Global microscope on the microfinance business environment 2012

6. Note that the survey
underlying the 2012 Microscope
was conducted in early 2011.
See, for example, Ahlin, Lin,
and Maio (2009) on the
importance of controlling for
growth and infl ation when
benchmarking MFI performance
across institutions operating in
different countries.
7. The Rule of Law index is
drawn from World Development
Indicators and is part of the
KKM index, a measure of broad
institutional development
created by Kaufmann, Kraay,
and Maztruzzi (2007). The
Doing Business Indicators are
described and the data can be
found at: http://www.
doingbusiness.org/.
69
The regression analysis is designed to explain
variation in multiple microfi nance penetration
measures including the number of borrowers as a
share of the total population, the number of
borrowers as a share of the poor population, and
additional measures based on the size of the loan
portfolios of microfi nance institutions. The
following equation links penetration measures to
the <strong>Global</strong> Microscope on the Microfi nance Business
Environment 2012:
(1) Penetration i = α + ß 1MICROSCOPE i + ß 2Country i + ε i
“MICROSCOPE” represents a set of explanatory
variables including the overall index, its broad subcategories
(regulatory framework and practices
and supporting institutional framework), and the
components of those sub-categories. Like the
penetration variables, the MICROSCOPE variable is
measured at the country level. “Country”
represents a set of control variables that have been
important in describing variation in MFI
performance and outcomes across countries. The
two key macroeconomic variables are GDP growth
and infl ation, which are both averaged over the
three years prior to the collection of the 2012
Microscope survey. 6 The set of country controls also
includes a general measure of institutional
development that summarizes a country’s
adherence to the rule of law and a measure of the
overall quality of the business environment from
the Doing Business database. 7
To capture potential interactions between
microfi nance penetration and the development of
the formal banking sector, the regressions also
© The Economist Intelligence Unit Limited 2012
<strong>Global</strong> <strong>microscope</strong> on the microfi nance business environment 2012
Appendix II: Regression Methodology
include the ratio of banks’ overhead costs to total
banking assets. High overheads indicate a less
effi cient formal banking sector, which could foster
opportunity for the microfi nance sector, and thus
have a positive effect on penetration. On the other
hand, high overhead costs ratios could also be an
indication of the general diffi culty of the
environment for provision of fi nancial services,
which could negatively impact microfi nance
penetration.
The ordinary least squares regression results in
Table 1 summarise the relationship between
penetration (measured by the number of
microfi nance borrowers as a percentage of the
population) and transparency in pricing.
Transparency in pricing is measured on a scale from
0 to 4, with higher values indicating greater
transparency. The coeffi cient for that variable is
highly signifi cant and also economically
meaningful. For each 1-point increase on the
pricing transparency indicator, the share of the
population that borrows from microfi nance
institutions increases by 1.96 percentage points.