This study will measure the financial inclusion
by using a multi-dimensional indices approach. It will use Norris and Deng’s
approach (Norris et al. 2015) in constructing three multi-dimensional indices
capturing different angles of financial inclusion:

 

             (i) utilization of financial services (supply
side) by households (Global Findex);

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            (ii)
utilization of financial services by SMEs (Enterprise Survey);

            (iii)
access to financial institutions (Financial Access Survey).

 

Findex

The
Global Financial Inclusion (Global Findex) dataset was launched in 2011 by the
World Bank. It was comprised of comparable indicators showing how people globally
tend to save, to borrow, to make payments; and to manage risk. The survey was
carried out covering 2011 and the 2014 by Gallup, Inc. under the umbrella of Gallup
World Poll.

 

The Global Findex dataset for 2014 contains
indicators exceeding 100, covering information regarding gender information,
age classification, and household income. The indicators were formed by using
the survey data from interviews conducted with 150,000 nationwide representative
and randomly selected adults (more than age 15) and in 143 countries
representing more than 97 percent of the global population (see appendix X for the list of included countries).

 

Face to face surveys were carried out in
countries where telephone coverage contitutes less than 80 percent of the
population. Mostly, the fieldwork was finalized between two to four weeks. In countries
where face-to-face surveys were completed, the first sampling stage was the primary
sampling unit classification. Survey respondents were randomly selected within
the designated households.

 

Data weighting was used to make sure that each country
was represented by a nation-wide sample. Closing weights consisted of the base
sampling weight, which provided corrections for unequal selection probability based
on size of the household; and the poststratification weight. This then corrected
sampling and non-response error. Population statistics on gender age, education
and socioeconomic status- where reliable data were available was used for poststratification
weights.

 

It should be noted that Findex data were a
milestone, which delivered exceptional comprehension to how people saved,
borrowed, made payments and managed risks in more than 140 countries.

 

The Findex is complimentary to other datasets given
that it focuses on persons, rather than financial institutions. It does not
provide aggregate measures of financial depth, as in the case of the IMF’s
Financial Access Survey data and World Bank Enterprise Surveys.

 

However, Findex dataset also have some restrictions. The
probable econometric methodologies and realistic endogeneity controls were
limited due to the lack of a time dimension. Additionally, an examination of development
of financial inclusion over time and its impact assessment on macroeconomic
outcomes are also very limited. Finally, individuals are not observable between
different years (Aslan et all., 2017).