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Journal of the Knowledge Economy

, Volume 9, Issue 1, pp 81–135 | Cite as

Conditional Determinants of Mobile Phones Penetration and Mobile Banking in Sub-Saharan Africa

  • Simplice A. Asongu
Article

Abstract

Using 25 policy variables, this study investigates determinants of mobile phone/banking in 49 sub-Saharan African countries with data for the year 2011. The determinants are classified into six policy categories, notably macroeconomic, business/bank, market-related, knowledge economy, external flows and human development. The empirical evidence is based on contemporary and non-contemporary quantile regressions. The following implications are relevant to the findings. First, mobile phone penetration is positively correlated with (i) education, domestic savings, regulation quality and patent applications, especially at low initial levels of mobile penetration; (ii) bank density; (iii) urban population density and (iv) internet penetration. Second, the use of the mobile to pay bills is positively linked with (i) trade and internet penetration, especially in contemporary specifications and (ii) remittances and patent applications, especially at low initial levels of the dependent variable. Third, using the mobile to send/receive money is positively correlated with internet penetration and human development, especially in the contemporary specifications. Fourth, mobile banking is positively linked with (i) trade in contemporary specifications, (ii) remittances and patent applications at low initial levels of the dependent variable and (iii) internet penetration and human development, with contemporary threshold evidence. The policy implications are articulated with incremental policy syndromes.

Keywords

Mobile phones Mobile banking Development Africa 

JEL Classification

G20 L96 O11 O33 O55 

Notes

Acknowledgment

I thank Nguena, C. L., Tchana, T. F. and Zeufack, A., for sharing the dataset of their paper entitled ‘Housing Finance and Inclusive Growth: Benchmarking, Determinants and Effects’. The underlying dataset which constitutes about 50 % of the data used in this study has been checked for consistency with the primary source (World Bank Development Indicators). Hence, any mistakes are assuredly mine and not theirs.

The project has benefited from partial funding from the African Economic Research Consortium (AERC).

The author is highly indebted to the editor and referees for constructive comments.

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© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.African Governance and Development InstituteYaoundéCameroon

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