In governance and institutions, specifically through the reinforcement

In summary, this paper developed a financial inclusion
measure which utilized available cross-country data while focusing on
developing countries in Asia. Additionally, this paper aimed at comprehending the
relationship between financial inclusion; poverty; and income inequality in
developing Asian countries.

 

Third, their estimates provided strong correlation
between financial access and poverty rates. Their findings pointed out that in
order to reduce poverty rates in Asia, policymakers must implement policies which
addresses barriers to financial inclusion. Promoting inclusive growth must
complement efforts to increase financial inclusion. Availability of credit to
lower income groups would improve their access to financial services, which in
turn would give them competence to conduct productive activities and to smooth
their consumption during short-term adverse shocks. 

 

Second, similar to the findings of Honohan (2008) and Rojas-Suarez
(2010), financial inclusion was significantly increased by good governance and
high quality of institutions. This implies that to broaden financial access, countries
in developing Asia must continue to improve the quality of its governance and
institutions, specifically through the reinforcement of the rule of law,
including enforcement of financial contracts and financial regulatory
oversight. Maintaining high quality rule of law will reduce involuntary
financial exclusion of majority of the inhabitants. 

 

First, the level of financial inclusion was
significantly influenced by the demographic characteristics of countries in
developing Asia. Highly populated countries had a tendency to offer greater
access to financial services. The countries with high dependency ratios had
lower access to financial services. These findings had important policy
implications, especially for economies with fast aging population structures.
For these countries, the provision of retirement pensions and other old-age
benefits would be critical in increasing access to financial services of elderly
population. 

 

The financial inclusion indicator showed a similar
pattern (in terms) of ranking as those of Honohan (2008) and Sarma (2008). The
factors which significantly influenced financial inclusion indicator in
developing Asian countries were tested. The estimates showed the importance of
per capita income, rule of law, and demographic factors. The authors then
tested whether or not financial inclusion in the region reduces poverty and
income inequality. Their findings clearly pointed out a robust and significant
correlation between higher financial inclusion and lower poverty and income
inequality. The findings were robust using Honohan’s (2008) financial access
indicator. 

 

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).

 

 

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. 

 

In order to test whether financial inclusion diminishes
poverty and income inequality in developing Asia, the authors created their own
financial inclusion indicator covering 37 Asian countries using various
dimensions of financial inclusion including availability and usage. 

 

The paper used the definition of Sarma (2008) which indicated
financial inclusion as a process that facilitates the access, availability, and
usage of financial services for the whole society. 

 

Park and Mercado (2015) examined the importance of
financial inclusion given that increasing the poor’s access to financial
services was known to be an effective instrument to reduce poverty and to
alleviate income inequality.