Revisiting ECOWAS-Eurozone exports in the light of asymmetry

Abstract

This article evaluates the asymmetric impact of exchange rate volatility on the exports of nine ECOWAS countries to the Eurozone. By comparing Autoregressive Distributed Lag (ARDL) and Nonlinear ARDL (NARDL) models, the study concludes that the effect of volatility on ECOWAS-Eurozone exports (EEE) is asymmetric. The study also investigates the impact of foreign income and prices on the EEE and categorises the goods and services that make up the EEE for each country based on their coefficients. The results show that exchange rate volatility has an asymmetric effect on the EEE, which comprise both substitute and inferior goods. The study recommends that ECOWAS authorities avoid using proportional policies to address increased and decreased volatility, as their impact on trade is asymmetric. The long-run coefficients of income for Nigeria, Togo, and Benin are -1.29, -4.67, and -2.64 respectively, indicating that their exports are dominated by inferior goods. The long-run coefficients of foreign price for Nigeria, Niger, and Burkina Faso are 5.32, 7.87, and 1.91 respectively, suggesting that their exports are mainly substitute goods. The authors confirm long-run asymmetry for three out of nine countries and short-run asymmetry for five countries. Only three countries have an asymmetric trade-volatility relationship in both the short and long run. The study suggests that Nigeria, Togo, and Benin diversify their economies, as their exports to the Eurozone are dominated by inferior goods and services. Additionally, the study recommends that the governments of Nigeria, Niger, and Burkina Faso provide support, as their goods and services are substitutes.

Keywords:

• Asymmetric relationship
• ECOWAS
• eurozone
• exchange rate volatility
• IGARCH
• NARDL

REVIEWING EDITOR:

• Elliott Caroline PhD, Editor-in-Chief, University of Warwick Faculty of Social Sciences, Professor of Economics, Economics, UNITED KINGDOM, Coventry

SUBJECTS:

• African Studies
• International Economics
• International Trade

JEL classification:

• C50
• F14
• F31

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data accessibility

The data that support the findings of this study is openly available in the database of International Financial Statistics at the following addresses

– Consumer/producer price index: https://data.imf.org/regular.aspx?key=61545849

– Exchange rate: https://data.imf.org/regular.aspx?key=61545850

– Trade of goods: https://data.imf.org/regular.aspx?key=61545859

Notes

1 See this site for more details: http://www.ecowas.int/member-states/

2 Specifically $R=E\times \frac{{\mathit{\text{CPI}}}^{*}}{\mathit{\text{CPI}}}$

3 The mean equation for the GARCH model of each country is the best ARIMA model for the natural logarithm of R.

4 The unit root tests are not reported to save space

5 To save space, the correlograms are not reported.

6 The highest lag order indicated by the lag selection criteria is 5. However, we consider using a maximum of 7 lags for all the countries to avoid losing many degrees of freedom.