ASSESSMENT OF FACTORS AFFECTING LOAN REPAYMENT

PERFORMANCE OF BORROWERS

AN EMPIRICAL STUDY ON SELECTED MICROFINANCE

INSTITUTIONS IN OROMIA REGION

BY

ABREHAM GAROMSA

ADVISOR

LAXMIKANTHAM (PHD)

Addis Ababa University

College of Business and Economics
Department of Accounting and finance
January, 2017
Addis Ababa, Ethiopia
 ASSESSMENT OF FACTORS AFFECTING LOAN REPAYMENT
PERFORMANCE OF BORROWERS

AN EMPIRICAL STUDY ON SELECTED MICROFINANCE

INSTITUTIONS IN OROMIA REGION

A THESIS SUBMITTED TO ADDIS ABABA UNIVERSITY COLLEGE OF

BUSINESS AND ECONOMICS DEPARTMENT OF ACCOUNTING AND FINANCE
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR DEGREE OF
MASTERS OF SCIENCE IN ACCOUNTING AND FINANCE.

BY

ABREHAM GAROMSA

ADVISOR

LAXMIKANTHAM (PHD)

Addis Ababa University

College of Business and Economics
Department of Accounting and finance
January, 2017
Addis Ababa, Ethiopia
 Declaration
I, the undersigned, declare that this thesis is my own work and has never been presented in
any other university. I have carried out the research work independently with the support of
research advisor. All sources of materials used for this thesis have been duly acknowledged.

Declared by:
Name: Abreham Garomsa
Signature: _____________
Date: 13th January 2017
Place: Addis Ababa, Ethiopia
Advisor: Laxmikantham (Dr.)
Signature: ______________
Date: __________________

I
 Statement of Certification

As members of the Examining Board of the Final M.Sc. Open Defense, we certify that we
have read and evaluated the thesis prepared by Abreham Garomsa entitled Assessment of
factors affecting loan repayment performance of borrowers: An empirical study on
selected Microfinance Institutions in Oromia Region and recommend that it be accepted
as fulfilling the thesis requirement for the degree of Master of Science in Accounting and
Finance.

……………………………….…… …………….. ………………………..

Name of Major Advisor Signature Date

…………………………………… …………….. ………………………..

Name of Internal Examiner Signature Date

………………………………….… …………….. ………………………..

Name of External Examiner Signature Date

II
 Acknowledgments

First, I would like to praise and thanks the almighty God for his giving me a strengths, joys and
patience in this long journey of the study. Following this, there are innumerous peoples who have
extensively take parts in the achievements of the goal of the study.

My grateful thanks would extend to my advisor, Laxmikantham (Dr.) for his valuable advisory
services to the paper successfulness. Also there are other peoples who deserves thankful from the
sample lending institutes, branch managers (Bilisuma, Endale, Amanuel, Ayansa, Lola and Melaku)
together with all officers and staffs from headquarters for their enthusiastic contributions in
facilitating and getting informed the major issues of the study.

My grateful also extends to staffs from National Bank of Ethiopia microfinance directorates, Sebeta
city administration MSEDA offices for their helps and provides important issues on the topic of the
study. Similarly, great thanks to all my friends, staffs and Mr. Henock who had supported me on
implementation of the software used for econometric analysis of the findings.

Moreover, my sincere thankful and appreciations goes to all sample respondents of the questionnaires
and interviews (borrowers, lending staffs and other key stakeholder staffs) who had taken part
actively in the assessment.

Finally, great thanks to all my beloved families who had been always besides me in encouraging,
supporting and gave their advisory service in the process.

III
 Acronyms
AEMFI Associations of Ethiopian Microfinance Institutes

AdCSI Addis Credit and Saving Institution

BG MFI Busa Gonofaa Microfinance Institutions

CDF Cumulative Distribution Function

FeMSEDA Federal Micro and Small Scale Enterprise Development Agency

GPL General Purpose Loan

IBL Individual Business Loan

MF Microfinance

MFI Microfinance Institutions

MSE Micro and Small Scale Enterprises

MSEDA Micro and Small Scale Enterprise Development Agency

NBE National Bank of Ethiopia

NGO Non-Government Organizations

OCSSCO Oromia Credit & Saving Share Company

TVET Technical and Vocational Education Training

SFPI Specialized Financial and Promotional Institution

SNNPR Southern Nations and Nationalities People Region

VIF Variation Inflation Factors

WoMSEDA Woreda level Micro and Small Scale Enterprise Development Agency

WEDP Women Entrepreneur Development Program

IV
 List of Tables

Table -1: Lists of MFIs that are operating either fully or partially in Oromia Region
Table -2: Microfinance Institutes that are fully or partially operates in Oromia Region
Table- 3: Microfinance Institutes selected for this study based on the number of clients outreach
Table -4a: Lists of active clients served by sample MFI per credit officers
Table -4b: Allocation of Sample Size among the selected MFIs
Table- 5 Number of active MSE and Individual Business Loan borrowers
Table-6: Repayment performance versus ages of the sample respondents
Table-7: Repayment performance versus gender
Table-8: Do you have any other source of income?
Table-9: Borrowers annual income from other sources.
Table-10: Sample respondents response to other source of credit
Table-11: Sample respondents repayment status to other credit sources
Table-12: Sample borrowers credit round versus repayment statuses
Table-13: Do you think that the amount you received is similar to your intended request?
Table-14: Repayment time Suitable
Table-15: Sample borrowers repayment intervals and trends
Table-16: Was the loan issued timely?
Table-17: Defaulted amount descriptive statistics
Table-18: Respondents causes for default
Table-19: Respondents perception on costs of default
Table-20: Sample Respondents Business type
Table-21: Respondents response to loan requested have received and sufficient
Table-22: Respondents response on reasons for loan diversion
Table-23: Response on members‟ knows & Monitor each other

Table-24: Sample borrower‟s response to action for wrong loan utilization

Table-25: At what time interval does the officer visit the client‟s businesses?

Table-26: Respondents repayment status versus training adequacy and sufficiency

Table-27: Does the training taken helps you in running business & credit management?
Table-28: Borrowers response to Availability of inputs, Production location, Adopting Technology
and Feasibility study
Table-29: Borrowers business experience before the credit scheme

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Table-30: Sample respondents response to their product Market demand
Table-31: Sample respondents with having book of records
Table-32: Sample respondents reasons for not keeping record
Table-33: Do you think that your branch credit officers have actively involved in screening the
creditworthy borrowers‟ before granting credits to the MSE borrowers?
Table-34: Do you think that the organizing and screening activity through the government bodied
sector is effective and efficient enough for the lending institutes?
Table-35: Do you think your institutes follow a proper loan rationing mechanisms to all credit needy
borrowers?
Table-36: Do you think that the credit lent has legal supports for any defaults?
Table-37: If you think that the credit lent is legally supported for any defaults, how do you measure
it?
Table-38: Do you think that the government sector involvement on loan agreement has an impact on
credit rationing inefficiency?
Table-39: Does the settlement of the defaulted loan by the city administration (Credit guarantor) have
a negative impact on the government projects subsidy?
Table-40: Maximum likelihood estimate of a probit model for loan repayment performance
Table-41: Multicollinearity test to independent variables
Table-42: The maximum likelihoods marginal effect of probit regression to Loan repayment
performance
Table-43: Comparison of the likelihoods of independent variables that influence repayment
performances

VI
 List of Figures

Figure_1: Conceptual Framework

Figure_2: Loan utilization supervised by lending Institutes

Figure_3: Sample borrowers loan repayment performance supervision

Figure_4: Loan repayment performance across different market demand

VII
 Abstract

Microfinance institutions in Ethiopia are playing an important role in poverty reduction

strategies initiated by the government of Ethiopia. These institutions have a mission of creating
and facilitating credit and other financial schemes to enhance self-employment opportunities
and poverty reduction. To address the main objectives of the study, four Microfinances were
selected for the study purpose. The study was aimed at identifying and analyzing the potential
factors that affects repayment performance of micro and small scale enterprises and individual
entrepreneur borrowers using the structured questionnaires, semi-structured interviews and
focus group discussions. Accordingly, in order to achieve this objective 319 sample borrowers
were selected from the total of 2910 borrowers served by those selected MFIs. The descriptive
statistics analysis and probit regression model was employed to estimate the model and analyze
the results of findings. The result shows that ten variables including constant: sex, income from
other sources, monitoring utilizations of other members in a group, credit timeliness, repayment
time suitability, repayment trend on monthly basis and training adequacy are found significant
and positively influence loan repayment performance of borrower. While loan utilization for the
intended purpose, repayment trend on irregular basis and visit & follow-up on irregular basis
was found negatively influence the repayment performance of borrowers. The extensive
involvement and interference of third parties on the decisions of loan approval processing to
lending institute were found as a contribution for high defaulting. Thus, it is recommended that
the lending institutes needs to focus on monitoring loan utilization systems of borrowers and
technical support needs of the target borrowers through delivering better awareness creation to
organize the more viable borrowers, close supervision and follow-ups and strengthening their
internal and external weaknesses though better integration with key partner stakeholders.

Key words: Microfinance, loan repayment, loan utilization, integration, stakeholders

VIII
 Table of Contents Page

Declaration …….…………………………………………………………………..……… I
Statement of Certification ………………………………..……………………………… II
Acknowledgments ….………………………………..………………………………..… III
Acronyms ….…………….…………………………..…………………………................... IV
List of tables…………………….……….…………………………………………………... V
List of figures………………………….….……………………………………………….. VII
Abstract……………………………………..…………………………………………….. VIII

CHAPTER ONE

1. Introduction ……………………….……………………….………………………. 1
1.1.Background of the study ……………………………………….…………………….…. 2
1.2.The Statement of Problem ………………………………….………………….…. 6
1.3.Objective of the study ...…………………………………….………………………... 8
1.4.Research Questions …………….………………………….…………….………… 8
1.5.Hypothesis ….…………………………………………….……………..………. 9
1.6.Significance of the study ……………………………………….……………….………. 9
1.7.Scope of the study ..……………………………….…….………………………. 10
1.8.Limitation of the study .………………………………….….……………….………. 10
1.9.Organization of the study……………………………….……….…………….………... 11
CHAPTER TWO

2. Literature Review …………………………………….………………..….……. 12

2.1.Theoretical Literatures …………………………………….….……………..………. 12
2.1.1. The concept of microfinance and its importance ..……………….….….……… 12
2.1.2. Loan Repayment performance of borrowers …………………………….………… 14
2.2.Empirical Literatures ....…………...……………………………………………..… 18
2.2.1. Empirical studies in other countries ..………………...………………………….... 18
2.2.2. Empirical studies in Ethiopia ……...………………..….…………………….…….. 20

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CHAPTER THREE

3. Research Methodologies ….……………………….…..……………………… 23

3.1.Methodology of the study ….……………………….…..……………………… 23
3.2.Area of the study ..……………….………………………..……...…………………… 25
3.3.Research design and type ………..…………………………..………………………… 26
3.4.Sampling techniques .………………………………..……………..……………… 30
3.5.Data sources …………………………………………………..……………...…… 35
3.6.Data collection tools .…..…………………………………………..…………........ 35
3.7.Data analysis technique ………………………………………………..………........... 36
CHAPTER FOUR

4. Descriptive Analysis ...………………………………….………..…..……. 44

4.1.Questionnaire response rate ..…………………………….…………..……............ 44
4.2.Socio Economic characteristics ………………………..………………….…..…........ 44
4.3.Loan related characteristics …………………………………………..………....... 47
4.4.Business related characteristics ………………………………………………….............72
4.5.Lending institutes and Government prospects ………………………………………. 80
CHAPTER FIVE

5. Econometric Analysis ...…..……………..……………………..……….…... 91

5.1.Factors affecting repayment performances ……………………………………..... 91
CHAPTER SIX

6. Summary, Conclusion and Recommendations ……….……..………. 99

6.1.Summary ..……………………………………………………………………..……..... 99
6.2.Conclusion and recommendations ..…..…………………………..…………..... 102
References

Annexes

10
 CHAPTER ONE

Introduction

Ethiopia is one the developing countries that were announced as the most poorest and low
leveled income groups of the world over the last few decades. During these periods, the
economy of the country was undermined because of different factors which can be
mentioned as internal as well as external factors. An increasing rate of poverty, famine and
high rate of unemployment were the major factors that have great contribution for the
economical undermining at large. Poverty and unemployment was a great problem in
Ethiopia that needs the government attention to eradicate through microfinance services
delivery to the non-served or underserved poor peoples (Wolday, 2002).

Besides, in recovering from this devastation and shocking situation of poverty, the
Government of Ethiopia took initiatives to reform the economy by redesigning various
strategies. In implementing the recovery steps, initiating the credit scheme through
microfinance institutions was one of the strategies that the government of Ethiopia embraced
in 1990th. As Birhanu (1999 was cited in Abafita, 2003), the sole recovery in the economy
were not found to be the satisfactory point in poverty reduction strategies rather creating a
self-employment opportunities through the expansion of private sector activities was the
pillar to attain the goal.

Moreover, microfinance service was the basic strategies to way out from the economic
backwardness and poverty pressure at large. According to Prof. Mohammed Yunus and
Grameen Banks phrases, an improvement in the economy and social welfare could partly be
realized through delivering micro-credits to the poor people (Microfinance and Micro-credit,
2016). Accordingly, the establishment of sustainable and profitable microfinance institutions
through realization of better repayment performance to serve large number of poor is the
prime component of the strategies to be attained by Ethiopian MFIs.

In this chapter, the overall background of the study, the statement of the problem, the
significance of the study, scope of the study, the objective of the study, the hypothesis and

1
limitations of the study were discussed in details. Furthermore, the views of various authors
indicated in this paper were assessed and discussed based on the relevance of their opinion
on the subject matters rather than stated in chronological order of the year of publications.

1.1. Background of the study

Microfinance is an important strategy to alleviate poverty in developing countries (Fikirte,

2011). As Prof. Muhammed Yunus and Grameen Bank phrased, Micro-credit is a means by
which large people can find the ways in which they can break poverty. Grameen Bank was a
source of ideas and models for many institutions in the field of micro-credit that have sprung
up around the world (Microfinance and Micro-credit, 2016).

The microfinance services are considered as an intervention instruments that Government

and Non-government sectors are using to enable low-income groups of the community to
improve their lives through increasing income, increase their productivity levels, enhance the
ability of providing quality inputs to the market, reducing poverty and ensuring food security
(Alemayehu, 2008). Bayeh (2012) similarly stated that microfinance institutions are
considered as a tool for poverty alleviation through improving access to finance and financial
services.

The difficulties of access to credit facilities might be resolved through: 1) identifying proper
ways to insure that a large number of the poor borrowers can access the loan, 2) developing
the best mechanisms to screen out the bad borrowers from the viable borrowers and 3)
determining how to give an incentive to borrowers who cannot provide collateral to repay the
loans on time (Hulme & Mosley, 1996). Abafita (2003) argued that an innovative target
designing and adequate screening mechanism is a major task of those lending institutes to
select the target poor clients who can sustainably and efficiently utilize the loan for the
intended purpose only.

Microfinance Institutions in Ethiopia

Although an intensive and well educated youths were existed in the economy of the country,
lack of financial services to the needy target poor peoples through conventional commercial
banks were found as a bottleneck for the poor or low-income group peoples to finance their

2
projects. Moreover, the collateral requirements and information asymmetries made by those
commercial banks to the large number of poor people on the world have lacked access to
formal banking services at all (Litenah, 2009).

Abafita (2003) were discussed in his study that a limited access to institutionalized financial
service for the poor peoples in Ethiopia enforces the needy society to borrow from iddir1,
iqub2, friends and relatives and other informal lenders to finance their business. As a result,
an initiation to establish the formal financial sources was in place to serve those poor peoples
by discouraging the exorbitant effects of those lenders.

The main objectives of the MFIs as development organizations were to serve the financial
needs of the non-served and underserved poor peoples but who have the ability to work hard
and change his/her life style due to the presence of these financial services. The major
objectives to meet are as follows: Creating job opportunities, reducing poverty, empowering
women, encouraging small and petty trades (Bayeh, 2012 and Tolosa, 2014)

In developing countries, like Ethiopia, Microfinance Institutions (MFIs) have been emerged
as a financial institutions with an intention of providing small sized financial service to the
poor who were in need of financial services but lack of access to formal commercial banks.
The microfinance institutions services consists provision of micro loans, micro savings,
micro insurance service, money transfer, leasing and other relevant schemes to the target
poor peoples who have been excluded by the conventional commercial banks due to lack of
collateral requirements and high transaction costs (Tolosa, 2014).

Microfinance institutions in Ethiopia have been evolved since the late 1990s as an economic
development tool intended to benefit low income poor peoples (Bayeh, 2012). As Mengistu,
2007 were cited by Abafita, 2003, the credit program by microfinances have been evolved to
empower poor households at urban areas of the country in the form of urban credit financing
schemes which had actually commenced its operation since 1994. During its commencement
this credit scheme was undertaken by some NGOs, Government departments and some

1
Iddir referred as an informal social institutions organized with a group of peoples
2
Iqub refers to informal financial institution organized with group of peoples

3
donors in inconsistent manner. To resolve this problem the government of Ethiopia took
initiatives to develop regulatory frameworks that govern the operational activities of similar
industries (Abafita, 2003). As a result Proclamation No.40/1996 has been enacted to govern
the operational activities of microfinance industries.

Moreover, those microfinance institutions have been established since 1994/95 through
government licensing under the supervision of National Bank of Ethiopia (NBE) with
proclamation #40/1996 (Zerai & Rani, 2012 as cited in Tolosa, 2014). Since its establishment
the numbers of MFIs were sixteen. Although the microfinance industry were started their
financial services most lately, the industry has shown the remarkable growth in terms of
clients outreaches and provision of diversified financial products for the needy societies at
large (Wolday, 2000). The number has been extensively increased at an increasing rate to 35
Microfinance institutions (NBE, 2016).

The microfinance institutions which are operating in Ethiopia are governed and supervised
through National Bank of Ethiopia. They were established legally under proclamations and
provide their financial services to farmers and entrepreneurs who are supposed to be engage
in micro and small scale businesses at urban and rural areas of the country (Abreham, 2011).

As a result, a rapid growth in Microfinance industry plays an indispensable role in addressing

the millennium developmental goals of the Government through delivering massive financial
service schemes to empower women, youths and other community groups. In achieving such
developmental goals of the country, the governments of Ethiopia have designed some
strategies on initiating job opportunities creation as core pillar to enhance youth‟s
developmental programmes and other community groups by organizing those individuals in
the form of Micro and Small Enterprises at urban and semi-urban areas of the country. It
arranges the required initial capitals through micro credit services which undertaken by those
microfinance institutions to eradicate the level of unemployment and enhancing economic
welfares of those community groups. The Government sector named as woreda level Micro
and Small Enterprise Development Agencies had took an initiatives to organize the target
MSE members and facilitate financial services particularly through microfinance institutions
(FeMSEDA, 2016).

4
Although microfinance institutions have a mission of alleviating and or reducing poverty by
improving the livelihood of the low-income groups of the community through credit
delivery, like other lending commercial banks they may face an obstacle in collecting the
outstanding loan amounts with its interest charges for the time period elapsed according to
the contractual agreements made between the lending institutions and the borrowers on the
specific dates.

In provision of this credits service to those who are in need of the financial services, MFIs
develops the credit provision policies which set the loan size, interest rates and repayment
schedules to be complied by those borrowers. As a result, a rapidly growing in supply of
micro-loans, the increasing competition in the micro-markets, the increasing over-
indebtedness among micro entrepreneurs and the current financial crises increases the credit
risks (i.e. the risk of failure of microfinance borrowers). Thus, it is a crucial issue for the
microfinance institutions to assess the problems of loan recovery to improve the financial
sustainability and profitability of their respective institutions by maintaining a strong credit
risk management systems (Abdulfettah, 2013).

The probability of being creditworthy of the borrowers can be characterized by the

willingness and ability of the borrowers and the lending characteristics of the institutes.
These factors might have significant impacts on the repayment performance of the respective
borrowers. In another word, the repayment behavior of borrowers can be determined by their
attitudes or willingness and ability to repay the loan, which might be expressed as a choice
between the two alternatives: either to repay or commit defaults. Moreover, the existence of
other internal and external factors that can influence the repayment attitudes of borrowers can
significantly affects the repayment recovery rate of lending institutes at large.

On the other hand, in reaching-out with the financial services to the large number of poor
peoples in the areas through delivering these financial services to enhance their livelihood
and improving their lifestyles, an increasing number of defaulters probably could have a
significant impact on the institution‟s social as well as economic objectives by retaining a
large amount of outstanding loans. This could results in difficulties to the lending
institution‟s capacity towards poverty eradication strategy as well as realizing their financial
sustainability due to the gradual diminishing loan repayment performances of borrowers.

5
Hence, the observed situations required the researcher to conduct an extra miles survey on
identifying the major possible factors that can affect the repayment performance of borrowers
as the study area to resolve the problem of delinquencies faced by the lending institutions.
The study were applied on four sample MFIs assuming that the findings are the
representatives of the whole MFIs at large. The reason and methodologies employed for
selecting those four MFIs have been discussed in chapter three of the paper.

Those factors that have been identified as an influential to explain repayment performances
were analyzed and discussed using the descriptive analysis and PROBIT regression model.
The marginal effects of those significant variables in influencing the repayment status of
borrowers have been also discussed in the subsequent chapters of the paper.

1.2. Statement of the problem

In alleviating poverty and underemployments, microfinance institutions plays an

indispensable role through provision of credit and saving services to the poor peoples who
lack financial services (Fikirte, 2011). Effective repayment performances of microfinance
institutions are a requirement for being serving the large poor needy borrowers in a
sustainable manner rather than subsidizing through government or donor supports.

Although the provision of financial services to the underserved or non-served poor peoples is
the primary objectives of microfinances, an increasing rate of defaulters with large amount of
outstanding loan is still the challenges of most microfinance institutions that are operating in
Ethiopia. According to the operational reports of some lending microfinance institutions,
although slight improvements in repayment recovery rate from year to year were obtained,
still there is a gap which required researchers to identify the major factors that undermines
repayment performance. Although various studies were revealed their results as socio-
economic features (age, sex, martial statuses, education level) have been identified as factors
that can influence loan repayment performances, still identifying individual borrower socio-
economic characteristics and adopting effective lending mechanisms by the lending institutes
is the major limitations that most microfinance managements lacks during their operations.
Moreover, assessment of the ability and willingness of the borrowers towards repayment of

6
the loan could be the other shortcomings that need researcher attention to enhance repayment
performance of borrowers.

Abafita (2003) argued that efficient characteristics of the lending institutes and other
concerned bodies while screening the target borrowers, effective attitudes of borrowers
towards credit service and socio-economic factor of the borrowers are among the factors that
can influence the repayment performances. Besides, although further study on level of the
significance of lending institutes staffs commitment were not conducted, it is believed that
the commitment of the lending institution staffs in providing the post training supplementary
and technical supports through close supervision and effective monitoring of repayment
status of borrowers may possibly enhance repayment performances of MFIs.

Moreover, no further studies were conducted by the researchers to evaluate the importance of
borrower‟s attitudes towards peer monitoring activities to influence group member‟s
repayment performances. In addition to this, evaluating the effectiveness of supervision and
monitoring time intervals by the MF practitioners to improve the gaps is another important
issue to be assessed by the researcher so that MFIs can improve their lending strategies to
attempt better repayment recovery rate.

Therefore, identifying the socio-economic, borrowers‟ attitude and institutional factors that
influences repayment performance is an essential issue of microfinances in provision
sustainable financial services. Moreover, identifying some of the possible paradoxes inclined
by the third parties towards safeguarding those institutes from suffering credit risks,
provision of technical supports by the concerned bodies to borrowers businesses, political-
legal support to enhance legislative actions on the defaulters may determines the repayment
performances of microfinance institutions.

7
1.3. Objective of the study

The general objective of the study is to identify and analyze the major factors that can
influence loan repayment performance of MFIs borrowers in Oromia Region. The specific
objectives of the study were to:

I. Identify the socio-economic factors that can influence loan repayment performance of
MFIs borrowers in Oromia Region. The socio economic factors such as: gender, age
and income of the borrowers.
II. Identify and analyze lending characteristics that can significantly influence the
repayment performance of MFIs borrowers in Oromia Region. .
III. Identify other internal and external factors (provision of technical and legal supports,
staff commitments and any unforeseen challenges faced by borrowers) that can
influence the loan recovery rates of MFIs.
IV. Recommend appropriate measures to minimize the default rate based on the identified
factors.

1.4. Research questions

In order to achieve the main objectives of the study three research questions were developed.

i. What socio-economic factors can significantly influence repayment performance of

borrowers in the study area?
ii. What loan related factors do have a significant impact on loan repayment performance
of borrowers in the study area?
iii. What other internal and external paradoxes do have significant impact on loan recovery
rate of lending institutes?

8
1.5. Hypothesis

In light of these study objectives, the researcher has hypothesized the following factors to
evaluate their effects on the loan recovery performances of borrowers.

H1: The socio-economic factors (age, Gender & Income) of the borrowers can significantly
influence loan repayment performances borrowers.

H2: Loan related factors (Loan size, peers monitoring, loan utilizations, credit timeliness,
repayment time suitability, repayment trend on monthly basis, repayment trend on
irregular basis, conducting supervision on monthly basis, irregular supervision, training,
business experience, technology and keeping book of records) can significantly influence
the loan repayment performance of borrowers.

H3: Availability of adequate legal and technical supports to Microfinances services can
significantly influence the loan recovery rate of MFIs.

1.6. Significance of the study

As it was discussed earlier in the background of the study, MFIs provide financial services
which are intended to fulfill the financial gaps of the poor that have not considered by other
commercial banks to access credits on their demand. Those micro finances which are
operating specifically in Oromia region have engaged in delivering credit services and other
financial schemes to the ultimate low income groups of the community. The existence of
secured loan repayment rate is the key success for the financial institutions to provide the
service in a profitable and sustainable manner. This requires the lending institutes to work on
enhancing an efficient loan repayment performance of the borrowers.

Although some empirical studies have been conducted on the credit delivery schemes of
MFIs in Ethiopia, further detailed empirical investigations in identifying the major factors
that can influence loan repayment performances of borrowers in the microfinance institutes
were found to be essential. Probably, it delivers a clear understanding on the findings to the
lending institute‟s management in order to make sound decision and corrective measures
where it is necessary. Moreover, the investigation will be more helpful for the MFIs

9
corporate governors, stakeholders and other microfinance institutes to revise their strategies
towards the findings in order to fix the default problems considerably.

1.7. Scope of the study

The study was conducted on microfinance institutions that are operating in Oromia National
Regional States. These microfinances provide financial service to individuals, groups,
enterprises, and other part of the societies to fulfill their financial needs in realizing their
economic and financial welfare. As it was discussed earlier, regardless of other factors that
can affect the sustainability (financial, economic and viability of borrowers) of those MFIs,
the study has been limited only to focus on the assessment of the viability (creditworthiness)
of micro and small scale enterprises and individual business loan borrowers. The study
covers the assessment of socio-economic and institutional factors that can affects loan
repayment performances of borrowers and other internal and external factors which
contribute for high default problems over the last 4 subsequent operational years of the
institutions.

1.8. Limitation of the study

The study was conducted on four sample MFIs that have large operational outreaches in
terms of number of client‟s outreaches among the 13 registered microfinance institutions
under the supervision of National Bank of Ethiopia which are operating in Oromia Region.
The number of MFIs selected for the study purpose was minimized due to the limited
timeframe to reveal the study results which is considered as a limitation of the study to
represent the populations at large. In addition, it was majorly relied on primary data collected
from sample borrowers and relevant partners including lending institute‟s staffs through
interviews and structured questionnaires. Lack of sufficient time and financial constraints
were also another limitation of the study. However, although the scope of the study was
limited to four MFIs that are operating in Oromia Region, it was believed that the responses
and data collected from those selected MFIs sample borrowers, lending institutes staffs and
relevant partners can represents the images of the overall microfinance Institutions operating
in Ethiopia at large.

10
1.9. Organization of the study

The major sections of this thesis paper have been organized as follows. The first chapter
consists of the introduction parts. The second chapter consists of review of the theoretical
and empirical related literatures on the evolution of MFI, importance of MFIs and related
factors that can influence repayment performance of borrowers at global and country wide
level. The third chapter describes the methodology of the study. In chapter four the data were
collected and descriptive results of the findings were discussed. In chapter five the economic
regression results of the findings have been analyzed and discussed. Finally, the sixth chapter
ends with summary, conclusions and recommendations of the study in general.

11
 CHAPTER TWO
Literature Review

In this chapter, important theoretical concepts on microfinance services and empirical studies
on factors that have been identified as determinants of loan repayment performances of
borrowers from various authors‟ points of view were presented.

2.1. Theoretical Literatures

The theoretical aspects of the literatures reviewed were focuses on the concepts of
microfinance services from the very beginning to today‟s operations in the microfinance
industries and the importance of these microfinance services in poverty eradication and
stabilization of high unemployment rates at global as well as country wide level. Moreover,
the concept of repayment performance were also reviewed and presented as follows.

2.1.1. The concept of microfinance services and its importance

The theorist Lysander Spooner was stated that the historical initiation of Micro financing
service was traced back in the middle of 1800‟s. Consequently he wrote the impact of the
credit schemes on the target entrepreneurs and farmers while targeting the poor peoples to get
out of the poverty. Meanwhile, the modern industry of microfinance service has been
initiated since 1970 by Grameen Bank of Bangladish and pioneer Mohammed Yunus. Shore
bank was the first microfinance and community development bank founded 1974 in Chicago.
According to Prof. Mohammed Yunus and Grameen Banks phrases, an improvement in the
economy and social welfare could partly realized through delivering micro-credits to the poor
people (Microfinance and Micro-credit, 2016).

Hor Kimsay (2011) reported that microfinance institutions were established originally as a
non-for- profit making financial schemes that had particularly serves the poor (low-income
groups of the society) at rural areas. As it was reported on this module, through time it was
believed by some peoples in Cambodia that serving those poor peoples as non-profit making
institute has its own impact on the financial sustainability of these MFIs to realize that the
services would address a wide range of poor peoples in the country. As a result MFIs in the
Cambodia has reviewed their credit scheme and tried to marginalize the services by

12
commercializing their credit schemes at lower interest rates than commercial banks. The
reason for transforming the MFIs service into commercial is to bring the transparency of the
financial services, increasing the confidence of donors and investors and to ensure that MFIs
are financially sustainable to serve wide range of poor societies which demands financial
services.

Moreover, the author stated that the average loan sizes of MFIs were steadily increased from
time to time based on the repayment experience of borrowers. However through periods an
increase in number of clients served and average loan sizes experiences some defaulted loans
over couple of few years that leads the microfinance practitioners to review their
implementation mechanisms and needs of new credit assessment methodologies that
emphasizes on the micro and small scale Enterprises (MSE). The assessment was focused on
the cash flow assessment of borrowers rather than the collateral requirements which may
fulfill the needs of MSE‟s. An increase in the average loan size and change of loan approach
to MSEs was the result of the increased capacity of lending larger loan size by MFIs (Hor
Kimsay, 2011).

Microfinance institutions in developing countries have a great contribution in reducing

poverty. It has been proved that microfinance service can be viewed as a developmental
strategy implementer that intended to empower poor women entrepreneurs, to initiate their
businesses and providing them awareness on how to manage their assets and its related risks
(Abdulfettah, 2013). Furthermore, the availability of these micro-credits schemes and other
financial schemes increases the number of enabled young poor groups which have been
organized in the form of micro & small scale enterprises. This in turn will creates a great
employment opportunities for the poor young societies which have been lacked with
financial sources at national level (Abdulfattah, 2013).

Alemayehu (2008) argued that microfinances are considered as a chance for the poor peoples
to promote self-employment through credit and saving service delivery. Microfinances have
been established to support the low income groups of societies by enabling them finance their
startup businesses and expansion of their low scaled income generating activities.
Moreover, people living in poverty, like in Ethiopia, need a wide range of financial services
for consumption smoothing, running their business and building assets. But due to collateral

13
requirement problems, poor people in most cases have no credit access from formal financial
institutes (Fikirte, 2011).

The banking requirements of high collateral valued assets or material guarantee and intrinsic
banking procedures are among the most difficulty cases that the poor cannot deal with. On
the other hand, the volume of loan demanded by small farmers/poor is not appealing to the
bank being there is an assumption that transactions are costly for small amount (Alemayehu,
2008). Furthermore, some theoretical frameworks also noted that unlike those microfinance
institutions, either government owned or private owned commercial banks are not willing to
serve the poor/low-income group peoples by providing small financial services due to the
fact that their requirements of collaterals. (Yunus, 1994)

In contrast, all microfinance institutions are intended to provide financial services in the
absence of any collateral values unlike the formal commercial banks by delivering various
microfinance schemes such as; micro credits, saving mobilization and provision of insurance
schemes to the poor. The major objectives of these microfinance services are to strengthening
the economic bases of the low-income generating activities of the poor peoples who are
living in the rural and urban areas of the country (Fikirte, 2011).

2.1.2. Loan Repayment Performance of borrowers

According to various researchers, microfinance institutions loan repayment performances can

be influenced by a number of factors identified as borrower‟s characteristics and lender‟s
lending characteristics. The lending approaches of microfinances can be classified as group-
based approach and individual-based approach. A common characteristic of group lending
approach is that the group obtains the loan under joint liability, where each member in a
group is responsible for repayment of loans of his or her peers. Screening of the viable loan
applicants, monitoring the individual borrower‟s efforts and enforcing repayment of their
peers‟ loan among the members are listed as the major characteristics of group-based lending
approaches (Zeller, 1996 as cited in Abafita, 2003)

Group lending approaches creates better information on borrower‟s efforts in settling the loan
obligations and have better monitoring advantages among the members than that of

14
individual borrowers. Members can get important information like reputation, indebtedness
and asset ownership of the loan applicants at a lower cost. They can also easily monitor
individual efforts made towards ensuring repayment. Moreover, group members appeared to
be in a better position to assess the reason for default and inform to the lending institutes for
the shocking experience exercised by the members which seems beyond their control (Zeller,
1996 as cited in Abafita, 2003).

Individuals are supposed to select those whom they trust to form a group with; that is they
are more interested to form group with those whom can make regular repayments and have a
good concern about the possible loss they face in case of non-repayments (Abafita, 2003). In
most of the cases, in group-lending approaches the functions of screening, monitoring and
enforcement of repayments are mainly endorsed to the group members than the lending
institutes (Abafita, 2003). Furthermore, in addition to the above benefits from group-based
lending approach, commitment of the borrower to feel indebtedness to the obligation they
entered into is an exemplified character of borrowers for on-time loan repayment
performances (Florence & Daniel, 2014).

On the other hand, individual based lending approach is the other approach that loan contract
obligation is endorsed only to the single individual borrower. According to Reikne (1996
cited in Abafita, 2003), individual based lending approach may have better repayment
performance than that of the group lending approach. This is due to the possible existence of
fragmented geographical locations and high market share competitions among the group
members which in turn affects mutual indebtedness‟s.

Besides, borrowers‟ characteristic that is the ability to repay the loan on- time can be
determined by: 1) the willingness of borrower to repay the loan, 2) capacity (how much debt
a borrower can handle) and 3) the cumulative capital (Assets) owned by the borrower. Before
delivering credit service, identifying and analyzing the characteristics of the borrowers is an
important issues to be considered by the credit managers to judge whether the borrowers
exerts the lowest efforts to honor the credit obligations (Florence & Daniel, 2014).

Repayment performance of borrowers can be affected due to various factors. An economic

theory suggests that a flexible repayment schedule set by the lending institutes can benefits

15
borrowers and potentially enhances their capacity of repaying their debts. On the contrary,
MFIs practitioners believed that high repayment recovery rate can be realized through
maintaining the regular repayment time schedules (Abdulfettah Bouri, 2013, Armendariz and
Morduch, 2000 and Morduch, 1999)

According to Bayang (2009 cited in Florence & Daniel, 2014), lack of sufficient monitoring
and reporting to ensure whether funds are utilized for the intended purposes are another
possible factors that determines repayment coverage. Furthermore, the repayment rate
improved as borrowers get closer to the loan limit, which is the maximum available loan. In
other words, motivation for reaching the maximum loan level is positively associated to the
repayment performance (Seyedmehrdad, Andrea, Giorgio, Paolo & Emanuele, 2016).

Majority of the literatures on repayment performance of the borrowers have been focused on
the group-based lending or joint liability lending category of the credit schemes. Most of
them have revealed that a group-based loan is more effective in minimizing the default rate
than that of the individual based loan (Ghatak, 1999 & 2000). As Greenbaum andThakor
(1995) and Coyels (2000) had been cited by Mohd Sherif (2012), borrower‟s inability and
unwillingness to repay the loan amount is considered as causes for high default rates.

Conceptualizations

The conceptual model for the study is to identifying and analyzing factors that can influence
the loan repayment performance of MFIs in Oromia region. In the literatures reviewed,
various empirical studies were focused on the probable factors that can determine repayment
performances. To carry on the empirical studies to investigate the probability of variables
that can affect repayment performance of borrowers, the study mainly focused on identifying
and analyzing borrowers socio-economic characteristics and lenders‟ lending characteristics.

16
Figure_1: Conceptual Framework

(Independent Variables) (Dependent Variable)

Borrowers socio-Economic
Characteristics:

 Age
 Gender
Loan Repayment
 Income from other
Status:
sources
 Fully Repaid
 Progressively
repaid
Loan related characteristics:  Past due
 Screening mechanisms  defaulted
 Loan Size
 Supervision and
Monitoring activities
Government’s
 Loan Utilizations
technical & legal
 Credit timeliness
supports
 Repayment schedule
 Provision of trainings
 Business Experiences
 Technology adoption

(Source: Adopted by Florence & Daniel (2014), modified by researcher)

17
 2.2. Empirical Literatures

Microfinance institutions plays an indispensable role in the developing countries especially

in Ethiopia by providing financial services (credit, saving mobilization and insurance
services) for the poor societies to substantiate their livelihoods although borrowers‟
repayment performance rate is stringent and demolished over the period of time.

The empirical studies on factors that can influence the loan repayment performance of
borrowers from various researchers‟ point of views were assessed and presented in the
following sub- sections. Those researchers have been conducted their studies to identify what
socio-economic and loan related factors can influence repayment performance of borrowers.
Moreover, the individual borrower‟s characteristics and lending institutes lending
characteristics at global and country levels were reviewed and presented as follows.

2.2.1. Empirical studies in other countries

Norhaziah Nawai & Mohd Noor Bin Mohd Shariff (2012) had studied factors affecting
repayment performance of microfinance programs in Malaysia. According to the researchers,
gender, formal religious education, distance to the lender office, business formality, total
sales per month, total loan received, monitoring loan utilization and disbursement lags have
significant effects on loan repayment performances. In addition, the researchers have
revealed also that loan diversions to unintended projects and weak pressure by the lending
institutes to repay the loan on regular basis have negative impact on repayment
performances. The researchers had employed multinomial logistic regression model to
estimate the equation of loan repayment and analyze the results.

Wongnaa and Awuyno (2013) have discussed factors that are affecting loan repayment
performances among Yam farmers in Sene District, Ghana and revealed that the expansion of
knowledge through education, business experience of the borrower, age, a diversified source
of income and close supervision to borrowers businesses are positively influence the
repayment performance of the borrowers while gender and marriage status have a negative
impact on repayment performance of borrowers. The researchers employed descriptive
statistics and probit regression model to estimate the equation and analyze the results.

18
Mohd Noor Bin, Mohd Shariff (2013) was conducted further study on the determinants of
repayment performance of microfinance programs in Malaysia in the case of individual
lending approach. He revealed that gender, business experience, education level, distance or
accessibility of market place, total loan size and transaction costs have positive coefficient to
repayment performances; while age, religion, total income, business sector, business status,
year of establishment, business area, total sales, loan type, repayment schedule, repayment
period and loan monitoring have negative coefficient between the delinquent borrowers and
good borrowers. The researcher had employed a descriptive analysis and multinomial logit
model to estimate the equations and analyze the results.

Njoku and Odii (1991) also studied on the determinants of loan repayment under the special
emergency loan schemes (SEALS) in Nigeria that late release of loans, cumbersome of loan
applications and disbursement procedures and political consideration to loan approval have a
negative coefficient to loan repayment performance. In addition to this loan diversion to non-
agricultural business, low enterprise returns due to poor adoption of agricultural
technologies, loan size, year of farming experience, year of formal education, household size,
loan period, farm size have significant effects for loan defaults.

Hunte (1996) argued that default problem destroys lending capacity of financial institutions
as the flow of repayment declines over periods. This implies that it seems transforming
lenders into welfare agencies, instead of a viable financial institution. The researcher stated
in the study that creditworthy borrowers may be adversely penalized whenever there is
inefficient screening mechanisms are employed by the lending institutes. Loan default may
also deny new applicants access to credit as the bank's cash-flow management problems
augment in direct proportion to the increasing default problem.

Hooman M. (2009) had also conducted the study on factors affecting loan repayment
performance of farmers in Khorasan-Razavi the Province of Iran. The researcher has been
revealed that interest rate has the most significant effects on repayment performances while
farming experience and loan application cost is the next important factor that can influence
repayment performance of farmer borrowers. The researcher has been used the logit model to
estimate the equations and analyze the results of findings.

19
2.2.2. Empirical studies in Ethiopia

In Ethiopia, loan repayment can be enhanced through having another source of income,
adequate educational background and borrowers own experience on the business world
(Abreham, 2002). Several researchers have conducted their studies in Ethiopia to determine
what borrower‟s behavioral attitudes, ability and willingness to repay their obligations have
been identified as factors that can influence borrower loan repayment performances.

Fikirte (2011) had conducted her studies on determinants of loan repayment performance of
borrowers in AdCSI MFI. The researcher revealed that age, family size, business types, sex,
dependence ratio and business experience were found to be significant to influence
repayment performance. Sex and constant variable have positive relation to the probability of
being defaulters while age, business experience, family size, business type and dependence
ratio have negative relationship to the probability of being defaulters. The researcher has
been employed a descriptive analysis method and binary logit model to estimate the equation
and analyze the results. As the age of the borrower increase the probability of being
defaulters becomes decreases. In another words the probability of being defaulter is higher
when borrowers are youngsters.

Similarly Abafita (2003) revealed also that borrowers with relatively younger aged are more
likely to commit default than that of the aged borrowers. In another words, borrowers with
aged groups are more likely to be creditworthy than youngsters assuming that they are
matured enough to sense responsible and settle their obligations on time. On the other hand,
Fikirte (2011) also stated that female borrowers have worse repayment status than that of
male borrowers.

Loan utilization supervision, suitable repayment schedule, availability of other sources of

income, educational background of the borrower and value of livestock were found to be
positively influence borrowers loan repayment performances, while an increase in number of
supported dependents, Sex and an intentional diversion of loans from its loan agreements
would negatively affects the repayment performance of borrowers (Abafita, 2003). Similar to
Fikirte‟s findings female borrowers are less likely to be creditworthy than that of male
borrowers. The significance level of those independent variables and its probability values in

20
explaining the dependent variable were estimated and discussed using tobit regression model,
while the probit regression model were employed to check and fix the hetroscedasticity
problems between the independent variable using the robust model to minimize the level of
the standard errors.

Abreham (2002) also discussed that loan diversion, featured by factors such as increased loan
size, longer grace period and credit experience of borrower are found to be significant to
influence repayment performance of borrowers. In line with this income from other sources,
having business experience on related economic activities and education are found to be
positively influence the repayment performance of borrowers while sex and repayment
period is negatively associated with loan repayment performances.

Moreover, the types of business activities that the borrowers engage in were found to be as a
factor that can influence the repayment performance of borrowers. The researcher reported
also that the size of the required collateral value determines the loan rationing mechanism.
That is the more the collateral values the borrower pledged, the favor they will be rationed
larger sized loan by the lending institutes. To arrive at these results the researcher has
employed a tobit model to estimate the significance of those explaining variable to Loan
repayment performances, loan diversion and credit rationing mechanisms equations
(Abreham, 2002).

Firafis (2015) has also been revealed that perception of borrowers towards repayment
periods, other source of income, availability of trainings, business experience, and family
size have been found as factors that can influence repayment performance of borrowers and
all are significant at 1, 5 and 10%. He has employed a logistic regression model to estimate
the significance of each explaining variables.

Tolosa (2014) have been conducted his study on performance of loan repayment
determinants in Ethiopian microfinances. The researcher revealed that an increasing age of
borrowers can significantly influence repayment performance of borrowers. The elder
borrowers have better repayment performance than that of youngsters (as argued by Abafita,
2003 and Fikirte, 2011 respectively). Hence age, education, time laps between loan
application and disbursement, loan size, loan diversion, repayment period, number of

21
dependents, availability of training and supervision and advisory service to borrowers were
found significant to influence repayment performance of borrowers at 1 and 5% significance
levels. The researcher employed binary logistic regression to estimate the model.

In general, all the above studies have basically focused on investigation of the determinants
of loan repayment performance of borrowers. However, conducting further assessment on
major factors that can affect repayment performance of borrowers of MFIs may provide an
additional picture of the gap for the microfinance practitioners to improve their lending
strategies.

22
 CHAPTER THREE

Research Methodology

The researcher have been employed various methodologies which enables the research
activities to be attained its results through different techniques specified in this chapter.
Those methodologies were discussed and presented as follows.

3.1. Methodology of the study

As it was discussed in the previous sections, in Ethiopia 35 Microfinance Institutions were

emerged in to the microfinance industry and provides their financial services to the poor
peoples who lacks financial services due to inaccessibility of banking service and collateral
requirements. These institutions provide their financial services in all nine national regional
states of the country (namely Amhara, Tigray, Oromia, SNNP, Afar, Hareri, Somalia,
Gambella & Benishangul Gumuz) and two city administrations (namely Addis Ababa & Dire
Dawa city admirations).

Among these microfinance institutions, the study was mainly focuses on microfinance
institutions that are either partially or fully operating in Oromia regions. The main reasons
for selecting the MFIs that are operating in Oromia region was due to the fact that large
numbers of microfinances are mainly operating in this particular area as compared to other
regions. Thirteen MFIs (which consists of 1 (8%) Government owned MFI and 12(92%)
Non-government and private owned MFIs) are providing their financial services in Oromia
National Regional State as of December, 2015 (AEMFI, 2015).

In the study the researcher have been employed a multistage random sampling techniques in
order to arrive at sample target respondents used for the study purpose. Hence, four
Microfinance institutions were selected from the total 13 MFIs that are operating in Oromia
region to conduct the study. The four microfinances were selected based on the operational
size and number of clients served by each selected microfinance institutions. Sample
borrowers were selected from the total micro and small enterprise borrowers and individual

23
business loan borrowers that are served with selected branches of those respective
microfinance institutions.

The following table presents the lists MFIs which are fully or partially operating their
microfinance services in Oromia Region.

Table -1: Lists of MFIs that are operating either fully or partially in Oromia Region

Ser. No. Name of MFIs

1 Aggar

2 AVFS

3 Busa Gonofa

4 Eshet

5 Gasha

6 Harbu

7 Meklit

8 OCSSCO

9 PEACE

10 SFPI

11 Shashemene

12 Wasasa

13 VisionFund

Source: AEMFI, Annual Report, December 2015

As it was discussed earlier, the MFIs selected for this study were selected due to their
significance in terms of clients outreach and loan amount disbursed in Oromia regional states
as compared to some other microfinance institutions. As a result, Busa Gonofa Microfinance,
Wasasa Microfinance, Oromia Credit and saving Share Company and VisionFund
microfinance institutions were selected as sample microfinance that was used for the study
purposes. The ratio and percentage sampling methods were also employed to determine the
24
number of sample borrowers to be selected from those selected MFIs. Finally, simple random
sampling techniques were employed to select the target sample borrowers which have been
used for the study purposes from all micro and small scale enterprises and individual
business loan borrowers.

The study have been applied a mixed research methodology to collect relevant research data
(both quantitative and qualitative data) using tools developed like but not limited to survey
questionnaire and Semi-structured interviews. Furthermore, during the survey sessions
typical observations to some selected borrowers business territories were also conducted to
identify the difficulties and challenges of sample borrowers while running their businesses.
This mixed methodology is considered as the best methods to answer the research questions
in an efficient and effective manner. The study has mainly used the primary data collected
from both lending institute staffs and sample borrowers.

3.2. Area of the study

Although the locations in Oromia regional state are segmented with different topologies, the
study mainly relied on few woredas of the region specifically near to Addis Ababa, Ethiopia.
Accordingly, the study was conducted on some sample respective branches of the four
selected microfinance institutes which are operating in Oromia region. Conventionally, the
sample branches to be used for the study purpose were selected from the nearby to Addis
Ababa, Ethiopia branches of those selected MFIs due to the shortage of timeframes to
explore the default problems of the those microfinance institutes in the region. The locations
of those selected branches are Burayu, Bishoftu, Dukem, Sebeta, and Nekemte. Four of these
branches are located in a radius of 30 to 40 Km to the West, East and South-West of Addis
Ababa respectively while the rest one is located 328 Km far from Addis Ababa, Ethiopia to
the Western Region of the country. In line with this, it was believed that conducting the study
from the diversified location in the Oromia region were ends with good results of findings to
deliver the ultimate conclusion and recommendations for the lending institutes managements,
policy makers, and interested stakeholders who uses the information for making proper
decisions.

25
 3.3. Research design and type

The study had applied a mixed research methodologies to analyze and interpret the findings.
The descriptive analyses approach were employed to explain the overall primary data
collected from the respondents using the structured survey questionnaires. The research also
used a quantitative and qualitative research method approaches to analyze the findings based
on the statistical data collected from the respective sources through the questionnaires, semi-
structured interviews and focus group discussions. The qualitative data method were
employed to collect the primary data from the sample respondents in relation to the socio-
economic characteristics of borrowers and loan related factors and other external and internal
factors that influences the repayment performance of borrowers. Whereas, the quantitative
data approaches were employed to gather the relevant information from various sources such
as the lending institutes, partner organizations and National Bank of Ethiopia.

In order to proceed with the research activities, the researcher defined the loan repayment
status (yi) of each individual sample borrowers of (ith) observation as a dependent variable.
The loan repayment is the dichotomous variable valued with either 0 or 1; meaning the loan
repayment status (y) of the ith borrower have the probability of being valued as either 0 or 1;
such that (value 1, if the respondent is creditworthy borrower (fully or progressively repaid)
the loan otherwise 0, if the borrower is defaulter.) In order to estimate the model for
dependent variable with limited range of values, applying the ordinary least square (OLS)
may result in biased and inconsistent parameters (Fikirte, 2011). The Common models for
estimating such parameters include probit (standard normal), logit (logistic) and tobit
(extreme value) (Maddala, 2005).

The probit model limits the probability value of dependent variables between 0 and 1. The
probit model was chosen to be used for the study purpose because it is simple to estimate the
probability of each explaining variables to influence the dependent variable using the
cumulative distribution function (CDF). Moreover, it is more helpful to determine the
marginal effects of coefficients on the dependent variables.

26
 ………………………………………………... (1)

Where yi* is the threshold value for yi and is assumed to be normally distributed.

Moreover, as Abafita, 2003, stated in his study Maddla, 1983 has employed the model for
utility index to estimate the repayment decision of borrowers. The utility index expresses the
decisions of borrowers to repay the loan either fully or partially due to some independent
factors which related with the repayment performances.

Ui= βXi + εi ………………………………………… (2)

The unobservable utility index (precisely a utility derived from repaying) to the decision of
repaying loan in full, assuming that:
LRPi=1, if Ui>o (borrower repaid loan in full); or
LRPi=O, if Ui < O (borrower did fail to repay loan in full),
Where, LRPi is loan repayment status of the ith borrower.
Assuming Ui are normally distributed with a zero mean and variance δ2, the probability that
Ui; >0 can be computed as:
Pi=Prob (Ui>0) = F (Ui) = F (β’Xi)- - - - - …………………………………………. (3)

Where; F is the CDF (Cumulative distribution function). Moreover, as (Maddala, 1983 were
cited by Fikirte, 2011), the normal and logistic CDFs are very close in the mid-range, but the
logistic function has slightly fatter tails than the normal function.

yi* = β+ βXi + εi ………………………………………………………….…………….(4)

27
Hence, the probability of cumulative distribution function of the repayment performance of
borrowers is explained as follows:

LRPyi* = f (AGE, GENDER, INCOMB, AVLSIZ, MONTRO, UTLIZED, CRDTIML,

RPTSUIT, RPMNTHL, RPIRRG, VSTMNTH, VSTIRRG, TRADQU,
BUSEXP, TECHN, BOOKK, ε) ……………….…...………. (5)

Definition of the variables:

Dummy variables have been designed for some factors as follows:

LRPyi The value of repayment status of the ith borrowers (i.e either 1
if creditworthy borrower otherwise 0, if defaulter)

β The parameters of the coefficient of the explanatory variables

which measures significance

Xi The value of the explaining variables that determines the

probability of repayment of ith borrower

εi The level of disturbance (Error terms)

Age (AGE): Age of the sample borrowers in year (0= if young, other wise 1
if adult)

Gender (GENDER): Gender categories of the sample respondents. (0 = if female,

otherwise 1 if Male)

Income (INCOMB): Income generated from other sources per month

Supportive supervision (UTLZSUP): Number of visits that the lending institution officers
conducted per month and the level of special supports other
than trainings delivered by the lending staffs and other
supporting bodies on the field to each members of borrowers.

28
UTLIZED: Used the proceeds received as loan either fully or partially for
the intended purpose only (0, if diverted otherwise, 1).

Loan Size (AVLSZ): The loan amounts disbursed to the respective borrowers based
on their work plan.

Members monitors each other (MONTO): Measures how members of an Enterprise or group-
based borrowers are more likely monitor one another about the
effective and efficient utilization of the credit to the intended
purposes (1, if members monitor each other, otherwise 0)

Suitability of repayment schedule (SUIRPM): The suitability of repayment schedules to the

borrowers (Weekly, Monthly after grace period, quarterly, once
a year) (1, if suitable, otherwise, 0)

Trainings (TRADQU): Provision of adequate trainings by the lending institutes; Post

training follow-up and technical supports by the lending
institutes and other concerned bodies (1, if adequate, otherwise,
0)

Technology (TECHN): Measures Borrower‟s advancement in manipulating

technologies if it is applicable to the business while running
their businesses (1, if applied otherwise 0)

Business type (BUSTYP): refers to the effects of business types that the sample borrowers
have been engaged in.

Timeliness of loan (CRDTIML): The appropriateness of loan release by the lending institutes
on time (1, if credit has been received on time, otherwise, 0).

Generally, we can categorize these explanatory variables as Socio-Economic factors, Loan

related factors and other internal and external factors that can influence the loan repayment
performances of the MFIs.

29
 3.4. Sampling Techniques

The study adopts multi-stage sampling techniques to arrive at target sample borrowers. As it
was discussed in the previous section, the sample MFIs have been selected from the total 13
microfinance institutions which are fully and partially operating in Oromia National Regional
States.

As it was indicated in table-2 below, four microfinance institutes (Busa Gonofa, OCSCO,
Wasasa & VisionFund) were selected for the study purpose from all 13 MFIs which are
operating in Oromia region based on the proportional level of their significance in terms of
number of client outreaches and amount of loans disbursed by each institutes.

Table -2: Microfinance Institutes that are fully or partially operates in Oromia Region

Proportional
Clients Outstanding
S/No. MFIs clients
Outreach Loan
outreaches
1 Aggar 10,878 165,717,214 0.84
2 AVFS 12,343 17,800,022 0.95
Busa
3 67,787 161,153,151 5.24 *
Gonofa
4 Eshet 15,406 53,534,199 1.19
5 Gasha 5,544 17,697,629 0.43
6 Harbu 27,565 52,438,497 2.13
7 Meklit 10,619 65,525,908 0.82
8 Ocssco 908,828 3,389,019,957 70.27 *
9 PEACE 22,210 93,498,440 1.72
10 SFPI 41,914 170,208,069 3.24
11 Shashemene 2,015 24,358,928 0.16
12 Wasasa 77,392 354,140,759 5.98 *
13 VisionFund 90,922 426,424,460 7.03 *
Total 1,293,423 4,991,517,233 100%
Source: AEMFI, Annual Report, December 2015

*Sample MFIs selected for the study

30
Table-3 below presents the proportional percentages of each selected sample microfinance
institutions clients outreaches to the total clients outreaches of the four MFIs. Accordingly,
Busa Gonofa MFI covers 6 percent of the total client outreaches, OCSSCO tooks the
majority proportions which is 79 percent of the total outreaches, Wasasa MFI covers 7
percent of the total client outreaches and Visionfund had a proportional clients outreach
percentages of 8 percent of the total clients served by all the four MFIs. The details presented
as follows.

Table – 3: Microfinance Institutes selected for this study based on the number of clients
outreach

Percentage of
Sample Clients Outstanding
Clients
MFI Outreach Loan
outreach
Busa
67,787 161,153,151 6%
Gonofaa
OCSSCO 908,828 3,389,019,957 79%

Wasasa 77,392 17,697,629 7%

90,922 52,438,497 8%
VisionFund
1,144,929 284,823,476 100
Source: Computed from AEMFI, Annual Report, December 2015

The table-4a below presents the maximum clients outreached which have been served per
credit officers of the sample microfinance institutes. Accordingly, OCSSCO relatively serves
much more clients per single loan officer as compared to other three MFIs. On the other
hand, VisionFund MFI is relatively served less clients outreach per credit officers.

31
Table -4a: Lists of active clients served by sample MFI per credit officers

# active Average # of
# of credit
Sample MFI Clients borrowers per
officers
Outreach credit officers
Busa Gonofaa 67,787 133 510
OCSSCO 908,828 1,221 744
Wasasa 77,392 137 565
VisionFund 90,922 269 338
Source: Computed from AEMFI, Annual Report, December 2015

Sample borrowers were determined systematically using the proportion method to determine
the proper sample size which may represents the overall population.

n = Z2pq/E2

Where,

n: proposed sample respondents

Z2 Level of confidence interval at 95%; i.e. ~1.96

p: Estimated proportion of sample defaulters

q: Estimated proportion of sample non-defaulters

E^2 Standard Error

n= ((1.96^2) (0.50*0.50)/ (0.05^2)

~ 246

Approximate Sample Design Error: 1.5*246 = 369

Estimated non-respondent rate: 8%*369 = 29

Adjusted sample size (n) = 398

As it is shown in the table-4b below, the full number of samples to be selected from each
selected MFI has been allocated as; 6% from BG MFI, 79% from OCSSCO, 7% from

32
Wasasa Microfinance and the remaining 8% from VisionFund Microfinance institutes that
operates in Oromia region. The allocated sample sizes to each respective MFI (BG MFI,
OCSSCO, Wasasa MFI & VisionFund MFI) considers both defaulters and creditworthy
borrowers equally for the study purpose.

Table -4b: Allocation of Sample Size among the selected MFIs

Total
Clients Outstanding Percentage of Sample
Sample MFI Sample
Outreach Loan Outreach Proportion
Size
Busa Gonofaa 67,787 161,153,151 6% 398 24
OCSSCO 908,828 53,534,199 79% 398 314
Wasasa 77,392 17,697,629 7% 398 28
VisionFund 90,922 52,438,497 8% 398 32
1,144,929 284,823,476 100 398
Source: Computed from AEMFI, Annual Report, December 2015

As it was stated in the previous section, the study mainly focuses on the individual
entrepreneurs and micro and small scale enterprises that have been served by those selected
MFIs. These borrowers were selected due to the significance of the loan sizes disbursed to
each MSE & Individual Business loan borrowers as compared to other group-based
borrowers. Furthermore, it is believed that number of researchers were conduct their studies
on rural and urban group-based borrowers of MFIs to assess the repayment performance of
borrowers while other borrower groups of MFIs are involved in different micro-credit
services of MFIs.

Most of the financial and operational reports of MFIs indicate that they are facing great
challenges due to an increasing number of defaulters from year to year which probably
undermines the respective institutions financial sustainability. Hence the paper intends to
assess the major factors that contribute for loan defaulters by considering MSE and
Individual entrepreneur borrowers as a major study area. As a result the sample respondents
were selected randomly from those borrower groups.

Table-5 below shows number of active MSE and individual business loan borrowers served
by selected branches of the four MFIs at some particular areas of the study (Burayu, Sebeta,

33
Dukem, Bishoftu & Nekemte) during the year ended 2014/15. The respective branches
outreaches are as follows:

Table- 5 Number of active MSE and Individual Business Loan borrowers

# of client
Sample
outreaches Loan Sample
Microfinance Selected branches
(MSE, IBL Disbursed Size
Institutions
borrowers,..)
BG MFI Bishoftu 2,187 26,686,000 24

OCSSCO Burayu,Sebeta,Bishoftu 327 21,612,624 314

& Nekemte
Wasasa Dukem 105 7,254,000 28
Vision Fund Sebeta 291 3,159,966 32
Total 398
Source: Computed from annual Operational Reports of MFIs, 2014-15

According to FeMSEDA Reports (2015, cited by NBE annual report, 2014-2015), in

Ethiopia 271,579 micro and small scale enterprises were organized and served through MFIs
with credit and other microfinance schemes to fill the gaps of their financial needs in
realizing an improvements in their economic and social welfare. Oromia Region shared a lion
proportion, i.e. 51.9% (140,858) MSE borrowers with an outstanding loan amount of Birr
5.84 Million from the total MSEs served through the MFIs in Ethiopia (NBE, 2016).

In light of this, OCSSCO have served larger number of MSE as compared to others. As it is
shown in the above table, the proportional sampling methods have been used to arrive at the
sample sizes to be allocated to each selected MFIs. Accordingly, 24 samples was selected
from BG MFI, 314 samples was selected from OCSSCO, 28 sample borrowers have been
alos selected from Wasasa Microfinance and the remaining 32 samples was selected from
VisionFund microfinance.

Generally, the study had been intensified and conducted over 398 sample borrowers who
have been served by those selected MFIs based on the proportional sample quotas allocated
in the table above. Simple random sampling techniques were employed to arrive at the
sample respondents. The reason for using the random sampling method is that the number of

34
target borrowers for the study i.e. MSEs and Individual business loan borrowers are
relatively smaller as compared to other rural & Urban group-based borrowers. As a result to
arrive at sample representative respondents from the target borrowers‟ random sampling
method was more appropriate than other methods.

3.5. Data Sources

The research has been conducted using both primary data and secondary data sources to
retrieve the findings and analyze the problems at hand. The primary data were collected
using the structured questionnaires to be responded by both selected sample borrowers
(Defaulters and creditworthy borrowers) and lending institute staffs (Branch managers,
Credit officers, Accountants, Management of the lending institutes, and other relevant staffs).
Furthermore, semi-structured interviews were also conducted with some sample borrowers
while on site visits to borrowers‟ business territories. Further interviews were also held with
National Bank of Ethiopia‟s Microfinance directorate department staffs on the subject matter.
Moreover, the researcher also had a chance to visit the borrowers businesses to identify the
problem they have faced while running their businesses after engaging into the credit
schemes. The Secondary data used for this research was found from borrowers master
register books, the year-end audited financial statements and operational reports of the
respective MFIs availed by NBE, AEMFI and lending institutes.

3.6. Data collection tools

As it was discussed on the above section, the study had employed some research tools to
collect the relevant data which helps for the better conclusion on the results of the findings.
Among the tools:

1. Interviewing the respondents (sample Borrowers: defaulter and non- defaulters)

2. The Structured Questionnaires were developed to be responded by both borrowers
and lending institutes staffs which supported by an open ended interviews with the
focal personnel (Clients, Managers, officers, Operation & Finance unit staffs and
other stakeholders). Since the study areas to be assessed were fallen in oromia region
where majority of the local people uses „Afan oromo‟ as a working language, the

35
 questioners were also redesigned in local language “Afan Oromo” to help the
respondents understand each queries and get reliable data. Pre-test to those
questionnaires were also implemented on four respondents to test how well they
could understand each question and avoid ambiguity and biasness while responding
to each question. Hence an appropriate modifications and corrections have been made
where it is necessary.
3. Focus group discussion methods were also employed in identifying further
unforeseen factors that may contributes for borrowers under performances.
4. All relevant secondary data (client‟s information and MFIs clients‟ outreaches) from
both lending institutions and other sources were also gathered and used for analysis.

3.7. Data analysis techniques

The qualitative data have been collected from the primary sources using the tools described
in the above section of the paper. The descriptive analysis approach were employed to
analyze the primary sample data collected from each sample borrowers, lending institutes
officers and other pertinent sectors. This method was also used to explain the observed
reflection of borrowers after the credit service during conducting the onsite field visits to the
borrower‟s business territories. Those data which have been collected from the target
samples were statistically tested using the t-test, Multicollinearity test & chi-square tests

The probability values and the significance level of each explanatory variable to influence
the dependent variable were explained and analyzed. Moreover, the econometric regressions
between the dependent and independent variables had been estimated and analyzed using the
models specified for this purpose on the pervious section to show the results of the findings
for the management of the lending institution, stakeholders and policy makers to take
corrective measures toward the findings based on the conclusion and recommendations
delivered by the researcher at the end of the paper.

The binomial probit regression models were employed to determine the significance of the
independent variables in explaining the loan repayment performance of borrowers.

36
Furthermore, the marginal effects of the coefficient of each explanatory variable were also
analyzed and discussed accordingly.

Description of the independent variables and their expected hypothesized signs

A. Socio-Economic factors and borrowers characteristics

1. Age: Some researchers have taken the ages of the borrowers as a variable that can
influence the repayment performance of borrowers. As it was stated in the previous section,
in group-based lending approaches, Abafita, 2003 have revealed that the more youngsters
the age of the borrowers the less the repayment recovery rates achieved by the lending
institutes; that means the more the aged group borrowers can take the responsibility of being
liable and creditworthy than that of the youngsters. Similarly, the more the older and aged
the borrower groups are the more likely they are creditworthy borrowers that have better
repayment performances while the young borrowers are more likely to be defaulter
borrowers (Fikirte, 2011). Both authors have been conducted the research on the group-
based lending approaches whereas this study might answer for some other borrower types
like MSE and individual Entrepreneurs borrowers too. Based on the above studies the study
cannot pre-determine the signs of the variable to influence the repayment performances.

2. Gender: This research considers the gender characteristics of the borrowing groups as
an explaining factor to evaluate how the gender is probably determine the repayment status
of the borrowers. As (Teferi 2000 and Berhanu, 1999 cited by Abafita, 2003), it was argued
that female borrowers are more creditworthy than that of male borrowers. The assumption
was females took great obligations and sense of responsibilities while managing their
households. This study also intends to see the magnitude of these gender characteristics in
the cases of MSE borrowers and Individual business loan borrowers. The expected signs of
this gender characteristic groups to the dependent variable could not still pre-determined.

3. Income from other sources: Borrowers with some diversified income sources can
make repayment performances more successful. Income from other sources can be listed as
follows but not limited to Salary/Wages, equipment rental services (such as house rent, and

37
others). An increase in other source of income earned by borrowers might have the
possibility that loan could probably repaid by respective borrowers on time. Thus, this
variable might have an expected value with positive signs to explain the probability of being
non-defaulter.

B. Loan related factors considered for the study

4. Monitoring others loan utilization: This refers to the probability of each member in a
borrowing group attempt monitoring the loan utilization statuses of others. As the
monitoring for the utilization of the credit for the intended purpose increases, the probability
of loan defaulting by group members can be minimized. Thus, positive coefficient sign is
expected.

5. Average loan size: This refers to the average loan size that the lending institutes
approved to the borrowers business appraisals. As it was revealed by some researchers, this
factor can negatively or positively influence the repayment performance of borrowers. The
assumption is that the more the sufficient loan amount disbursed to the requesters the more
they can finance the proposed business and the more they can succeed the business
profitably. On the other hand, the less approved loan size below the proposed business plan
to the borrower, the higher the possible difficulties they can face while running the business
due to insufficiency of funds available by the lending institutes. On the contrary, the excess
loan size approval to the ambitious loan amount requested by borrowers may have imposed
the burdensome liabilities on the shoulder of the borrowers. To mitigate these problems,
efficient and effective utilization of the loan funds could be very essential for the borrowers
while running their business. Accordingly, the sign of the coefficient cannot pre-determine
by the researcher.

6. Timeliness of loan released: This refers to the time laps that taken from the borrowers
screening process to the credit delivery time by the lending institutes. From the fact that
some borrowers businesses have seasonal basis nature, the longer time passes by the lending
institutes to process the credit can significantly influence the successfulness of that

38
particular business and hence affects the repayment performance of that particular borrower.
The assumption is that the more the fastest the credit service are the more the borrower can
utilize the loan for the intended business plan timely and the more the credit would be
settled on time profitably. Positive sign is expected for this variable.

7. Repayment period suitability: Most of the MFIs in Ethiopia set the maturity date of the
loan for an annum i.e. they deliver credit for one year. Some MFIs like OCSSCO and
Wasasa do have a credit terms for more than a year (2-3 years) based on the nature of
business types. The flexible grace period for some months after the loan disbursement
enables the borrowers to have sufficient working capital so that they can run their businesses
profitably. Accordingly, the expected sign for this variable is positive.

8. Repayment on Monthly Basis: Refers to the frequency of borrowers repayment

intervals on monthly basis. Most microfinance institutions usually set the regular repayment
schedules to be effected on monthly basis. The more frequent the repayment trends
experienced by the borrowers, the better repayment performances to be attained by the
microfinance institutions. Accordingly, positive sign is expected to influence the repayment
performance of borrowers.

9. Repayment on irregular Basis: Refers to the frequency of borrowers repayment trends

on irregular time intervals. Although microfinance institutions set the regular repayment
schedules to be effected on monthly basis, some borrowers‟ arbitrary repays the loan on
irregular basis which leads for pass dues. The more time lags in repayment trends
experienced by the borrowers, the less probability of better repayment performances to be
attained by the microfinance institutions. Accordingly, negative sign is expected to
influence the repayment performance of borrowers.

10. Loan utilization: Refers to how the borrowers of the lending institutes utilized the loan
amounts for the pre-intended business plan based on the loan agreement they are binding to.
Some borrowers utilize the loan for some unintended projects that is termed as project
diversion. As it is described in the definition of the terms, there are possible causes for the
borrowers to use the proceeds received for some other activities. Loan diversion for some

39
activities that can generate better profits could positively influence the repayment
performance of borrowers. On the other hand the utilization of credit for some other
activities that cannot generate returns may negatively influence the repayment performance
of borrowers. Accordingly, the expected sign for this variable cannot be pre-determined.

11. Training: Capacity building activities through delivering workshops and short term
trainings by well-organized and trained personnel to borrowers could enhance their well
understanding about the credit services and maintain their skills and knowledge on the
business environment. Borrowers who are equipped with relevant trainings and skill
developments can effectively manage and monitor the day to day operations of their
business. Training has an indispensible contribution to the borrower‟s business success.
Therefore, delivering an adequate and sufficient training to all borrowers in a consistent
manner may increase the repayment performance of borrowers. Accordingly, positive sign
is expected for this variable.

12. Business Experience: Borrowers with better knowledge and experiences on the relevant
businesses can profitably run their businesses. As the time of crises happening to the
specific business segment, borrowers with previous business exposures and experiences
may recover their business and will succeed consequently. On contrast, borrower with no or
less experience on the market and know how on business activities might face high
probability of challenges to run profitably. The good experienced the borrowers are the
more they can succeed their business and repay the loan timely. On the other hand, the less
they are experienced the highest the probability of being defaulters they are. Hence the
variable expected to have positive coefficient to influence the probability of being
creditworthy borrower.

13. Technology: Today businesses equipped with advanced technology do have high
probability of success. Enterprises and individual entrepreneurs who have employed a
modern technology while running their respective businesses could have high possibility of
success which in turn enables them to repay the loan timely. On the contrary, borrowers
who have not employed the best technology could earn less profit as compared to others.

40
The variable is expected to have a positive sign to explain the probability of being non-
defaulters.

14. Irregular supportive supervision: Refers to the frequency of lending institutes

officers‟ visits to the clients business to monitor the effective utilization of the loan for the
intended purpose. The more time gaps between the first visits and the second round visits
irregularly or more than the standard visit time which is mostly beyond one month might
have a considerable effect on the loan utilization of borrowers which leads for loan
diversion to the unintended project purposes. Accordingly, it is expected to have a negative
effect to the probability of borrowers being creditworthy.

15. Monthly supervision: Refers to the frequency of lending institutes officers‟ visits to the
clients business to monitor the effective utilization of the loan for the intended purpose. The
more frequent the visits and supervision to the client‟s business territory might help the
borrower to utilize the loan for the intended purpose only. Furthermore, the visits to those
target borrowers will helps in identifying the loops that faces the borrowers either
technically or financially in order to minimize the risks suffer from defaults. Accordingly, it
is expected to have positive effects to the probability of borrowers being creditworthy.

16. Keeping book of records: This refers to borrower‟s trends of recording the financial
transaction to book of records to monitor and evaluate the profitability and financial position
of their respective businesses. The borrowers who manage their expenses and revenues as
well as cash flows could probably better monitor their loan repayment status than none.
Hence, positive sign is expected.

C. Other external parameter that may influence repayment performance of

borrowers

17. Technical and Legal Support: In this study it refers to the availability of consistent
government unit‟s technical and legal support to the MFIs operation. The efficient legal
supports enacted by the legislative bodies for the wrong acts of defaulters in enforcing them

41
 to repay the outstanding loans could have positive effects in increasing the loan recovery
rate of MFIs. The more supports provided by the concerned bodies to the MFIs credit
delivery service might enhance the availability of loanable funds to finance the next needy
new borrowers as a result of on time repayment is collected. Similarly, provision of
technical supports to borrowers business by the concerned bodies may contribute for
betterments of running the business at profit margin. This variable could positively
influence the loan repayment performance of borrowers and efficiency of lending institutes.

From the above explanatory variables, some variables are continuous which are measured in
terms of years such as age and business experiences. On the other hand, group size, loan size
and income generated from other sources are also other continuous variables that are
measured in numeric value. These variables were explained in descriptive statistics in the
next chapter. After the estimation of the model, the marginal effects of those continuous
explanatory variables were also calculated in order to know the probability effects of those
explaining variables on loan utilization and repayment performances.

There are also discrete variables that need the respondents to choose among the available
alternatives. To treat those variables the binary model were employed. Borrow from other
credit sources has been valued 0, if the borrowers did not take additional credit from other
sources (Iddir, Iqub 3 , friends/relatives or Banks), otherwise 1. Similarly socio-economic
factors like gender characteristics of the sample borrowers were also treated as discrete
variables valued with 1 if male otherwise 0 if the sample borrower is female.
Additionally, other seventeen discrete and one continuous explanatory variable were
identified and similarly valued as 0 and 1. Therefore, the discrete variables used to compute
the marginal effects of the explanatory variables on the dependent variables were denoted
and listed as follows:
1. Age: is a discrete variable that valued 0, if the respondent is in the category of young
(20-29), otherwise 1, if adult (greater than 29)

3
‘Iqub’ is informal associations local organized to contribute savings

42
2. Gender: is a discrete variable that valued 0, if the sample respondent is female,
otherwise 1, if male
3. INCOMB: valued 0, if sample borrower do not have other source of income, other
wise 1, if borrowers have another income sources other than income generated from
credit scheme
4. MONTRO: valued 0, if borrowers did not monitor the utilization status of other
members, other wise 1, if they experienced monitoring.
5. UTLIZED: valued 0 if borrowers didn‟t utilized the loan for the intended purpose,
otherwise 1, if properly utilized.
6. CRDTIML: valued 0, if the borrower didn‟t receive the requested loan timely,
otherwise, 1, if they received on time.
7. RPTSUIT: valued 0, if borrowers assumed repayment time is not suitable, otherwise,
1 if suitable.
8. RPMNTHL: valued 0, if borrowers didn‟t experience repayment on monthly basis,
otherwise, 1 if applicable.
9. RPIRRG: valued 0, if borrowers didn‟t experience repayment on irregular basis,
otherwise, 1 if applicable.
10. VSTMNTH: valued 0, if borrowers didn‟t experience monthly visits to their business,
otherwise, 1 if applicable.
11. VSTIRRG: valued 0, if borrowers didn‟t experience irregular visits to their business,
otherwise, 1 if applicable.
12. TRADQU: valued 0, if borrowers didn‟t get adequate and sufficient training,
otherwise, 1 if applicable.
13. BOOKK: valued 0, if borrowers didn‟t kept book of records, otherwise, 1 if
applicable.
14. UTLZSUP: valued 0, if loan utilization did not supervised, otherwise, 1 if applicable.
15. RPMSUP: valued 0, if loan repayment did not monitored, otherwise, 1 if applicable.
16. LSUFFCNT: valued 0, if loan size did not sufficient, otherwise, 1 if sufficient.
17. BUSEXP: valued 0, if sample borrower do not have relevant business experience,
other wise 1, if applicable

43
 CHAPTER FOUR

Descriptive Analysis

The descriptive statistics used to analyze the results of the data collected were used tools
such as percentages, mean, frequency distribution and standard deviations. Tables, charts,
graphs have been also used to express the descriptive results of the survey. Furthermore, the
t-test and chi-square test were also employed to evaluate the variations between the
creditworthy and defaulters based on each explanatory variables.

4.1. Questionnaire Response rate

Based on the sample size determination, the researcher distributed 398 questionnaires in
order to collect primary data from sample borrowers of the four sample microfinance
institutes. Even if maximum effort was exerted to make sure all the distributed questionnaires
are returned back, some questionnaires were not submitted due to various reasons like
political volatilities arisen during the survey season. From the total 398 questionnaires
distributed 319 of them were successfully filled and returned back. That is, 79 of them were
not returned back and thus not used in the research. Therefore, the response rate of the
questionnaire was 80.15 percent. Accordingly, the research data presentation, analysis, and
conclusions were based on these responses.

4.2. Socio-economic characteristics

Age: The cross-tabulation shown in Table-6 indicate that the loan repayment performance of
borrowers aged in youngster groups which covers 62 percent of the total young respondents
were the credit defaulter while the remaining 38 percent of the total young borrowers were
creditworthy borrowers. On the other hand, 56.9 percent of the total adult borrowers were the
credit defaulters while 43.1 percent of adult respondents were creditworthy borrowers.
Defaulters represent the majority relative to creditworthy in both youngsters and adult
grouped sample borrowers.

44
Table-6: Repayment performance versus ages of the sample respondents

Age (Binned) Total

Youth (19-29) Adult (30-65)

Count 31 153 184

Defaulter % within LRP 16.8% 83.2% 100.0%

% within Age (Binned) 62.0% 56.9% 57.7%

LRP
Count 19 116 135

Credit worthy % within LRP 14.1% 85.9% 100.0%

% within Age (Binned) 38.0% 43.1% 42.3%

Count 50 269 319

Total % within LRP 15.7% 84.3% 100.0%

% within Age (Binned) 100.0% 100.0% 100.0%

Source: Survey result

Gender: Based on the gender assessment, from the total sample respondents, 133 (41.7%) of
them were females while the remaining 186 (58.3%) of them were male. Further, it was
evident that 57.7 percent of the total respondents were defaulters and thus the remaining 42.2
percent of the respondents were creditworthy, regardless of sex or any other variable. Cross-
tabulation of sex with loan repayment performance, which is being creditworthy or defaulter,
showed that 56.4 percent of female respondents were defaulter while 58.6 percent of male
respondents were defaulters, that means 43.6 percent of female and 41.3 percent of male
respondents were creditworthy borrowers. The figure shows that male respondent borrowers
relatively have less repayment performance than female. The table-7 below shows these and
related figures in the detailed cross tabulation of sex with loan repayment performance
(LRP).

45
Table-7: Repayment performance versus the gender

GENDER Total

Female Male

Count 75 109 184

Defaulter % within LRP 40.8% 59.2% 100.0%

% within SEX 56.4% 58.6% 57.7%

LRP
Count 58 77 135

Credit worthy % within LRP 43.0% 57.0% 100.0%

% within SEX 43.6% 41.4% 42.3%

Count 133 186 319

Total % within LRP 41.7% 58.3% 100.0%

% within SEX 100.0% 100.0% 100.0%

Source: Survey result

Borrowers Income Characteristics:

Table-8: Do you have any other source of income?

Frequency Percent Valid Cumulative Percent

Percent
No 198 62.1 62.1 62.1
Valid Yes 121 37.9 37.9 100.0
Total 319 100.0 100.0
Source: survey results

Based on the response of the sample respondents, 121 of the sample respondents had income
from other sources while 198 of the respondents did not have any other source of income.

46
Table-9: Borrowers annual income from other sources (in ETB) (Binned)

Frequency Percent Valid Cumulative

Percent Percent
<5000 20 6.3 16.5 16.5
5001-10000 35 11.0 28.9 45.5
10001-15000 18 5.6 14.9 60.3
Valid 15001-20000 17 5.3 14.0 74.4
20001-25000 2 .6 1.7 76.0
>25000 29 9.1 24.0 100.0
Total 121 37.9 100.0
Missin
System 198 62.1
g
Total 319 100.0
Source: survey results

The assessment on the income from other source before credit service shown that from the
total 121 valid respondents, 20 respondents, 35 respondents, 18 respondents, 17 respondents
have annual earnings less than Birr 20,000 while 2 respondents and 29 respondents had
earnings greater than Birr 20,000. This implies that majority 74 % of the valid respondents
have an annual income before the loan less than Birr 20,000 while the remaining 26% of the
respondents have income greater than Birr 20,000. Income from other sources have
significantly influence the repayment performances at 5 % level. This is shown in the table
above.

4.3. Loan related characteristics

In this sub-section, the loan related factors that can influence repayment performance of
borrowers have been analyzed and presented as follows.

4.3.1. Loan Disbursement and Repayment performances

Credit from other sources: Microfinance institution borrowers might also use other source
of finance. From this regard, sample borrower respondents were asked whether they have
taken loan from other sources and from which sources do they borrowed so far. Accordingly,

47
their responses indicates that 5, 8, 36, and 3 of sample respondent borrowers were took other
credits from „Idir, Money lenders, friends or relatives and Bank respectively. That is, 267 of
the sample respondents did not took any credit from other sources to finance their businesses.
The other issues to be considered was cross-tabulating these sources with that of loan
repayment performances. Accordingly, from those using „Idir‟, 60 percent of them were
defaulters while 40 of them were creditworthy; from money lender users 62.5 of them were
defaulters while 37.5 of them were not; from those using friends or relatives as other source
of credit, 42.2 percent and 27.8 percent of them were defaulters and creditworthy
respectively; finally those who were not borrowed from other sources of credit consisted 55
percent defaulters and 45 percent credit worthy respondents. These figures were presented in
detail in the table-10 below.

Table-10: Sample respondents response to other source of credit (Cross tabulation)

Friends/
Money relative
Idir Bank Non-
lenders s Total
Borrower
s
Count 3 5 26 3 147 184
%
Defaulter within
60.00% 62.50% 72.20% 100.0% 55% 57.70%
colum
n
LRP
Count 2 3 10 0 120 135
%
Creditwort
hy within
40.00% 37.50% 27.80% 0.00% 45% 42.30%
colum
n
Count 5 8 36 3 267 319
%
Total within
100.0% 100.0% 100.00% 100.0% 100.00% 100.0%
colum
n
Source: Survey result

Regarding the repayment performance of sample borrowers who took credit from other
sources, it is important to explain their repayment statuses. Accordingly, as shown in the

48
table-11 below, 52 sample respondents were borrowed from other sources of credit. 18 of
them were defaulters to credit from other sources while the remaining 34 respondents were
not. From those who defaulted to other sources of credit, 94 of them were similarly defaulted
to the recent lending microfinance institutions‟ loan.

Table-11: Sample respondents repayment status to other credit sources

Credit from other sources

Repaid Defaulted

Creditworthy count 14 1

% within
column 41% 6%

Defaulters count 20 17

% within
column 59% 94%

count 34 18

% within
Total column 100%

Source: Survey result

On the other hand, from those who repaid the loan from other sources of credit, 41 percent of
them were creditworthy borrowers while the remaining 59 percent of them were sample
defaulters who failed to repay the loan from the recent lending microfinance institutions. It is
significant to influence repayment performance at 5% level (Chi2=4.79). The statistics also
shows that the defaulters of the current lending institute experiences the same situation to the
credit from other sources.

Loan Size versus credit rounds

As it was shown in the table-12 below, it is summarized that from borrowers who had taken
only first round loans, 70.9 percent of the sample respondent borrowers were defaulters while
29.1 percent of them were creditworthy. From the total sample borrowers who had taken the
loan for second round, 33.3 percent of them were defaulters, while the remaining 66.7
percent of them were creditworthy borrowers. Considering the sample borrowers who took

49
loans for the third round, 58.3 percent of them were defaulters and thus other representing
41.7 percent were creditworthy. Similarly, from those who had taken the loan for the 4 th
round 16.9 percent of the sample borrower had not repaid the loan, while the remaining 83.1
percent has been settled the loan fully.

Table-12: Sample borrowers credit round versus repayment statuses (Cross tabulation)

Round 1 Round 2 Round 3 Round 4

Credit Credit Credit Credit
Defaulter Defaulter Defaulter Defaulter
worthy worthy worthy worthy
less Count 39 15 1 2 5 4 8 50
than
20000 % within Row 72% 28% 33% 67% 56% 44% 14% 86%
20000- Count 42 18 0 1
40000 % within Row 70% 30% 0% 100%
40000- Count 19 11 2 1
60000 % within Row 63% 37% 67% 33%
60000- Count 17 7 1 0 1 0 1
80000 % within Row 71% 29% 0% 100% 0% 100% 0% 100%
80000- Count 21 13 2 4 0
100000 % within Row 62% 38% 33% 67%
100000- Count 4 0 0 1 0 1 0
120000 % within Row 100% 0% 0% 100% 100% 0%
120000- Count 2 0 0 0
140000 % within Row 100% 0%
140000- Count 3 0 1 0 0 0 1
160000 % within Row 100% 0% 0% 100% 0% 100%
160000- Count 1 0
180000 % within Row 100% 0%
180000- Count 7 0 1 0 1 1
200000 % within Row 100% 0% 100% 0% 50% 50%
Above Count 6 2 1 0 1 0
200,000 % within Row 75% 25% 100% 0% 100% 0%
Count 161 66 5 10 7 5 11 54
Total
% within Row 71% 29% 33% 67% 58% 42% 17% 83%

Source: Survey result

From this survey result for the sake of comparisons, we can understood that borrowers who
had experienced repeated round for fourth time (83 percent) were more creditworthy
borrowers group than the other three rounds creditworthy borrowers, while sample borrowers

50
who took loan for the first time were more defaulters (71 percent) as compared to the other
loan repeated defaulter borrowers as shown in the table. Regarding the loan size, borrowers
who had taken loan sized above 200k4 were found to be defaulters at all rounds. Similarly
sample borrowers who have taken the loan less than 200k for only first round had
experienced defaults as compared to other rounds regardless of loan size. The defaulters and
creditworthy of each category by amount for each round of payments were different and a
detail of it were presented in the above table.
Table-13: Do you think that the amount you received is similar to your intended request?

Frequency Percent Valid Cumulative

Percent Percent
No 107 33.5 33.5 33.5
Valid Yes 212 66.5 66.5 100.0
Total 319 100.0 100.0
Source: Survey result

Table-14: Repayment time Suitable

Frequency Percent Valid Cumulative
Percent Percent
No 120 37.6 37.6 37.6
Valid Yes 199 62.4 62.4 100.0
Total 319 100.0 100.0
Source: Survey result

Loan requested have received and Repayment time suitability: As presented in the table-
13 above, 33.5 percent of the respondents did not think the amount received was similar to
their intended requests, which means the remaining 66.5 percent of respondents of the total
respondents responded that the amount received was similar to their requests. Besides this,
questions forwarded to assess the suitability of the repayment schedule showed that it was
suitable to 62.4 percent of the respondent while not suitable for the remaining 37.6 percent of
the respondents as it is shown in table-14. The suitability of repayment time is significant at
1% (Chi2=97.46) to influence repayment performance.

4
K- thousands in Ethiopian Birr

51
Table-15: Sample borrowers repayment intervals and trends (Cross tabulation)

Repayment Trends
Bi-
Weekly Monthly Quarterly Irregularly
Weekly Total
Count - - 33 44 107 184
%
within 0.0% 0.0% 17.9% 23.9% 58.2% 57.7%
Defaulter LRP
%
within 0.0% 0.0% 24.1% 75.9% 89.9%
column
LRP
Count 4 1 104 14 12 135
%
within 0.03% 0.01% 77.0% 10.4% 8.9% 42.3%
Credit
LRP
worthy
%
within 100.0% 100.0% 75.9% 24.1% 10.1%
column
Count 4 1 137 58 119 319
%
within .01% 0.0% 42.9% 18.2% 37.3% 100.0%
Total LRP
%
within 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
column
Source: Survey result

Borrower’s repayment intervals trend: Table-15 represented above shows that out of the
184 total sample defaulters, 33 of them were repaid the loan on monthly basis, 44 of them
have repaid the loan on quarterly basis while the remaining 107 have had a repayment
interval trend with irregular (inconsistent) basis. On the other hands, out of the total 135
creditworthy sample borrowers, 4 of them had a repayment trends on weekly basis, 1 with bi-
weekly basis, 104 of them have a repayment trend on monthly basis, 14 respondents were
have on quarterly basis and 12 creditworthy sample borrowers has a repayment trend with
irregular basis. From the discussion above we can say those sample borrowers who have the
trend of repayment on quarterly and irregular basis which is 23.9 percent and 58.2 percent
had faced the problem of defaults while sample borrowers repayment trend with less than
monthly basis performs better repayment comparably. The repayment on monthly basis,

52
quarterly basis and irregular basis are significant at 1% (chi2=117.27), (chi2=10.12) and
(chi2=90.28) respectively.

Table-16: Was the loan issued timely?

Frequency Percent Valid Cumulative

Percent Percent
No 39 12.2 12.2 12.2
Valid Yes 280 87.8 87.8 100.0
Total 319 100.0 100.0
Source: Survey Results

Credit timeliness: Data was collected to identify whether the loan was issued for the
respondent timely or not. In line with this, the response of sample shown in table-16 that, 280
respondents (87.8 percent) of the total sample respondents were reported that the loan was
issued on time; while for the remaining 39 respondents (12.2 percent) were not. The factor is
significant at p-value =1%, (Chi2=21.87) to influence repayment performances.

Table-17: Defaulted amount descriptive statistics

N Minimum Maximum Mean Std. Deviation

Defaulted amount 141 1000.00 700000.00 34,487.23 70,327.73

Valid N (listwise) 141

Source: survey result

On average, the defaulted amount was 34,487.22 Birr while the minimum and maximum
amount defaulted was 1000 and 700000 Birr respectively. This is presented and shown in the
table-17 above.

53
Causes for Defaults

The research tried to assess the reasons for defaulting from the sample defaulters‟ side, and
thus questions were included to get the response of respondents in evaluating the possible
causes of defaulting. The following table and explanation presents their responses.

Table-18: Respondents causes for default

Consider Credit as worthless

Frequency Percent Valid Cumulative
Percent Percent
No 170 92 92 92
Valid Yes 14 8 8 100.0
Total 184 100.0 100.0
Source: survey result

Among the reasons for defaulting, from the total sample defaulters only 14 respondents (8
percent) were perceived credit as less worthy to run their businesses, while the remaining 92
percent of them were not consider this as the cause.

Used loan for consumption

Frequency Percent Valid Cumulative
Percent Percent
No 74 40 40 40
Valid Yes 110 60 60 100.0
Total 184 100.0 100.0
Source: survey result

Again, for 110 (60 percent) of the defaulted respondents used the loan for consumption while
the remaining 74 (40 percent) of the respondents did not used loan for consumption. Meaning
that majority 60 percent of the respondent were used the loan for consumption either partially
or fully.

54
Sales on credit were not collected timely
Frequency Percent Valid Percent Cumulative Percent
No 154 84 84 84
Valid Yes 30 16 16 100.0
Total 184 100.0 100.0
Source: survey result

Out of 184 defaulters, only 30 respondents which covered 16 percent of the total sample
defaulters were engaged in a business that was sold on credit which in turn did not collected
on time.

Bankruptcy
Frequency Percent Valid Cumulative
Percent Percent
No 154 84 84 84
Valid Yes 30 16 16 100.0
Total 184 100.0 100.0
Source: survey result

Out of the total sample defaulters, only 30 respondents which covered 16 percent were
reported that they have faced bankruptcy while running their businesses which in turn
undermines their repayments.

Loss of Assets
Frequency Percent Valid Cumulative
Percent Percent
No 175 95 95 95
Valid Yes 9 5 5 100.0
Total 184 100.0 100.0
Source: survey result

55
Loss of assets due to seasonal natural disaster, spread of disease caused default for only 9
respondents while loss of assets was not the cause for default to the remaining 175
respondents.

Perceived loan as Donation/Government support

Frequency Percent Valid Cumulative
Percent Percent
No 150 82 82 82
Valid Yes 34 18 18 100.0
Total 184 100.0 100.0
Source: survey result

Some respondents who constitute 34 (18 percent) of the total sample defaulters were reported
as perceiving the loan as donation or government support as a cause of default. That is the
remaining 150 (89.3 percent) of the respondent did not have such perception as a cause for
default.

Costs of Defaulting

The assessment were also continued to identify the possible perceptions of sample borrowers
to decide on whether to repay or not the loan in-terms of the associated costs in case the
default is committed. Accordingly, the report shows that 17.9 percent of the respondent from
the total sample respondents were suffer of claims against their personal wealth, and thus the
remaining respondents who constitute 82.1 percent did not perceive such claims against their
personal wealth.
Table 19: Respondents perception on costs of default

a. Claims against personal wealth

Frequency Percent Valid Cumulative
Percent Percent
No 262 82.1 82.1 82.1
Valid Yes 57 17.9 17.9 100.0
Total 319 100.0 100.0
Source: survey results

56
On the other hand, 26.3 percent of the total respondent reported that claims against their
grantor were considered as the costs while the remaining 73.7 percent of them were not.
b. Claims against Guarantor
Frequency Percent Valid Cumulative
Percent Percent
No 235 73.7 73.7 73.7
Valid Yes 84 26.3 26.3 100.0
Total 319 100.0 100.0
Source: survey results

Social sanction in the form of exclusion, missing relationship with lenders and so on, was
considered as possible cost of defaulting. Accordingly, 20.4 percent of the respondents were
facing such sanctions while the remaining 79.6 percent of them were not experienced it.

c. Social Sanction (Exclusion, missing relation with Lenders,)

Frequency Percent Valid Cumulative
Percent Percent
No 254 79.6 79.6 79.6
Valid Yes 65 20.4 20.4 100.0
Total 319 100.0 100.0
Source: survey results

Loss of the next round credit service was also as a possible cost of defaults. Accordingly, it
was experienced by 32 percent of the respondents and thus 68 percent of the sample
respondents did not experience it.
d. Loss of next round
Frequency Percent Valid Cumulative
Percent Percent
No 217 68.0 68.0 68.0
Valid Yes 102 32.0 32.0 100.0
Total 319 100.0 100.0
Source: survey results

57
Therefore, based on the assessment on the sample borrowers‟ perception on the costs of
defaulting, the survey result shown above that borrower‟s willingness and ability to repay the
loan on-time was not to lose the next round credit service as the major possible costs of
defaults which supposed to enforce most respondent borrowers to repay on agreed period.

4.3.2. Purpose of the Loan and Utilization

Once the loan was received from the microfinance institutions, the purpose and utilization
related issues are more important to be assessed for its relation with the repayment
performance of sample borrowers. The first discussion focuses on the purpose for which the
loan was borrowed. This is explained with the support of tables as follows.

The business types and the purpose of the loan for which the sample borrowers have taken
the credit have been categorized in nine and listed as: purchase of raw materials, Metal and
wood work activity, assembling semi-finished materials to finished products, construction
type, fattening, diary, poultry and services. For simplicity purpose the service type includes
(Baltina, Cafeteria, Juices, Shops, Boutiques, cereal trade, Bakery, beauty salon, printing &
Laundry.)

Table-20 below presents the cross tabulation of loan repayment performance with business
engagement of respondents. 36 (11 percent) of the sample respondents were used the
borrowed money for purchase of raw materials of which 52.8 percent of them were found
being defaulters while the remaining 47.2 percent of them were creditworthy. 31 sample
respondents have been involved on metal and wood work business, of which 54.8 percent of
them were repaid their loan, while the remaining 45.2 percent of them were defaulters.
Respondents who had used the credit money for assembling of semi-final product to final
products were 14, of which 64 percent of them were the defaulters while the remaining 36
percent have been settled the loan totally.

58
Table-20: Sample Respondents Business type (Cross-tabulation)

Services
(Baltina,
Purchase Assembling Cafeteria,
Wood Production
of raw semi-final Juices, Shops,
& of Cattle
materials product Boutiques, Fattening Poultry Diary
metal construction Trade
/inputs (for into final cereal trade,
work materials
production) products Bakery, beauty
salon, printing &
Laundrry.)

Count 19 14 9 19 64 25 21 4 9
%
Defaulter

within 10% 8% 5% 10% 35% 14% 11% 2% 5%

LRP
%
within 53% 45% 64% 79% 49% 61% 91% 50% 60%
column
LRP
Count 17 17 5 5 67 16 2 0 6
Credit worthy

%
within 13% 13% 4% 4% 50% 12% 2% 3% 4%
LRP
%
within 47% 55% 36% 21% 51% 39% 9% 50% 40%
column
Count 36 31 14 24 131 41 23 4 15
%
within 11% 10% 4% 8% 41% 13% 7% 1% 5%
Total LRP
%
within 100% 100% 100% 100% 100% 100% 100% 100% 100%
column

Source: Survey results

Similar to the preceding business type, 24 sample borrowers have been engaged on
construction material production. 21 and 79 percent of them were creditworthy and defaulters
respectively which is significant at 5% level. Service business types were took the majority
of the business type on which the borrowers are engaged in. 131 sample respondent were
involved on it. Among them 49 percent were credit defaulters while the remaining 51 percent
was creditworthy borrowers. Fattening, cattle trade and diary business engagements were
found to have higher defaulters compared to those who were creditworthy. Defaulter
respondents from fattening, cattle trade and diary were 61 percent, 91.3 percent and 60
percent respectively. Generally, from the survey results borrowers who have involved in
service business category have greater default rate over the whole sample defaulters.
Borrowers who have been involved on cattle trade was also more defaulters which is
significant at 1%.

59
Loan requested have been received and Sufficient: On the other hand, table-21 shown
below, 81 (25.4%) of the respondents reported that the loan requested was not received thus
it was not sufficient for the intended purpose, while 110(34.5%) of respondents reported that,
the loan requested was received but not sufficient for the intended purpose. On the other
hand, 205 (64.3%) of respondents reported that, the loan requested was not received but it
was sufficient for the respondents‟ intended purpose. In line with this, 209(65.5%) of
respondents were received sufficient loan which was sufficient for the intended purpose.

Table-21: Respondents response to loan requested have received and sufficient

(Cross- tabulation)
Loan received sufficient for Total
intended purpose
No Yes
Count 81 205 286
No % of
25.4% 64.3% 89.7%
loan requested have Total
been received Count 29 4 33
Yes % of
9.1% 1.3% 10.3%
Total
Count 110 209 319
Total % of
34.5% 65.5% 100.0%
Total
Source: survey results

From this matrix we can understand that majority 65.5% of the sample borrowers have
received the loan that can enable them to finance their business sufficiently while only 25.4%
of sample borrowers took insufficient loans which assumed to be underfinance their
businesses portfolios.

Reasons for loan diversion: Different factors can influence borrower‟s decision to divert the
loan borrowed from the intended purpose. These reasons are discussed based on the response
of the sample as follows with the support of tabular data.

60
Table-22: Respondents response on reasons for loan diversion
a. Insufficient fund received

Frequency Percent Valid Cumulative

Percent Percent
No 286 89.7 89.7 89.7
Valid Yes 33 10.3 10.3 100.0
Total 319 100.0 100.0
Source: survey results

For 33 respondents, it was receiving insufficient fund that led to project diversion, and thus
for 286 respondents this was not a reason for the project diversion.

b. Change in Market demand

Frequency Percent Valid Cumulative
Percent Percent
No 284 89.0 89.0 89.0
Valid Yes 35 11.0 11.0 100.0
Total 319 100.0 100.0
Source: survey results

Change in market demand was considered as potential reason for diversion of project. This
was a reason for only 35 respondents and was not for the remaining 284 respondents.

c. To make better profitable business

Frequency Percent Valid Cumulative
Percent Percent
No 297 93.1 93.1 93.1
Valid Yes 22 6.9 6.9 100.0
Total 319 100.0 100.0
Source: survey results

Among the total valid sample respondents, 22 respondents have been mentioned that they
have been used the loan for another project to make better profits. Although they are
important to deal with another alternative of possible causes for loan diversion was

61
questioned with regard to respondents response on loan agreement matching with the
intention, using the excess amount of the proceeds received from the loan for another
purpose and using the loan for settlement of another credits, the analysis were skipped this
part because few in number of sample respondents were replied.

Generally, we can understand that borrower have the possibility to divert the loan from the
intended purpose majorly due to frequent change in market demand while few borrowers
diverts the loan to make better profits.

4.3.3. Follow Up, Monitoring and Training provision to borrowers:

Table-23: Response on members‟ knows & Monitor each other.

(Cross-tabulations)
Do you attempt to
Do you know all
monitor the loan
(most) of the
utilization of other
members in your Total Total
members in your
group?
group?
No Yes No Yes
Count 54 130 184 88 96 184
Defaulter %
within 29.30% 70.70% 100.00% 47.80% 52.20% 100.00%
LRP
LRP
Count 9 126 135 10 125 135
Credit %
worthy within 6.70% 93.30% 100.00% 7.40% 92.60% 100.00%
LRP
Count 63 256 319 98 221 319
Total %
within 19.70% 80.30% 100.00% 30.70% 69.30% 100.00%
LRP

Source: Survey result

Members Knows each other: Table-23 above shows that from the total sample respondents
19.7 percent (63 respondents) did not know all (most) of the members in their group, while
80.3 percent (256 respondents) knows almost all or most of the members in their respective
groups. Considering loan repayment performance, 54 and 9 respondents out of 63
respondents of those who did not know all or most of the members were defaulters and

62
creditworthy respectively. In line with this, 130 and 126 out of 256 respondents of those who
did know all or most of the members were defaulters and creditworthy. Whether they did or
did not know all or most of the members, most of the respondent in each response category
were defaulters. It is significant at 1% (Chi2=28.17).

Members monitor others loan utilization: 88 (47.8 percent) of sample credit defaulters
were not experienced monitoring the utilization status of others members while the
remaining were conduct monitor to others although both are categorized as defaulters. On the
other hands, among the total 135 sample creditworthy borrowers, 10 (7.4 percent) were not
bothering to monitor other members loan utilizations while the majority of creditworthy
(92.6 percent) conduct monitoring. In both categories of borrowers, majority of the sample
borrowers were monitor other member‟s activities and significant at 1% (Chi2=67.53). The
details are presented in table-23 above.

Table-24: Sample borrower‟s response to action for wrong loan utilization

Inform to Put
Accuse Advise
lender‟s social Other Total
diverters Diverters
officer sanction

Count 48 1 72 54 38 184
Defaulter % within
49.00% 33.30% 54.10% 65.90% 71.70% 57.70%
column
LRP
Count 50 2 61 28 15 135
Credit
worthy % within
51.00% 66.70% 45.90% 34.10% 28.30% 42.30%
column

Count 98 3 133 82 53 319

Total % within
100.00% 100.00% 100.00% 100.00% 100.00% 100.00%
column

Source: Survey result

Besides, data was also collected from respondents‟ actions on other members who use the
loan wrongly. The respondents‟ response shown in Table-24 stated that 98, 3, 133 and 82 of
them take action of informing the lenders officers, accusing diverters, putting social

63
sanctions, and advises diverters respectively. The remaining respondents take other actions.
On the other perspective, from those informing to lending officers, 51% of them are
creditworthy while the remaining 49 percent of them are defaulters; from those putting social
sanctions 54.1 percent of them were defaulters while 45.9 percent of them were creditworthy.
Those who advise diverters, at large were found to be defaulters (65.9 percent) and limited
number of them were creditworthy (34.1 percent). Most of the respondents claim to put
social sanctions for wrong utilization exercised by the borrowers, as shown in the table
above.

Figure_2: Loan utilization superised by lending Institute

9.1

No Yes

90.9

Source: survey results

As shown in the above pie chart, it was showed that most of the respondents (90.9 percent)
were supervised by the lending institute officers. On the other hand, few of the respondents
(9.1 percent) replied „No‟ and thus implied that their loan utilization was not sufficiently
supervised by lending institute officers.

Frequency of Visits: Loan utilization supervision has been conducted to all sample
borrowers based on the respondents report. However the assessment on how frequent the
visit happening has been discussed as follows. All of the respondents said that there had been

64
no weekly visits, with 100% of the respondents replying “No” as shown in the table below.
Regarding bi-weekly visits questions, it was only 6 respondents which constitute 1.9 percent
of the total respondents who has replied that they had been visited bi-weekly and thus the
remaining 98.1 percent of the respondents still saying “No” there was no bi-weekly visits
conducted.
Weekly Basis

Frequency Percent Valid Cumulative

Percent Percent
Valid No 319 100.0 100.0 100.0
Source: survey results

Bi-Weekly Basis

Frequency Percent Valid Cumulative

Percent Percent
No 313 98.1 98.1 98.1
Valid Yes 6 1.9 1.9 100.0
Total 319 100.0 100.0
Source: survey results

The monthly basis visits were experienced by 98 respondents, 71 respondents replied as

“yes” they have been visited on quarterly basis, while 144 of sample respondents were
visited to their business on irregular basis as it is shown in the tabular presentations indicated
here below.

Monthly Basis (Source: survey results)

Frequency Percent Valid Percent Cumulative Percent

No 221 69.3 69.3 69.3
Valid Yes 98 30.7 30.7 100.0
Total 319 100.0 100.0

65
Quarterly Basis

Frequency Percent Valid Percent Cumulative Percent

No 248 77.7 77.7 77.7
Valid Yes 71 22.3 22.3 100.0
Total 319 100.0 100.0
Source: survey results

Irregular Basis

Frequency Percent Valid Cumulative

Percent Percent
No 175 54.9 54.9 54.9
Valid Yes 144 45.1 45.1 100.0
Total 319 100.0 100.0
Source: survey results

From the above discussion on the topic of supervision and monitoring visits to the borrowers
territory to make sure the utilization of loan for the intended purpose was critically identified
as majority (45.1 percent) of sample borrowers were visited and supervised by the lending
institutes officers irregularly which may behaves borrowers to use the proceeds received to
another purpose. On the other hand less frequency of visit was conducted on bi-weekly bases
which may in turn increases the likelihoods of borrower‟s repayment performances at an
increasing rate. Follow-up visits on monthly basis and irregular basis to clients business are
significant at 1 % (Chi2= 88.09 & Chi2=75.09) respectively.

The respective MFI staffs were also asked to identify the time interval that officers‟ needs to
visits client‟s business. The response shown that most (51.1 percent) of the officers‟ conduct
visits monthly, and followed by 20 percent of the respondents were reported weekly. Besides,
the other responses were bi-weekly and quarterly which constituted 8.9 percent each, and
11.1 percent referring irregular or arbitrary visits by the officers.

66
Table-25: At what time interval does the officer visit the client‟s businesses?

Frequency Percent Valid Percent Cumulative Percent

Weekly 9 20.0 20.0 20.0
Bi-Weekly 4 8.9 8.9 28.9
Monthly 23 51.1 51.1 80.0
Valid Quarterly 4 8.9 8.9 88.9
Irregularly or
5 11.1 11.1 100.0
Arbitrary
Total 45 100.0 100.0
Source: Survey results

The survey results has identified the contradiction on the supervision frequencies that
reported by the lending institutes officers and sample borrowers. Although the respondent
officers from the lending institutes revealed majorly on monthly basis the high number of
sample respondent borrowers have still experienced irregular visitors to their business
territories as shown in the above table.

Loan Repayment supervised

Frequency Percent Valid Cumulative

Percent Percent
No 71 22.3 22.3 22.3
Valid Yes 248 77.7 77.7 100.0
Total 319 100.0 100.0
Source: survey results

Regarding loan repayment supervision, 248 respondents (77.7 percent) of the total
respondents replied “yes” as loan repayment had been supervised, while 71 respondents (22.3
percent) of the total respondents replied “No” loan repayment status had not been supervised.
Moreover, it significant to influence the repayment performances at 1% (Chi2=67.05).

67
Figure_3: Sample borrowers loan repayment performance supervision

90.0%
80.0%
70.0%
60.0%
Percentage

50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
Bi-Weekly Monthly Quarterly Irregularly
Frequence of repayment visit
Defaulter Credit worthy

Source: survey results

i. Repayment supervision and Monitoring: As shown in the above figure, except for
monthly visits to monitor the repayment, other showed defaulter dominated respondents
relative to creditworthy respondents. The highest percentages of defaulters were observed
with irregular repayment visit intervals.

ii. Availability of adequate trainings: Almost all respondent replied that they had got
training. However, the training types provided differs. With this regard, 111 respondents
replied that they had got business skill development while the remaining 208 respondents
replied no business skill development training was given to them which is significant at 1%
(Chi2=16.37)
a. Business skill Development
Frequency Percent Valid Cumulative
Percent Percent
No 208 65.2 65.2 65.2
Valid Yes 111 34.8 34.8 100.0
Total 319 100.0 100.0
Source: survey results

68
Based on the response of the samples, 10.7 percent of the total respondents had got
marketing training while the remaining 89.3 percent did not get the marketing training which
is significant at 5%.
b. Marketing
Frequency Percent Valid Cumulative
Percent Percent
No 285 89.3 89.3 89.3
Valid Yes 34 10.7 10.7 100.0
Total 319 100.0 100.0
Source: survey results

It was also reported that saving culture training was given to 271 of the total sample
respondents while the other 48 respondents did not get the training, as shown by the response
of the samples.
c. Saving culture
Frequency Percent Valid Cumulative
Percent Percent
No 48 15.0 15.0 15.0
Valid Yes 271 85.0 85.0 100.0
Total 319 100.0 100.0
Source: survey results

Training on book keeping techniques were not given to 303 sample respondents, and was
given to only 16 respondents, as the response of the samples shows.
d. Book Keeping techniques
Frequency Percent Valid Cumulative
Percent Percent
No 303 95.0 95.0 95.0
Valid Yes 16 5.0 5.0 100.0
Total 319 100.0 100.0
Source: survey results

On the other hand, 146 and 173 of the total respondents did get and did not get respectively
the training on credit management.

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e. Credit management

Frequency Percent Valid Cumulative

Percent Percent
No 173 54.2 54.2 54.2
Valid Yes 146 45.8 45.8 100.0
Total 319 100.0 100.0
Source: survey results

From the tables shown above we have learnt that the training schemes provided by the lending
institutes and other sector offices would more relies on awareness creation on saving cultures
(46.9%) followed by training on how credits can be managed (25.3%) with remaining coverage
19.2%, 5.9% and 2.8% focuses on Business skill development, marketing and awareness
creation on record keeping respectively.

Table-26: Respondents repayment status versus training adequacy and sufficiency (cross
tabulation)

Training Adequate &

Sufficient

No Yes Total

LRP Defaulter Count 96 88 184

% within LRP 52.2% 47.8% 100.0%
% within column 86.5% 42.3% 57.7%

Credit Count 15 120 135

worthy
% within LRP 11.1% 88.9% 100.0%
% within column 13.5% 57.7% 42.3%

Total Count 111 208 319

% within LRP 34.8% 65.2% 100.0%

% within column 100.0% 100.0% 100.0%

Source: survey results

70
As it is indicated in the table-26 above, from the total sample respondents, 208 of them
replied that the training provided were adequate and sufficient, while 111 of the respondents
opposes this by replying „No‟ to the statement training was adequate and sufficient. Among
those found the training was not adequate and sufficient, most of them (86.5 percent) were
found to be defaulters while only 13.5 percent of them were creditworthy. On the other hand,
among those who considered training adequate and sufficient, 42.3 percent of them were
defaulters while 57.7 percent of them were creditworthy. It is significant at 1% (Chi2=63.35)
to influence repayment performance of borrowers.

Table-27: Does the training taken helps you in running business & credit
management?

Frequency Percent Valid Percent Cumulative Percent

No 47 14.7 14.7 14.7
Valid Yes 272 85.3 85.3 100.0
Total 319 100.0 100.0
Source: survey results

The 272 respondents which are the majority of the sample respondents have reported that
training availed by the lending institutes and others helped them in running their respective
business and credit management, while 47 respondents were reported that the training
provided by the lending institutes and others were worthless in running our businesses. It is
significant at 1% (Chi2=41.19). Accordingly, we have learnt above also that training
provided by the lending institutes and other sectors was majorly adequate and more
important for borrowers in running the day to day business operations while few have been
reported that the inadequacy and insufficient availability of trainings have negative effects on
running their business as it was pre-intended.

Furthermore, based on the semi-structured interview responded by some MFIs staffs, like
VisionFund MFIs, borrowers screening activity was undertaken by the lending institute
officers only, which is based on the credit policy of the institution. The respondents reported
also that sufficient training will be delivered to each target borrowers before financing their
business. The training session more focuses on how to manage the credit or loan utilization
71
systems, awareness creation on inducing saving cultures, awareness on the insurance
schemes that the institute is going to provide to safeguard their loan and other relevant
matters. On the other hand, OCSSCO staffs informed that in government affiliated MFIs like
OCSSCO, target MSE borrowers selection and screening and provision of training is not the
sole responsibility of lending institutes officers rather staffs from woreda level MSEDA‟s5 is
taking part although the level of their involvement have some limitations.
.

4.4. Business related characteristics

In this sub-section, the overall business related characteristics, challenges, and prospective of
sample borrowers have been analyzed and discussed based on the data collected and
presented as follows.

A. Input, Production site and Availability of Market

Availability of Sufficient Input

Frequen Percent Valid Cumulative
cy Percent Percent
No 100 31.3 31.3 31.3
Valid Yes 219 68.7 68.7 100.0
Total 319 100.0 100.0
Source: survey results

The assessment shows that 219 respondents (68.7 percent) reported that there was sufficient
input available in the market to run their business, while 100 (31.3 percent) of respondents
have faced the problem with lack of sufficient inputs in running the day today businesses.
From the respondents point of views we can learn that majority of the sample respondents
have been equipped with sufficient inputs while running their business although the counter
parts seems affected by these factors.

5
Woreda level MSEDA is a government unit that organizes micro and small enterprises at woreda level

72
Have suitable production place

Frequen Percent Valid Cumulative

cy Percent Percent
No 45 14.1 25.9 25.9
Valid Yes 129 40.4 74.1 100.0
Total 174 54.5 100.0
Missin Syste
145 45.5
g m
Total 319 100.0
Source: survey results

Production place was suitable for 129 respondents, who constitute 74.1 percent of the valid
sample respondents. Accordingly, 45 of which constitute 25.9 percent of respondents out of
the total valid respondents replied that there was no suitable production place available by the
concerned bodies which may in turn have negatively affects their businesses. Meaning that
the missing data for 145 sample respondents indicated in the table shows that this factor have
no relevance to the nature of their business.

Market/Production place suitable for consumers

Frequen Percent Valid Cumulative
cy Percent Percent
No 127 39.8 43.2 43.2
Valid Yes 167 52.4 56.8 100.0
Total 294 92.2 100.0
Missin Syste
25 7.8
g m
Total 319 100.0
Source: survey results

Suitability of market location to consumers is considered as a major factor for borrowers to

sale the end products to the target consumers on the proper time. Accordingly, the assessment
shown above stated that from the total 294 valid respondents, 167 of the respondent have

73
accessible market location to the consumers while 127 of the respondent reported that the
production and market place is not accessible to consumers as required. Meaning that,
majority of the sample respondents had an accessible business location to be visited by the
consumers.
Adopt technology
Frequen Percent Valid Cumulative
cy Percent Percent
No 198 62.1 69.5 69.5
Valid Yes 87 27.3 30.5 100.0
Total 285 89.3 100.0
Missin Syste
34 10.7
g m
Total 319 100.0
Source: Survey result

On the other hand, adopting technology while running the business was assumed to be a
major factor inputs that enables borrowers get successful business which in turn could
enhance borrower‟s repayment performances. Accordingly, only 87 (30.5 percent) of the
valid respondents replied as they were adopting new technologies in running their business,
while the majority 198 (69.5 percent) of the respondents were not utilize the updated
technologies to run their business.

As it was summarized in table-28 below, 111 (50.7 percent) of the sample respondents who
have sufficient inputs were credit defaulters while the remaining 108 (49.3 percent) were
found to be creditworthy borrowers which is significant at 1% (Chi2=14.46). In a similar
speaking, it is shown that 80 (52.09 percent) of the sample respondents had suitable
production and market locations where it is applicable, while remaining 47.91 percent of the
respondents were among the creditworthy borrowers who have suitable market locations.
Furthermore, it is significant at 1% (Chi2=13.86) to influence repayment performances.

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Table-28: Borrowers response to Availability of inputs, Production location, Adopting
Technology and Feasibility study (Discrete variables)

Sufficient
Input Suitable Adopt Feasibility
available prod./market technology Study
(Yes) place (yes) (Yes) (Yes)

LRP Defaulter Count 111 80 40 66

% within 50.7% 52.09% 46.0% 59.5%
column

Credit Count 108 61 47 45

worthy
% within 49.3% 47.91% 54.0% 40.5%
column

Total Count 219 167 87 111

% within 100.0% 100.0% 100.0% 100.0%
column

Source: Survey result

On the other hand, it was also observed that 46 percent of the sample borrowers who have
been adopt advanced technology were defaulters, while the remaining 54 percent of the
sample borrowers who have been adopt technology were the creditworthy borrowers. It is
also significant at 1% to influence repayment performance of borrowers. Moreover, it was
observed that among the total valid sample respondents who have been conducted feasibility
study before engaging into the business was also revealed as; 59.5 percent were credit
defaulters while the remaining 41.5 percent was the creditworthy borrowers.

Table-29: Borrowers business experience before the credit scheme

Frequen Percent Valid Cumulative Percent

cy Percent
No 154 48.3 48.3 48.3
Valid yes 165 51.7 51.7 100.0
Total 319 100.0 100.0
Source: Survey result

75
 Year of Experience Frequency Percent
< 3 61 37.9
3 < Year < 5 50 30.3
>5 years 54 21.8

Total 165 100%

Source: Survey result

B. Business Experiences: Business experience before the credit scheme was assessed in
this research and the response of the respondents shown in table-29 above that 165
respondents (51.7 percent) of them replied „yes‟ we had relevant business experience before
the credit scheme, while the remaining 154 respondents (48.3 percent) of the total respondents
replied „no‟ we did not have any relevant business experiences before the credit scheme.
Among the sample borrowers who had a relevant experience, 37.9 percent of them had
experience of less than 3 years while 21.8 of the valid sample respondents had greater than 5
years of business experiences and the rest valid respondents have relevant experience between
3 to 5 years. Borrowers who have relevant business experiences can significantly influence
repayment performances at 1%.

C. Market demand to the products: From the total respondents, 21.9 percent of them
measured their product market demand as high, while 59.9 and 17.9 of them measured as
medium and low respectively. From those responding as having high market demand,
majorities (72.9 percent) of the sample respondents were creditworthy, while those responding
having medium and low market demand, the majority were (57.6 and 96.5 percent
respectively) found to be defaulters. Having high and low market demand to the end products
are significantly influence the repayment performance of borrowers at 1% (Chi2=34.46 &
Chi2=54.19) respectively. This is shown in detail in the below table-30. Further comparison
can be seen from the figure_4 below.

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Table-30: Sample respondents response to their product Market demand (Cross tabulation)

High Medium Low

demand Demand Demand
Count 19 110 55
% within
10.30% 59.80% 29.90%
Defaulter LRP
% within
27.10% 57.60% 96.50%
column
LRP
Count 51 81 2
% within
Credit 37.80% 60.00% 1.50%
LRP
worthy
% within
72.90% 42.40% 3.50%
column
Count 70 191 57
% within
21.90% 59.90% 17.90%
Total LRP

% within
100.00% 100.00% 100.00%
column
Source: Survey result

Figure_4: Loan repayment performance across different market demand

120.0%
96.5%
100.0%

80.0% 72.9%
Percent

57.6%
60.0%
42.4%
40.0% 27.1%
20.0%
3.5%
0.0%
High demand Medium Demand Low Demand
Market demand

Defaulter Credit worthy

Source: survey result

77
The figure shows least percentage of creditworthy borrowers was seen in low demand while
the highest was for those who have higher market demand for their products. That is, as
market demand decreases, defaulters were increasing, which implies on the other way
creditworthy borrowers were increasing as market demand for the product increases.

D. Having book of records: Keeping book of records for monitoring daily transactions
enable borrowers to manage their costs against revenues generated from the activities
financed through credit services. According to the data collected from the sample
respondents shown in the table-31 below, from those who kept book of records for their
financial transactions, 40.7 percent of them were defaulters while the others who are slightly
higher in percent, 59.3 percent, were creditworthy. But, from those who did not have book of
records to handle their financial transactions, majority of them were found as credit
defaulters which represents 77.55 percent, while the remaining which represents 22.45
percent was creditworthy. However, regardless of their repayment status majority of the
sample borrowers (53.92 percent) experienced with keeping book of record to evaluate the
financial position and performances of their respective businesses which is significant at 1%
(Chi2=45.65).

Table-31: Sample respondents with having book of records (Cross tabulation)

Have Book of records

Total
No yes
Count
% within LRP
Defaulter
% within having
Book of records
LRP
Count
Credit % within LRP
worthy % within having
Book of records
Count
% within LRP
Total
% within having
Book of records
Source: survey results

78
Based on the assessments, respondents who had used the book of records for evaluation of
profit and loss of their business were 149, which make (46.7 percent) of the total valid
respondents. On the other hand, those who did not use to evaluate profit and loss were 170
(53.3 percent). To monitor repayment status, only 45 (14.1 percent) of respondents has kept
the book of records, while the remaining 274 respondents were not used it. This is given and
clearly explained in the table presented below. Generally speaking from the respondent point
of view majority 172 (53.92 percent) of respondent borrowers kept records to evaluate the
profitability and repayment status of their businesses, while the remaining 147 (46.08
percent) did not.

Reason for keeping book of records

Valid Cumulative
Frequency Percent
Percent Percent
To evaluate Profit & loss
No 170 53.3 53.3 53.3
Valid yes 149 46.7 46.7 100
Total 319 100 100
To monitor Repayment status
No 274 85.9 85.9 85.9
Valid yes 45 14.1 14.1 100
Total 319 100 100
Source: Survey result

Based on the respondent response the potential reason for not keeping book of records was
lack of knowledge, considering it as worthless, and the existence of small transaction can be
listed. According to the assessment, reasons for not keeping record showed that 50, 31 and
66 of the respondents mentioned lack of knowledge, considered it as it is worthless and
having small transaction as the reasons respectively. Form those who mentioned lack of
knowledge as a reason for not keeping record, 64 percent of them were defaulters while 36
percent of them were creditworthy. Those who mentioned considering as worthless as the
reason was also dominated by defaulters than creditworthy: 90.3 percent were defaulters and
9.7 percent of them were creditworthy. Furthermore, those who reported because of having

79
small transaction were also larger to defaulters, 78.8 percent while 21.2 percent of them were
creditworthy borrowers. This is shown in the table-32 below with detail explanations.

Table-32: Sample respondent‟s reasons for not keeping record (Cross tabulation)

Considere
Lack of d as Small
Knowledge worthless Transaction

LRP Defaulter Count 32 28 52

% within 28.6% 25% 46.4%
LRP
% within 64% 90.3% 78.8%
column

Credit Count 18 3 14
worthy
% within 51.4% 8.6% 4%
LRP
% within 36% 9.7% 21.2%
column

Total Count 50 31 66

% within 34% 21.1% 44.9%

LRP

% within 100.0% 100.0% 100.0%

column

Source: Survey result

4.5. Lending institutes and Government prospects

As it was discussed in the first chapter the government of Ethiopia had took decisive
initiatives of poverty and unemployment eradication through facilitating different strategies.
Among those strategies, facilitating credit service for micro and small scale enterprises
through microfinance institutions is listed (FeMSEDA, 2016). Taking this in to account,
micro and small scale enterprises are organized as a group of few in number and screened
through the integration of government sectors (WoMSEDA, TVET and lending MFI).

80
Hence, measuring the level of involvement and active participations on screening the viable
borrowers is the intention of the study. Assessment on the lending institutes and prospective
government sectors screening mechanisms, adequacy of the provision of legal and technical
supports by the concerned bodies to credit services and the effects of defaults on the
developmental strategies of the country were conducted. 45 sample respondents from the
lending institutes were involved on the assessment and their responses are presented as
follows.

A. Screening Mechanisms: As it is shown in the table-33 below, the assessment shows

that 31 (68.9 percent) of sample respondents from the sample lending institutes staffs have
been confirmed that branch office staffs are actively involved on screening activities of
borrowers while 14 (31.1 percent) of them were responded that the staffs have limited
involvements on screening the creditworthy borrowers before granting credits to the MSE
borrowers.

Table-33: Do you think that your branch credit officers have actively involved in screening
the creditworthy borrowers‟ before granting credits to the MSE borrowers?

Frequency Percent Valid Cumulative

Percent Percent
No 14 31.1 31.1 31.1
Valid Yes 31 68.9 68.9 100.0
Total 45 100.0 100.0
Source: Survey result

From those who replied „no‟, 9 respondents explained that there is limited involvement of
credit officers in screening activities, and even in the credit approvals. As it was reported by
those respondents mostly these activities were taken place at Kebele level and woreda level
MSEDA‟s and the lists are submitted to lending institutes. The researcher has understood that
there is a gap of cooperation among the partners in organizing and selecting those target
borrowers before granting the loan. Further study on this area might be recommended.

81
Table-34: Do you think that the organizing and screening activity through the government
bodied sector is effective and efficient enough for the lending institutes?

Frequency Percent Valid Cumulative

Percent Percent
No 30 66.7 68.2 68.2
Valid Yes 14 31.1 31.8 100.0
Total 44 97.8 100.0
Missin Syste
1 2.2
g m
Total 45 100.0
Source: Survey result

Taking in to consideration the involvement of government unit (woreda level MSEDA) in

screening of borrowers, respondents were asked whether it is effective or not. Accordingly,
the response showed that 68.2 percent of the total 44 valid respondents reported that it was
not effective and efficient enough for lending institutes, while the remaining 31.8 percent
respondents considered as if it was effective and efficient.

Furthermore, among those replied as „no‟, 27 respondents were also expressed that the
screening activities being undertaken majorly through government units is not appropriate so
that it is more critical and important to involve the lending institutes officers before
promising the loan. Even a respondent reported that the potential involvement of government
unit with least involvement of the lending institute‟s officers could negatively affect the
selection of the best viable borrowers from less productive borrowers. Furthermore the
respondents reported that maximizing the level of involvement in screening and selecting
activity by government units (WoMSEDA) could possibly leads for committing corruptions
(Adverse selection). Hence, in the sample areas where the study was undertaken the
researcher observed that more involvement on organizing & screening MSE borrowers
activities took place with government units (WoMSEDA) mostly while less emphasis was
given to lending institutes to take part of it.

82
Table-35: Do you think your institutes follow a proper loan rationing mechanisms to all credit needy
borrowers?

Frequency Percent Valid Percent Cumulative

Percent
No 14 31.1 31.8 31.8
Valid Yes 30 66.7 68.2 100.0
Total 44 97.8 100.0
Missin Syste
1 2.2
g m
Total 45 100.0
Source: Survey result

Regarding loan rationing mechanisms of MFI, 31.8 percent of the staff respondents replied
that the loan rationing mechanisms for all MSE borrowers were not comply with proper loan
rationings, while the remaining 66.7 percent of them replied „yes‟, they have proper loan
rationing mechanisms. Those respondents saying „no‟ explained further, the credit rationing
systems of the lending institutes should adhered to comply with the credit history of the
borrowers, business experience, business types, and availability of funds and/or lender
repayment recovery rate.

B. Legal Supports: As shown in the table-36 below, 86.7 percent of the respondents
from lending institutes staffs replied that credit lent were legally supported for any defaults
while the other 13.3 percent of them did not think there were no strong legal supports.
Regarding the legal supports, based on the open-ended questions some respondents
responded „yes‟ reported that legal intervention is not a prior requirement as there is peer
groups liability among the borrowers. It requires awareness creation rather than accusing or
charging at the court. On the contrary, others said that special and fast legal measures should
be taken so that the loan can be secured and made available to others that are in need of
financial service. This action can be a good lesson for other potential defaulters.

83
Table-36: Do you think that the credit lent has adequate legal supports for any defaults?

Frequency Percent Valid Percent Cumulative Percent

No 6 13.3 13.3 13.3
Valid Yes 39 86.7 86.7 100.0
Total 45 100.0 100.0
Source: Survey result

In order to quantify the respondents‟ opinion to the adequacy of legal support, further
assessment on rating the implementation status was done. Accordingly, 33.3 percent, 15.6
percent and 44.4 percent of the respondents rated as high, low, and medium respectively.
Thus it is learned that medium level of legal supports is delivered to MFIs credit service for
claiming repayments against the potential defaulters. The details are presented in the table-37
below.

Table-37: If you think that the credit lent is legally supported for any defaults, how do you
measure it?

Frequency Percent Valid Cumulative

Percent Percent
Missing 3 6.7 6.7 6.7
High 15 33.3 33.3 40.0
Valid Low 7 15.6 15.6 55.6
Medium 20 44.4 44.4 100.0
Total 45 100.0 100.0
Source: Survey result

As it is shown in table-38 below, respondents‟ idea toward government sector involvement

impact on the credit rationing inefficiency, majority of them, which represented as 60 percent
of the respondents, replied that the involvement of government units (MSEDA) on loan
contract agreement has negative impact on delivering an efficient and effective credit
services to target MSE borrowers. The other 40 percent of them on the other hand replied it
has no effects on effective and efficient loan rationing systems of the lending microfinance
institutes.

84
From the respondents point of view, although the government unit involvement took a major
parts in screening the to be micro and small enterprise borrower is incredible, there is a loop
on the effective and efficient operation of MFIs in delivering the ultimate financial services
which leads to defaults problems. The respondents reply to the question has been presented
in tabular form as follows.

Table-38: Do you think that the government sector involvement on loan agreement has an
impact on credit rationing inefficiency?

Frequency Percent Valid Percent Cumulative Percent

No 18 40.0 40.0 40.0
Valid Yes 27 60.0 60.0 100.0
Total 45 100.0 100.0
Source: Survey result

Respondents‟ explanation to the open ended questions showed that government involvement
in the loan agreement can even increase the loan processing cost of borrowers, and
sometimes political volatility at some study area might mislead loan to unqualified
borrowers, change the perception of borrowers of the loan towards loan repayment and
increase the possibility of corruption during lending process.

On the other hand, lending institutions officer‟s response showed that 82.2 and 17.8 percent
of the respondents responded „yes‟ and „no‟ to the question „Does the settlement of the
defaulted borrower‟s loan by the city administration (Credit guarantor) have a negative
impact on the government projects subsidy?‟

Table-39: Does the settlement of the defaulted loan by the city administration (Credit
guarantor) have a negative impact on the government projects subsidy?

Frequency Percent Valid Cumulative

Percent Percent
No 8 17.8 17.8 17.8

Valid Yes 37 82.2 82.2 100.0

Total 45 100.0 100.0

Source: Survey result

85
Respondent also supplemented using open ended questions that settlement of unforeseen
huge default loan from government subsidy may have negative impact on: the government
projected costs, the behavior of projected clients, the economic growth of the country,
development plan and mission of lending institutes, and moral effects of the society and
staffs at large in which the institutes operates. In another words, the settlement of loan from
the government custody could mislead the behavior of the existing active borrowers not to
repay or unwilling to repay the outstanding loans. On the contrary, as it was discussed earlier
other group 8 respondents were responded that group liability can handle the problem with
the defaulters and hence the government unit had an obligation only to facilitate it, thus it
will not affect the government development programs. To fix this contradiction of views, the
researcher recommended further study on the impact of settlement of defaulted loans from
the government subsidy on developmental programs.

In addition to the above discussions, although it is not supported by quantitative data to

regress the model using the STATA package, in order to check the level of their significance
to loan repayment performance of both borrowers and lending institutes, there are some other
variable that are considerably have significance to influence loan repayment performance of
borrowers. These data have been collected during the survey from relevant sources. During
discussion with the target sample borrowers, lending institutes staffs, Micro and Small
Enterprise Agency staffs and National Bank of Ethiopia‟s staffs, plenty of other factors other
than that had reported through questioners have been revealed. Those lists of factors have
been presented as follows.

I. Government’s prospects

In creating employment opportunity through organizing the youths and women entrepreneur
groups of the society who have been faced lack of financial resources to make realize their
entrepreneurial skill truth, the government of Ethiopia had took an initiatives to take a
responsibility of organizing as micro and small scale enterprises and facilitate financial
inputs necessary for the implementation of the strategy. This financing strategy takes place
through Microfinance institutions that are operating in Ethiopia.

86
 FeMSEDA‟s (referred as government unit) had took the initiative of coordinating the
implementer sectors to deliver financial supports through MFIs and facilitation of local and
international market linkages for those borrowers particularly for MSE borrower groups to
fix the problem of market gaps. However, there are some rumors from the target borrowers
under the study that facing limited market linkage with the suppliers, wholesalers, input
providers and end product users in the local market had a negative impact on their business
profitability. Moreover, there is a gap from this sector in facilitating the suitable production
places at some areas under the study which may in turn undermine their productivity and
repayment performances as per the agreed repayment schedule which might be considered as
slight contradiction with the missions (FeMSEDA, 2016 and response of MSE borrowers).

Moreover, during the survey the followings were identified as major factors to influence the
repayment performances:

Limitations of Government sectors

i. Lack of exerting consistent technical supports by the concerned government sectors like
Agricultural experts to the borrowers agricultural related businesses where it is subject to
be applicable.
ii. Provision of market place where it is inaccessible for the target customers.
iii. Lack of consistent integration among the relevant sectors (Lending institutes, MSEDA
and TVET) on screening and monitoring activities.

II. MFIs characteristics and prospects

Follow-up and supportive supervision to borrower’s business territory

During the interview and focus group discussion period it was reported by some of lending
institutes staffs that there is big weaknesses to conduct a regular follow-up to the clients
business due to the availability of fewer number of credit officers at branch offices level who
can take over the regular supervision activities. On the other hand, the challenges faced due
to geographical location inaccessibleness of the clients‟ residence to reach their supervisory
services have been considered as another big constraint to attempt the regular follow-up.
Furthermore, it was the observation result that there is a limitation by credit officers to exert

87
their commitment to take over this follow-up activity. Hence all these limitations towards
supervisory and follow-up activities have significant impacts on the borrower‟s repayment
performance that probably leads them for defaults.

Moreover, from the respondents point of view the researcher has been categorized and
discussed the lists of factors as borrowers, lending institutes and government sectors
limitations as follows

Borrowers’ limitations

1. Lack of knowledge, business skill and experience.

2. High rate of borrower‟s migration from place to place makes difficult to visit
borrowers business.
3. Risks suffered due to engagement of some borrowers in illegal business types (like
contrabands, etc.) will increase the loss of assets which leads for high credit risk.
4. Bad trends to be exercised by the new borrowers in case the city administration
(guarantor) pay out the defaulted amounts which may affects their attitudes not to
repay the loan on time.
5. Engagement of sample borrowers on homogenous businesses at similar location or
town. For instance, designing similar business proposals on fattening or poultry or
diary production at similar locations. This seems hectic business portfolios

MFIs limitations

6. Inadequacy of trainer‟s skills and knowledge to provide sufficient knowledge based

training for the target borrowers.
7. Lack of periodic capacity building (updates to staffs) by the lending institutes in
general.
8. Lack of credit management; meaning that at some point credit service provided by the
lending institute is only to fulfill the gaps of the credit demand (Quota) or increasing
the reporting number of client‟s outreach which is initiated by internal forces as well
as externals rather than focusing on the quality service delivery.

Other factors

88
 9. The occurrence of input price rises up from time to time (unstable market condition),
fluctuation of market demand to borrower‟s end products, limitation of market
linkage with supplier, consumer, and any other production units.
10. The effects of external challenges to borrowers businesses like natural disaster such
as droughts and animal diseases like Elino and bird flu which had severely affect
borrowers businesses.

Similar questions of interviews were raised to NBEs staffs to identify the possible factors that
could significantly influence repayment recovery rate of borrowers. Accordingly, it was
reported that the following factors do have a substantial impact on loan recovery rate of MFIs
in general.

MFIs Limitations

11. There is a demand from the institutions management side that new branches are
supposed to be opened at babble areas (regions) where they are not sure of operating
the services sustainably. This may undermines MFIs loan recovery rate which leads
for high credit risk and under recovery rates.
12. Screening mechanisms weaknesses of some MFIs to identify the more viable clients
or borrowers.
13. Ineffective credit appraisals development by some microfinance institutes. In other
words, ambitious loan size appraisal approvals to borrowers without conducting
effective assessments of borrower‟s ability.
14. Inexistence of strong and consistent follow-up and monitoring activities by MFIs
officers. The beliefs of some MFIs under study was no more monitoring service for
loan utilization activities are expected to be undertaken by the lending staffs rather
sticking on the repayment status of those borrowers is the only mandatory
requirement to be achieved.
15. High staffs turn-over. This may affects the credit history of microfinances where
there is a gap to make handover borrowers history by the resigning staffs to the newly
assigned one.
16. Ghost loan (fraudulent actions) committed by some unethical staffs‟ i.e. organizing
fictitious number of borrower members and preparing payment sheets for non-

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 existent persons and signing on the loan disbursement sheet increases the default
rates.
17. Weakness of corporate governance of microfinances (i.e. Management and board of
directors weaknesses to take corrective actions where less performance were achieved
by their respective branches)
18. Lack of setting strong loan provision.
(Source: survey results collected through semi-structured interviews with lending
institute staffs, sample borrowers and: NBE, MFI directorate staffs)

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 CHAPTER FIVE

Econometric Analysis

The econometric analysis of repayment performance of borrowers uses a model where the
loan repayment-LRP (yi) = [1, if the respondent is creditworthy borrower otherwise 0, if the
borrower is defaulter] is regressed on possible explanatory variables. The probit regressions
model was employed for the estimation and marginal effects of each significant explanatory
variable. The STATA package was used to estimate the model and compute the marginal
effects, so that direct marginal implication of those explaining variables to influence the
dependent variable was discussed accordingly. Multicollinearity test between the
independent variables were also conducted using the variation inflation factor (VIF). To
handle the heteroscedasticity problem, the robust probit regressions were also conducted and
presented as follows.

5.1. Factors affecting repayment performances

It is initially important to assess the overall significance of the model. This has been made by
considering chi-square test at the given degree of freedom. As shown in the below probit
regression, the chi-square test is showing a statistically significant result at 95 percent
confidence level, p-values is less than 5 percent. Therefore, it is evident that the model is
good to fit to the data than no model.

On the other hand, it is important to identify the statistical significance of each explanatory
variable. As shown in the table below, out of sixteen independent variables regressed in the
model, the constant variable and other ten coefficients of the explanatory variables were
found to be statistically significant at 95 percent confidence level.

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Table-40: Maximum likelihood estimate of a probit model for loan repayment
performance

Probit Regression Number of obs. 319

Wald Chi2 (16) = 121.11
Prob > Chi2 = 0.0000
Log psuedolikelihood = -75.23307 Pseudo R2 = 0.6538
Robust
LRP Coef. Z p>│z│ [95% conf. Interval
Std. Err.

1 AGE 0.0465325 0.0239042 1.95 0.052 -0.0003188 0.0933839

2 GENDER -0.481536 0.2409358 -2.00 0.046 -0.9537617 -0.0093106 **
3 INCOMB 0.6229444 0.2545055 2.45 0.014 0.1241228 1.121766 **
4 AVLSIZ -1.27E-06 1.97E-06 -0.64 0.519 -5.13E-06 2.59E-06
5 MONTRO 1.886531 0.332748 5.67 0.000 1.234357 2.538705 *

6 UTLIZED -0.598333 0.2806061 -2.13 0.033 -1.148311 -0.0483554 **

7 CRDTIML 0.9975261 0.3251537 3.07 0.002 0.3602366 1.634816 *
8 RPTSUIT 1.283008 0.3102632 4.14 0.000 0.6749035 1.891113 *
9 RPTMNTHL 0.9173058 0.2871186 3.19 0.001 0.3545636 1.480048 *
10 RPIRRG -1.047014 0.2875843 -3.64 0.000 -1.610669 -0.4833589 *
11 VSTMNTH 0.5792137 0.2995815 1.93 0.053 -0.0079552 1.166383
12 VSTIRRG -0.680136 0.2710021 -2.51 0.012 -1.21129 -0.1489815 **
13 TRADQU 0.8011287 0.267557 2.99 0.003 0.2767266 1.325531 *

14 BUSEXP -0.068354 0.2290698 -0.30 0.765 -0.5173224 0.3806146

15 TECHN 0.2098048 0.2667934 0.79 0.432 -0.3131007 0.7327103
16 BOOKK 0.2821492 0.2369228 1.19 0.234 -0.182211 0.7465095
Cons. -5.425588 1.018258 -5.33 0.000 -7.421336 -3.429839 *
Source: survey data *, ** the variables are significant at 1% and 5% respectively

The explanatory variables such as GENDER (Sex of the sample respondent), INCOMB
(Income from other sources), MONTRO (Monitor the utilization of other members in the
group), UTLIZED (Utilization the loan for the intended purpose), CRDTIML (credit timely
released), RPTSUIT (Repayment time is suitable), RPMNTHL (repayment on monthly
interval), RPIRRG (repayment on irregular time interval), VSTIRRG (Visit on irregular
basis) and TRADQU (Adequate and sufficient training) are found to be statistically
significant to influence repayment performance of borrowers.

Variables such as MONTRO, CDTIML, RPTSUIT, RPMNTHL and TRADQU were found
to be positively influence the repayment performances at 1% significance level, while
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irregular repayment (RPIRRG) and constant have been found as negatively influence the
repayment performance of borrowers at 1% significance level. All except repayment time
suitability (RPTSUIT) were coincide with the prior expectation while repayment time
suitability was determined by sample respondent‟s feelings. Accordingly, the repayment time
scheduled were found to be suitable possibly due to borrowers familiarization to the lending
institutes lending characteristics tends to increase their beliefs and attitudes to repay their
obligations.

Similarly, INCOMB (Income from other sources) have positively influence repayment
performance of borrower at 5% level of significance. These are also agreed with what was
priori expected. GENDER and UTLIZED have negative coefficients to influence repayment
performance of borrowers at 5% level of significance. The variable UTLIZED (utilized for
the intended purpose) is in contrast to what was expected while the expected sign for Sex
were not predetermined. The possible reasoning for this negative coefficient to GENDER
could be female borrowers have better repayment performance than male being they are
more likely to feel responsible and more obliged to manage their households. Abafita (2003)
reports also argued that female borrowers are more creditworthy than the counter male
borrowers. The (UTLIZED) Utilization with negative coefficient to the loan repayment
status could be due to the fact that although the borrower utilizes the loan for the intended
purpose, there is a possibility that the repayment performance of the borrowers can be
undermined. For instance borrowers who have been utilized the loan for intended purpose but
have shortage of market linkage, insufficient inputs can less performs with its repayment.

On the other hand, the above table also shows that AGE (Age of the sample respondents),
AVLSIZ (Loan size), VSTMNTH (Supervision or visit on monthly basis), BUSEXP
(Business Experience), TECHN (Adopting technology) and BOOKK (Keeping book of
records) were found to be statistically insignificant variables to explain the loan repayment
performances.

The other important thing is post estimation test for multicollinearity among the variables
identified as an explanatory. Multicollinearity problem is identified when the independent
variables have a linear combination to each other. A common rule to use can be either VIF

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(Variance Inflation Factor) or tolerance. The STATA collinearity test results are shown
below in the table.

Table-41: Multicollinearity test to independent variables

(Obs = 319)

Collinearity Diagnostics

SQRT R-
Variable VIF VIF Tolerance Squared
----------------------------------------------------
AGE 1.06 1.03 0.9416 0.0584
GENDER 1.14 1.07 0.8794 0.1206
INCOMB 1.14 1.07 0.8808 0.1192
AVLSIZ 1.22 1.11 0.8171 0.1829
MONTRO 1.31 1.14 0.7652 0.2348
UTLIZED 1.35 1.16 0.7409 0.2591
CRDTIML 1.13 1.06 0.8873 0.1127
RPTSUIT 1.42 1.19 0.7046 0.2954
RPMNTHL 2.10 1.45 0.4764 0.5236
RPIRRG 1.95 1.40 0.5134 0.4866
VSTMNTH 1.78 1.33 0.5615 0.4385
VSTIRRG 1.75 1.32 0.5708 0.4292
TRADQU 1.27 1.13 0.7878 0.2122
BUSEXP 1.16 1.08 0.8616 0.1384
TECHN 1.19 1.09 0.8404 0.1596
BOOKKP 1.47 1.21 0.6788 0.3212
----------------------------------------------------
Mean VIF 1.40

As a rule of thumb, VIF greater than 10 or tolerance less than 0.1 are considered as an
indicators of multicollinearity or collinearity in short. As shown in the above table, the
independent variables in the model have all less than 10 VIF or 0.1 tolerances. Thus, there is
no possible serious threat of multicollinearity problem to the model.

The above discussion presents a probit regression and thus the coefficients explain that the
increase in these statistically significant variables will also increase the predicted probability
of the dependent variable, loan repayment performance of the borrower. In line with this, it is
important to compute the marginal effects, which are presented below.

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Table-42: The maximum likelihoods marginal effects of probit regression to Loan repayment
performance

Marginal effects after probit

y = Pr(LRP) (predict)
= .21020649

variable dy/dx Std. Err. z P>|z| [ 95% C.I. ] X

AGE .0134185 .00706 1.90 0.057 -.000424 .027261 34.4389

GENDER* -.1427197 .07016 -2.03 0.042 -.280238 -.005201 .583072
INCOMB* .1888827 .07846 2.41 0.016 .035112 .342653 .37931
AVLSIZ -3.66e-07 .00000 -0.64 0.519 -1.5e-06 7.5e-07 60818.7
MONTRO* .3932305 .05157 7.63 0.000 .292163 .494298 .69279
UTLIZED* -.1866253 .09267 -2.01 0.044 -.368254 -.004997 .69279
CRDTIML* .2007118 .05186 3.87 0.000 .099071 .302353 .877743
RPTSUIT* .3191931 .05954 5.36 0.000 .202491 .435895 .623824
RPMNTHL* .2737007 .08857 3.09 0.002 .100104 .447297 .429467
RPIRRG* -.2671733 .05986 -4.46 0.000 -.384501 -.149845 .373041
VSTMNTH* .1803027 .10234 1.76 0.078 -.020273 .380878 .30721
VSTIRRG* -.189766 .07299 -2.60 0.009 -.33282 -.046712 .451411
TRADQU* .2070395 .0614 3.37 0.001 .086694 .327385 .652038
BUSEXP* -.0197284 .06617 -0.30 0.766 -.14942 .109964 .517241
TECHN* .0627501 .08348 0.75 0.452 -.100859 .226359 .272727
BOOKKP* .0805471 .06825 1.18 0.238 -.053228 .214322 .539185

(*) dy/dx is for discrete change of dummy variable from 0 to 1

The marginal effect computation for statistically significant coefficients shows the change in
probability of being non-defaulter for a unit change in the discrete explanatory variables.
Hence, for a change from 0 to 1 in GENDER (from female to male borrowers), the
probability of being creditworthy decreases by 0.1427197 at 5% significance level, other
things held constant. The probability effects of this variable did not predetermined in the
hypothesis. Female borrowers are more creditworthy than the male borrowers. Further
assessment and efforts on selecting the more viable male borrower should be the
considerable issues to be taken into account by the lending institutes. This argued with the
reports reveled by Abafita (2003).

For the change from 0 to 1 in INCOMB (Income from other sources), the probability of being
creditworthy increases by 0.1888827 at 5% significance level, other things held constant.
This argues with what was expected in the hypothesis, and similarly coincide with that of

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Abreham (2002) and Abafita‟s (2003) reports. Income from any other diversified sources is
expected to increase the probability of being non-defaulters.

For the change from 0 to 1 in MONTRO (Monitor the utilization of other members in the
group), the probability of being creditworthy increases by 0.4305229 at 1% significance
level, other thing held constant. This variable coincides with what was expected in the
hypothesis to influence the repayment performance of borrowers not to be the defaulters.

For the change from 0 to 1 in UTLIZED (Utilized the loan for the intended purpose), the
probability of being creditworthy decreases by 0.1866253 at 5% significance level, being
other things held constant. Again this found to be having different coefficient sign from what
was expected in the hypothesis. The (UTLIZED) Utilization with negative coefficient to the
loan repayment status could be due to the fact that although the borrower does utilize the loan
for the intended purpose, there is a possibility that the repayment performance of the
borrowers can be undermined. For instance borrowers who have been utilized the loan for
intended purpose but have shortage of market linkage, availability insufficient inputs can
lead them for less performance of repayments.

Regarding credit timeliness, for the change from 0 to 1 in CRDTIML (credit timely released),
the probability of being creditworthy increases by 0.2007118 at 1% significance level, being
other things held constant. This have also similar coefficient sign with what was expected in
the hypothesis; Meaning that as the requested loan is released by the MFIs to the borrower on
time, there is a possibility that borrowers become successfully finance their business so that
they are less likely to become defaulters. Similarly, for the change from 0 to 1 in RPTSUIT
(Repayment time suitability), the probability of being creditworthy increases by 0.3191931 at
1% significance level being other things held constant. The expected effects of this variable
were not pre-determined since the sample respondent could have possible different feelings.

The other important thing to be regressed was repayment interval trends of sample
borrowers. Accordingly, the result shows that for the change from 0 to 1 in RPMNTHL
(repayment on monthly interval), the probability of being creditworthy increases by
0.2737007 at 1% significance level, other things held constant. This is also agreed with what
was expected to influence the dependent variable in the hypothesis. Meaning borrowers who

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have repayment trends on a monthly basis could have high repayment performances as
compared to other repayment trends as shown in descriptive analysis. On the other hand, for
the change from 0 to 1 in RPIRRG (repayment trend on irregular time interval), the
probability of being creditworthy decreases by 0.2671733 at 1% significance level, being
other things held constant. Hence again this variable have similar coefficient with what was
hypothesized. Meaning borrowers with high trends in repayment intervals on irregular basis
or beyond a month could possibly fail to repay the loan on time (become defaulters).

Regarding frequency of officer visit to client‟s business territory, further effects of visit on
monthly and irregularly basis were evaluated. Accordingly, for the change from 0 to 1 in
VSTIRRG (visiting on irregular time intervals), the probability of being creditworthy
decreases by 0.189766 at 5% significance level, being other things held constant. This
variable also has similar significance level with what was expected to influence the
repayment performances, negatively.

The study also reveals that for the change from 0 to 1 in TRADQU (Adequate and sufficient
training), the probability of being creditworthy increases by 0.2070395 at 1% significance
level, being other factors held constant. Meaning that borrowers who have got sufficient and
adequate training on business management, saving cultures, credit management and others
have high possibility of being creditworthy borrowers than others who did not. However, it
was discussed in the descriptive analysis that the training provided by the lending institutes
and other partners was inconsistent in nature which needs to be improved by the training
providers.

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Table-43: Comparison of the likelihoods of independent variables that influence repayment
performances

Methodologies Employed

Sampling Regression
Authors Significant Variables Negative sign Positive sign techniques model

Age, Sex, business

experience, family size, Business experience,
business type and family size, business
dependence ratio and type and dependence
Fikirte, 2011 constant ratio Age, Sex and constant SRS Logit

Age, Education level,

Saving Culture, suitable
OSC, Loan size, repayment time,
Age, Sex, OSC, SRP, LSZ, Number of Income from other
INC, INCA, LSTK, NDP, dependents, Loan source, Livestock &
Abafita, 2003 BK, LDR, SPV, TIM diversion and sex Supervision SRS Logit

Age, Education, Income Education level,

from other source , Age, repayment Relevant business
Number of dependents, period, Loan experience, Income
Abreham, 2002 Loan diversion and Sex diversion and sex from other source Stratified Tobit

Borrowers perceptions, Family size, borrowers

other source of income, perception towards Sytematic
training, business exp., repayment, Availability Random
Firafis, 2015 family size, of training sampling Logit
Gender, Income from
other source,
Monitoring other
members, Loan
utilization, Credit Income from other
release on time, source, Monitoring
Suitability of repayment Gender , Utilization other group members
time, Repayment on of the loan for the for loan utilization,
monthly basis, intended purpose, Credit release on time,
repayment on irregular Repayment on Repayment time
basis, Visit on irregular irregular basis and suitability, Repayment
basis and Adequacy of Visit on irregular on monthly basis, and
Abreham, 2016 training basis Adequacy of training SRS Probit

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 CHAPTER SIX

Summary, Conclusion and Recommendation

The chapter summarizes the overall findings and conclusions of the study with drawing the
possible recommendations to be addressed by the concerned bodies. Accordingly the
summary report will be presented below and followed with the conclusion and
recommendations for policy makers, lending institutes management and other stakeholders‟
decision makings

6.1. Summary

In developing countries like Ethiopia poverty is the major problem of the societies at large.
Peoples in Ethiopia are living in rural and urban areas of the country. Majority of those
peoples were affected with lack of financial capitals to improve their livelihoods especially
of the target poor peoples. They were inaccessible with financial services that are available
through formal commercial banks. To mitigate these gaps, microfinance industries has been
emerged in to the economy to serve those peoples who are in financial needs. However,
during the last couple years of operations those microfinances that are operating in Ethiopia
have been facing a severe decline in repayment recovery rates according to the NBE‟s annual
reports 2014- 2015.

In light of this, the study was intended to extend its investigation on factors that are possibly
affects loan repayment performance of microfinance institutes borrowers that are operating in
Oromia regional states. Accordingly, sample MFIs were selected based on high clients
outreaches and thus Oromia Credit & Saving Share Company (OCSSCO), Busa Gonofaa
MFI, Wasasa MFI and VisionFund microfinances were included as the study area. A total of
319 sample respondents were selected from respective microfinance institutes. The samples
were allocated to those MFIs based on their respective clients‟ outreaches proportional
percentages.

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In order to identify those relevant factors such as socio-economic and institutional loan
related factors, primary data were collected from sample respondents. The descriptive and
econometric regression analysis was employed to predict the effects of those independent
variables to the loan repayment performances using the probit model. Most of the variables
that are related to those factors were analyzed with the statistical descriptive method while
due to endogenous problem of some variables only 16 variables were included in
econometric regression model.

The study revealed that the proportion of female and male defaulters was found as male
borrowers are relatively higher defaulters than that of female borrowers and significant at 5%
which argued by Abafita (2003). Borrower‟s ages with the age category of 30 and above had
less likely to be defaulters than that of youngsters (less than 29) which is significant at 10%.
It argued with Fikirte (2011) and Abafita (2003) study results. On the other hand, monitoring
the loan utilization of other members within the group was observed as slightly higher
monitoring actions were implemented by the defaulter to other member in their respective
groups and significant at 1%. While higher portion of the creditworthy borrowers conduct the
monitoring activities.

The selected sample borrowers have majorly took social sanction measures on members who
experienced diversion or wrongly misuses the loan amount otherwise informed the issues to
the credit officers of the lending institutes. Majority of the defaulters had took an additional
credits from friends and relative, of which majority of them has settled these credits. Sample
borrowers who had experienced different round loan service were assessed. Accordingly, on
average sample borrowers who had only served for the first round were attempt high default
rates while borrowers who experienced for the fourth time was less likely to be defaulters.

From the survey result again it was found that majority of sample borrowers were received
an equivalent amount of loan requested. The repayment time set by the lending institutes was
more suitable for majority of the sample borrowers. Majority of the defaulting borrowers
were experiencing repaying the loan on irregular basis, while the higher portions of the
creditworthy client were experiencing repayment on monthly basis.

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The majority of sample borrowers were deployed on service provision businesses. Among
those it was revealed that the slightly higher number were defaulters. However from those
business type categorized in the study, high defaulters were reported as those who engaged
on fattening, cattle trade and poultry production services. The timeliness of credit delivery
was one of the study areas to be assessed. Accordingly, almost higher numbers of the
samples were financed on time. Majority of the sample respondents were found defaulters of
the loan. In line with this the mean value of the defaulted amount were discussed in the
descriptive section of the paper. From the borrower‟s point of views, majority of the sample
defaulters were undermined the repayment due to utilizing the loan for personal household
consumption, comparatively while fewer had reported defaults due to unforeseen natural
disaster and diseases.

Losses of next round credit service were considered as the highest costs of defaults by
majority of the sample respondents. The highest portion of the sample respondents had
received the requested loan fund that is sufficient enough to finance their respective projects.
Based on the decision of diverting the loan from the intended project to another by the
defaulters, the major reasoning for diverting the loan was found as the unstable market
demand change to borrower‟s end product over time.

On the other hand, regardless of the frequency of supervision and follow-ups, almost all
sample respondents were visited to their business territory by the lending staffs. Majority of
them were supervised on irregular basis which is negatively influence the probability of
being creditworthy at 5% significance level, while few had got on weekly time intervals.
Almost from the lending policies of those microfinances, the supervision time interval is
usually expected at least once in a month.

Provision of appropriate and sufficient training on relevant issues on the subject matter of
financial service is very crucial for the success of microfinance activities. Accordingly,
regardless of its training natures almost all sample borrowers had got the training provided by
the institutions as well as sector training providers which is significant at 1%. For instance,
majority of them had training on saving mobilization while least number had got training on
how to keep book of records. In light of these, higher number of the creditworthy borrowers
had got adequate training, while on the contrary higher proportion of the defaulters was not

101
trained very well. Majority numbers of the respondent have no other source of income before
engaging in to the credit schemes. While some others who have a diversified source of
income have higher probability of being creditworthy at 5 % significance level.

Higher numbers of borrowers were faced the problem of unsuitable market place although
higher numbers of sample borrowers have an accessible and sufficient input to run their
businesses. Among the sample borrowers the slightly higher number of borrowers had
relevant business experiences. The proportional higher numbers of sample defaulters were
experienced medium range of market demand to their end products. Moreover, among the
sample respondents only few numbers has not saved their money at the bank. The highest
proportion of the defaulted sample borrowers were not kept book of records while, the
greatest portion of the sample creditworthy borrowers do. The possible reasoning was due to
running fewer transactions by their businesses and lack of knowledge.

On the other hand, although the financial service of microfinances is delivered to the target
borrowers through its credit policies starting from organizing and screening of the viable
clients to loan approvals, there are some challenges that faces them internally (like staffs
commitment, high staff turnover, etc.) as well as externally (like; high level of third parties
involvement on loan processing and approvals) which had a great contributions for low
repayment performances by the lending microfinance institutes. Moreover, settlement of the
defaulted loan by loan guarantor (City administration) through court process misleads other
viable borrower‟s behaviors not to repay the loan as loan agreement. On the contrary,
according to the sample staff responses it was experienced that medium leveled legal support
was exerted by the concerned legislative bodies might enhance risks suffered from defaults.

6.2. Conclusions and Recommendations

Although the results of the overall study revealed and discussed in the previous sections of
the paper was equally important, the findings were summarized but not limited to the
following conclusions and recommendations.

Male borrowers in a given enterprise were found to be more defaulters than females although
they have relatively higher utilization rate of the loan for the intended purpose as compared

102
to that of females. Thus, the institutions should more rely their focuses on male borrowers to
identify the more viable clients. Although the age of the borrowers was not significant to
influence repayment performance, the study implied that borrowers with higher age (adult
group) slightly had better repayment performance than youngsters. So, the institution should
exert its effort on identifying the problem of youngsters rather than excluding them from the
service.

Having income from other diversified sources is more helpful for borrowers to repay their
loan on time. The good trend of monitoring the loan utilization status of other members in a
group by the borrowers encourages members in a group to settle the loan timely. Although
there is good utilization trends by the sample borrowers to the intended purpose, there are
high number of borrowers who fail to repay the loan on time. The possible reason could be
due to the observed least close follow-up by MFIs and limited technical support by the
concerned bodies to the clients business contributes for delay. Thus, the institutions and
concerned bodies should exert their effort to fill the gaps. Provision of the loan funds by the
lending institutes on time has positive effects on the probability of borrowers to being non-
defaulters.

Although there are some sample borrower who feels disappointed with shortage of sufficient
grace period, majority of the sample borrowers were convinced with the available repayment
time schedule set by those lending institute had good impact on the repayment performance.
However, the study recommends lending institutes‟ to incorporate those disappointed, where
there is a possibility for grace time improvements. Borrowers who has an experience of
repayment on irregular basis (possibly due to shortage of cashes or unwillingness behaviors)
were fail to repay the loan as promised. Hence the institution needs to work on awareness
creation on cash management and enforcing the repayment through close monitoring and
supervisions.

Borrower’s prospects

In additions to the above descriptive and regression analysis results the followings have also
a considerable impact on repayment performance of borrowers.

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Borrowers lack of business skills and experience, migration from place to place, engagement
on some risky and illegal business types, involvement on non-diversified business portfolios,
negative attitude towards credit service (considering as donation or government‟s or other
NGOs grant supports) and adverse selection of not to repay the loan are among the major
factors undermines the repayment performances. Moreover, settlement of the defaulted loan
amount either partially or fully by the loan guarantor (City Administration) does have a
negative consequence on the behavior of other new and existing borrowers to fall in a similar
default problem.

Lending Institutes Prospects

Lending institutions lack of internal control to loan disbursement, limited number of credit
officers, commitment of the lending institutes staffs to supervisory activities on a regular
basis, lack of training skills of credit officers and other partner staffs on providing relevant
trainings types and financial service delivery on quantity based approach with less
consideration to quality experienced by some MFIs due to internal as well as external forces
have also a considerable significant effects for less repayment performance of borrowers.
Quick and close follow-up to clients business after the missing repayment time, maintaining
a strong solidarity among the group members of borrowers are listed among the solutions to
minimize the default rates of MFIs (Fikirte, 2011).

Government prospects

Among the loops that have been observed during the survey, there are also some other factors
that corresponds to the government involvement and supports to the lending institutes and
borrowers‟ needs. Limited facilitation of market linkage with suppliers, venders and end
users of products, provision of inaccessible and unsuitable production places, limited legal
and technical supports to the borrowers business and lending institutes financial services,
lack of infrastructures (suitable production and market place, sufficient inputs, roads) have
reported as significant challenges to the success of borrowers business. Moreover, as it was
discussed in the previous section, the respondents from the lending institutes have reported
that although the goal of sector government are realizing and enhancing better economic
development in poverty reduction programs, this missions have been probably mislead by

104
some borrowers, lending institute staffs and corresponding sector staffs due to information
gaps on credit service delivery (information asymmetry) which contributes for high default
rates.

The weakness in integration between the lending institutes and other partners on organizing
and screening the viable MSE borrowers would have also a considerable effect on the
repayment performance of MFIs. Organizing and selecting borrowers with less emphasis to
the viability leads for high default rate (adverse selection). Regarding moral hazard effects,
credit service with less emphasis given to close supervision and monitoring service by both
lending institutes and peer groups might leads borrowers fail to repay the loans.

More points of recommendations and focuses to the lending institutes, policy makers and
stakeholders

i. From the study point of view, male borrowers are high defaulter than females. Thus,
the lending institutes should pay attentions on maintaining effective screening
mechanisms to identify the more viable male borrowers from those of bad borrowers.
ii. As the study revealed, conducting supportive supervision on irregular (arbitrary)
bases had negative impact on the probability of serving creditworthy borrowers. This
implies that maintaining consistent and regular supportive supervision to the
borrowers business territory at least once in a month is highly preferable although
other factors like staff turnover and insufficient number of credit officers problem
exists in a given MFIs.
iii. Based on the challenges identified and explained from the borrowers‟ perspective,
lending institute perspectives and government perspectives microfinances and other
stakeholders should design the proper integration strategies to overcome the
problems.
iv. Enhancing the commitments of credit officer through different incentives like
provision of short-term trainings and other incentives will probably minimizes the
density of defaulters due to their efforts.
v. Microfinances are recommended to match the number of credit officers with in
reachable size of borrowers to provide effective supervisory service.

105
vi. In implementing the developmental strategies through enhancing self-employment
opportunities initiated by the government of Ethiopia, the weakness in integration
between the implementing partners should be improved.
vii. It is also recommended that enforcing repayment through awareness creation and
social acts (sanctions) among the borrowers‟ members is more incredible than taking
as the solution of settlement of the defaulted loan through the guarantor (City
Administration) due to the fact that credit settlement with loan guarantor affects the
credit history of the institutions.
viii. There is a need of improvements in legal supports to the financial services provided
by the lending institute in safeguarding the credit from suffering default risks.

Finally, the study highly recommend interested researchers to extend further investigation
on the impact of settlement of defaulted amount from government subsidy on other
developmental project costs.

106
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Annex I

A. The Survey Questionnaire

KEBELE/PA________________________

ENNUMERATOR____________________ DATE______________________________

I. Personal Details
1.1. Name of Borrower____________________ Age__________
1.2. Sex__________ 0. Female 1. Male
1.3. Marital Status________ 1. Single 2. Married 3.divorced 4. Widowed

II. Information on group formation

2.1. How many members does the group in which you belong have? ___ ________

2.2. Do you know all (most) of the members in your group? ___ 1.Yes 0.No

2.3. Do you feel responsible (liable) to other members of your group?____ 1. Yes 0. No

2.4. Did you have the feeling that you might be sued in case of failure to repay the loan? ___
1.Yes 0.No

2.5. Do you attempt to know or monitor the loan utilization of the other members of your group?
__________1.Yes 0. No

2.6. If yes, what action do you take in case you observe wrong utilization of the loan, say usage of
loan for non-intended purpose?___

1) Inform to your lenders officers 2) accuse the diverter

3) Put social sanction 4) Other (specify)________________________

III. Loan and Repayment

3.1. Did you have any source of credit other than OCSSCO, BG MFI, Wasasa MFI or VisionFund
MFI? ___ 1. Yes 0. No

3.2. If yes, what is your source?__ 1)Iddir 2)Money lenders 3)Friends/relatives 4) Banks 5)
Other

3.3. How many times and how much money did you receive from these sources during the past 12
months?

Source Year Amount of Loan

3.4. Have you finished repayment of loan from these sources? ____ 1. Yes 2. No

3.5. How much money did you received as loan from OCSSCO , BG MFI, Wasasa MFI or
VisionFund MFI credit scheme?

Round 1 Round 2 Round 3 Round 4 Round 5 Round 6

3.6. Do you think that the amount you received is similar to your intended request? _____1. Yes
0. No

If no, what is your feeling? __________________

3.7. Is the repayment period set by OCSSCO, BG MFI, Wasasa MFI or VisionFund MFI suitable
in your opinion?___ 1.Yes 0. No

3.8. If no, recommend a suitable repayment period:___________________

3.9. Was the loan issued timely? _____ 1. Yes 0. No

3.10. If no, what was the impact of the delay?___________________________

_______________________________________________

3.11. What is the status of recent loan? _______

1. Fully repaid 2. Delinquent 3. Repayment in arrears/Defaulted

3.12. If defaulted, what is the balance remaining/outstanding? _________

3.13. What was the cause for the loan to be in arrears?

1. A beliefs/attitudes that loan based business activities were worthless to generate profit

2. Used some of the loan to finance household living expense

3. Sold on credit but receivables did not get paid back on time

4. Bankruptcy of the business

5. Loss of assets acquired by the loan

5. Perceived the loan as if it is a donation, a grant by the Government bodies

6. Other (specify)_____________________________

3.14. Do you perceive the cost of default to be high? ______ 1. Yes 0. No

3.15. If yes, which of the following is the most important in forcing you to repay the loan in time?
 1. Claim against personal wealth

2. Claim against guarantors

3. Social sanctions (e.g. loss of social status)

4. Fear of losing next round loan in future

5) Other (specify)_____________

IV. Loan purpose and Utilization

4.1. What was the purpose for which the loan was taken?____

a. Purchase of raw materials for further processing

b. Woodworks and Metal works

c. Assembling of semi-finished products into final products

d. Construction and Engineering activities

e. Small and petty trades (Shops, Baltina, and others, if any)

f. Other; (specify)_________________________

4.2. Was the amount of loan you took enough for the purpose intended? ____ 1. Yes 0. No

4.3. If no, what was the amount you requested? Birr_______

4.4. Did you spend the entire loan on purposes specified in the loan agreement? ___1. Yes 0.
No

4.5. If no, state those non-intended purposes and the amount spent on them

Purpose Amount spent (Birr)

1_________________________ ________________

2_________________________ ________________

3_________________________ ________________

4_________________________ ________________

4.6. What was/were the reason(s) for spending part/entire loan on non intended purposes?_____

1. The loan amount was not enough for the intended purpose

2. The loan agreement did not coincide with my initial intention

3. The proceeds received from the loan is exceeder than my actual costs
 4. The change in Market demand 5. To settle another Credits

6. To make a better profitable business 7. Other (specify)___________________

V. Supervision, Advisory Visits and Training

5.1. Have you ever been supervised for loan utilization by OCSSCO, BG MFI, Wasasa MFI or
VisionFund MFI staffs? ___________ 1. Yes 0. No

5.2. Have you ever been supervised for loan repayment? ___ 1. Yes 0. No

5.3. If yes to either on. No. 5.1 or 5.2, how many times were you supervised? ___

5.4. If yes to either 5.1 or 5.2, was it adequate enough in your opinion?_____ 1.Yes 0. No

5.5. Do you consider supervision as being important for loan repayment? ___ 1. Yes 0. No

5.6. Did you get any training before receiving loan? _____ 1.Yes 0. No

5.7. If yes, what kind of trainings did you take? _____

1. Business (Entrepreneurial, Innovative skill development) 2. Marketing

3. Saving culture 4. Book keeping 5. Other (specify)

5.8. Do you think the training you took is adequate and sufficient enough? ________1. Yes
0.No

5.9. Do you think that the training you took has helped you to enhance your knowledge about
credits, mechanisms of asset management‟s and increasing your income? ___ 1. Yes 0.
No

5.10. If no, what do you expect to be improved? _________________

VI. Income Level

6.1. What was your annual income from activities financed by the loan during the last 12 months?

1. Below Birr 5,000 2.Between Birr 5,001-10,000 3.Between Birr 10,001- 15,000

4. Between Birr 15,001-20,000 5.Between Birr 20,001-25,000 6.Above Birr 25,000

6.2. Currently, do you have any other/new sources of income? ___ 1. Yes 0. No

6.3. If yes, what are those other sources and your annual income from them?
 Source Annual Income

_______________________ _____________

_______________________ _____________

VII. Production Location, Market Place and Technology Adoption

7.1. Do you think that you have sufficient inputs around your business? _____ 1. Yes 0. No

7.2. If no, what measures do you take? ________________________

7.3. Does your business have a suitable production place? ___ 1. Yes 0. No

7.4. If no, what are its impacts while running your business, profitably? _____________________

7.5. Do you think that your production or market place is accessible for consumers? __1.Yes 0.
No

7.6. Do your business adopt an advanced technology while running the business ____1. Yes 0.
No

7.7. If yes, what type of technology do you use? _______________________

VIII. Business Experience and Market Situation

8.1. Do you have any similar business experience before engaging in this credit scheme? _1. Yes 0.
No

8.2. If your answer is yes, for how long did you involve in?

a) Below 3years b) 3-5years C) Above 5years

8.3. What are the major end products and/or services did you produced or rendered using the loan you
borrowed?

1.___________________________

2.___________________________

3.___________________________

8.4. How was the market demand status of your product? ___

1. High 2. Average 3. Low

8.4. If it is low, have you ever been assessed the feasibility of your business before starting
operations? ________ 1. Yes 0. No

8.5. What was the trend of the profitability of your business after engagement in the credit program
during the past few years? _____ 1. Increased 2. Decreased 3. No change
8.6. If increased, what was the reason to your business of being profitable?

1. Having sufficient loan fund 2.Availability of sufficient market

3. Selling at reasonable price 4.Quality advantage 5. Other (Specify)___

IX. Other Information

9.1. Do you have any book of records? ______ 1. Yes 0. No

9.2. If yes, for what purpose?

1) To evaluate profit and loss and financial positions of the business

2) For monitoring loan repayment status 3) Other (specify)____________________

9.3. If no, explain the reason(s) of not keeping records?

1. Lack of knowledge 2. Assumed as if it is not necessary

2. The transaction seems too small to keep a record 3. Other (specify)___________

X. Lending Institutes and Government Prospects

10.1. Do you think your branch credit officers are actively involved in screening the creditworthy
borrowers before granting credits to the MSE borrowers? ________1. Yes 0. No

10.2. If no, what is the reason for not involving? Give your opinion_________________________

10.3. Do you think that the screening activity through the government bodied sectors is effective
and efficient enough for the lending institutes? ___________ 1. Yes 0. No

10.4. If no, what do you recommend? __________________

10.5. Do you think your institutes follow a proper loan rationing mechanisms to all credit needy
borrowers? ______1. Yes 0.No

10.6. If No, what philosophy does it uses? ___________________

10.7. In what time interval does the officer visit the client‟s businesses? ______________

1. Weekly 3. Monthly
2. Bi-weekly 4. Quarterly 5. Other (Specify)

10.8. Do you think that the credit lent to borrowers have an adequate legal supports to protect MFIs
from default risks? ______ 1. Yes 0. No

10.9. If your answer for Q.12.8 yes, how do you measure it? ____________
A) High B) Low C)Neutral

10.10. If your answer for Q.12.8 is no, what do you suggest? _________________________
10.11. Do you think that the government sector involvement on loan agreement has an impact on
credit rationing inefficiency? _________ 1. Yes 0. No

10.12. Does the delinquency of repayment by borrowers have a negative impact on the government
projects subsidy?

____________ 1. Yes 0. No

Annex - II

B. Interview questions:

Sample Borrowers

1. What factors other than those indicated in the questionnaires had seriously undermines your
repayment performances?

Sample MFIs staffs:

2. What factors other than those indicated in the questionnaires had seriously undermines the
lending institutes repayment recovery rates?

NBEs views on MFIs repayment performance:

3. In your opinion, what factors does affect the repayment performance of microfinance
institutions in Ethiopia?