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A study of the factors affecting mobile money penetration rates in the West African Economic and Monetary Union (WAEMU) compared with East Africa

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  • Sionfou Seydou Coulibaly

    (University Félix Houphouët Boigny of Abidjan)

Abstract

According to the 2017 Global Financial Inclusion (Global Findex) database, the average penetration rate of mobile money accounts in East Africa is higher than that of the WAEMU. This study attempts to understand the factors driving the adoption and the use of mobile financial services in the WAEMU compared to East Africa. To achieve this, micro-level data from the 2017 Global Findex database are used to perform probit and multinomial logit estimations. The findings reveal that the same determinants influence the adoption and use of mobile money accounts across the populations of both groups of countries, specifically those related to the least vulnerable social categories (i.e., males, older, more educated, richer and part of the workforce). Therefore, in comparison to East Africa, the delay in the penetration of mobile money accounts observed in the WAEMU may be attributed to insufficient policies for increasing the awareness of the benefits of mobile financial services. The study recommends that governments in WAEMU countries promote the use of mobile money accounts among the working-age population (adults aged between 25 and 64) through the improvement of individual income level, and the introduction of incentives into the education system to encourage their population to attain higher levels of education.

Suggested Citation

  • Sionfou Seydou Coulibaly, 2021. "A study of the factors affecting mobile money penetration rates in the West African Economic and Monetary Union (WAEMU) compared with East Africa," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
  • Handle: RePEc:spr:fininn:v:7:y:2021:i:1:d:10.1186_s40854-021-00238-0
    DOI: 10.1186/s40854-021-00238-0
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    References listed on IDEAS

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    1. Allen, Franklin & Demirguc-Kunt, Asli & Klapper, Leora & Martinez Peria, Maria Soledad, 2016. "The foundations of financial inclusion: Understanding ownership and use of formal accounts," Journal of Financial Intermediation, Elsevier, vol. 27(C), pages 1-30.
    2. Hausman, Jerry & McFadden, Daniel, 1984. "Specification Tests for the Multinomial Logit Model," Econometrica, Econometric Society, vol. 52(5), pages 1219-1240, September.
    3. Komivi Afawubo & Mawuli K. Couchoro & Messan Agbaglah & Tchapo Gbandi, 2020. "Mobile money adoption and households’ vulnerability to shocks: Evidence from Togo," Applied Economics, Taylor & Francis Journals, vol. 52(10), pages 1141-1162, February.
    4. Conrad Murendo & Meike Wollni & Alan De Brauw & Nicholas Mugabi, 2018. "Social Network Effects on Mobile Money Adoption in Uganda," Journal of Development Studies, Taylor & Francis Journals, vol. 54(2), pages 327-342, February.
    5. Aron, Janine, "undated". "'Leapfrogging': a Survey of the Nature and Economic Implications of Mobile Money," INET Oxford Working Papers 2017-02, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, revised Jan 2017.
    6. Asli Demirguc-Kunt & Leora Klapper & Dorothe Singer & Saniya Ansar & Jake Hess, 2018. "Global Findex Database 2017 [La base de datos Global Findex 2017]," World Bank Publications - Books, The World Bank Group, number 29510, December.
    7. Maëlle Della Peruta, 2018. "Adoption of mobile money and financial inclusion: a macroeconomic approach through cluster analysis," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 27(2), pages 154-173, February.
    8. Janine Aron, 2018. "Mobile Money and the Economy: A Review of the Evidence," The World Bank Research Observer, World Bank, vol. 33(2), pages 135-188.
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    Cited by:

    1. Regean Mugume & Enock W. N. Bulime, 2022. "Post‐COVID‐19 recovery for African economies: Lessons for digital financial inclusion from Kenya and Uganda," African Development Review, African Development Bank, vol. 34(S1), pages 161-176, July.
    2. Richard Chamboko, 2024. "Digital financial services adoption: a retrospective time-to-event analysis approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-27, December.

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    More about this item

    Keywords

    Financial inclusion; Mobile money; Probit; Multinomial logit; East Africa; WAEMU;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

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