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Learning to walk before you run : Financial Behavior and mobile banking in Madagascar

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  • Venet, Baptiste
  • Arestoff, Florence
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    Abstract

    In Madagascar, Orange introduced its mobile banking services in September 2010. Mobile-banking (m-banking) is a system that allows users to conduct a number of financial transactions through a mobile phone. The existing body of literature suggests that the use of m-banking services may have a positive impact on individual savings, affect money transfer behavior and/or encourage financial inclusion. In 2012, we conducted a survey of 598 randomly selected Orange clients in Antananarivo. We use the matching methodology to assess the impacts of m-banking on clients' financial behavior. The results show that the use of m-banking services increases the number of national remittances sent and received. It is in line with the conclusions of the existing literature devoted to M-Pesa in Kenya. Yet we find that using of m-banking services has no significant impact on the sums saved by users or the sums of remittances sent and received, which appears to contradict the users' perceptions. This result may, however, be explained by a learning-by-doing process: users need to first learn to trust the e-money system before making any significant changes to their financial behavior.

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    Bibliographic Info

    Paper provided by Paris Dauphine University in its series Economics Papers from University Paris Dauphine with number 123456789/11979.

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    Date of creation: Sep 2013
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    Publication status: Published in DIAL Document de travail, 2013
    Handle: RePEc:dau:papers:123456789/11979

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    Related research

    Keywords: Banque mobile; Matching; Comportements financiers; Pays en développement; Mobile banking; Low Income countries; Financial behavior; Matching methodology;

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    1. Isaac Mbiti & David N. Weil, 2011. "Mobile Banking: The Impact of M-Pesa in Kenya," NBER Working Papers 17129, National Bureau of Economic Research, Inc.
    2. Demombynes, Gabriel & Thegeya, Aaron, 2012. "Kenya's mobile revolution and the promise of mobile savings," Policy Research Working Paper Series 5988, The World Bank.
    3. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Wiley Blackwell, vol. 65(2), pages 261-94, April.
    4. Alberto Abadie & Guido W. Imbens, 2006. "On the Failure of the Bootstrap for Matching Estimators," NBER Technical Working Papers 0325, National Bureau of Economic Research, Inc.
    5. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
    6. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    7. Olga Morawczynski & Mark Pickens, 2009. "Poor People Using Mobile Financial Services : Observations on Customer Usage and Impact from M-PESA," World Bank Other Operational Studies 9492, The World Bank.
    8. Claire Bonnard, 2011. "Les incitations à l'innovation dans le secteur privé," Post-Print halshs-00599700, HAL.
    9. Heckman, James J & Ichimura, Hidehiko & Todd, Petra E, 1997. "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Wiley Blackwell, vol. 64(4), pages 605-54, October.
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