How to measure microfinance impact on poverty alleviation: what does available evidence tell us?

[email protected] www.e-mfp.eu

How to measure microfinance impact on poverty alleviation: what does available evidence tell us?

Some Lessons Emerging from Buusaa Gonofaa’s System of Tracking

Improvements in Clients’ Livelihood By Teshome Dayesso, General Manager

[email protected]


Buusaa Gonofaa MFI - Introduction Started by a local NGO, HUNDEE, later transformed into NBFI in 1999,

regulated by the central bank of Ethiopia Provides micro credit and savings services through joint liability groups of

15-20 members; Short term general-purpose loans (8 – 12 months) for income generating

activities, microenterprises, farm inputs, productive assets (ox, cow), housing improvements, consumption smoothening

Community managed saving and credit facilities in hard-to-reach remote rural areas

Current outreach >50,000 active clients; total assets of >US $6 million; outstanding portfolio of US$5 million


Buusaa Gonofaa MFI: Our Intentions

Mission:- To provide flexible & efficient microfinance service on a sustainable basis to improve the livelihood of the resource poor, particularly women, landless youth & smallholder farmers

Progress overtime

Outreach to target group – the poor

Improved livelihood

Flexible & efficient

Financial performanceSustainable/profitable

Client satisfaction

Client profile, poverty level


Why BG Wanted Client Assessment Scorecard (or ‘Social Ledger’)

Double-bottom line: standardized measurement of financial sustainability; but tracking social goals relied on simple success stories, and intuitive decision making; but this was not enough and we wanted data ‘evidence’ to describe it.

With financial maturity, we wanted a more systematic way to understanding what is happening out there, Whom do we reach? How poor are they? Is there a change (+ve, -ve) in our clients’ livelihood? Where do we succeed in changing client’s livelihood? Where do we fail?

Why? Who benefits from BG most? Does our loan assist either survivalists or

entrepreneurial poor? Or both?


Poverty as ‘lack’ and how the poor measure their progress (or improvements) in overcoming it

What the poor ‘lack’ in comparison to the not-so-poor

Food security Clothing Shelter Income Education Health Housing ownership Access to electricity, water Land Capital/savings

What the poor consider as progress or improvement

25% - Expanding the business (ox/cow fattening, more inputs for farming)16% - Improvements to the house or house construction14% - Buying ox, cow, sheep13% Acquire basic household furniture, utensils13% Buying “luxuries” (radio-cassette, TV, jewellery, etc)


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Measurable Indicators Weight Year/Round of Scoring Date of scoring as Month/Year: m1/yr m2/yr m3/yr m4/yr m5/yr

o Roofing material:- T=thatch; I=iron; P=plastic, O=other

T T T I I

O Number of rooms/huts 4 2 3 3 3o Housing/improvement 0 5 10 4 9o # Oxen 18 0 1 3 3 2o # Cows 16 1 1 1 3 2o # Sheep/goats (shoats) 2 0 1 4 1 1o # Bed type – Metal 2 2 2 2 2 2o # Bed type - Wood/Mosvold 4 1 1 2 2 2o # Tape recorder 2 0 1 1 1 1o # TV 24 1 1 1 1 1

Total Score of HH Assets: 100 127 183 213 188% Change in Asset score 21% 44% 14% -12%

BG’s Poverty Indicators & Score Weight


Poverty category & cut-off points

A person with total score of 5 is poorer than a person with score of 15, and vice versa

Collection of data (scoring) from clients by LO as part of routine loan application on every cycle – baseline at Intake, wealth Scoring on each loan cycle

Poverty category Score rangeApproximate Income range

Very poor 0 – 16 ≤ $1/day

Poor 17 – 60 $1 – $2/day

Not so poor >60 ≥ $2/day

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Improvements in the poverty status of clients between the 1st and 3rd Scoring (N=2,113)


Mean Score Growth by Components

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Very Poor Poor Not so poorAsset score-1st scoring 2 35 83Asset score-3rd scoring 27 38 72Biz score-1st scoring 33 46 36Biz score-3rd scoring 41 53 49Total wealth-1st scoring 37 78 120Total wealth-3rd scoring 64 88 125

Asset score growth (%) 1,005% 8% -14%Biz score growth (%) 24% 15% 35%Wealth score growth (%) 71% 12% 4%


What contributed towards assets score growth?

Asset Score Growth

Pearson Correlation Sig. (2-tailed)

Ox score growth .683 (**) .000

Cow score growth .638 (**) .000

Shoat score growth .153 (**) .001

Bed score growth .107 (**) .000

Tape score growth .093 (**) .003

TV score growth .439 (**) .000

Asset score growth 1

** Correlation is significant at the 0.01 level (2-tailed)


Some Emerging Lessons and conclusion It is very important to know what matters most for our target groups – identification of

indicators from the bottom up, thus relevant ‘evidence’ The system provided us with good insight about what is happening ‘out there’ – more

informed decision to better serve the very poor and poor; ‘evidence’ to refine our services and refocus on improvement areas that matter most for the target group

It would not tell us what loan size or mix of financial services are most likely to keep the poor healthy or enable them send their children to school; but it may help us in understanding how the poor might progress overtime towards those ideals of dignified living.

Our intention is to improve livelihoods; the target groups have diverse priorities and hence there is no single goal that can be measured with a single indicators. But the system complements our judgments and decisions and helps us to be mindful of our promises.

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How to measure microfinance impact on poverty alleviation: what does available evidence tell us?