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The Impact of Microfinance on Economic Wellbeing in Azerbaijan

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16 diapositives · 286 Views · Sep 07, 2014

This presentation focuses on the findings from the 7th Annual MicroEnterprise Conference, examining how microfinance influences economic wellbeing in Azerbaijan. It discusses the methodology used for the study, including survey distribution and participant selection, and explores results that indicate the correlation between credit cycles and improved household welfare. Key insights highlight the unique characteristics of clients, the role of female clients, and the implications for data collection and analysis in microfinance. The presentation closes with reflections on how these findings can inform future microfinance initiatives.

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  1. 7th Annual MicroEnterprise Conference Provo, UT March 12, 2004 The Impact of Microfinance on Economic Wellbeing: Contributions from Azerbaijan Kris Johnson

  2. Outline • Methodology • Results • Implications • Questions

  3. Central Hypothesis The more credit cycles a client completes, the better his/her household’s economic wellbeing.

  4. In Azerbaijan… • Clients are 46% male. • Overwhelmingly urban poor. • Village banks are loose affiliations. • Difficult for clients to give up time. • 97% literacy rate allows for a written survey.

  5. The Instrument (English)

  6. Sampling Distribution 69.5% 22.3% 8.2%

  7. Methodology • 2 banks per credit officer randomly selected. • Members of selected banks formally invited to event in prestigious locale. • Credit officers incented to have high turnout (resulted in roughly 85%). • Instruction and explanation given. • Each survey triple-checked for completeness and plausibility. • Raffle prizes given after all surveys pass inspection.

  8. Positive Externalities • Clients honored to be gathered in such a prominent location. • Good PR within circles of influence. • Clients received instruction and practice on general accounting. • Local staff actually enjoyed doing it.

  9. Econometric model DPCI = f (Time, Client Type, Age, Gender, Education, Assets, Social Capital) Y1 = f (T2, C, O, G, E, A, S)

  10. Initial OLS Regression

  11. Data Plots

  12. 3 Stage SS (log) • No significant correlations found between measures of household economic wellbeing and time in the microfinance program. • Interaction terms of time and age, and time and client type are significantly correlated with economic wellbeing.

  13. The Crossroads • Correlated interaction terms suggest that time spent by female clients does increase DPCI. • A cross-sectional snapshot will never allow us to account for differences between individuals and their response to time spent in the program. (Ex.)

  14. Implications • For the NIS, we have a methodology and an instrument that will allow us to collect valid panel data at very low cost. • Panel data allows us to track individual clients through their microcredit history and precisely measure impact. • Time series data empower us with information for essentially all “proving” and “improving” audiences.

  15. Questions?