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Assessing the potential impact of Microfinance with agent-based modeling

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  • Rashid, Salim
  • Yoon, Youngeun
  • Kashem, Shakil Bin

Abstract

Recent empirical results have cast doubt on the value of Microfinance as a tool for reducing poverty. But, the difficulty lies in evaluating the impact of Microfinance in a world where the Microfinance institutions, their borrowers, and government policies are constantly changing. There is a need for a comprehensive and transparent framework to develop the theoretical grounds for believing in (or against) the efficacy of Microfinance, which can at the same time be used as a testing ground for policymakers. This paper presents a first attempt to develop an agent-based modeling (ABM) framework for pre-policy-implementation testing of the effects of Microfinance. Under the ABM paradigm, a set of behaviors for individual agents in the economy is used to construct a simulation whereby random interaction allows agents to change their state over time. Simulation of the model in different scenarios supported all our intuitions about Microfinance; in particular, there was positive impact of Microfinance on the wealth level of the poor. It was found that increase of available funds, easy access for producers and lower interest rates increase the effectiveness of Microfinance.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecmode:v:28:y:2011:i:4:p:1907-1913
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    References listed on IDEAS

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    Cited by:

    1. Raihan, Selim & Osmani, S. R. & Khalily, M. A. Baqui, 2017. "The Macro Impact of Microfinance in Bangladesh: A CGE Analysis," Conference papers 332868, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    2. Lahkar, Ratul & Pingali, Viswanath, 2016. "Expansion and welfare in microfinance: A screening model," Economic Modelling, Elsevier, vol. 53(C), pages 1-7.
    3. 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.
    4. 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).
    5. Raihan, Selim & Osmani, S.R. & Khalily, M.A. Baqui, 2017. "The macro impact of microfinance in Bangladesh: A CGE analysis," Economic Modelling, Elsevier, vol. 62(C), pages 1-15.
    6. Tanjinul Hoque Mollah & Sharmin Shishir & Wahid Ullah & Takaaki Nihei, 2019. "Assessing NGOs micro-credit programs: a geo-spatial and socio-economic scenario from rural Bangladesh," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 66(2), pages 79-99, June.
    7. Mallick, Debdulal & Nabin, Munirul H., 2018. "Cost effectiveness or serving the poor? Factors determining program placement of NGOs in Bangladesh," Economic Modelling, Elsevier, vol. 69(C), pages 281-290.
    8. Cong, Rong-Gang & Smith, Henrik G. & Olsson, Ola & Brady, Mark, 2014. "Managing ecosystem services for agriculture: Will landscape-scale management pay?," Ecological Economics, Elsevier, vol. 99(C), pages 53-62.
    9. Samitas, Aristeidis & Polyzos, Stathis & Siriopoulos, Costas, 2018. "Brexit and financial stability: An agent-based simulation," Economic Modelling, Elsevier, vol. 69(C), pages 181-192.

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