Mobile money innovations, income inequality and gender inclusion in sub-Saharan Africa

Financial Innovation

Table 5 Correlation matrix (uniform sample size: 1680)

	WoPol	WoBiz	Gini	Mobsen	Mobpay	FID	FIA	FIE	Infl	NODA	Gov	GDPg	FDI	Remit	Trade
WoPol	1.000
WoBiz	0.098	1.000
Gini	− 0.127	− 0.363	1.000
Mobsen	0.126	− 0.007	− 0.051	1.000
Mobpay	0.234	− 0.058	− 0.035	0.873	1.000
FID	− 0.014	0.299	0.001	0.024	0.056	1.000
FIA	− 0.092	0.406	− 0.156	− 0.081	− 0.100	0.412	1.000
FIE	− 0.150	0.297	− 0.034	− 0.089	− 0.087	0.312	0.305	1.000
Infl	0.037	− 0.072	0.012	− 0.017	− 0.017	− 0.025	− 0.022	0.001	1.000
NODA	0.021	− 0.098	0.097	0.083	0.117	− 0.251	− 0.164	− 0.264	− 0.013	1.000
Gov	0.018	0.095	0.017	0.016	0.001	0.036	0.018	0.073	− 0.095	− 0.092	1.000
GDPg	0.055	0.114	0.005	0.043	0.044	0.001	0.029	0.069	− 0.062	− 0.017	0.146	1.000
FDI	0.118	0.190	− 0.094	− 0.031	− 0.040	0.058	0.196	− 0.010	− 0.017	0.069	0.031	0.081	1.000
Remit	− 0.016	− 0.107	0.044	0.037	0.180	0.111	− 0.013	− 0.052	− 0.009	0.034	0.088	0.031	0.014	1.000
Trade	0.115	0.181	− 0.040	− 0.062	− 0.005	0.255	0.380	0.005	− 0.028	− 0.056	0.083	0.059	0.308	0.305	1.000

WoPol Women in Politics, WoBiz Women in Business, Gini the Gini Coefficient, Mobsen Mobile phones used to send money, Mobpay Mobile used to pay bills online, FID Financial Institutions Depth, FIA Financial Institutions Access, FIE Financial Institutions Efficiency, Infl Inflation, NODA Foreign Aid, Gov Government Expenditure, GDPg Gross Domestic Product growth, FDI Foreign Direct Investment, Remit Remittances