I would start with impact evaluation reports of different projects/activities implemented by these institutions in one country.

NOMINAL IMPACT

Most impact assessment tends to focus only on the nominal impact, i.e. direct impact on the person receiving the micro-financing and those who are benefited from micro-financing, i.e. job creation. This nominal impact may be defined as:

(1) I = y + y^ + m

… y = income to the project owner; y^ = income of others people derived from job creation of the project under micro-financing; and other secondary impact, such as consumption, investment or job creation as the result of the actions of y and y^ in the economy.

REAL IMPACT

Micro-financing is one form of debt financing of projects aiming at creating jobs and income for the purpose of reducing poverty. While micro-financing may produce jobs and create income among participants in the project, the project owner carries the debt burden of the micro-finance. This burden must be accounted for. The real impact (adjusted) impact should be:

(2) I^ = I – d

… where I^ = adjusted impact; I = nominal impact; and d = debt burden. The debt burden is defined as:

(3) d = [D(r) + D] / n

… where D = total debt financed; r = interest rate; and n = number of payment period.

Inflation is not factored into the calculation because with or without micro-finance the effect of inflation is present, i.e. inflation affects everyone: rich or poor.

INADEQUACY OF LINEAR MODELING

In both cases discussed above, the modeling approach is linear in nature. A more accurate approach is to model the growth of the “poverty reduction” or the growth of income that lifts the people above the poverty line in a non-linear fashion by using growth model. The general growth model follows:

(4) Y = [K(y) exp(r(t))] / [K + y(exp(r)(t))]

… where Y = income growth; K carrying capacity (must not be equal to or less than zero); y = income of last period, i.e. even in poverty level; r = rate of income growth; t = period of measurement.

Note that many micro-financing projects failed because the carrying capacity (K) is not factored into the model. The carrying capacity (K) may include:

-Education

-Among financed

-Size of project

-Market response

-Infrastructural support

-Etc.

In this non-linear modeling, accurate measurement of the reduction of poverty may be directly measured as:

(5) Y* = [(y(t1) – y(t0)) + y(t0)] / 365

… Y* = new income per day, Y(t1) = income of this period; and Y(t0) = income of last period (baseline). Note 365 = number of days in one year.

Poverty reduction may be measured with following conditional statements:

Y* / 1.25 > 1.00 : indicated poverty reduction

Y* / 1.25 = 1.00 : indicates no improvement

Y* / 1.25 < 1.00 : indicated worse off than implementing micro-finance, i.e. may be due to debt burden from the micro-financing. Note 1.25 is the poverty line defined as USD1.25 per day per person income level. World Bank 2008. This number may be adjusted to 2.50 per day in the present day level.

The issue of debt burden as an adjustment for Y* may be applied to arrived at real impact or real Y*.

Many thanks Mr. Paul Louangrath i just glance through your contribution to my topic and i must say i am really delighted with your model. I will read it again, try to analyze some critical issues you raise and get back to you soon. Once again thank you very much for such a valuable contribution.

Thank you Mr. Dragos Cimpoies for your contribution to my topic. I will get back to you soon.