3. • Microfinance refers to the activity or
business of providing financial services to
poor people or new businesses in poor
countries
• In business theory, microfinance is the
activity of providing financial services such
as small loans to poor people or new
businesses that cannot use traditional
banking services usually in developing
countries.
• The policy is guided by a vision of
achieving widespread access to
microfinance throughout the country and
made possible by institutions operating on
commercial principles.
• A wide range of institutions will be
involved in the provision of services,
including specialized and non-specialized
banks, non-bank financial institutions, rural
community banks, cooperative banks,
SACCOS, and NGOs
BACKGROUNDOFSTUDY
4.
5. PROBLEMSTATEMENT
What is the distribution of
microcredit users across developing
countries?
How the performance of loans of disbursed
by microfinance institutions (MFIs)?
What is the relationship between the of
impact of microcredit user on the
performance of microfinance institutions
(MFIs)?
-Less knowledge
about the importance
of MFIs
6. OBJECTIVES
To analyze the
distribution
of microcredit
users across developing
countries.
To identify the
relationship between the
impact of microcredit
users on the performance
of microfinance
institutions.
To examine the
performance of loans
disbursed by the
microfinance
institution (MFI).
8. NO
.
YEAR REFERENCE OBJECTIVE
OF STUDY
ARGUMENT AND
HYPOTHESIS
DATA METHOD
LOGY
FINDINGS
1 2020 Chen Zeng,
Junru Zeng The
impact of
Covid19 on the
efficiency of
microfinance
institutions.
To
investigate
the effect of
the Covid 19
induced
decline in
economic
activities on
the financial
and social
efficiency of
microfinance
institutions
(MFIs).
Hypothesis 1:
Covid19 induced
economic slowdown is
associated negatively
with MFI financial
performance.
Hypothesis 2:
Covid19 induced
economic slowdoen is
associated positively
with MFI social
performance.
1) MFI
performance by
utilizing Data
Envelopment
Analysis F7.
2) the impact
Covid19 from
Asian
Development
Bank (ABD)
non-
parametric
linear
programmi
ng
1. support a
weakening effect of
Covid19 on MF1
financial efficiency
but a strengthening
effect on MFI social
efficiency. 2) The
effect of COVID-19
on MFI efficiency is
mediated by lending
rates
2 2019 Jean Michel
Banto, Atoke
Fredia Monsia.
Microfinance
institutions,
banking, growth
and transmission
channel : A
GMM panel data
analysis from
developing
countries.
To analyse
the statistical
significance
of MFIs' and
banks'
performance
on economic
development
through a
GMM panel
analysis
between
1999 to
2016.
- the researcher
consider a greater
variety of indicators to
capture different
aspects of the banks’
and MFIs’
performance. Beside
traditional channels of
transmission channel
such as investment and
human capital, the
researcher account for
an important potential
transmission channel,
which is consumption.
-obtained bank
data from
TheGlobalEcon
omy,
macroeconomic
indicator from
World
Development
Indicators,
Education
Statistics, The
Penn World,
Federal Reserve
Economic Data.
-MFIs’ data
obtained from
Microfinance
Information
Exchange
(MIX) Market
Database.
- Multiple
Linear
Regression
Model for
individual.
-Fixed
Effect
Model
(assumes
the
correlation
of
unknown
form
between
the entity’s
error term
and
explanator
y
variables)
-
-Mainly find that
despite their
relatively small size,
MFIs’ performance
contributes to
economic
development even
when banks’
performance is taken
into account. The
result is by
improving the social
and financial
performance, MFIs’
increase investment
and consumption.
The bans’
performance
improves GDP per
capita through
investment,
consimption and
human capital.
9. 3. 2020 K. Brickell et
al./World
Development 1
-reliance on
microfinance
for everyday
survival will
be deepened
by the
COVID19
pandemic.
-the majority
of
microfinance
borrowers
globally are
women.
- Servicing
microfinance
loans will
heighten
burdens of
(un)-paid
work that
women
undertake as
part of social
reproduction
.
-the researcher argue
that the promotion of
microfinance as
market-based relief
and recovery from the
pandemic should be a
source of concern, not
comfort.
- the interplay between
over-indebtedness,
pre-existing
malnutrition
challenges, and the
global public health
crisis of COVID-19
represents a major
challenge to gender
equality and
sustainable
development
-The World
Bank
- Based on
existing
theory
There are no
conflicts of interest
related to the
submission ofthe
manuscript titled
‘Compounding crises
of social
reproduction:
Microfinance, over-
indebtedness and the
COVID-19
pandemic
4. 2020 Int. J. Financial
Stud
the impact of
a specific
regulatory
regime, the
“Microcredit
Regulatory
Authority
Act, 2006”,
enacted by
the
Bangladesh
government
to monitor
and
supervise
nonprofit
nongovernm
ent
organization
s (NGOs)
Hypothesis 1 (H1) :
Clients of regulated
nonprofit,
nongovernment
organization
microfinance
institutions
areassociated with
higher financial
literacy compared with
clients of unregulated
counterparts.
H2 : Clients of
regulated nonprofit,
nongovernment
organization
microfinance
institutions
areassociated with
higher financial status
than clients of
Survey and
interview data
provided by
clients of both
nonprofit
microfinance
institutions
(MFIs)
registered under
the Act and
nonprofit
institutions that
are unregistered
Client-
level
analysis
using fixed
effects for
specific
MFI
membershi
p
The researcher found
compelling evidence
of a positive
association between
the financial status,
financial literacy,and
financial awareness
of clients of
registered MFIs, but
not unregistered
MFIs.
10. CONCEPTUALFRAMEWORK
Dependent Variable Independent Variable
Dependent Variable Independent Variable
Figure 1 : The Conceptual Framework Of Research
The Productivity Of
Microfinance
The Distribution of
Microcredit Users
The Performance Of MFIs
Loans
The Effects on Microcredit
User
11. Time series and Cross Section
In this study, data collected from year 2017 until year 2020
In this study, 40 sample of MFIs from selected country are taken
Paneldata
Timeseries
Crosssection
DATAANDSAMPLE
12. PRODit = β0 + β1 AVGLS it + β2 CC it + β3
ROA it + β4 ROE it + β5 OSS it + μit
Where :
β0 = Intercept
β1, β2, β3,
β4 and β5=
Coefficient
value
AVGLS it = Average
Loans Size
CC it = Number Of
Credit Client
ROA it = Return of
Assets
ROE it = Return of
Equity
OSS it =
Operational
Self-Sufficiency
μit = Error term
EMPIRICALMODEL
13. Variables Abbreviation Description
Dependent Variables
Productivity Prod It is the inverse of the operating cost of an MFI, the lower the operating
cost, the higher is the productivity of MFI and vice versa.
Independent Variables
Average Loan Size AVGLS Average loan size is an indicator of the depth of outreach. A small
average loan size indicates that the MFI serves the poorest client
Number of Credit Clients CC The percentage of total borrowers of MFIs.
Return on Assets ROA An MFI’s revenue through its assets utilization.
Return on Equity ROE An MFI’s on its owner’s investments.
Operating Expense OE When MFIs cover their operational costs by the income generated
through operations.
14. AnALYSIS METHOD
1. Panel Data
2. Panel Unit Root Test
5. VECM based Granger
Causality
6. Diagnostic Test
(Auto Correlation and
Multicollinearity)
4. Fully Modified Ordinary
Least Square (FMOLS) and
Dynamic Ordinary Least
Square (DOLS).
3.Panel Cointegration
Test
