One addition to usage indicators, credit to GDP

One difference between their measure with Sarma’s
(2008) indicator was that they included all available data regardless of
dimension. In Sarma’s (2008) index, domestic credit and domestic deposit were
included as measures of usage dimension. In addition to usage indicators, credit
to GDP indicator was included.


 The second term
of the numerator in equation stood for the Euclidean distance from an ideal
point. The authors then normalized it by taking the square root of the number
of observations and then subtracting it by 1. The authors normalized the
indicator for placing the calculated values between 0 and 1, where 1 was the
highest financial inclusion index and 0 was the lowest, again in line with
Sarma (2008).

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where Ai is the actual value of dimension
i, MINi was the minimum value of dimension i, MAXi was the maximum value of
dimension i. The index of financial inclusion for country i was then calculated
by the normalized inverse of Euclidean distance of point di computed in
Equation (1) from the ideal point I which was equal to 1. Specifically, the formula
was the following:




After computing the period average for each financial
inclusion indicator for 188 countries, the dimension index was calculated in
line with Sarma (2008), where the dimension index for ith dimension
di was derived as: 


The authors followed the methodology of Sarma (2008)
in constructing their financial inclusion indicator. They included five
measures: (i) automated teller machines (ATM) per 100,000 adults, (ii) commercial
bank branches per 100,000 adults, (iii) borrowers from commercial banks per
1,000 adults, (iv) depositors with commercial banks per 1,000 adults, and (v) domestic
credit to GDP ratio. The first two measures fall under the availability of
banking services as a dimension of financial inclusion, while the following
three belong to the usage dimension of financial inclusion. All indicators were
taken from the World Bank’s World Development Indicators, and each indicator
for each economy used the average value from 2004 to 2012. The authors
preferred to use average values, instead of conducting an annual analysis, to
avoid yearly fluctuations and to include as many economies as possible. In sum,
the authors downloaded data for 188 countries including those from developing
Asia. R


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