7 th annual microenterprise conference provo, ut march 12, 2004 the impact of microfinance on...
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7th Annual MicroEnterprise
Conference
Provo, UTMarch 12, 2004
The Impact of Microfinance on Economic Wellbeing:
Contributions from Azerbaijan
Kris Johnson
Outline
1. Methodology
2. Results
3. Implications
4. Questions
Central Hypothesis
The more credit cycles a client completes, the better his/her household’s economic wellbeing.
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.
The Instrument (English)
Sampling Distribution
City/Area # Target % ∆
Baku 239 69.5% 67.5% -2.0%
Imishli 80 22.3% 22.6% 0.3%
Masalli 35 8.2% 9.9% 1.7%
Total 354 100% 100.0% 0%
69.5%
22.3%
8.2%
Respondent # %
Current 219 61.9%
New 101 28.5%
Non 34 9.6%
Total 354 100.0%
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.
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.
Econometric model
Y1 = f (T2, C, O, G, E, A, S)
DPCI = f (Time, Client Type, Age, Gender, Education, Assets, Social Capital)
Initial OLS Regression
Explanatory Variables
Dependent Variables
DPCI ($) (Y1)
R2 = 0.1241
Coef. P>|t|
Age (O) -0.0010153 0.956
Education (E) 0.0923308 0.155
Gender (G) 0.8126927 0.016
Client Type (C) -0.2876257 0.633
Assets (A) 0.0000383 0.000
Social capital (S) 0.4136135 0.015
Cycles (T2) 0.1287165 0.037
Data Plots
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.
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.)
Implications1. For the NIS, we have a methodology and an
instrument that will allow us to collect valid panel data at very low cost.
2. Panel data allows us to track individual clients through their microcredit history and precisely measure impact.
3. Time series data empower us with information for essentially all “proving” and “improving” audiences.
Questions?
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