Trying to Measure Poverty Alleviation

There's been a lot of chatter about measuring poverty alleviation.  I'm often asked if Prisma is contributing to poverty alleviation through its micro-credit loans.  I've given a lot of thought to how a subject that has so many parts (financial, educational, social, physical living conditions, market interest rates, and so forth) can be neatly packaged and scored in a simple rating scale.

I sat down with my staff in Honduras to decide how we as a small micro-credit institution could approach the measurement of poverty alleviation.  Articles I've read and many one-on-one discussions with other practitioners often left me a little bewildered and asking myself how any of the great claims about the success of poverty alleviation could be proved.

I went back to my academic roots.  It felt more like a setup for a doctoral dissertation,...... and we did eventually come to the conclusion that YES, we as a micro-credit organization do help about 60-70% of our clients rise above the poverty level.

Here's how we approached the question.  THE HYPOTHESIS:  the success of poverty alleviation measurement (the dependent variable) is based upon the interplay of various independent variables such as good financial underwriting statistics, education levels, physical living conditions, size of families, family health, urban or rural, market interest rates, and so forth.

My staff and I had to decide which of the various independent variables we would control or had major impact over.  It became obvious that we had control over financial underwriting statistics and little else.  Sad to say, we had no power nor control over the rest of the independent variables.  We as a small financial institution could be active in country associations to advocate fair banking laws, foreign aid, better schools, electricity, etc.  However, our impact as an organization would be indirect and relatively minor.  A very humbling realization.

With that reality in mind, we attacked financial underwriting.  We came up with the following:

1.  Our underwriting is based upon a DEBT-TO-INCOME RATIO calculation.  We comb through a client's monthly expenses and divide it by monthly income.  We set up 3 major categories.

2.  Those with debt-to-income ratios of 90% or higher fell into the absolute poverty category. Hardly any margin of extra money over monthly expenses.  Any little emergency or unforeseen expense would completely devastate these borrowers.  Our loans for simple businesses such as food production to sell on the streets, used clothing, ambulatory sale of other cheap products - would produce the only income for the borrower and his/her family.  What little money is made goes to feed the family and perhaps a little leftover for education.  These clients represent about 20-25% of our clients.  Poverty alleviation rarely touches this category of clients.  We do our part to grant them loans because the government and private industry do not.

3.  Those clients who fall into the 80-70% of debt-to-income ratio where someone in the family probably has a regular income be it from farming, government job, or low wage job in the private sector.  The family now wants to mount a little grocery store in its garage, sell food items, etc. to supplement income.  These clients represent 30-35% of our clients.  They are pulling themselves above subsistence level living by mounting a small business that will add to their overall earnings.  Yes, we are helping this category of clients rise above poverty.

4.  Clients who have debt-to-income ratios of 70% or less.  They already have small businesses and need lines-of-credit for maintenance or expansion.  They have at least a 30% margin of income and don't live on the poverty line.  They are still poor, but really moving beyond poverty.  They represent about 30-35% of our clients.

5.  We have another category of clients who borrow to improve their living conditions, mainly solar electricity where the national electrical grid does not reach.  They are usually small merchants who need the electricity for their businesses, and clients who have enough income to support loans for solar installations that will improve their daily living conditions.  We do not include this category in poverty alleviation statics.

In summary, we can say that we are helping between 60 and 70% of our clients rise above poverty levels while 20-25% remain so poor that all we are able to do is help put food on the table.  This is our DIRECT IMPACT.

As to the INDIRECT IMPACT, we are active on the board of directors of our MFI country association, dedicate many volunteer hours, and strongly advocate better education, social services, etc.  However, we do not declare any miracles of poverty alleviation from this category of activity.

     

Comments

[Alex]

Very cool! I wonder, though, if applying for a micro-loan and implementing it - bring it to its intended purpose - is a kind of reward? Is it one of the intangibles of poverty alleviation? While there may not be any movement from one debt-to-income category to another after the first micro-loan, is there a greater likelihood of such movement after a second loan? Despite how much I dislike the hidden assumption in this question but "is the process transforming"? I'm curious because a lot of my MBA colleagues believe it is while my own experience has led me to understand that most villagers already know how to be accountants - they stretch a penny in the most dire and difficult of circumstances.

-Alex

[Kendall Mau]

Alex, in the C category, repeated loans are like a drug. They can't continue living without constant refreshing of loans. Earn just enough to put some food on the table, but never save enough to put them on the next level. Their working capital never really increases. Of course there are always some exceptions and we gladly work with them as they move to Category B.