Post on 10-Jun-2018
THE RELATIONSHIP BETWEEN FINANCIAL INCLUSION AND ECONOMIC
DEVELOPMENT IN KENYA
ELIZABETH WANGUI WANG’OO
D61/71243/2008
A RESEARCH PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE AWARD OF THE DEGREE OF MASTER OF BUSINESS
ADMINISTRATION, UNIVERSITY OF NAIROBI
OCTOBER 2013
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DECLARATION
This research project is my own original work and has not been submitted for examination in any
other university
Signature ................................. Date .........................................
ELIZABETH WANG’OO
D61/71243/2008
This research project has been submitted for examination with my approval as the university
supervisor
Signature ................................. Date .........................................
MIRIE MWANGI
Lecturer, Department of Finance and Accounting
University of Nairobi
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ACKNOWLEDGEMENTS
Mr. Mirie Mwangi has been the ideal project supervisor. His insightful criticism and patient
encouragement aided the writing of this research project in innumerable ways. I would also want
to thank Patrick Gikaria whose support and encouragement was deeply appreciated.
Heartfelt thanks to all lecturers in the department of accounting and finance for the knowledge
they have impacted in me. Sincere thanks to my fellow students for their assistance
God bless you all
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DEDICATION
This research project is dedicated to God first, my husband for his advice and support and to my
entire family
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ABSTRACT
The importance of an inclusive financial system is widely recognized in the policy circle and has
become a policy priority in many countries including Kenya. This research project seeks to
examine critically financial inclusion and economic development in Kenya. The objective of the
study is to review existing sources of detailed data on financial inclusion and economic
development and establish the relationship between financial inclusion and economic
development in Kenya and make recommendation. The research design chosen for analysis was
meta-analysis. Secondary data was collected from United Nations Development Programme
(UNDP), International Monetary Fund (IMF) and Financial Access Surveys (FAS). This data
was analyzed using descriptive statistical approach, regression and correlation analysis. The
excel software was used to transform the variables into a format suitable for analysis after which
the statistical package for social sciences for data analysis (SPSS) was used, which provided
various statistics. The output from SPSS provided the basis for analysis and findings of the
study. The period covered by the study was 7 years from the year 2005 to 2011.The study found
out that there is a positive relationship between financial inclusion and economic development
and an increase in financial inclusion leads to an increase in economic development. This was
revealed by the various correlation tests and regression test carried out i.e. the Pearson
correlation matrix highlighted that there is a significant correlation between the dependent
variable human development Index (HDI) independent variable number of bank branches and
number of bank accounts at 0.985 and 0.952 respectively. Financial inclusion ensures ease of
availability, accessibility and usage of the formal financial system to all members of the
economy. Financial inclusion is an important aspect of development. Policymakers in developing
countries have an important role to play in creating the conditions for improved access, and
thereby unlocking the economic potential of their populations. The potential for economic
growth and poverty alleviation through the development of a more inclusive financial services
sector has been recognized as a priority issue in many countries. There is need for government of
Kenya to recognize the importance of financial inclusion and make policies that are more
inclusive for greater economic development. Further research is needed on financial inclusion, its
indicators and determinants as well as its impact on development. Its impact as an effective
developmental policy is still under research.
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TABLE OF CONTENTS
DECLARATION............................................................................................................................ii
ACKNOWLEDGEMENT..............................................................................................................iii
DEDICATION................................................................................................................................iv
ABSTRACT.....................................................................................................................................v
LIST OF TABLES..........................................................................................................................vi
LIST OF FIGURES.......................................................................................................................vii
ABBREVIATIONS......................................................................................................................viii
CHAPTER ONE: INTRODUCTION..............................................................................................1
1.1 Background of the study............................................................................................................1
1.1.1 Financial Inclusion..................................................................................................................2
1.1.2 Economic development...........................................................................................................6
1.1.3 Financial Inclusion and Economic development....................................................................6
1.1.3 Financial Inclusion and Economic development in Kenya.....................................................8
1.2 Research problem.....................................................................................................................10
1.3Research Objectives ……………..…………………………………………....……………...12
1.4 Value of the Study ………………………….....…………………………………..…..….....13
CHAPTER: TWO LITERATURE REVIEW……………………………………...……..…...…14
2.1 Introduction……………………………………………………………………...…………...14
2.2 Theoretical Framework ………………………………………………...….…………...……14
2.2.1 Classical Economics Theory……………………………………………………………….14
2.2.2 Keynesian Economic Theory………………………………………………………………16
2.2.3 Keynesian Theory II……………………………………………………………………….17
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2.3 Review of Empirical research………………………......……….…………..……………….18
2.3.1 Access to Financial Services……………………………………………………………….27
2.3.2 Mobile Financial Services in Kenya……………………………………………………….28
2.3.3 Determinants of Financial Inclusion……………………………………………………….30
2.4 Summary of Literature Review …………………………...…………………………………32
CHAPTER THREE: RESEARCH METHODOLOGY…………..……………………………..33
3.1 Introduction ………………………………………………….…………………………...….33
3.2 Research Design……………………………………….………………………......................33
3.3 Data Collection………………………………………………………………………………34
3.5 Data analysis……………………………...…………………………………..……………...35
CHAPTER FOUR: DATA ANALYSIS AND PRESENTATION OF FINDINGS…………..37
4.1 Introduction………………………………………………………………………………….37
4.2 Human Development Index…………………………………………...……………………..37
4.3 Financial Inclusion…………………………………………………………………………...39
4.4 Correlation Analysis……………………………………………………………...………….41
4.4.1 Pearson Correlation………………………………………………………………………...42
4.4.2 Partial Correlation………………………………………………………………………….43
4.5 Regression Analysis……………………………………………………………………….…43
4.5.1 Regression Model………………………………………………………………………….44
4.5.2 Test of Coefficients Statistical Significance T-test……………………………………..….46
4.5.3 Test of Prediction of Ability of Variables…………………………………………………46
4.5.4 Analysis of Variance (ANOVA)…………………………………………………………..48
4.5.5 Test of Collinearity………………………………………………………………………...49
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4.6 Summary of data analysis……………………………………………………………………49
CHAPTER FIVE:
SUMMARY OF FINDINGS, CONCLUSION AND RECOMMENDATIONS………………50
5.1 Introduction…………………………………………………………………………………..50
5.2 Summary of Findings………………………………………………………………………...50
5.3 Conclusion…………………………………………………………………………...………52
5.4 Recommendation ……………………………………………………………………………53
5.5 Limitation…………………………………………………………………………………….55
5.6 Suggestions for future research………………………………………………………………56
REFERENCES……………………………………………….………………………………….58
APPENDICES…………………………………………………………………………………...64
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LIST OF TABLES
4.4a Pearson correlation of financial inclusion and HDI
4.4a Partial correlation of financial inclusion and HDI
4.5a: Regression analysis (Model summary)
4.5 c: R square measure
4.5 d: Regression analysis (ANOVA)
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LIST OF FIGURES
4.2a: A graph showing the Human development index trend of Kenya
4.2b: A graph showing the trend of Human Development Index for Kenya as compared to other
countries
4.3a: A graph showing the trend of the number of bank accounts (per 1000 adult population) in
Kenya
4.3b: A graph showing the trend of the number of bank branches (per 100,000 people) in Kenya
4.3c: A graph showing the trend of the amount of bank credit and bank deposits trend of Kenya
4.5 b: A scatter plot showing the relationship between the dependent and standardized
independent variables
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ABBREVIATIONS
AFI - Alliance for Financial Inclusion
ATMS - Automatic Teller Machine
CGAP - Consultative Group to Assist the Poor
FSDK - Financial Sector Deepening Kenya
GDP - Gross Domestic Product
FAS - Financial Access Surveys
FI - Financial Inclusion
HDI - Human Development Index
IFI - Index of Financial Inclusion
IMF - International Monetary Fund
M-Pesa - M-Pesa is derived from ―M‖ for mobile and ―Pesa‖ for money in Swahili.
MFI - Micro Finance Institutions
MDGs - Millennium Development Goals
MSMEs - Micro,Small and Medium-sized Enterprises
ROSCA - Rotating Savings and Credit Associations
SACCO - Savings and Credit Co-operatives
SPSS - Statistical Package for Social sciences
UNDP - United Nations Development Program
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CHAPTER ONE:
INTRODUCTION
1.1 Background of the Study
Globally, 2.7 billion adults do not have access to formal financial services (Demirguc-kunt,
Levine and Ross 2009). Through its Financial Inclusion 2020 project, the Centre for
financial inclusion defines full financial inclusion as a state in which everyone who can use
them has access to a full suite of quality financial services, provided at affordable prices, in
a convenient manner, with respect and dignity. Financial services are delivered by a range
of providers, in a stable, competitive market to financially capable clients. Through a
survey carried out in 2011, the center expanded the definition to note that full inclusion
requires the clients of these services to be financially literate (Gardeva & Rhyne, 2011).
Financial deepening is sometimes used as a synonym for financial inclusion however it is
important to note that these two are not the same. It refers to the increased provision of
financial services with a wider choice of services geared to all levels of society. Financial
deepening generally means an increased ratio of money supply to GDP or some price
index. It refers to liquid money. The more liquid money is available in an economy, the
more opportunities exist for continued growth. It can also play an important role in
reducing risk and vulnerability for disadvantaged groups, and increasing the ability of
individuals and households to access basic services like health and education, thus having
a more direct impact on poverty reduction Deepening can happen without financial
inclusion if volumes of financial flows increase while only a fraction of the population
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participates. It is essentially the process of increasing financial intermediation or
engagement within the financial system (Ardic & Damar, 2006).
Finance is an essential part of the development process, and modern development theories
emphasize the key role of access to finance. Access to finance makes transactions quicker,
cheaper, and safer, because it avoids cash or barter payments. Greater access to financial
services enables poor people to plan for the future and invest in land and shelter, and to
utilize productivity. It is widely recognized that the development pathway requires access
for families and firms to appropriate financial products, including savings, credit,
insurance, and investment instruments. Sustained long-term economic progress at both
household and economy- wide levels depends on access to financial products and services.
Access to financial services is a fundamental driver of increased household income and
resilience in an increasingly shock-prone global economy (Stijn Honohan, and Rojas-
Suarez, 2009).
1.1.1 Financial Inclusion
According to Asli Demirguc-Kunt (2008) financial inclusion or broad access to financial
services is defined as an absence of price and non price barriers in the use of financial
services. In order for a country to attain full inclusion the following are of great
importance. Financial services should be accessible to all: this is often seen as the goal of
financial inclusion. Financial services provided should also be of quality: quality financial
inclusion includes the following traits: affordability, convenience, product-fit, safety,
dignity of treatment, and client protection. Financial inclusion involves provision of the
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full suite of basic financial services; this refers to group of core financial services that
includes basic credit, savings, insurance and payment services (Gardeva & Rhyne, 2011).
Financial exclusion has been defined it in the context of a larger issue of social exclusion
of certain groups of people from the mainstream of the society. Leyshon and Thrift (1995)
define financial exclusion as referring to those processes that serve to prevent certain social
groups and individuals from gaining access to the formal financial system. Carbo,
Gardener and Molyneux (2005) have defined financial exclusion as broadly the inability of
some societal groups to access the financial system. According to Conroy (2005), financial
exclusion is a process that prevents poor and disadvantaged social groups from gaining
access to the formal financial systems of their countries. According to Mohan (2006)
financial exclusion signifies the lack of access by certain segments of the society to
appropriate, low-cost, fair and safe financial products and services from mainstream
providers.
Millions of people across the developing world do not have access to banking services.
Faced with barriers related to cost, geography and education, these individuals have no
way of securely transferring funds, saving money, insurance or accessing credit (BASA,
2003).These four services serve different needs that each household encounters, and
ensuring access to this product range is an important goal of financial inclusion. Credit
allows households to use future income to manage current vulnerabilities or to capitalize
on investment opportunities. Savings provide a safe and value-retaining place where
households can store funds, allowing them to tap into "past income" as needed. Insurance
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protects against vulnerability to shocks (e.g. death, illness, or disability in the family).
Payments services allow people to carry out financial transactions without having to be
face-to-face
Access has many dimensions: services need to be available when desired, and products
need to be tailored to specific needs; the prices for these services need to be affordable,
including all non price costs, such as having to travel a long distance to a bank branch; and,
most important, it should also make business sense, translate into profits for the providers
of these services, and therefore be available on a continuous basis. Access is difficult to
measure. Usage is often used as a proxy, although it can underestimate the number of
households that have access because it fails to capture those who currently have access to a
financial service but are not using it (Demirguc-kunt, Levine and Ross 2009).
Notwithstanding the fact that achieving all-encompassing financial inclusion requires
access and availability to a whole gamut of financial services; in developing countries like
ours, access to a simple bank account, is to start with, the gateway to basic banking
services. The bank account as a product incorporates values such as security, convenience,
liquidity, confidentiality, and product appropriateness for their needs, friendly service and
potential access to loans. Thus, a savings bank account can play an important role in
helping poor /vulnerable people save safely and securely
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1.1.2 Economic Development
According to Sen, (1999) development involves reducing deprivation or broadening
choice. Deprivation represents a multidimensional view of poverty that includes hunger,
illiteracy, illness and poor health, powerlessness, voicelessness, insecurity, humiliation and
a lack of access to basic infrastructure (Narayan, Patel, Schafft, Rademacher,and S.K
Schulte 2000). Seers (1979) argues that the purpose of development is to reduce poverty,
inequality, and unemployment.
Sampson, (2012) defines economic development in terms of objectives. These are most
commonly described as the creation of jobs and wealth, and the improvement of quality of
life. Economic development can also be described as a process that influences growth and
restructuring of an economy to enhance the economic well being of a community. In the
broadest sense, economic development encompasses three major areas: Policies that
government undertakes to meet broad economic objectives including inflation control, high
employment and sustainable growth, Policies and programs to provide services including
building highways, managing parks and providing medical access to the disadvantaged and
finally policies and programs explicitly directed at improving the business climate through
specific efforts, business finance, marketing, neighborhood development, business
retention and expansion, technology transfer, real estate development and others. The main
goal of economic development is improving the economic well being of a community
through efforts that entail job creation, job retention, tax base enhancements and quality of
life.
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According to Sen, (1983) economic development generally refers to the sustained,
concerted actions of policymakers and communities that promote the standard of living
and economic health of a specific area. It can also be referred to as the quantitative and
qualitative changes in the economy. It includes development of human capital, critical
infrastructure, regional competitiveness, environmental sustainability, social inclusion,
health, safety, literacy, and other initiatives. Economic development is a policy
intervention endeavor with aims of economic and social well-being of people. The scope of
economic development includes the process and policies by which a nation improves the
economic, political, and social well-being of its people (O'Sullivan and Sheffrin, 2003).
Broadly speaking, economic development has been defined in different ways and as such it
is difficult to locate any single definition which may be regarded entirely satisfactory
1.1.3 Financial Inclusion and Economic Development
The Consultative Group to Assist the Poor, CGAP (2007), in their report estimated that 80
percent of people in least developed countries are un-banked. The term un-banked refers to
people who do not use simple banking services that the developed world and most people
in urban areas take for granted, such as remittances and savings. Barriers to conventional
methods of banking include lack of education, illiteracy, high fees, and proximity to
banking facilities. This lack of access to banking services hinders economic development.
It gives the poor no option other than the informal, cash economy, leaving them vulnerable
to risks and without a means to efficiently save or borrow money.
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Financial markets and institutions exist to mitigate effects of information asymmetries and
transaction cost that prevent the direct pooling and investment of society‘s savings.
Financial institutions help mobilize savings and provide payments services that facilitate
the exchange of goods and services. In addition, they produce and process information
about investors and investment projects to enable efficient allocation of funds. Lack of
efficient and developed financial institutions and markets leads to lower incomes and
standards of living of people leading to low economic development
When they work well, financial institutions and markets provide opportunities for all
market participants to take advantage of the best investments by channeling funds to their
most productive uses, hence boosting growth, improving income distribution, and reducing
poverty. Developing the financial sector and improving access to finance are likely not
only to accelerate economic growth, but also to reduce income inequality and poverty. The
term financial inclusion needs to be interpreted in a relative dimension depending on the
stage of economic development of a country For example, in a developed country
nonpayment of utility bills through banks may be considered as a case of financial
exclusion, however, the same may not (and need not) be considered as financial exclusion
in an underdeveloped nation as the financial system is not yet developed to provide
sophisticated services (Demirguc-kunt, Levine and Ross 2009).
Finance can contribute not just to income growth and poverty reduction, the most
important of the Millennium Development Goals (MDGs), but also to MDGs such as
improving education, gender equality, and health, with some goals more specifically
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affected. More investment and higher productivity translate not only into more income and
therefore better nutrition and health; it also enables parents to send their children to school
instead of merely regarding them as a source of labor. Access to finance creates equal
opportunities for everybody. Access to financial services helps women in determining their
own economic destiny and increases their confidence and ―say‖ in their households and
communities. More sophisticated financial markets discriminate less; they provide capital
to those with attractive investment opportunities, regardless of other characteristics—for
firms, size, ownership, and profitability do not matter; for households, current income,
wealth, education, gender, and ethnicity are irrelevant. Indeed, financial development can
reduce inequality as it broadens opportunities (Stijn, Honohan, and Rojas-Suarez (2009).
1.1.4 Financial Inclusion and Economic Development in Kenya
The access to financial services can be measured in the form of access to certain
institutions such as banks, cooperatives, non-banking finance companies, credit unions,
micro finance institutions, insurance companies or in terms of functions that institutions
perform or services they provide such as payment services, saving or loans and credit One
of the popular benchmarks employed to assess the degree of financial services to the
population of the country is the quantum of deposit accounts held as ratio to the adult
population. The primary barriers in expansion of financial services are identified as: Non-
availability of a bank branch within near distance for physical access, banks do not prefer
low income people as their clients, perceptions of financial services are found as
complicated, high charges and penalties attached to banking products and services which
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make them unaffordable, other factors include gender, age, legal entity, illiteracy, place of
living, physical and cultural barriers, type of occupation etc (Beck, Demirgüç-Kunt and
Peria 2010).
Low and moderate income households are especially in need of effective financial
products, services, and tools to manage and grow their money in a way that meets their
daily needs and allows for future investments. Yet, the financial services currently
available to the rural poor are often costly, unsafe, and inefficient. Money kept at home
may be subject to theft or temptation, as well as family demands, whereas moneylenders
and other intermediaries charge high fees and prohibitive interest rates. These constraints
are reflected in only 22.6% of adults having access to a formal bank account in Kenya
(Arnold, Beck, and Ellis, 2011).
Kenya has made impressive strides towards financial inclusion. The formally included
(defined as those using a bank, post bank or insurance product) went up from 18.9% in
2006 to 22.6% in 2009. The proportion of financially excluded decreased from 38.4% to
32.7%.Savings usage increased in all but the top wealth quintile between 2006 and 2009.
Most importantly, savings rates increased in the lowest wealth quintile, from 23% in 2006
to 29% in 2009.Bank usage increased in every single wealth quintile between 2006 and
2009. The number of bank branches in the county country grew by 12%. Gains have come
from the introduction of mobile money and the responding rollout of branchless agency
banking models by commercial banks. (Arnold,Beck, and Ellis, 2011).
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The Kenya Financial Sector Deepening programme (FSDK), was established in 2005 to
stimulate wealth creation and reduce poverty by expanding access to financial services for
lower income households and smaller scale enterprises. Competition is strong amongst a
diverse group of financial service providers that have moved deeper into the low-income
market over the last five years, in part thanks to FSDK interventions. Gains too have come
from the introduction of mobile money and the responding rollout of branchless agency
banking models by commercial banks competing for the mass market space. The Kenyan
government has also been instrumental in introducing appropriate regulations to facilitate
low-income banking and strengthen SACCOs and MFIs
The vital role of the financial system and technology is entrenched in the Kenya‘s
development blue print – Vision 2030, which aims at transforming the country into a
newly industrialized middle-income country that provides high quality of life to its
citizenry by the year 2030. Under Vision 2030‘s economic pillar, the financial services
sector and information, communication and technology are two of the six priority sectors
amongst Tourism, Agriculture and Livestock, Wholesale and Retail Trade, Manufacturing,
identified to address Kenya‘s economic challenges and grow GDP to 10% by the year
2012. The six priority sectors contribute the most to Kenya‘s GDP (57%) and create half of
formal sector jobs
1.2 Research Problem
There is a general consensus among economists that financial development spurs economic
growth. Nyasetia (2012) conducted regression analysis to establish the relationship
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between financial deepening and savings and investments in Kenya and found a strong
positive correlation between savings and investments. Theoretically, financial development
creates enabling conditions for growth. Empirical research supports the view that
development of the financial system contributes to economic growth (Rajan and Zingales,
2003). There has not been any research done on the relationship of financial inclusion and
economic development in Kenya. This is an obvious gap in literature
A developed financial system broadens access to funds; conversely. Arnold, Beck, Ellis
(2011) carried out a survey on the barriers to financial access in Kenya on the findings of
FinAccess 2009, they found out that investment in productive assets correlates with access
to formal financial services, rapid expansion of financial service market led to inclusion of
those most able to take up the services, usage of informal products and services rose
alongside formal usage and nation-wide increases in financial access did not necessarily
translate into greater equality of access. Based on this research, questions for further
research were raised into why the informal products and services rose alongside formal
usage and why nation-wide increases in financial access did not necessarily translate into
greater equality of access.
Empirical evidence consistently emphasizes the nexus between finance and growth, though
the issue of direction of causality is more difficult to determine. Beck, Demirguc-Kunt and
Peria (2010) assessed the stability, efficiency, and outreach of Kenya's banking system,
using aggregate, bank-level, and survey data. They found out that Banks' asset quality and
liquidity positions had improved over the recent years, making the economic system more
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resistant to shocks, and interest rate spreads had declined. Outreach remained limited, but
had improved in recent years, driven by mobile payments services in the domestic
remittance market. This study proposes also to close the knowledge gap on the relationship
of financial inclusion and economic development and to provide further evidence that
promoting financial inclusion as a policy will lead to economic development of the country
Recent research suggests that financial inclusion is an issue well beyond households living
on less than $2 a day instead, it shows how in many countries, the number of financially
excluded adults significantly exceeds the adult population living under the $2-a-day
poverty line.(Hannig and Jansen 2010). Does this mean there is not a clear correlation
between financial inclusion and economic development? This is the main research question
this study aim at answering by studying and analyzing the relationship between financial
inclusion and economic development in Kenya
There exist disconnect between evidence on the effects of national financial depth and the
effects of household financial penetration (Beck, Demirgüç-Kunt and Levine, 2005).This
study aims at closing the of research gap on how financial inclusion influences the
individual welfare in terms of the social and economic development.
1.3 Research Objectives
The objective of this study is to investigate the relationship between financial inclusion and
economic development in Kenya
1.4 Value of the Study
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Financial inclusion and its importance is a relatively new concept, its relationship to
economic development has been under research for only a decade. This study will go on to
add to the theory of financial inclusion as it gains preeminence as a vital aspect of
economic development of any country.
This study aims at examining the current status of financial inclusion in Kenya and
analyzing the relationship between its financial inclusion and economic development
which will aid policy makers in making policies that are more inclusive for economic
development. Policymakers in developing countries have an important role to play in
creating the conditions for improved access, and thereby unlocking the economic potential
of their populations. The potential for economic growth and poverty alleviation through the
development of a more inclusive financial services sector has been recognized by leaders
in developing and developed countries and is emerging as a priority issue on political
agendas (Chetty, 2013).
Researchers and students particularly those pursing postgraduate studies in Finance,
Economics and Accounting will find this study useful in their quest to understand financial
inclusion and economic development.
Consultants especially in the area of financial inclusion and economic development will
find this report useful in their quest to provide appropriate, feasible and informed advice to
both public and private sector organizations and players.
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CHAPTER: TWO:
LITERATURE REVIEW
2.1 Introduction
Well-functioning financial systems serve a vital purpose, offering savings, credit, payment,
and risk management products to people with a wide range of needs. Inclusive financial
systems—allowing broad access to financial services, are especially likely to benefit poor
people and other disadvantaged groups. Without inclusive financial systems, poor people
must rely on their own limited savings to invest in their education or become
entrepreneurs—and small enterprises must rely on their limited earnings to pursue
promising growth opportunities. This can contribute to persistent income inequality and
low economic development (Demirguc-Kunt & Levine 2009).
2.2 Theoretical Framework
A theoretical (or conceptual) definition gives the meaning of a word in terms of the
theories of a specific discipline. This type of definition assumes both knowledge and
acceptance of the theories that it depends on .To theoretically define is to create a
hypothetical construct
2.2.1 Classical Economics Theory
The earliest proponent of free market economy was first discussed in the Classical 1776
wealth of nations by Adam Smith. He advocated for the ―invincible hand‖ in the economic
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set-up where the economy was to be left to operate on its own where forces of supply and
demand interact to bring about an equilibrium state in the economy of a country.
According to Adam smith the classical economic theory is rooted in the concept of a
laissez- faire economic market. Laissez-faire also known as free-market requires little to no
government intervention. It also allows individuals to act according to their own self
interest regarding economic decisions. This ensures economic resources are allocated
according to the desires of individuals and businesses in the marketplace. Bagehot (1873),
in his classical Lombard street, where he emphasized the critical importance of the banking
system in economic growth and highlighted circumstance when banks could actively spur
innovation and future growth by identifying and funding productive investments.
Schumpeter (1912) is very explicit on this score: ―The banker, therefore, is not so much
primarily the middleman in the commodity ―purchasing power‖ as a producer of this
commodity. He argued that the services provided by financial intermediaries –Mobilizing
savings, evaluating projects ,managing risks, monitoring managers and facilitating
transactions are essential for technological innovation and economic development.
King, Levine (1993) presented cross-country evidence consistent with Schumpeter's view
that the financial system can promote economic growth, using data on 80 countries over
the 1960–1989 periods. He found out that various measures of the level of financial
development are strongly associated with real per capita GDP growth, the rate of physical
capital accumulation, and improvements in the efficiency with which economies employ
physical capital. Further, the predetermined component of financial development is
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robustly correlated with future rates of economic growth, physical capital accumulation,
and economic efficiency improvements.
2.2.2 Keynesian Economic Theory
Keynes (1930) in his treatise on money also argued for the importance of the banking
sector in economic growth. He suggested the bank credit ― is the pavement along which
production travels, and the bankers if they knew their duty, would provide the transport
facilities to just the extent that is required in order that the productive powers of the
community can be employed at their full capacity‖. In the same spirit Robinson (1952)
argued that financial development follows growth, and articulated this causality argument
by suggesting that ―where enterprise leads finance follows‖. Both, however, recognized
this as a function of current institutional structure, which is not necessarily given.
Keynesian economic relies on government spending to jumpstart a nation economic
growth during sluggish economic downturns. Similar to classical economists, Keynesians
believe the nation economy is made up of consumer spending, business investment and
government spending.
Keynesian economics often focuses on immediate results in economic theories. Policies
focus on the short-term needs and how economic policies can make instant corrections to a
nation‘s economy. During economic recessions and depressions, individuals and
businesses do not usually have the resources for creating immediate results through
consumer spending or business investment. The government is seen as the only force to
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end these downturns through monetary or fiscal policies providing in aggregate demand
and that will increase the level of output.
In the Keynesian theory, financial deepening or inclusion occurs due to an expansion in
government expenditure. In order to reach full employment; the government should inject
money into the economy by increasing government expenditure. The financial sectors in
developing countries are not only regulated, but heavily ―repressed,‖ if one uses the
terminology of McKinnon (1973) and Shaw (1973). Efficiency and equity lead to
government intervention in credit allocation in developing countries. Well functioning
financial institutions and markets provide opportunities for all to make investments by
channeling funds to their most productive uses, hence boosting growth, improving income
distribution, and reducing poverty. Developing the financial sector and improving access to
finance accelerate economic growth and reduce income inequality and poverty
2.2.3 Keynesian Theory II
Keynes (1936) later supported an alternative structure that included direct government
control of investment. Financial deepening occurs due to an expansion in government
expenditure. An increase in government expenditure increases aggregate demand and
income, thereby raising demand for money. This disequilibrium is resolved by reducing
private investments resulting from higher interest rates. Since higher interest rates lower
private investment, an increase in government expenditure promotes investments and
reduces private investment concurrently (Dornbusch and Fischer 1978).It is necessary to
design government policies that are attentive to the various imperfections and
18
inefficiencies of the markets. Financial Inclusion seeks to overcome the frictions that
hinder the functioning of the market mechanism to operate in favor of the poor and
underprivileged.
2.3 Review of Empirical Studies
Greenwood and Jovanovic (1990) developed a model that predicted a nonlinear
relationship between financial development, income inequality, and economic
development. At all the stages of economic development, financial development improved
capital allocation, boosted aggregate growth, and helped the poor through this channel.
However, the distributional effect of financial development, and hence the net impact on
the poor, depended on the level of economic development. At early stages of development,
only the rich can afford to access and directly profit from better financial markets. At
higher levels of economic development, many people access financial markets so that
financial development directly helps a larger proportion of society. He used the Gini
coefficient, which measured deviations from perfect income equality. He found out that
financial development reduces income inequality there is a negative relationship between
financial development and the growth rate of the Gini coefficient, which holds when
controlling for real per capita GDP growth
Rousseaua and Wachtelb (1996) conducted causality tests between financial development
and real GDP using recently developed time series techniques. Their results provided little
support to the view that finance is a leading sector in the process of economic
development. They found however, considerable evidence of bi-directionality and some
19
evidence of reverse causation. Their findings also clearly demonstrated that causality
patterns vary across countries and, therefore, highlighted the dangers of statistical
inference based on cross-section country studies which implicitly treat different economies
as homogeneous entities
Li, Xu, and Zou (2000) carried out a cross-country research on the impact of inflation on
income distribution and economic growth found out that inflation worsens income
distribution, increases the income share of the rich, has a negative but insignificant effect
on the income shares of the poor and the middle class and it reduces the rate of economic
growth
Guiso, Sapienza and Zingales (2002) used individual regions of Italy household dataset
and examined the effect of differences in local financial development on economic activity
across the different regions. They found that local financial development enhances the
probability that an individual starts a business, increases industrial competition, and
promotes growth of firms. And these results are stronger for smaller firms which cannot
easily raise funds outside of the local area
Clarke, Xu and Zou (2003) examined the relationship between finance and income
inequality for 83 countries between 1960 and 1995. Their results suggested that, in the
long run, inequality is less when financial development is greater also that inequality might
increase as financial sector development increases at very low levels of financial sector
development, as suggested by Greenwood and Jovanovic (1990), this result is not robust.
20
In their results they suggested that in addition to improving growth, financial development
also reduces inequality.
Beck, Demirguc-Kunt and Peria (2005) under the World Bank research initiative used
information from 193 banks in 58 countries; the researchers developed and analyzed
indicators of physical access, affordability, and eligibility barriers to deposit, loan, and
payment services. They found that substantial cross-country variation in barriers to
banking showed that in many countries these barriers could potentially exclude a
significant share of the population from using banking services. Correlations with bank-
and country-level variables showed that bank size and the availability of physical
infrastructure were the most robust predictors of barriers.
Thorsten, Demirguc-Kunt and Peria (2005) carried out research on various indicators of
banking sector penetration across 99 countries, based on a survey of bank regulatory
authorities, showed that greater outreach or penetration is correlated with standard
measures of financial development, as well as with economic activity. The researchers also
found out that better communication and transport infrastructure and better governance are
also associated with greater outreach. They also found out that firms in countries with
higher branch and ATM penetration and higher use of loan services report lower financing
obstacles, thus linking banking sector outreach to the alleviation of firms' financing
constraints.
Demirgüç-Kunt and Levine (2007) used cross –country data to show that financial
development disproportionately raised incomes of the poorest quartile, both by directly
21
reducing income inequality and more strongly through impacts on aggregate economic
growth. Countries with higher levels of financial development also experienced swifter
reductions in the share of the population living on less than $1 per day .Controlling for
other relevant variables; almost 30 percent of the variation across countries in rates of
poverty reduction could be attributed to cross-country variation in financial development
Bruhn and Love (2009) examined the effects of providing financial services to low-income
individuals on entrepreneurial activity, employment, and income. The analysis used cross-
time and cross-municipality variation in the opening of Banco Azteca in Mexico to
measure the effects with a difference-in-difference strategy. Banco Azteca opened more
than 800 branches simultaneously in 2002, focusing on low-income clients. The results
showed that the opening of Banco Azteca led to an increase in the number of informal
business owners by 7.6 percent.The research findings showed that expanding access to
finance to low-income individuals can have a positive effect on economic activity.
Morawczynski (2009) examined the adoption, usage and outcomes of mobile (MPESA) in
Kenya. His qualitative work by suggested that incomes of rural mobile money transfer
recipients had increased due to remittances, which had also led to higher savings by the
households. These results were based on an ethnographic study conducted in Kibera, a
slum in Kenya, in 2007.
Beck, Demirguc-Kunt and Peria (2010) collected and analyzed information from 209
banks in 62 countries and used it to develop indicators of barriers to banking services
around the world. They found out that barriers such as minimum account and loan
22
balances, account fees, and required documents were associated with lower levels of
banking outreach. While country characteristics linked with financial depth, such as the
effectiveness of creditor rights, contract enforcement mechanisms, and credit information
systems, were weakly correlated with barriers, strong associations were found between
barriers and measures of restrictions on bank activities and entry, bank disclosure practices
and media freedom, and development of physical infrastructure. Barriers were higher in
countries where there were more stringent restrictions on bank activities and entry, less
disclosure and media freedom, and poorly developed physical infrastructure. Also, barriers
for bank customers were higher where banking systems were predominantly government-
owned.
Ellis, Alberto and Juan-Pablo (2010) study showed that access to financial services enables
households to invest in activities that are likely to contribute to higher future income and,
therefore, to growth. People borrow and save for a range of investment purposes, even in
the poorest groups. Rural inhabitants save and borrow more for agricultural investments,
while urban inhabitants tend to save and borrow more for other purposes, such as starting a
business. Individuals with a better education are more likely to borrow, save and invest
than those with less education. Econometric analysis using data from the 2009 Kenya
FinAccess survey showed that people who borrow specifically to invest are 16 percentage
points more likely to use formal financial services than those who borrow for consumption
purposes, after taking other possible factors into account. Similarly, people who save to
invest are 10 percentage points more likely to use formal financial services than people
who save for consumption purposes. This suggests that formal financial services are more
23
suitable for investment purposes than other forms of provision. Individuals who cite supply
side barriers to accessing a bank account are 4 percentage points le than people who do
not. They are also 6-8 percentage points less likely to borrow for investment purposes,
which suggest that access to a bank account may play an important role in helping
individual‘s to access credit. These results represent the first concrete, quantitative
estimates of the negative impact of access barriers on household investment
Beck (2010) analyzed FinAcess 2009 data for the drivers and determinants of access to
finance across countries and at Kenya‘s the individual level and found out that the use of
formal financial services in Kenya is at similar levels as in other East African countries,
but below that of several countries in Southern Africa. However the share of population
that is completely excluded from any formal or informal financial service is lower in
Kenya than in any other country except for South Africa. The use of formal banking and
other formal financial services has increased significantly between 2006 and 2009, driven
by higher use of transaction services, especially M-PESA, and higher use of MFIs and
banks. While the use of formal banking and other formal financial services has increased
across all population groups, men are more likely to use to formal financial services than
women. Urban Kenyans are more likely to use formal financial services than rural
Kenyans; gains in use of formal financial services have been more prominent in urban than
in rural areas. While low income is still the most prominent barrier for the unbanked,
access-related barriers, especially documentation related barriers, have gained in
prominence compared to 2006. M-PESA has revolutionized the remittance market and has
expanded the access frontier. The challenge being to link unbanked M-PESA users to other
24
financial services. When comparing the predictive power of different factors; income,
education, age, geographic location and employment status are strong predictors of the use
of financial services, while gender, risk aversion and numeracy are not.
Chaia, Aparna, Tony, Maria and Robert (2010) under the Financial Access Initiative found
out that almost all of the 2.5 billion people in the world lacking access to financial services
reside in Africa, Asia, and Latin America and the majority (60%) of these adults resided in
East and South Asia. Based on the population breakdown by income level the researchers
found that out of a population of 1.2 billion adults using formal financial services, a third,
or 800 million people are in the lowest income category (i.e. living on under $5/day). The
researchers found that apart from socioeconomic and demographic factors, the main
drivers of inclusion were an effective regulatory and policy environment and enabling the
actions of financial service providers
Sarma and Pais (2010) examined the relationship between financial inclusion and
development by empirically identifying country specific factors that are associated with the
level of financial inclusion. They found that levels of human development and financial
inclusion in a country move closely with each other. Among socio-economic and
infrastructure related factors, income, inequality, literacy, urbanization and physical
infrastructure for connectivity and information were important. The health of the banking
sector did not seem to have an unambiguous effect on financial inclusion whereas
ownership pattern did seem to matter.
25
Mbiti and Weil (2011) found that the major use of M-PESA is for transfers and that there
is relatively little storage of value. At the same time, they also showed that a significant
number of survey respondents indicated that they use their M-PESA accounts as a vehicle
for saving. Mbiti and Weil also found evidence that M-PESA use decreases the use of
informal savings mechanisms and increases the probability of being banked
Nyasetia (2012) set out to establish the implications of financial deepening on savings and
investments in Kenya. He adopted a causal research design in investigating the relationship
between financial deepening and savings and investments in Kenya. He used secondary
data on financial deepening indicators, savings and investments from 2006-2011. He
conducted regression analysis to establish the relationship and found a strong positive
correlation between savings and investments. The study established that when there is
proper financial deepening, the level of savings and investments in Kenya also improve. If
interest rates are not favorable, if the stock market is not doing well, if deposits in banking
institutions are not growing, then there will be slow growth and improvement in savings
and investments.
Waihenya (2012) investigated the relationship between agent banking and financial
inclusion in Kenya. The study utilized descriptive survey research method. The study
investigated agent banking in Kenya with emphasis on the factors contributing to financial
exclusion, both natural barriers such as rough terrains and man-made barriers such as high
charges on financial services and limited access due to limited bank branches. The study
found out that agent banking is continuously improving and growing and as it grows, the
26
level of financial inclusion is also growing proportionately. The study findings showed that
increasing the area covered by agents within the country had the effect of increasing the
reach of the financial services to the people thus raising the levels of financial inclusion.
Ndege (2012) set out to establish the impact of financial sector deepening on economic
development in Kenya. He adopted a Quantitative comparative design. The target
population for this study was 44 banking institutions operating in Kenya as at 31st
December 2011.During the period of the study (2007-2011), financial sector deepening
was high as the commercial banks strived to leverage their operations through adoption of
new technologies. The depth of the financial sector was found to promote economic
growth by increasing economic efficiency, investment and growth.
Latortue and Ardic (2013) in their financial access 2012 report which was based on eight
years data (2004-2011) showed the global strands taken on financial inclusion. High
income countries had 10 times the deposit penetration as low income countries, and lower
middle income countries having three times the deposit penetration of low income
countries there was a steady growth on the number of commercial bank branches and
ATMs. Low-income countries had 3.2 ATMs and 3.8 branches per 100,000 adults in 2011,
while high-income countries had 123 ATMS and 34 branches per 100,000 adults. The
number of insurance policies more than doubled since 2004; life insurance being the
dominant service provided.
27
2.3.1 Access to Financial Services
Empirical evidence suggests that improved access to finance is not only pro-growth but
also pro-poor, reducing income inequality and poverty. Cross-country studies have shown
that countries with more developed formal financial systems record faster declines in
income inequality and poverty levels (Levine,2005)
Access to credit, savings and payment services provides opportunities for in income
through three channels: New economic opportunities: access to credit and information on
investments through the financial system allows poor people to invest in income-
generating activities. Manage risk: savings, insurance and credit allow poor people to
smooth their consumption, protect their assets and income against shocks and make lumpy
investments in housing, education and health. Facilitate exchange of goods and services:
payments services help poor people remit money, trade in goods and services and reduce
their transaction costs.
The poor access financial services from three types of financial service providers, Informal
providers: including family, friends and money lenders, Informal unregulated financial
service providers: such as Rotating Savings and Credit Associations (ROSCA) and credit
unions, Formal financial institutions: regulated by general laws but not specific banking
laws including microfinance institutions and Savings and Credit Co-operatives (SACCOs)
and Formal deposit taking institutions regulated by specific banking laws such as banks
and building societies
28
Increasing access to financial services through regulated providers is necessary to reduce
systemic risk and support financial sector deepening through the diversification of
financial instruments and financial institutions. However, there are a number of barriers to
the expansion of formal financial services including: Small-scale financial systems: the
total size of most formal financial systems in Africa is less than $1bn - equivalent to a
small bank in an industrialized country (Bossone, Honohan, and Long 2002). Small
financial systems are less competitive, less efficient, more costly to regulate than larger
financial systems. Physical access: typically, financial transactions by poor people are
high-frequency and low-volume emphasizing the importance of easily accessible services
in close proximity. Limited take-up: servicing costs, including fees and minimum account
requirements, can be prohibitive for poor clients while formal financial products are not
suited to the low and erratic incomes of the poor. Poor people may lack knowledge of
financial services or the skills to use them effectively. Information asymmetries: the poor
often lack official identification documents, records of their financial transactions and
collateral, which increases the risk of service provision
2.3.2 Mobile Financial Services in Kenya
Mobile banking has been the most effective driving factor towards greater financial
inclusion in Kenya. It is refers to the provision banking and financial services through
mobile technology and the scope of services offered may include facilities to conduct bank
and stock market transactions, as well as enabling users to access customized information.
Access and the cost of mainstream financial services act as a barrier to financial inclusion
29
for many in the developing world. The convergence of banking services with mobile
technologies means however that users are able to conduct banking services at any place
and at any time through mobile banking thus overcoming the challenges to the distribution
and use of banking services (Gu, Lee & Suh, 2009)
The available mobile banking options in Kenya are M-PESA launched in 2007 by
Safaricom. The name M-Pesa is derived from ―M‖ for mobile and ―Pesa‖ for money in
Swahili. This is the most popular and widely used with a market share of 80%. Others
include Airtel Money, Mobicash, Orange money, Yu-cash, Elma, Pesa-Pap and Pesa-
Connect (Central Bank of Kenya, 2010).
According to Williams and Torma, mobile transactions can simultaneously enhance the
outreach of financial services, reduce information asymmetries and provide relatively low
cost informational and transactional financial products. It therefore has the potential to
transform the access to finance for a significant number of people. It brings closer to reality
the aspiration to provide mass access to finance to all countries and income groups
(Williams & Torma, 2007, p 18).
Branches have been the traditional bank outlet. Hence geographic distance to the nearest
branch, or the density of branches relative to the population, can provide a first crude
indication of geographic access or lack of physical barriers to access (Beck, Demirgüç-
Kunt, and Martinez Peria 2007b). Mobile banking presents an opportunity for banks to
expand without necessary opening new branches. It offers a potential solution for the
30
millions of people living in the rural Kenya that have access to a cell phone, yet remain
excluded from the financial mainstream. (Ivatury,2006).
2.3.3 Determinants of Financial Inclusion
Several indicators have been used in the literature to assess the extent of financial
inclusion. Financial access can broadly be divided into two broad categories; one based on
the supply side information from the perspective of credit providers, such as banks and
other service providers. The other based on demand side information from the perspective
of users-individuals, households or firms. Some of the commonly used indicators for
measuring financial inclusion are: number of bank accounts (per 1000 adult population),
number of bank branches (per million people), number of ATMs (per million people),
amount of bank credit and amount of bank deposit. However, these indicators of financial
access provide only partial information on the inclusiveness of the financial system of an
economy and thus, in turn, fail to capture adequately the overall extent of financial
inclusion. Formally included households are considered those who use financial services
provided by banks or by other formal financial service providers
It is desirable to examine the determinants of financial inclusion so as to undertake
appropriate policy measures for bringing about a more inclusive society in terms of the
access to financial services. Several socio-economic factors simultaneously determine the
potentiality of borrowers of formal financial institutions. Broadly, the process of financial
inclusion is conditioned upon a numbers of factors: some are social, some are economic,
some are demographic and some are institutional.
31
Laha (2011) sort to identify the broad determinants of financial inclusion in some selected
districts of west Bengal, India. Empirical results using Bivariate Probit model showed that
asset level of the household, as determined by the operated land holding, significantly
enhances the probability of becoming a bank customers and the existence of information
asymmetry in financial services acts as an obstacle to the process of financial inclusion.
Kumar (2011) assessed the behavior and determinants of financial inclusion in India. The
study found that the factory proportion and employee base were considered as the
significant variables indicating that income and employment generating schemes lead the
public to be more active, aware, interested with regard to banking activities, which
contributes towards financial inclusion.
Singh & Kodan (2012) analyzed the relationship between financial inclusion and
development to identify factors associated with financial inclusion. With the help of
Regression he found that per capita NSDP and urbanization were significant explorers of
financial inclusion while the literacy, employment and sex-ratio were not statistically
significant explorers/predictors of the financial inclusion
Chithral and Selvam (2013) in their attempt to identify and analyze the determinants of
financial Inclusion carried out empirical analysis that revealed that socio-economic factors
like Income, Literacy and Population were found to have significant association with the
level of financial inclusion. Further, physical infrastructure for connectivity and
information were also significantly associated with financial inclusion. Among the banking
variables deposit and credit penetration were found significantly associated with financial
32
inclusion. Finally, Credit-deposit ratio and Investment ratio were not significantly
associated with financial inclusion.
2.4 Summary of Literature Review
Early financial deepening theories emphasized the need to increase savings in order to
stimulate investment and help emerging economies achieve catch-up growth, with poverty
reduction to follow. Evidence to support the effectiveness of this approach has been mixed.
It was quickly overtaken by the global microfinance movement, which promotes the
benefits of direct financial service provision to the poor. Many financial inclusion
promoters now agree that direct access to finance services can improve individual
livelihoods amongst the poor by enabling them to manage scarce resources more
efficiently, thereby smoothing consumption and protecting against economic shocks.
(Collins, Murdoch, Rutherford & Ruthven, 2009)
Financial inclusion is of great importance for economic development of a country.
However the arguments for financial inclusion and it relationship to economic
development both theoretical and empirical are relatively recent and fragile. Most of these
studies have been recent and cross county. Indeed, there is good reason to ask us questions
about the relationship between financial inclusion and economic development in particular
emphasis to Kenya. This study therefore seeks to fill the eminent knowledge gap on the
relationship of financial inclusion and economic development in Kenya
33
CHAPTER THREE:
RESEARCH METHODOLOGY
3.1 Introduction
Kothari (2004) defines research as an original contribution to the existing stock of
knowledge making for its development. The systematic approach concerning
generalizations and formulation of a theory is also research. As such the term ‗research‘
refers to the systematic method consisting of enunciating the problem, formulating a
hypothesis, collecting the data, analyzing the facts and reaching certain conclusions either
in the form of solutions(s) towards the concerned problem or in certain generation for
some theoretical formulation
3.2 Research Design
Kothari (2004) describes a research design as the conceptual structure within which the
research is conducted; it constitutes the blueprint for the collection, measurement and
analysis of data. It specifies the methods and procedures for collecting and analyzing the
needed information. In this proposal, I will comprehensively carry out a Meta –analysis
study. My proposal will effectively explore the descriptive technique. Descriptive research
describes characteristics of a population or phenomenon it portrays an accurate profile of
persons, events or situations (Shields, 2013)
34
Meta-analysis is a statistical technique to quantitatively synthesize the empirical evidence
of a field of research. It refers to methods focused on contrasting and combining results
from different studies, in the hope of identifying patterns among study results, sources of
disagreement among those results, or other interesting relationships that may come to light
in the context of multiple studies. (Greenland, O'Rourke 2008).In this proposal, I am seeking
to investigate and substantiate the relationship between financial inclusion and economic
development in Kenya. Meta-analysis has become an increasingly accepted research tool in
finance and economics phenomena, since it is proving to be useful for policy evaluation
(Stanley, 2001). In this context a Meta-analysis analysis approach is justified as the most
effective statistical technique to correlate both the dependent and independent study
variables in my proposal.
3.3 Data Collection
Data collection is gathering empirical evidence in order to gain new insights about a
situation and answer questions that prompt undertaking of the research (Kothari, 2004). In
my proposal I will be utilizing secondary data from International Monetary Fund and
Unites Nations Development Program (UNDP) for a period of 7 years from the year 2005
to 2011. Secondary data is data that has been collected, analyzed and made available from
sources other than you (White, 2010). Collecting and analyzing primary data can be
expensive and time consuming so the use of secondary data is important.
35
3.4 Data Analysis
Secondary data from various developmental and financial annual reports will be reviewed
for completeness and consistency in order before statistical analysis. According to
Mugenda (1999), data must be cleaned, coded and properly analyzed in order to obtain a
meaningful report. The secondary data will be analyzed using descriptive statistical
approach, regression, correlation analysis. The excel software will be used to transform
the variables into a format suitable for analysis after which the statistical package for social
sciences for data analysis (SPSS) will be used, which will provide various statistics when
applied to analyze the quantitative data in terms of graphs and tables whose results would
facilitate comparison. The unit of analysis will be the various annual developmental reports
and library analyzed over a period of 7 years from the year 2005 to 2011.
This study will adopt a multiple regression model
Y=f(x) (1)
Yi = β0 + βX1 + βX2 + βX3 + … + βXn + ε (2)
Where
Y= Dependent variable is (Development) The most widely used development index is the
Human Development Index (HDI) developed by United nations development program
encompassing various aspects of development.
36
X= Independent variable (Financial inclusion) whereby as measured by the various
indicators of financial inclusion ie measures of penetration, access and usage
X1= Number of bank accounts (per 1000 adult population),
X2= Number of bank branches (per 100,000 people),
X3= Amount of bank credit to amount of bank deposit as a percentage
β0= Constant term
β0= Gradient/Slope of the regression measuring the amount of the change in Y associated
with a unit change in X
ε= Error term within a confidence interval of 5%
3.4.1 Test of significance
2 tailed T-test will be performed to test the significance of the coefficients on the
hypothesis
H0 = There is no relationship between Financial inclusion and Economic development
indicators in Kenya
Ha = There is a relationship between Financial inclusion and Economic development
indicators in Kenya
37
CHAPTER FOUR
DATA ANALYSIS, RESULTS AND DISCUSSION
4.1 Introduction
This chapter discusses and presents the analysis and their interpretations. The analysis
results presented include descriptive statistics, correlation tests, multiple regression and
statistical test of significance
4.2 Descriptive Statistics
4.2.1 Human Development Index
The Human Development Index (HDI) is a composite measure of health, education and
income developed in 1990 by economists Mahbub ul Haq and Amartya Sen. It is an
alternative to purely economic assessment of national progress, such as GDP growth and
serves as a frame of reference for both social and economic development. It is prepared
yearly as an independent report commissioned by the United Nations Development
Programme. It is used to distinguish whether a country is developed, developing or
underdeveloped and also to measure the impact of economic policies on quality of life. The
Human Development Index (HDI) was chosen as the best representative measure of the
dependent variable economic development in Kenya. Data was collected from the HDI
reports for the period 2005 to 2011
38
Years
...2011201020092008200720062005
Hum
an D
evel
opm
ent i
ndex
.52
.51
.50
.49
.48
.47
.46
4.2 a: A graph showing the Human development index trend of Kenya
Kenya is considered is a developing country and its Human Developmental Index is above
the average of other Sub Saharan countries however below the average of the world‘s
human developmental index
Years
.201220112010200920082007200620052000
.8
.7
.6
.5
.4
.3
Kenya
Low HDI
Sub saharan Africa
w orld
4.2b: A graph showing the trend of Human Development Index for Kenya as compared to
other countries
39
4:2.2 Financial Inclusion
Financial inclusion is measured by various measures, the two most widely used measures
of accessibility the number of bank accounts (per 1000 adult population) and the number
of bank branches and ATMS (per 100,000 people). The proxy used for the usage
dimension of financial inclusion is the amount of bank credit and amount of bank deposit.
The data on the number of bank accounts (per 1000 adult population) and the number of
bank branches and ATMS (per 100,000 people) was collected as prepared by International
Monetary Fund and also Financial Access survey yearly reports on Kenya for the period
between 2005 and 2011. For each country its calculated based on the reported number of
depositors per 1000 adult population and the number of financial institutions branches and
ATMS 100,000 adult people.
Years
...2011201020092008200720062005
Num
ber o
f ban
k ac
coun
ts
700
600
500
400
300
200
100
0
4.2c: A graph showing the trend of the number of bank accounts (per 1000 adult
population) in Kenya
40
Years
...2011201020092008200720062005
Num
ber
of b
ank
bran
ches
5.5
5.0
4.5
4.0
3.5
3.0
2.5
2.0
4.3b: A graph showing the trend of the number of bank branches (per 100,000 people) in
Kenya
The amount of bank credit and amount of bank deposit refers to the financial resources
provided to the private sector by domestic money banks as a share of total deposits.
Domestic money banks comprise commercial banks and other financial institutions that
accept transferable deposits, such as demand deposits. Total deposits include demand, time
and saving deposits in deposit money banks. Data was collected from the electronic
version of the IMF‘s International Financial Statistics.
41
Years
...2011201020092008200720062005
Am
ou
nt
of
ba
nk c
red
it a
nd
de
po
sits
84
82
80
78
76
74
72
4.3c: A graph showing the trend of the amount of bank credit to amount of bank deposit as
a percentage in Kenya
4.4 Correlation Analysis
Correlation is a concept for investigating the relationship between two quantatiave
continuous variables. Correlation coefficient measures the strength of the association
between the two variables
The study sought to test the relationship between financial inclusion and economic
development using correlation analysis presented in the table below
42
4.4.1 Pearson Correlations
4.4a Pearson correlation of financial inclusion and HDI
Variables
Human
Developmen
t index
Number
of bank
accounts
Number of
bank
branches
Amount of
bank credit
and deposits
Human
Development index
Pearson Correlation 1 .952(**) .985(**) .461
Sig. (2-tailed) . .001 .000 .298
N 7 7 7 7
Number of bank
accounts
Pearson Correlation .952(**) 1 .950(**) .615
Sig. (2-tailed) .001 . .001 .141
N 7 7 7 7
Number of bank
branches
Pearson Correlation .985(**) .950(**) 1 .551
Sig. (2-tailed) .000 .001 . .199
N 7 7 7 7
Bank credit to bank
deposits (%)
Pearson Correlation .461 .615 .551 1
Sig. (2-tailed) .298 .141 .199 .
N 7 7 7 7
** Correlation is significant at the 0.01 level (2-tailed).
The Pearson correlation matrix highlights that there is a significant correlation between the
dependent variables (HDI) and independent variable Number of Bank branches and
Number of bank accounts at 0.985 and 0.952 respectively
43
4.4.2 Partial Correlation
4.4a Partial correlation FI and HDI
The Partial correlation matrix highlights that there is also a significant correlation between
the dependent variables (HDI) and independent variable Number of Bank branches and
Number of bank accounts.
4.5 Regression Analysis
Regression analysis is a statistical process for estimating the relationships among variables.
It includes many techniques for modeling and analyzing several variables, when the focus
is on the relationship between a dependent variable and one or more independent variables.
Our research objective is to determine the relationship between financial inclusion and
economic development, thus regression analysis is one of the best analytical models to
analyze this relationship
Variables
Partial correlation
(Pearsons r)
(Constant)
Number of bank accounts .669
Number of bank branches .918
Amount of bank credit to deposits (%) -.771
44
4.5.1 Regression Model
A multivariate regression model was used to determine the relative importance of each of
the three variables in respect to HDI
The Multiple regression model for the study was
Y=f(x) (1)
Yi = β0 + βX1 + βX2 + βX3 + … + βXn + ε (2)
Where
Y= Dependent variable is (Development)
X= Independent variable (Financial inclusion) whereby as measured by the various
indicators of financial inclusion ie measures of penetration, access and usage
X1= Number of bank accounts (per 1000 adult population),
X2= Number of bank branches (per 100,000 people),
X3= Amount of bank credit to amount of bank deposit as a percentage
β0= Constant term
β0= Gradient/Slope of the regression measuring the amount of the change in Y associated
with a unit change in X
45
ε= Error term within a confidence interval of 5%
4.5a: Regression analysis (Model summary)
Unstandardized
Coefficients t Sig.
Correlation
s
Collinearity
Statistics
B Std. Error Partial Tolerance VIF
(Constant) .500 .030 16.696 .000
Number of bank
accounts 2.478E-05 .000 1.560 .217 .669 .086 11.607
Number of bank
branches .012 .003 4.022 .028 .918 .097 10.361
Bank credit to
bank deposits
(%)
-.001 .000 -2.098 .127 -.771 .610 1.639
Dependent Variable: Human Development index
From table 3 we obtain the values for regression equation which can be presented as
follows:
Y= 0.5+ 0.00002478X1+ 0.012X2- 0.001X3+ ε β0=0.5 β1= 0.00002478 β2=
0.012 β3= -0.012
The regression equation clearly shows that the number of the number of bank accounts (per
1000 adult population) and the number of bank branches (per 100,000 people) have a
positive relationship with HDI. Therefore an increase number of the number of bank
accounts (per 1000 adult population) and the number of bank branches (per 100,000 people
will lead to increase in HDI by the proportion of the ratios β1(0.00002478) and β2(0.012).
46
Where else he amount of bank credit to amount of bank deposit (%) reveals a negative
relationship thus its increase will lead to decrease in HDI by the proportion of β3( -0.012).).
Regression Standardized Predicted Value
1.51.0.50.0-.5-1.0-1.5
Hu
ma
n D
eve
lop
me
nt
ind
ex
.52
.51
.50
.49
.48
.47
4.5 b: A scatter plot showing the relationship between the dependent and standardized
independent variables
4.5.2 Test of Coefficients’ Statistical Significance (T-test)
To test the significance of the coefficients a t-test was performed on the null hypothesis
that the coefficient/parameter is 0. Since this was a 2 tailed test, we compared each p value
to the preselected value of alpha which was 0.05(5%). Coefficients having p value less
than alpha are usually significant. In our analysis the statistically significant coefficients
47
are β0 and β2 which have p-values of .000 and .028 respectively, while β1(p-value=217)
and β3 (p-value=.127) are not significantly different from zero. This therefore means that
the coefficients are β0 and β2 can significantly explain the proportion that Y changes due
to change in X.
4.5.3 The Test of Prediction Ability of Independent Variables (R square)
To test the ability of the independent variables in determining the dependent variables the
measure of R square is used. A value above 0.5 of R-square means that the predictors are
able to explain a great proportion of variance in dependent variable. The value test of R-
square is shown in the table below:
4.5 c: R square measure
R R Square
Adjusted R
Square
Std. Error of the
Estimate
.995(a) .989 .979 .002329
a Predictors: (Constant), Amount of bank credit to bank deposits(%), Number of bank
branches, Number of bank accounts
b Dependent Variable: Human Development index
According to table 4 the R square which is 0.989 depicts that the independent variables
explains great proportion of the variance of independent variable. Therefore the
independent variables explain better the change in dependent variables. Since some of this
increase in R-square would be simply due to chance variation in that particular sample, the
48
adjusted R-square attempts to yield a more honest value to estimate the R-squared for the
population. From the above table a high value of adjusted R square (0.979) further shows
the suitability of the independent variables in predicting the dependent variable
4.5.4 Analysis of Variance (ANOVA)
ANOVA table shows results of analysis of variance, sum of squares, degrees of freedom
(df), mean squares, regression and residual values obtained from regression analysis. The
reliability of the independent variables in predicting the dependent variable is further
shown by the Analysis of Variance (ANOVA test) as illustrated in the table below:
4.5 d: Regression Analysis (ANOVA)
Sum of
Squares df Mean Square F Sig.
Regression .002 3 .001 92.625 .002(a)
Residual .000 3 .000
Total .002 6
a Predictors: (Constant), Amount of bank credit to deposits (%), Number of bank branches,
Number of bank accounts
b Dependent Variable: Human Development index
In this case the p value (0.002) is less than 0.05 (confidence level) and therefore we reject
the null hypothesis and conclude that there exists a significant relationship between the
independent and dependent variables and thus the independent variable reliably predicts
the dependent variable.
49
4.5.5 The Test for Collinearity
In multiple regression analysis we usually assume that the predictors entered into the
regression equation are not perfectly correlated with one another. Collinearity is therefore
the existence of bivariate correlations within the independent variables. To measure this
aspect the researcher used variance inflation factor (VIF) and tolerance. The variance
inflation factor (VIF) provides us with a measure of how much the variance for a given
regression coefficient is increased compared to if all predictors were uncorrelated. On the
other hand tolerance is the reciprocal of VIF. Perfect collinearity exists when tolerance of
one independent variable is 0.000, according to table 3 this scenario does not occur. Even
though there exists collinearity as evident by low values of tolerance of X1 and X2 it is not
perfect and therefore SPSS doesn‘t eliminate any of the three independent variables.
4.6 Summary
From the above correlation and regression analysis there is an apparent strong relationship
between the two major indicators of financial inclusion ie the number of bank accounts and
(per 1000 adult population) and the number of bank branches (per 100,000 people). The
amount of bank credit to amount of bank deposit (%) though not strongly related is also an
indicator of financial inclusion.
50
CHAPTER FIVE
SUMMARY OF FINDINGS, CONCLUSION AND RECOMMENDATIONS
5.1 Introduction
This chapter summarizes the findings, draws conclusions relevant to the research and
makes recommendations
5.2 Summary of Findings
From the Pearson correlation tests, the analysis showed that HDI is positively correlated
significantly with both the number of the number of bank accounts (per 1000 adult
population) and the number of bank branches (per 100,000 people) at 0.952 and 0.985 (r
<0.01) 2 tailed . The amount of bank credit to amount of bank deposit (%) though not
strongly related is also an indicator of financial inclusion. The partial correlation matrix
also highlighted the strong correlation of the number of bank accounts and (per 1000 adult
population) and the number of bank branches (per 100,000 people) at 0.699 and 0.918
(r<0.05). The amount of bank credit and amount of bank deposit though had a negative
with -0.771
The regression analysis also established that the number of bank accounts (per 1000 adult
population) and the number of bank branches (per 100,000 people) have a positive
relationship with HDI. Therefore an increase number of the number of bank accounts (per
1000 adult population) and the number of bank branches (per 100,000 people) will lead to
51
increase in HDI by the proportion of the ratios β1(0.00002478) and β2(0.012). Where else
he amount of bank credit to amount of bank deposit (%) reveals a negative relationship
thus its increase will lead to decrease in HDI by the proportion of β3( -0.012).
The test of coefficients‘ statistical significance revealed that the coefficients β0 and β2 can
significantly explain the proportion that HDI changes due to change in financial inclusion
indicators ie number of the number of bank accounts (per 1000 adult population) and the
number of bank branches (per 100,000 people) and the amount of bank credit to amount of
bank deposit.
From the adjusted R square measure, the analysis revealed that the independent variables
chosen were suitable for predicting the dependent variable at an R square of (0.979).
From the ANOVA tables we the p value was at (0.002) and is less than 0.05 (confidence
level) and therefore we rejected the null hypothesis and concluded that there exists a
significant relationship between the independent and dependent variables and the
independent variable reliably predicts the dependent variable. Ie there is a relationship
between financial inclusion and economic development indicators in Kenya
In multiple regression analysis we usually assume that the predictors entered into the
regression equation are not perfectly correlated with one another. Collinearity is therefore
the existence of bivariate correlations within the independent variables. Perfect collinearity
exists when tolerance of one independent variable is 0.000, according to table 4.5a this
scenario does not occur. Even though there exists collinearity as evident by low values of
52
tolerance of the number of the number of bank accounts (per 1000 adult population) and
the number of bank branches (per 100,000 people) it is not perfect and therefore SPSS
doesn‘t eliminate any of the three independent variables.
5.3 Conclusion
Financial inclusion is an important aspect of development. Access to finance enhances the
ability of people to engage in economical activities that lead to development. The study has
reinforced this hypothesis and we can conclude that by increasing financial access we can
increase economic development in Kenya. Regression and correlation analysis established
that the number of the number of bank accounts (per 1000 adult population) and the
number of bank branches (per 100,000 people) have a positive relationship with HDI at
0.952 and 0.985 (r <0.01) 2 tailed and thus by increasing this two financial access
indicators we can increase economic development in Kenya
The amount of bank credit to amount of bank deposit (%) had a negative with -0.771 this
could be due to the fact as a measure of the second dimension of financial inclusion usage,
usage is beyond the basic adoption of banking services, usage focuses more on the
permanence and depth of financial service and product use. Hence determining usage
requires more details about the regularity, frequency, and duration of use over time. To
measure usage, it is critical that information reflect the user‘s point of view, that is, data
gathered through a demand-side survey rather than the supply side as collected from the
financial institutions
53
Along with various poverty eradication and employment generation programmes be the
government focus should also be on the financial inclusion policies as a means of
ameliorating poverty this can be viewed from the use of the human development index
which is a composite measure of health, education and income as opposed to GDP. The
analysis showed that by increasing financial inclusion you also increase human
development index which is a measure of for both social and economic development.
5.4 Recommendations
The relevance of financial inclusion in economic development cannot be over emphasized.
The study examined the relationship between financial inclusion and economic
development. Financial inclusion plays a vital role in development and it is important that
the government recognizes the vital role played by financial inclusion and develops
policies to encourage financial inclusion.
The government can also through its role in regulation create a regulatory framework that
encourages financial inclusion, this it has already done by allowing mobile telecoms to
operate money transfer system without having to comply to central bank banking
regulations. More of such efforts should be encouraged to allow more people to access
financial services. In Sweden and France, banks are legally bound to open an account for
anybody who approaches them
Data collection is vital for measuring the most effective financial inclusion initiatives and
their effects as well as helping to shape financial inclusion policy of the government, I
54
would recommend that more data is collected on the various indicators of financial
inclusion as well as disaggregated data on the regions and counties to allow effective
measures and policies to be adopted to encourage financial inclusion
Innovative technological financial inclusion has proved to be the most effective measure of
financial inclusion initiative in Kenya, these initiatives should be encouraged and
expanded to offer more value added financial services to the recipients to enhance
availability of the full set of financial services which lead to full financial inclusion.
Financial inclusion involves the delivery of banking services at an affordable cost to the
vast sections of disadvantaged and low income groups. Currently one of the major
hindrances to expansion of financial services to the poor rural areas is the cost involved in
financial institutions setting up branches in the rural areas. Incentives should be availed to
banks and other financial institutions to increase their rural area branch network through
the county government or central bank. Growing theoretical and empirical evidence as outlined
above suggest that financial systems that serve low-income people promote economic
development
The banking sector can also be encouraged to adopt banking initiatives that are aimed at
increasing the number of people who hold bank accounts. Countries like India through
their ―No frills‖, Germany with ―Everyman‖ and South Africa with their ―Mzansi‖
accounts have increased the population of people with ban accounts.
55
5.5 Limitations of the Study
Although this study contributes to the body of literature on various dimensions, the results
are not conclusive, the extent to which findings can be generalized beyond the sample
period and country studied is unclear.
The study period covered a period of 7 years due to the unavailability of data for the period
before 2005 .It would therefore be desirable to extend the present study by complementing
it with other studies using other statistical methods and including comparative data. The
inclusion of other financial inclusion determinants would also improve the reliability of the
conclusions arrived at.
Correlations and regression are bivariate and multivariate in nature meaning that two or
three variables from different data sets are compared at a time. However, this is not
realistic because there are almost always multiple relationships and effects on something.
The definition of financial indicators has traditionally been shaped by previously
formulated policy objectives. On other occasions, as is in this study some indicators may
introduce distortions i.e. the negative correlation of financial inclusion to the amount of
bank credit and bank deposits, as discussed earlier the use of this measure as a proxy for
the dimension of usage in financial inclusion did not reflect the user‘s point of view, the
data used should have been from the demand side surveys.
Two important dimensions of financial inclusion have not been analyzed in this research
due to the serious methodological challenges in the survey design required, this are quality:
56
the relevance of the financial service or product to the lifestyle needs of the consumer and Impact:
measure of changes in the lives of consumers that can be attributed to the usage of a financial
device or service.
5.6 Suggestions of Further Research
The use of disaggregated analysis is suggested as the next frontier for research and analysis
in this subject matter. It would be interesting to analyze a similar study but disaggregated
for the various regions or counties in Kenya to determine access and look for means to
improve it.
Financial inclusion can be determined by various indicators, reliable and comprehensive data
that captures the various dimensions of financial inclusion is critical for evidence-based
policymaking. I would suggest research to be carried out on the other financial inclusion
variables such as available choices of financial service providers and the consumers
understanding of these choices to enable the government make better financial inclusion
policies.
Measuring and monitoring levels of financial inclusion, deepening our understanding about
factors that correlate with financial inclusion and, subsequently, the impact of policies is
very important. It is also important to translate the concept of financial inclusion into
operational terms to allow tracking progress and measuring outcomes of policy reforms.
Research should be carried out on levels and factors of financial inclusion as well as how
to translate financial inclusion into operational terms.
57
There are two other dimension of financial inclusion apart from access and usage as
discussed and analyzed above this are quality: the relevance of the financial service or
product to the lifestyle needs of the consumer and Impact: measure of changes in the lives
of consumers that can be attributed to the usage of a financial device or service. Further
research should be carried out in these two dimensions of financial inclusion and their
relationship to economic development with an aim of formulating more effective financial
inclusion policies.
Despite the considerable progress made by microfinance institutions, credit unions, and
savings cooperatives over the last two decades, the majority of the world‘s poor remain
unserved by formal financial intermediaries that can safely manage cash and intermediate
between net savers and net borrowers. Microfinance institutions, credit unions, and savings
cooperatives were viewed as effective measures to enhance financial inclusion as
advocated by their founders, their effectiveness needs to researched on as the policy
makers and other stakeholders seek new initiatives for financial inclusion.
Cross county studies on access of financial services should be carried out as well as on
effectiveness of various financial inclusion measures to allow various countries share the
benefits of the proven successful measures in increasing financial inclusion in their
individual countries
58
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.
APPENDIX I
HUMAN DEVELOPMENT INDEX - KENYA
Year Kenya Low human
development Sub-Saharan
Africa World
2012 0.519 0.466 0.475 0.694
2011 0.515 0.464 0.472 0.692
2010 0.511 0.461 0.468 0.690
2009 0.505 0.455 0.463 0.685
2008 0.495 0.448 0.456 0.683
2007 0.491 0.442 0.449 0.678
2006 0.480 0.432 0.440 0.672
2005 0.472 0.424 0.432 0.666
2000 0.447 0.385 0.405 0.639
1995 n.a. n.a. 0.397 0.618
1990 0.463 0.350 0.387 0.600
1985 n.a. n.a. 0.378 0.578
1980 0.424 0.315 0.366 0.561
66
APPENDIX II
Variable Indicator name Short definition Long definition Coverage Source
X1 Bank accounts per 1,000 adults
Number of depositors with commercial banks per 1,000 adults. The data is from commercial banks-bank survey. (International Monetary Fund, Financial Access Survey)
For each country calculated as: (reported number of depositors)*1,000/adult population in the reporting country. (International Monetary Fund, Financial Access Survey)
2001-2011
International Monetary Fund, Financial Access Survey
X2 Bank branches per 100,000 adults
Number of commercial bank branches per 100,000 adults. The data is from commercial banks-bank survey.(International Monetary Fund, Financial Access Survey)
For each country calculated as:(number of institutions + number of branches)*100,000/adult population in the reporting country. (International Monetary Fund, Financial Access Survey)
2001-2011
International Monetary Fund, Financial Access Survey
X3 Bank credit to bank deposits (%)
The financial resources provided to the private sector by domestic money banks as a share of total deposits. Domestic money banks comprise commercial banks and other financial institutions that accept transferable deposits, such as demand deposits. Total deposits include demand, time and saving deposits in deposit money banks. (International Monetary Fund, International Financial Statistics)
Raw data are from the electronic version of the IMF’s International Financial Statistics. Private credit by deposit money banks (IFS line 22d); bank deposits (IFS lines 24 and 25). (International Monetary Fund, International Financial Statistics)
1960-2011
International Financial Statistics (IFS) - International Monetary Fund (IMF)
67
APPENDIX II Region :Sub-Saharan Africa
Income Group: Low-income economies
Country Year GFDD.AI.01 GFDD.AI.02 GFDD.SI.04
Burundi 2005 14.43 1.52 83.88
Burundi 2006 15.71 1.63 77.74
Burundi 2007 16.30 1.73 76.10
Burundi 2008 16.67 1.76 66.85
Burundi 2009 19.17 1.91 74.28
Burundi 2010 26.75 2.13 79.17
Burundi 2011 31.32 2.40 100.71
Central African Republic 2005 7.77 0.30 125.67
Central African Republic 2006 8.26 0.29 121.89
Central African Republic 2007 17.95 0.49 92.29
Central African Republic 2008 24.25 0.52 96.37
Central African Republic 2009 30.81 0.74 77.91
Central African Republic 2010 43.71 0.84 102.62
Central African Republic 2011 46.67 0.88 101.68
Chad 2005 5.89 0.38 94.21
Chad 2006 7.07 0.37 53.15
Chad 2007 8.11 0.37 62.40
Chad 2008 9.43 0.50 76.62
Chad 2009 15.42 0.57 85.36
Chad 2010 18.95 0.64 80.21
Chad 2011 21.26 0.72 82.50
Comoros 2005 58.55 0.53 58.47
Comoros 2006 50.03 0.52 47.78
Comoros 2007 43.79 1.02 50.76
Comoros 2008 47.18 1.00 52.58
Comoros 2009 60.27 1.22 65.08
Comoros 2010 74.25 1.42 69.74
Comoros 2011 69.18
Congo, Dem. Rep. 2005 0.77 0.45 44.51
Congo, Dem. Rep. 2006 1.50 0.44 48.79
Congo, Dem. Rep. 2007 2.86 0.47 46.56
Congo, Dem. Rep. 2008 4.76 0.46 67.14
Congo, Dem. Rep. 2009 11.66 0.48 58.95
Congo, Dem. Rep. 2010 11.79 0.59 53.05
Congo, Dem. Rep. 2011 16.19 0.66 50.78
Eritrea 2005 24.30
Eritrea 2006 24.00
Eritrea
2007
18.9
68
Country Year
GFDD.AI.01 GFDD.AI.02 GFDD.SI.04
Eritrea 2008 18.46
Eritrea 2009 16.53
Eritrea 2010 14.80
Eritrea 2011 15.20
Ethiopia 2005 0.91 54.51
Ethiopia 2006 65.98 0.94 60.94
Ethiopia 2007 74.39 1.08 59.28
Ethiopia 2008 77.46 1.19 65.62
Ethiopia 2009 90.27 1.32
Ethiopia 2010 102.84 1.37
Ethiopia 2011 114.76 1.97
Gambia, The 2005 4.23 35.76
Gambia, The 2006 4.92 37.78
Gambia, The 2007 5.79 38.93
Gambia, The 2008 6.94 39.16
Gambia, The 2009 7.25 37.65
Gambia, The 2010 8.88 37.36
Gambia, The 2011 8.88 36.90
Guinea 2005 39.62
Guinea 2006 30.26
Guinea 2007 37.46
Guinea 2008 1.03 29.16
Guinea 2009 1.19 26.92
Guinea 2010 1.30 24.28
Guinea 2011 1.46 38.49
Kenya 2005 115.34 2.61 76.41
Kenya 2006 139.93 2.71 74.69
Kenya 2007 217.25 3.54 72.60
Kenya 2008 287.98 4.12 78.21
Kenya 2009 370.79 4.43 75.79
Kenya 2010 549.32 4.74 75.27
Kenya 2011 651.51 5.17 82.62
Liberia 2005 46.37
Liberia 2006 0.85 49.59
Liberia 2007 1.12 52.56
Liberia 2008 1.64 50.29
Liberia 2009 2.91 51.17
Liberia 2010 3.59 51.70
Liberia 2011 3.81 51.65
Madagascar 2005 17.49 1.18 69.61
Madagascar 2006 19.18 1.25 64.27
Madagascar 2007 21.58 1.35 61.95
69
Country Year GFDD.AI.01 GFDD.AI.02 GFDD.SI.04
Madagascar 2009 32.50 1.48 66.66
Madagascar 2010 42.71 1.55 68.71
Madagascar 2011 44.30 1.43 62.70
Malawi 2005 41.62
Malawi 2006 58.55
Malawi 2007 52.07
Malawi 2008 59.58
Malawi 2009 64.86
Malawi 2010 72.04
Malawi 2011 191.46 1.09 64.15
Mali 2005 97.24
Mali 2006 101.70
Mali 2007 93.02
Mali 2008 98.61
Mali 2009 88.18
Mali 2010 86.52
Mali 2011 98.12
Mozambique 2005 1.99 49.95
Mozambique 2006 2.03 53.84
Mozambique 2007 2.36 50.05
Mozambique 2008 2.50 62.06
Mozambique 2009 2.87 70.18
Mozambique 2010 3.30 72.34
Mozambique 2011 3.63 70.22
Niger 2005 88.11
Niger 2006 103.91
Niger 2007 86.93
Niger 2008 105.61
Niger 2009 109.94
Niger 2010 102.63
Niger 2011 119.36
Rwanda 2005 8.59 0.75 77.39
Rwanda 2006 10.30 0.72
Rwanda 2007 23.34 1.05
Rwanda 2008 185.08 4.49
Rwanda 2009 212.61 4.81
Rwanda 2010 262.10 4.81
Rwanda 2011 171.46 5.50
Sierra Leone 2005 1.29 32.61
Sierra Leone 2006 60.65 1.45 32.02
Sierra Leone 2007 63.23 1.73 35.21
70
Country Year GFDD.AI.01 GFDD.AI.02 GFDD.SI.04
Sierra Leone 2010 183.52 2.81 47.76
Sierra Leone 2011 153.54 2.96 46.97
Tanzania 2005 1.21 45.99
Tanzania 2006 1.26 52.79
Tanzania 2007 1.52 59.71
Tanzania 2008 1.69 64.82
Tanzania 2009 1.82 58.77
Tanzania 2010 1.84 56.80
Tanzania 2011 1.95 61.50
Togo 2005 59.26 1.58 78.43
Togo 2006 64.88 1.94 69.56
Togo 2007 73.83 2.45 79.17
Togo 2008 190.39 4.21 61.30
Togo 2009 203.62 4.18 62.94
Togo 2010 68.28
Togo 2011 81.02
Uganda 2005 96.33 1.15 56.87
Uganda 2006 110.86 1.16 66.25
Uganda 2007 108.10 1.35 62.92
Uganda 2008 149.82 1.99 74.53
Uganda 2009 167.86 2.31 72.75
Uganda 2010 186.15 2.41 71.51
Uganda 2011 2.43 83.81