic variables is concerned. The few studies that have been done with data from Ghana (e.g. Insah and Chiaraah, 2013; Mumuni and Owusu-Afriyie, 2004) have resorted to the use of regression and cointegration analytical methods, which lack the capacity to determine the complex structural relationship between macroeconomic variables and the cedi-dollar exchange rate.

We submit that the current study is relevant for some reasons. Exchange rate stability achieved through stable macroeconomic variables gives credibility to the economy and communicate very good news to both local and foreign trade partners. Fluctuations in exchange rates may have a direct influence on price stability, financial stability as well as trade balance (Ozkan and Erden, 2015). Importantly, the adoption of inflation targeting strategy by many central banks has accentuated the need to monitor the connection between exchange rates and macroeconomic variables. The findings of the study provide fresh insights into the relationship between exchange rate and macroeconomic fundamentals which will immensely assist central banks including the Bank of Ghana to monitor the macroeconomic variables that impact exchange rate. A deeper understanding of the complex structural relation between macroeconomic variables exchange rate provides insights to policy makers in budgeting for the various sectors of the economy to ensure its (the economy’s) efficient performance.

Section snippets

Selection of variables

Based on the extant literature (Kwakye, 2015, Sani and Idakwoji, 2014, Abbas et al., 2012, Adom et al., 2012, Kim and Roubini, 2000) we assess the impact of inflation (INF), monetary policy rate (MPR); current account balance (CAB), money and quasi money supply per GDP (M2GDP), annual GDP growth rate (GDPGRO), and total external debt (EDBTOT) on the Cedi-dollar exchange rate (EXRATE).

EXRATE is the dependent variable in our model. INFL, MPR, CAB, M2GDP, GDPGRO and EDBTOT are the independent

NEGCORR” latent variable

MPR, INF and CAB have inverse relationships with EXRATE. It implies that an increase in MPR, INF and CAB is likely to trigger the depreciation of the Ghana cedi against the dollar. Fig. 10 illustrates the trend of these indicators with the cedi/dollar exchange rate.

“POSCORR” latent variable

GDPGRO, M2GDP and EDBTOT correlate positively with EXRATE. Fig. 11 depicts the relationships between the three macroeconomic variables and EXRATE.

Convergent validity

The combined loadings and cross-loadings are used to describe convergent validity of

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