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Assessing the relative poverty level in clients of microfinance institutions

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  • Seller, Manfred
  • Sharma, Manohar

Abstract

Many microfinance institutions (MFIs) receive public support. In return for this support, governments and donors demand MFIs not only become financially sustainable but also reach the poor, or even the poorest of the poor. Effective evaluation of the achievement of these objectives requires appraising both the MFI's financial sustainability and the relative poverty of its clients. In recent years, several tools have emerged to assist donors in their assessment of the financial sustainability of MFIs. For example, the Consultative Group to Assist the Poorest (CGAP), which seeks to promote sustainable microfinance institutions for the poor, disseminates a number of tools that allow assessing the financial sustainability and other aspects of institutional performance of MFIs. Currently, no operational tool exists for measuring how well a MFI reaches the poor through its services. In order to gain more transparency on the depth of poverty outreach, CGAP supported research at IFPRI during 1999 and 2000 to design and test a simple, low-cost operational tool to measure the poverty level of MFI clients relative to nonclients. This policy brief summarizes the main features of the tool, how it can be applied, and what type of results can be obtained.

Suggested Citation

  • Seller, Manfred & Sharma, Manohar, 2000. "Assessing the relative poverty level in clients of microfinance institutions," MP05 briefs 10, International Food Policy Research Institute (IFPRI).
    • Handle: RePEc:fpr:mp05br:10
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    Cited by:

    1. Hargreaves, James R. & Morison, Linda A. & Gear, John S.S. & Makhubele, Mzamani B. & Porter, John D.H. & Busza, Joanna & Watts, Charlotte & Kim, Julia C. & Pronyk, Paul M., 2007. ""Hearing the Voices of the Poor": Assigning Poverty Lines on the Basis of Local Perceptions of Poverty. A Quantitative Analysis of Qualitative Data from Participatory Wealth Ranking in Rural," World Development, Elsevier, vol. 35(2), pages 212-229, February.
    2. Delia Boccia & James Hargreaves & Bianca Lucia De Stavola & Katherine Fielding & Ab Schaap & Peter Godfrey-Faussett & Helen Ayles, 2011. "The Association between Household Socioeconomic Position and Prevalent Tuberculosis in Zambia: A Case-Control Study," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-11, June.
    3. Rohini Somanathan & Isha Dewan, 2003. "Identifying targeting with nonparametric methods: An application to an Indian microfinance program," Discussion Papers 03-11, Indian Statistical Institute, Delhi.
    4. Kent Ranson, M. & Sinha, Tara & Chatterjee, Mirai & Acharya, Akash & Bhavsar, Ami & Morris, Saul S. & Mills, Anne J., 2006. "Making health insurance work for the poor: Learning from the Self-Employed Women's Association's (SEWA) community-based health insurance scheme in India," Social Science & Medicine, Elsevier, vol. 62(3), pages 707-720, February.

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