Exchange rate modelling in the development community using the ARDL cointegration approach: The case of emerging markets

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Abstract

Despite rising interest in African economies, there is little prior research on the determinants of exchange rate movements in the region. This paper examines the monthly exchange rates of the country members of the Southern African Development Community (SADC) from 1990 to 2010 inclusive. Long-run equilibrium exchange rate models are established, exchange rate determinants are identified, and ex-post forecasts are generated for a period of 18 months (Sekantsi, 2011). The autoregressive distributed lag (ARDL) cointegration model is used in this paper, given its statistical advantages over commonly, applied cointegration techniques. Findings show that the ARDL method generates accurate forecasts for eight out of 11 sampled exchange rates. In keeping with earlier literature (e.g., Redda & Muzindusti, 2017; Zerihun & Breitenbach, 2017; etc.), findings suggest that the chances of SADC member countries fulfilling the requirements of a currency union are quite low. This paper marks one of the first attempts in the literature to forecast exchange rates in SADC using the ARDL approach (Pesaran & Shin, 1995). The results would be of interest to policy-makers, researchers and investors.

Keywords: African Economies, Exchange Rates, Regional Integration, Cointegration

Authors’ individual contribution: Conceptualization – A.A. and C.K.; Methodology – A.A.; Writing – Original Draft – A.A. and C.K.; Investigation – C.K.; Resources – A.A.; Supervision – C.K.; Project Administration – A.A.; Writing – Review & Editing – C.K.

Declaration of conflicting interests: The Authors declare that there is no conflict of interest.

JEL Classification: C53, F31, F36

Received: 23.05.2020
Accepted: 03.07.2020
Published online: 09.07.2020

How to cite this paper: Aljandali, A., & Kallandranis, C. (2020). Exchange rate modelling in the development community using the ARDL cointegration approach: The case of emerging markets. Risk Governance and Control: Financial Markets & Institutions, 10(2), 53-70. https://doi.org/10.22495/rgcv10i2p5