Revisiting ECOWAS-Eurozone exports in the light of asymmetry

Figures & data

Figure 1. Rolling correlation between the natural logarithms EEE and volatility (1999 to 2017).

Figure 2. ECOWAS-Eurozone exports in million dollars (1999 to 2017).

Figure 3. Bar chart for the total ECOWAS-Eurozone exports in million dollars (1999 to 2017).

Figure 4. Pie chart for the total ECOWAS-Eurozone exports in million dollars (1999 to 2017).

Figure 5. Network graph of literature on exchange rate volatility based on author keywords.

Figure 6. Network graph of literature on exchange rate volatility by author.

Figure 7. The architecture of the GARCH estimate (source: authors).

Table 1. Mean and variance equations of the GARCH.

	Mean Equation			GARCH Equation
Country	${\mathbf{R}}_{\mathbf{t}-\mathbf{1}}$	${\mathbf{R}}_{\mathbf{t}-\mathbf{2}}$	${\epsilon }_{t-1}$	${\epsilon }_{t-1}^2$	${\mathbf{h}}_{\mathbf{t}-\mathbf{1}}$
Nigeria	−0.251***		0.503***	−0.039***	1.039***
Ghana	0.175***	0.240***		−0.018***	1.018***
Senegal	0.016***			−0.057***	1.057***
Niger	0.216***			0.066***	0.934***
Burkina Faso	0.177***			0.034**	0.966***
Cote D’Ivoire	0.227**			0.068***	0.932**
Mali	0.255***			0.045***	0.955***
Benin	−0.023***			−0.057***	1.057***
Togo	0.224**			0.081***	0.919***

Note. *** and ** stand for 1% and 5% level of significance respectively.

Table 2. F-statistic of cointegration relationship.

Country	Test Statistic	F-Value	I(0)	I(1)
Nigeria	Symmetric Model (ARDL)	5.677***	2.79	3.67
	Asymmetric Model (NARDL)	16.349***	2.56	3.49
Ghana	Symmetric Model (ARDL)	3.025	2.79	3.67
	Asymmetric Model (NARDL)	3.361*	2.56	3.49
Mali	Symmetric Model (ARDL)	9.953***	2.79	3.67
	Asymmetric Model (NARDL)	12.061***	2.56	3.49
Senegal	Symmetric Model (ARDL)	29.713***	2.79	3.67
	Asymmetric Model (NARDL)	30.297***	2.56	3.49
Niger	Symmetric Model (ARDL)	33.622***	2.79	3.67
	Asymmetric Model (NARDL)	31.531***	2.56	3.49
Togo	Symmetric Model (ARDL)	4.3424**	2.79	3.67
	Asymmetric Model (NARDL)	8.604***	2.56	3.49
Benin	Symmetric Model (ARDL)	7.0716***	2.79	3.67
	Asymmetric Model (NARDL)	7.475***	2.56	3.49
Burkina Faso	Symmetric Model (ARDL)	10.191***	2.79	3.67
	Asymmetric Model (NARDL)	11.412***	2.56	3.49
Cote D’Ivoire	Symmetric Model (ARDL)	8.402***	2.79	3.67
	Asymmetric Model (NARDL)	18.544***	2.56	3.49

Note. ***, **, and * denote “rejection” of the null hypothesis that there is no long-run relationship at 1%, 5% and 10% level of significance respectively. The critical value bounds are obtained from Pesaran et al. (2001). The ARDL lower (upper) critical values for 1% and 10% are 3.65 (4.66) and 2.37 (3.20), respectively. While the NARDL lower (upper) critical values for 1% and 10% are 3.29 (4.37) and 2.20 (3.09), respectively.

Table 3. Short run estimates of the NARDL.

	Nigeria	Ghana	Mali	Senegal	Niger	Togo	Benin	Burkina	Cote
$\Delta \mathit{\text{ln}}{X}_{t-1}$		−0.445***				−0.233***	−0.252***
$\Delta \mathit{\text{ln}}{X}_{t-2}$									0.127**
$\Delta \mathit{\text{ln}}{X}_{t-3}$	0.158***
$\Delta \mathit{\text{ln}}{X}_{t-5}$					0.121**
$\Delta \mathit{\text{ln}}{X}_{t-6}$	0.124**						−0.151**
$\Delta \mathit{\text{ln}}{X}_{t-7}$					0.124**		−0.128**
$\Delta \mathit{\text{ln}}{Y}_{t-1}$	3.350**				21.873**
$\Delta \mathit{\text{ln}}{Y}_{t-2}$									−5.973**
$\Delta \mathit{\text{ln}}{Y}_{t-3}$				3.288**	18.577**		−8.045*
$\Delta \mathit{\text{ln}}{Y}_{t-4}$							−9.794**
$\Delta \mathit{\text{ln}}{Y}_{t-5}$							8.996**
$\Delta \mathit{\text{ln}}{Y}_{t-6}$							8.608**
$\Delta \mathit{\text{ln}}{Y}_{t-7}$							9.006**
$\Delta \mathit{\text{ln}}{P}_t$	10.503***							16.747**
$\Delta \mathit{\text{ln}}{P}_{t-1}$			−1.429**					−1.870***
$\Delta \mathit{\text{ln}}{P}_{t-2}$		7.438**					22.4260**
$\Delta \mathit{\text{ln}}{P}_{t-3}$				−9.429***				−18.643***
$\Delta \mathit{\text{ln}}{P}_{t-4}$		−8.334**	−1.688***			26.099***
$\Delta \mathit{\text{ln}}{P}_{t-5}$	7.884**	7.869**	−19.600**
$\Delta \mathit{\text{ln}}{P}_{t-6}$									0.707**
$\Delta \mathit{\text{ln}}{V}_t^{+}$				2.303***
$\Delta \mathit{\text{ln}}{V}_{t-1}^{+}$
$\Delta \mathit{\text{ln}}{V}_{t-3}^{+}$				−1.407*
$\Delta \mathit{\text{ln}}{V}_t^{-}$								5.110**
$\Delta \mathit{\text{ln}}{V}_{t-1}^{-}$							1.425**
$\Delta \mathit{\text{ln}}{V}_{t-3}^{-}$							−1.335**
$\Delta \mathit{\text{ln}}{V}_{t-4}^{-}$		0.709**					−1.410**
$\Delta \mathit{\text{ln}}{V}_{t-6}^{-}$			−5.410***
$\Delta \mathit{\text{ln}}{V}_{t-7}^{-}$					−7.235**	−2.526**
Wald-Sp	2.934*	0.283	1.525	0.017	0.237	0.726	2.0335	3.345	2.303
Wald-Sn	6.227**	0.102	2.778*	0.044	0.364	2.248	0.891	3.837*	3.958*

Note that ***, **, and * indicate significance at 1%, 5% and 10% respectively. While Wald-S_p and Wald-S_n stand for the Wald test of positive and negative volatilities respectively.

Table 4. Model selection and diagnostic tests.

Test Statistic	SC	H	AR	CQ	CS	SIC
Nigeria ARDL	3.40(0.18)	13.38(0.15)	0.29(0.59)	S	S	0.182
Nigeria NARDL	3.41(0.49)	75.82(0.17)	3.02(0.08)	S	S	0.035
Ghana ARDL	0.12(0.94)	10.68(0.30)	0.86(0.35)	S	S	0.738
Ghana NARDL	2.07(0.72)	54.65(0.79)	2.76(0.10)	S	S	0.769
Senegal ARDL	0.83(0.66)	11.96(0.22)	3.17(0.07)	S	S	0.077
Senegal NARDL	0.32(0.99)	72.72(0.05)	5.70(0.02)	S	S	0.049
Niger ARDL	2.30(0.32)	19.27(0.02)	0.15(0.70)	S	U	3.639
Niger NARDL	0.88(0.93)	50.07(0.91)	0.24(0.63)	S	S	3.647
Cote ARDL	2.68(0.26)	43.54(0.00)	45.34(0.00)	S	U	1.188
Cote NARDL	5.64(0.23)	122.95(0.00)	65.95(0.00)	S	S	1.178
Burkina ARDL	0.91(0.63)	7.59(0.58)	16.50(0.00)	S	S	1.496
Burkina NARDL	3.03(0.55)	91.98(0.00)	15.81(0.00)	S	S	1.453
Togo ARDL	2.56(0.28)	47.32(0.00)	20.85(0.00)	S	U	1.979
Togo NARDL	6.15(0.19)	79.81(0.00)	11.74(0.00)	S	U	1.924
Benin ARDL	0.69(0.71)	35.65(0.00)	5.07(0.02)	S	S	2.175
Benin NARDL	1.48(0.83)	169.52(0.50)	7.58(0.01)	S	S	2.123
Mali ARDL	2.76(0.25)	6.21(0.72)	0.25(0.62)	S	S	1.780
Mali NARDL	3.49(0.48)	54.87(0.44)	0.03(0.87)	S	S	1.764

SIC, SC, H, AR, CQ, and CS stand for Schwarz Information Criterion, Akaike, Serial Correlation (LM), Heteroskedasticity (BPG), Normality, Arch, CUSUM and CUSUM of Squares test, respectively. S stands for “stable” and U for “unstable”. Probabilities are given in parenthesis.

Table 5. Long-run estimates of the NARDL.

	Intercept	lnXt	lnYt	lnPt	$\mathit{\text{ln}}{V}_t^{+}$	$\mathit{\text{ln}}{V}_t^{-}$
Nigeria	−14.4215***	−0.53728***	−1.29497***	5.318205***	−0.05657*	0.057608**
Ghana	−2.65415	−0.1726a	−0.06689	0.797061	0.063634	0.029014
Mali	−0.59665	−0.37626a	−0.8386	1.127874	0.19329	0.255651*
Senegal	−0.52217	−0.80754a	0.979944**	−0.29964	0.009037	0.011453
Niger	−20.8789	−0.85632a	−2.90125	7.868398**	−0.1302	−0.15162
Togo	19.98572***	−0.4295a	−4.66982a	0.390314	−0.08846	−0.13559
Benin	18.30617***	−0.36394a	−2.63724**	−1.37982	0.270814	0.149152
Burkina	−9.24378*	−0.39507a	0.330142	1.912765**	−0.29171*	−0.27254*
Cote	−0.04303	−0.59184a	−0.29258	1.002229	−0.1543	−0.18311**

Note that ***, **, and * indicate significance at 1%, 5% and 10% respectively. The long run coefficients are calculated as $Y=-\frac{{\delta }_1}{{\delta }_0},\mathit{\text{lnP}}=-\frac{{\delta }_2}{{\delta }_0},\mathit{\text{ln}}{V}_t^{+}=\frac{-{\delta }^{+}}{{\delta }_0}$ and $\mathit{\text{ln}}{V}_t^{-}=-\frac{{\delta }^{-}}{{\delta }_0}.$

Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. https://doi.org/10.1002/jae.616

 Web of Science ®Google Scholar