IDEAS home Printed from https://ideas.repec.org/a/aic/saebjn/v65y2018i1p13-29n96.html
   My bibliography  Save this article

Rethinking Microfinance in a Dual Financial System: An Agent-based Simulation

Author

Listed:
  • Sara Bourhime
  • Mohamed Tkiouat

Abstract

Critics concerning the real impact of traditional microfinance as a tool for poverty alleviation are becoming frequent. In contrast, the financial crisis brought out interest for Islamic finance, whose models have been increasingly studied. Today, the real challenge lies in evaluating the impact of microfinance in a complex environment, where both Islamic and conventional microfinance institutions exist and address evolving clients in constant interaction. New methods and models are therefore needed in order to test the efficacy and assess the impact of introducing Islamic microfinance products, compared to the conventional system. In this context, this paper proposes an approach to build an Agent-Based Modeling (ABM) framework, which is aiming to test the effects of such products implementation using Islamic interest-free group loans. It also helps assess the impact of the behavioral biases as well as agents’ interactions within the repayment process. JEL Codes - C63; G21

Suggested Citation

  • Sara Bourhime & Mohamed Tkiouat, 2018. "Rethinking Microfinance in a Dual Financial System: An Agent-based Simulation," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 65(1), pages 13-29, March.
  • Handle: RePEc:aic:saebjn:v:65:y:2018:i:1:p:13-29:n:96
    as

    Download full text from publisher

    File URL: http://saeb.feaa.uaic.ro/index.php/saeb/article/view/1084
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    2. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    3. Beatriz Armendáriz de Aghion & Jonathan Morduch, 2000. "Microfinance Beyond Group Lending," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 8(2), pages 401-420, July.
    4. Loewenstein, George, 1999. "Experimental Economics from the Vantage-Point of Behavioural Economics," Economic Journal, Royal Economic Society, vol. 109(453), pages 23-34, February.
    5. McCauley, Joseph L., 2000. "The futility of utility: how market dynamics marginalize Adam Smith," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 285(3), pages 506-538.
    6. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    7. Kalliopi Kravari & Nick Bassiliades, 2015. "A Survey of Agent Platforms," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(1), pages 1-11.
    8. Hermes, Niels & Lensink, Robert, 2011. "Microfinance: Its Impact, Outreach, and Sustainability," World Development, Elsevier, vol. 39(6), pages 875-881, June.
    9. Joseph L. McCauley, 1999. "The Futility of Utility: how market dynamics marginalize Adam Smith," Papers cond-mat/9911291, arXiv.org, revised Feb 2000.
    10. Rashid, Salim & Yoon, Youngeun & Kashem, Shakil Bin, 2011. "Assessing the potential impact of Microfinance with agent-based modeling," Economic Modelling, Elsevier, vol. 28(4), pages 1907-1913, July.
    11. Shubhashis Gangopadhyay & Maitreesh Ghatak & Robert Lensink, 2005. "Joint Liability Lending and the Peer Selection Effect," Economic Journal, Royal Economic Society, vol. 115(506), pages 1005-1015, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Polyzos, Stathis & Samitas, Aristeidis & Katsaiti, Marina-Selini, 2020. "Who is unhappy for Brexit? A machine-learning, agent-based study on financial instability," International Review of Financial Analysis, Elsevier, vol. 72(C).
    2. Klaus Jaffe, 2015. "Agent based simulations visualize Adam Smith's invisible hand by solving Friedrich Hayek's Economic Calculus," Papers 1509.04264, arXiv.org, revised Nov 2015.
    3. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Francesco Lamperti & Giovanni Dosi & Mauro Napoletano & Andrea Roventini & Alessandro Sapio, 2018. "And then he wasn't a she : Climate change and green transitions in an agent-based integrated assessment model," Working Papers hal-03443464, HAL.
    5. Giovanni Dosi & Marcelo C. Pereira & Andrea Roventini & Maria Enrica Virgillito, 2018. "The labour-augmented K+S model: a laboratory for the analysis of institutional and policy regimes," LEM Papers Series 2018/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Matus Halas, 2018. "Balancing Against Threats In Interactions Determined By Distance And Overall Gains," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(05), pages 1-22, August.
    7. Zhang, Hui & Cao, Libin & Zhang, Bing, 2017. "Emissions trading and technology adoption: An adaptive agent-based analysis of thermal power plants in China," Resources, Conservation & Recycling, Elsevier, vol. 121(C), pages 23-32.
    8. Chen, Yong & Irwin, Elena G. & Jayaprakash, Ciriyam, 2011. "Incorporating Spatial Complexity into Economic Models of Land Markets and Land Use Change," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 40(3), pages 1-20, December.
    9. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An objective function for simulation based inference on exchange rate data," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(2), pages 125-145, December.
    10. Glötzl, Erhard, 2022. "Macroeconomic General Constrained Dynamic models (GCD models)," MPRA Paper 112385, University Library of Munich, Germany.
    11. Georg Jäger & Laura S. Zilian & Christian Hofer & Manfred Füllsack, 2019. "Crowdworking: working with or against the crowd?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 761-788, December.
    12. repec:hal:spmain:info:hdl:2441/7kr9gv74ut9ngo58gia97t83i7 is not listed on IDEAS
    13. Ashraf, Quamrul & Gershman, Boris & Howitt, Peter, 2017. "Banks, market organization, and macroeconomic performance: An agent-based computational analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 143-180.
    14. Filatova, Tatiana & Parker, Dawn C. & van der Veen, Anne, 2011. "The Implications of Skewed Risk Perception for a Dutch Coastal Land Market: Insights from an Agent-Based Computational Economics Model," Agricultural and Resource Economics Review, Cambridge University Press, vol. 40(3), pages 405-423, December.
    15. Richard Holt & J. Barkley Rosser & David Colander, 2011. "The Complexity Era in Economics," Review of Political Economy, Taylor & Francis Journals, vol. 23(3), pages 357-369.
    16. Seppecher, Pascal, 2012. "Flexibility Of Wages And Macroeconomic Instability In An Agent-Based Computational Model With Endogenous Money," Macroeconomic Dynamics, Cambridge University Press, vol. 16(S2), pages 284-297, September.
    17. Li, Xi Hao & Gallegati, Mauro, 2015. "Sectoral Imbalance in Two-Sector Economy with Mobility Constraint and Firm Migration," MPRA Paper 66002, University Library of Munich, Germany.
    18. Sandye Gloria, 2019. "From Methodological Individualism to Complexity: The Case of Ludwig Lachmann," Post-Print halshs-02345495, HAL.
    19. Fenintsoa Andriamasinoro & Raphael Danino-Perraud, 2021. "Use of artificial intelligence to assess mineral substance criticality in the French market: the example of cobalt," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 34(1), pages 19-37, April.
    20. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo & Möst, Dominik, 2007. "Agent-based simulation of electricity markets: a literature review," Working Papers "Sustainability and Innovation" S5/2007, Fraunhofer Institute for Systems and Innovation Research (ISI).
    21. Kashif Zia & Umar Farooq & Sakeena Al Ajmi, 2023. "Finding the Impact of Market Visibility and Monopoly on Wealth Distribution and Poverty Using Computational Economics," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 113-137, January.

    More about this item

    Keywords

    agent-based simulation; dual-financial system; Islamic microfinance; interest-free lending;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aic:saebjn:v:65:y:2018:i:1:p:13-29:n:96. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sireteanu Napoleon-Alexandru (email available below). General contact details of provider: https://edirc.repec.org/data/feaicro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.