assessing m-shwari and cane-farmers' households in muhoroni, kenya

ASSESSING THE EFFECTS OF M-SHWARI ON FINANCIAL INCLUSION AMONG

SUGARCANE OUT - GROWERS’ HOUSEHOLDS IN MUHORONI SUB-COUNTY,

KENYA

OKUMU LAWI OLELA

A Project Report Submitted to the Graduate School in partial fulfilment for the

Requirements of the Conferment of Master of Business Administration Degree in

Financial Accounting of Laikipia University

March, 2016

ii

Declaration and Recommendation

Declaration:

This Project Report is my original work and has not been presented before for an award or

conferment of a certificate or degree in any University or College.

LAWI OLELA OKUMU

MB24/2072/13

Signature: . Date: .

Recommendation:

This Project Report has been submitted for examination with our recommendation as University

supervisors.

DR. PAUL MUOKI NZIOKI

SCHOOL OF BUSINESS

LAIKIPIA UNIVERSITY


DR. FREDRICK NDEDE

SCHOOL OF BUSINESS

KENYATTA UNIVERSITY


iii

Dedication

I dedicate this Project Report to the School of Business, the entire Laikipia University and

Almighty God.

iv

Acknowledgements

Many individuals have contributed to the success of this work. First I wish to sincerely thank The

Director of Post Graduate Studies Prof. Francis Aswani, The Dean School of Business Dr. Isaac

Odongo Ochieng all of Laikipia University, My Supervisors Dr. Paul Muoki Nzioki and Dr.

Fredrick William Ndede for their guidance, support and advice from the inception to the

conclusion of this work. Lastly warm regards to all my colleagues and relations for their

constructive criticism and company throughout this process.

v

Abstract

Muhoroni Sub-county is in a geographically remote part of western Kenya; the resident households

are among cane out-growers in western Kenya of who up to 82.6% direly depend on extension

credit facility from public or private extension credit providers. After the financial crisis of the

90’s, mainstream Banks and extension capital moved their focus and products beyond the cane

Out-growers’ households, putting six million Kenyans dependent directly or indirectly on cane at

risk of financial exclusion. With the advent of M-Shwari did the cane farmer find an access to a

means to fund this gap? The general objective of the study was to assess the effects of M-Shwari

on financial inclusion among cane out-growers’ households in Muhoroni Sub-County, Kenya. The

study was guided by the following theories; financial intermediation theory, financial growth

theory, and modern growth theory. These theories play a central role in influencing key decisions

regarding human and physical capital accumulation and occupational choices. In theories stressing

entrepreneurship, financial imperfections determine the extent to which talented but poor

individuals can raise external funds to initiate projects. The study used descriptive survey design

to characterize certain groups and make predictions. The targeted population was 5,000 cane out-

growers’ households. The researcher used Stratified proportionate random sampling technique that

allowed construction of error estimates. Primary data was collected by administration of

predetermined structured questionnaires on a sample of 370 respondents. Secondary data

collection was guided by Electronic codebooks that greatly facilitated the review relevant

literature; Pearson Product-Moment Correlation Coefficient (r) was determined at 0.98 on the pre-

test sample of 37 respondents, appropriate for the pilot study to measure reliability. For accuracy,

uniformity, consistency, and completeness Statistical Package for Social Sciences Version 21, a

computer program aided in the data analysis and presentation. Descriptive statistics and data

relationships; Independent t-tests, tables, and simple analysis of variance (ANOVA) were

calculated to summarize data. The results revealed that M-shwari enabled up to 56.6% increased

formal access among the cane out-growers’ households in Muhoroni Sub-County, meaning that

the M-Shwari has addressed supply-side constraints of limited access to credit. Independent t-tests

showed that access to transactions, suitability of the product and procedural formalities were

statistically significant predictors of the outcome, financial inclusion, whereas the fourth variable

was not statistically significant predictors of the outcome. The study concluded that M-Shwari as

a personal source of savings should stress more on terms and conditions and loan product quality

so that saving on an individual basis is promoted with a view to increase the preference associated

with the present form of the product among cane Out-growers’ households in Muhoroni sub-

county. The study recommends financial inclusion reach as earmarked in policies should be

assessed to trace leakages in fiscal and monetary policy implementation.

vi

Table of Contents

Declaration and Recommendation .................................................................................................. ii

Dedication ...................................................................................................................................... iii

Acknowledgements ........................................................................................................................ iv

Abstract ........................................................................................................................................... v

List of Tables ................................................................................................................................. ix

List of Figures ................................................................................................................................ xi

Acronyms and Abbreviations ....................................................................................................... xii

CHAPTER ONE: INTRODUCTION ............................................................................................. 1

1.1 Background of the Study ...................................................................................................... 1

1.1.1 Financial Sector Regulation and Stability.......................................................................... 2

1.1.2 The Credit Market in Kenya .............................................................................................. 5

1.1.2.1 M-Shwari versus Formal Financial Access..................................................................... 5

1.1.3 Contextual background ...................................................................................................... 7

1.1.3.1 Cane Out-Growers in Western Kenya. ........................................................................... 7

1.1.3.2 Muhoroni Sub-County .................................................................................................... 8

1.2 The Statement of the Problem............................................................................................... 9

1.3 Objectives of the Study ......................................................................................................... 9

1.3.1The General Objective ........................................................................................................ 9

1.3.2 Specific Objectives ............................................................................................................ 9

1.4 Research Questions ............................................................................................................. 10

1.5 Scope of the Study .............................................................................................................. 10

1.6 Significance of the Study .................................................................................................... 10

1.7 Operational Definition of Terms ......................................................................................... 11

CHAPTER TWO: LITERATURE REVIEW ............................................................................... 12

vii

2.1 Theoretical Review ............................................................................................................. 12

2.1.1 Financial Intermediation Theory...................................................................................... 12

2.1.2 Finance Growth Theory ................................................................................................... 12

2.1.3 Modern development theory ............................................................................................ 13

2.2 Empirical Literature Review ............................................................................................... 13

2.2.1 Access to Transactions ..................................................................................................... 13

2.2.2: Product Suitability .......................................................................................................... 15

2.2.3: Procedural Formalities .................................................................................................... 16

2.4 Review of Knowledge Gap ................................................................................................. 18

2.5 Conceptual Framework ....................................................................................................... 19

CHAPTER THREE: RESEARCH METHODOLOGY ............................................................... 20

3.1 Research Design.................................................................................................................. 20

3.2 Target Population ................................................................................................................ 20

3.3 Sampling Procedures and Sample Size ............................................................................... 20

3.3.1 Sampling Procedures ....................................................................................................... 20

3.3.2 Sample Size ...................................................................................................................... 21

3.4 Data Collection Procedure .................................................................................................. 21

3.5 Validity and Reliability ....................................................................................................... 22

3.6 Data Analysis and Presentation .......................................................................................... 22

3.6.1 Conceptual Model ............................................................................................................ 23

3.6.2 Analytical Model ............................................................................................................. 23

CHAPTER FOUR: RESULTS AND DISCUSSIONS ................................................................. 25

4.1 Muhoroni Cane Out-growers’ Households and Increased Financial Access ...................... 25

4.1.1 Demography and Financial Inclusion .............................................................................. 26

4.1.2 Households' Profile .......................................................................................................... 27

viii

4.2.1 Socio-Economic Factors .................................................................................................. 29

4.3 Assessing the Effects of M-Shwari on Financial Inclusion ................................................ 32

4.3.1 Access to Transactions and financial inclusion ............................................................... 32

4.3.2 Suitability of Product and Financial Inclusion................................................................. 34

4.3.3 Procedural Formalities and Financial Inclusion .............................................................. 35

4.3.4 Moderating variables ....................................................................................................... 36

4.4 Multiple Regression in SPSS .............................................................................................. 36

4.4.1 Model fitting in regression analyses ................................................................................ 37

4.4.2 Model Summary............................................................................................................... 37

4.5 Discussion ........................................................................................................................... 38

CHAPTER FIVE: CONCLUSIONS AND RECOMMENDATIONS ......................................... 40

5.1 Conclusion .......................................................................................................................... 40

5.2 Recommendation ................................................................................................................ 40

5.4 Suggested Areas for Further Study ..................................................................................... 41

WORK PLAN ............................................................................................................................... 42

BUDGET ...................................................................................................................................... 43

REFERENCES ............................................................................................................................ 44

APPENDICES .............................................................................................................................. 49

APPENDIX: I ............................................................................................................................... 49

APPENDIX: I I:Transmittal Letter ............................................................................................... 52

APPENDIX: III: Questionnaire .................................................................................................... 53

APPENDIX: IV:SPSS Output ...................................................................................................... 55

ix

List of Tables

TABLE 4.1: RESIDENTIAL WARDS (PERCENTAGE) .................................................................................................................... 27

TABLE 4.1.2: PARENTAL STATUS OF HOUSEHOLD HEADS (PERCENTAGE) .................................................................................... 28

TABLE 4.1.3: FAMILY SIZE OF OUT-GROWERS HOUSEHOLDS (PERCENTAGE) ............................................................................... 28

TABLE 4.1.4: AGE OF HOUSEHOLD HEADS (PERCENTAGE)........................................................................................................ 29

TABLE 4.2.4: ANNUAL ACREAGES CANE (PERCENTAGE) ........................................................................................................... 31

TABLE 4.3.1: ACCESS TO TRANSACTIONS .............................................................................................................................. 33

TABLE 4.3.2: SUITABILITY OF M-SHWARI .............................................................................................................................. 34

TABLE 4.3.3: PROCEDURAL FORMALITIES EVALUATION ............................................................................................................ 35

TABLE 4.3.4: MODERATING VARIABLES ................................................................................................................................ 36

TABLE 4.4.1: COEFFICIENTS FROM SPSS OUTPUT ................................................................................................................... 37

TABLE 4.4.2: MEANS AND STANDARD DEVIATIONS OF USAGE AND PRODUCT INDICATORS ............................................................. 38

TABLE 1: WORK PLAN ....................................................................................................................................................... 42

TABLE 2: BUDGET ............................................................................................................................................................. 43

TABLE 3: SAMPLE SIZE SELECTION ......................................................................................................................................... 49

TABLE 4: PEARSON PRODUCT-MOMENT CORRELATION COEFFICIENT (R) ..................................................................................... 50

TABLE 5: TARGET POPULATION’S DISTRIBUTION ...................................................................................................................... 50

TABLE.6: STRATA PROPORTIONAL SAMPLING ......................................................................................................................... 51

TABLE 7: ACCESS TO M-SHWARI TRANSACTIONS .................................................................................................................... 54

TABLE 8: SUITABILITY OF M-SHWARI .................................................................................................................................... 54

TABLE 9: M-SHWARI PROCEDURAL FORMALITIES .................................................................................................................... 54

TABLE A-1: COEFFICIENTS .................................................................................................................................................. 55

xi

List of Figures

FIGURE 2.5 CONCEPTUAL FRAMEWORK ................................................................................................................................ 19

FIGURE: 4.1 PERCENTAGE PIE CHART ON INCLUSION ............................................................................................................... 26

FIGURE: 4.1.2 CHART ON INCREASED FORMAL ACCESS ACROSS WARDS...................................................................................... 27

FIGURE: 4.1.3 GROSS INCOME (ANNUAL CANE TURNOVER) ...................................................................................................... 31

FIGURE 3.3.1: PROPORTIONAL ALLOCATION FORMULA ............................................................................................................ 51

xii

Acronyms and Abbreviations

ASCAs

CGAP

CBA

CBK

KCB

KDIC

SMEs

MFBs

MFI

M‐PESA

M‐SHWARI

Accumulation Savings and Credit

Associations

Consultative Group to Assist the Poor

Commercial Bank of Africa

The Central Bank of Kenya

Kenya Commercial Bank

Kenya Deposit Insurance Corporation

Small and Medium Size Enterprises

Microfinance Banks

Microfinance Institution

A money transferring system developed by

SafariCom and Vodafone

A paperless banking product for M-PESA

subscribers, and provided by the Commercial

Bank of Africa in conjunction with

SafariCom

1

CHAPTER ONE: INTRODUCTION

1.1 Background of the Study

Agricultural production needs to increase by 70 percent by 2050 in order to feed the world,

however demographic growth, climate change, and urbanization put pressure on available

cultivable land, Parada and Gretabull, (2014). Around the world agriculture remains a major

building block in the pursuit of the Millennium Development Goals (MDGs), Kalunda, (2014). In

Kenya, agriculture is a very important part of the economic sector and is the best opportunity for

economic growth and poverty alleviation, (Kalunda, 2014). Agriculture is practiced by both large

and small scale farmers; most of who have little education and limited exposure to modern

financial instruments, furthermore, many of these small scale farmers have little or no experience

in financial management, and therefore, this brings new attention to the issue of banking sector

outreach in the agricultural sector on small scale rural farmers, (Kalunda, 2014).

Financial Management involves accounting, financial reporting, budgeting, collecting accounts

receivable, risk management, and insurance for a business, (Wanyungu, 2001). Financial

management and bank products and services knowledge can be acquired through effective and

efficient information flow, (Kalunda, 2014). Information is an economic resource, and

“information poverty” is increasingly being recognized as one of the prime causes of

underdevelopment; Mburu, Njuki and Kariuki, (2012). Information is important as households

whose access to information is either limited or very costly, may fail to allocate their resources

efficiently or bear unnecessarily high levels of risk foregoing income-enhancing opportunities,

(Mburu et al., 2012).

Financial inclusion or banking sector outreach is the process of availing a range of required

financial services, at a fair price, at the right place, form and time, through formal means and

without any form of discrimination to the populace, (Parada et al., 2014). Financing small holder

farming is one of the major concerns of Kenya’s development efforts. Smallholders are resource

poor and operate below their potentials; Nyikal, (2000): (Kalunda, 2014). Access to financial

services by small scale farmers has a potential to make a difference in agricultural productivity,

food security and poverty reduction. However a sustainable tailor made and accessible rural

agricultural financial system remains a major development challenge in Kenya, (Kalunda, 2014).

2

Many credit programs have performed dismally due to lack of access to banking transactions,

financially unsuitable products and cumbersome procedural formalities, (Kalunda, 2014).

Furthermore financial inclusion reach as earmarked in policies should be assessed, Yojana, (2016).

In India budget tracking and social audits on public expenditure as a monitor of the fund flow

process has been conducted since the 1990s by government agencies and civil society, (Yojana,

2016).The PMJDY intends to provide a platform for Direct Benefits Transfer (DBT) which will

help plug leakages in subsidies and thereby provide savings to the exchequer, (PMJDY, 2016).

The Prime Minister's People Money Scheme "Pradhan Mantri Jan Dhan Yojana," is the latest

National Mission for Financial Inclusion in India, (PMJDY, 2016). PMJDY is the world’s biggest

financial inclusion initiative with 18,096,130 bank accounts opened in the week 23rd to 29th

August 2014, (PMJDY, 2016).

In August 2005, India Opened of No-Frills Accounts, relaxed Know Your Customer (KYC), to

overcome language barrier and simplified Savings Bank Account Opening Form, permitted banks

to engage business facilitation and correspondence as intermediaries to provide doorstep financial

and banking services, (Chakma, 2014). In December 2009, opened branches in rural centers,

simplified branch authorizations and undertook, Electronic Bank Transfer, and Financial

Education (Chakma, 2014).

Financial exclusion and poverty levels are high in Sub-Sahara Africa especially in rural than urban

areas, (M’Amanja, 2015). The costs that are segmented informal markets, risk factor, and greater

access to informal than formal financial services, (M’Amanja, 2015). Access and distance to

financial markets; lack of traditional collateral; stringent requirements for opening and maintaining

accounts; high transaction costs and lack of appropriate products; improper risk assessment criteria

and information asymmetry constitute barriers to entry, (M’Amanja, 2015).

1.1.1 Financial Sector Regulation and Stability

Internationally the Government and The Reserve Bank of India have together undertaken general

and special measures in order to promote financial inclusion for economic growth to increase the

banking penetration in India, Chakma, (2014). Furthermore India previously undertook the

3

following initiatives to expand financial inclusion; it created State Bank of India in 1955,

nationalized commercial banks in 1969 and 1980, initiated the Lead Bank Scheme in 1970,

Priority sector lending norms subject to reporting branch licensing without taking permission from

the Reserve Bank in each case, , National Bank for Agriculture and Rural Development was set up

in 1982 mainly to provide refinance to the banks extending credit to agriculture, and the

establishment of regional rural banks in 1975, Raman, (2012); (Chakma, 2014).

Licensing of financial institutions in Kenya is done by the cabinet secretary of finance through the

central bank of Kenya. The companies Act, the Banking Act and the Central Bank of Kenya,

govern the banking industry, Republic of Kenya, (2014). Ideally financial reforms and free market

should spur the adoption of innovations that improve efficiency and provide a healthy balance

between lending and deposit rates, (The Central Bank of Kenya, 2014).

Kenya has experienced banking problems since 1986 culminating in major bank failures (37 failed

banks as at 1998) following the crises of; 1986 - 1989, 1993/1994 and 1998,(Kalunda, 2014). In

the late 1990’s, most mainstream commercial banks closed down some rural branches in order to

cut costs and improve profits, Kibaara, (2006). The non-traditional financial institutions have

emerged to fill the gap created by the mainstream banks which locked out low income and irregular

earners, (Kibaara, 2006).As at 2012, only around 6 million people (less than 20%) had access to

financial institutions. With the launch of products such as M-Shwari, the number of people with

access to financial institutions is expected to increase significantly, (CBK, 2014).

The Kenyan parliament reviewed the banking act 2009 to enable the central bank of Kenya to

license banking agents, CBK, (2014). Agency banking was introduced in May 2010 after the CBK

publicized prudential guidelines on agent banking and by January 2011, banks had already started

using agency banking. Agency banking allows banks to use various outlets like mobile Telco

agents and other CBK approved business to act as bank agents in an effort to expand financial

access to low income households on fair and equitable terms, CBK, (2014). Both customers and

non-customers can still transact even without having to go to where bank‘s branches are. By March

2013, agency banking transactions cumulatively stood at $ 3 Billion, as at that time, there were 11

commercial banks which had contracted over 18,082 agents, (CBK, 2014).

4

These changes have implications for monetary policy formulation and implementation, and

impacts monetary policy transmission mechanism and the information content of indicators

(Central Bank of Kenya, 2014). The number of deposit accounts (million) and net loans and

advances (Ksh billion) have increased with introduction of mobile money transfers, number of

transactions and value traded has increased over time. Improved access to financial services has

led to reduction in currency outside the banking sector, (Central Bank of Kenya, 2014).

The pronounced decline in the velocity of money in Kenya since 2010 compared with previous

years has enhanced implementation of Monetary Policy (i.e. money is mostly ‘inside money’

which can support improvement in the transmission mechanism of monetary policy) primarily

because unstable velocity of money implies unstable demand for money function over time which

can inhibit effectiveness of monetary policy, (CBK, 2014).This has allowed; the market and

regulators to partner and achieve sustainable outcomes, generated appropriate products for the

various market segments and kept the market vibrant resulting in increased financial inclusion,

(CBK, 2014).

Market monetary policy only works with a proportionally large financially included population,

(M’Amanja, 2015). Financial inclusion for the poor will solve the poverty problem sustainably,

build strong institutions to support the markets and foster financial system stability, and build

capacity for future growth through finance, long-term and targeted finance, (M’Amanja, 2015).

Promotion of financial inclusion and development ensures capital accumulation for the poor to

escape poverty, encourages access, which increases the number of participants (reducing the unit

cost of financial services hence more financial inclusion therefore increased financial deepening)

which is expected to improve welfare, enhance efficiency as well as the evolution of monetary

policy, (Central Bank of Kenya, 2014).

5

1.1.2 The Credit Market in Kenya

In the Kenyan credit market each single lender, with respect to loan characteristics, offers different

types of product, Afande, (2015). According to Afande, (2015); firstly, the formal financial

institutions don’t have diversified loan portfolios catering for the different financial needs of

SMEs. Secondly there is no room to expand the capacity of informal credit sources to enable them

to increase their potential to lend to SMEs. The typical agricultural portfolio in the range of Kenyan

financial institutions is around 2 percent and no institution in Kenya has really perfected lending

to normal agriculture per se and most of their loans go to school fees, business development and

building houses or commercial premises, (Kalunda, 2014)

In the formal sector, (Afande, 2015), terms and conditions focus on concerns with default risk and

high transaction costs. In the informal sector, failure to seek loans is due to the failure by the

different lenders to offer the credit package required by specific borrower categories. However

informal credit sources provide easier access to their credit facilities for small and micro

enterprises, (Afande, 2015). This is because informal lenders have their own insurance

mechanisms, which guarantee loan repayment, yet they lack adequate financial resources to enable

them to expand their coverage particularly deposit insurance schemes available in the formal

sector, (Afande, 2015).

The reliance upon informal financial services draws low income households further into a cycle of

poverty, Matoke, (2012). This is mainly because informal financial service providers charge high

fees that make it more difficult for the low income households to save and plan financially for the

future (Matoke, 2012). Currently despite the wide and established branch network of commercial

banks in Kenya, their lending terms and conditions don’t favour significantly out-growers’

accessibility to credit and would not consider extending credit to individual farmers unless they

went through cooperative societies that kept financial records, (Afande, 2015).

1.1.2.1 M-Shwari versus Formal Financial Access

The CBK has licensed three credit reference bureaus to date allowing changes in the collateral

technology so as to reduce cost of doing business by building information capital, (Central Bank

of Kenya, 2014). This has reduced information search costs together with problems associated

6

with information asymmetry and facilitated extending credit based on financial identity, (Central

Bank of Kenya, 2014).

M-Shwari launched in November 2012, is a paperless banking product for M-PESA subscribers,

provided by the Commercial Bank of Africa, Cook and McKay, (2015). CBA is one of East

Africa’s largest privately owned banks, together with SafariCom each bring comparative strengths

to the offering, and they both share in the revenue generated, (Cook et al., 2015). SafariCom brings

its broad reach to the 68 percent of the population using M-PESA, provides access to both its know

your customer (KYC) data and customer airtime/M-PESA usage history to enable CBA’s account

opening and credit scoring, markets the product through above-the-line advertising and

promotions, and has incorporated the M-Shwari menu in the M-PESA SIM toolkit, (Cook et al.,

2015).

CBA issues the savings accounts and loans and leverages its banking assets: a dedicated

management information system, regulatory compliance, and data analytics, reporting to the credit

bureau and leverage’s its capital to fund the loan portfolio, (Cook et al., 2015). Critically, CBA

carries the risk and absorbs losses from nonperforming loans (NPLs), (Cook et al., 2015). M-

Shwari is branded as a product run by CBA for SafariCom M-PESA customers’ M-Shwari Savings

account is a bank account subject to full bank regulations, including being subject to the Kenya

Deposit Insurance Corporation (KDIC), (Cook et al., 2015). The M-Shwari accounts sit on CBA’s

financial statement and are tracked in a dedicated banking system linked to SafariCom’s data and

to the bank’s core banking system, (Cook et al., 2015). All M-Shwari transactions are free to the

customer.

However, any transactions on the client’s M-PESA mobile money account, including person-to-

person transfers, transfers to other banks, and cashing out, are subject to M-PESA’s standard fees,

(Cook et al., 2015).As in all bank accounts in Kenya, an M-Shwari account is subject to regulation

requiring banks to verify the identity of the customer according to KYC principles, (Cook et al.,

2015). However, in the case of M-Shwari, CBA does this digitally using the existing KYC details

from the customer registration of the phone number (SIM) and M-PESA account, which requires

7

physical presentation of an ID, (Cook et al., 2015). So, for the majority of customers, opening this

bank account (for many, the first in their lives) takes less than a minute, (Cook et al., 2015).

M-Shwari’s procedural formality uses the existing identification verification considered compliant

for a small-value (level 0) account by CBA and enables the customer to keep up to KES 100,000

in his or her M-Shwari account, (Cook et al., 2015). If a customer’s identification details can be

confirmed by cross-referencing with the Integrated Population Registration System (IPRS)

managed by the government (all national IDs are registered in this system covering the majority

of the population, and 96 percent of M-Shwari accounts have been identified through this system),

(Cook et al., 2015).

M-Shwari account are especially suitable for low-income Kenyans whom are extremely active

money managers, constantly balancing the need for short-term liquidity by ensuring their limited

funds are “working” and providing a return for the future, (Cook et al., 2015). In this context, M-

Shwari accounts may help customers keep some funds liquid for emergencies or short-term needs,

(Cook et al., 2015). However the agreement with SafariCom restricts transfers between M-Shwari

accounts or with other bank accounts so that all funds move in and out of the account via M-PESA,

(Cook et al., 2015).

Customers also appreciate the extra degree of separation from M-PESA in that this money is less

visible and requires an extra step to access, (Cook et al., 2015). They feel that this keeps the money

safer from potential thieves or prying family members and provides extra discipline for them, since

the main appeal of M-Shwari savings is that it accomplishes several objectives at once; short-term

savings while the single biggest reason customers deposit into M-Shwari is to increase their loan

limit, (Cook et al., 2015).

1.1.3 Contextual background

1.1.3.1 Cane Out-Growers in Western Kenya.

The establishment of five cane out-grower schemes under contract farming between 1968 and

1981 in Western Kenya represented a major turning point in the regional economy, Casaburiy,

Kremer, and Mullainathan, (2012). According to Milu and Jayne,(2006), extension agencies such

8

as Muhoroni Sugarcane Out-growers Company and Chemelil Out-growers Company operate and

supports up to 82.6% of Out-growers by supplying credit facility either from public or private

extension providers.

These facilities also motivate customers to buy more products in future, (Milu et al., 2006).

However with; population growth, land scarcity, partial inheritance and the persistence of mono-

cropping declining yields has become eminent, (Casaburiy, et al., 2012). The decline in cane

production per given unit area implies an increase in poverty for approximately 6 million people

(about 20% of Kenya’s population) who depend on sugarcane farming either directly or indirectly,

Kenya Sugar Board, (2011). Contracted cane farmers supply 90% of the total sugar cane to the

Kenyan sugar factories, Dindi, (2013). The majority of these are small-scale out-growers, whilst

the remaining is supplied by factories Nucleus Estates. Therefore contracted cane farmers are an

important entity in sugarcane production, (Casaburiy et al, 2012).

Furthermore, (Casaburiy et al., 2012), in 1996, the buyer out-growing scheme included about

65,000 smallholder farmers. However at any point in time an account is held by one or more

contracting farmers, (Casaburiy et al., 2012). Firstly, because contracting farmers recorded on a

given account can vary over time across members of the same household or inheritance episodes.

Second, land rental markets are quite developed in the area. Following a formal rental agreement,

the tenant can then replace the landlord on the contract, (Casaburiy et al., 2012), each account is

typically matched to one (sub) parcel as defined by the Kenyan land registry. Different accounts

can share the same parcel in cases where a parcel gets split into two parts, for instance between

two brothers or between a landlord and a tenant, (Casaburiy et al., 2012).

1.1.3.2 Muhoroni Sub-County

The Muhoroni Sub-County has its headquarters is Chemelil ward, which is one of the four

administrative wards, the other wards are Fort Tenan, Koru, and Muhoroni, Osieko, (2013). The

Sub-County has favourable moderate climatic conditions, with temperatures averaging 27o C and

receives bimodal rainfall ranging from (560 -1630) mm per annum, (Casaburiy et al, 2012).

Muhoroni Sub-County comprises of the main topographical land formations namely, the Nandi

hills, the Nyando plateau and Kano plains which are sandwiched between two hills. The Kano

9

plains comprise predominantly black cotton clay soils derived from igneous rocks. The Sub-

County’s altitude ranges from 1000-1860 in meters above sea level, (Casaburiy et al., 2012).The

population of the cane out-growers Households in Muhoroni Sub-county is approximately 5000

Contracted cane farmers, (Osieko, 2013).

1.2 The Statement of the Problem

Muhoroni Sub-county is in a geographically remote part of western Kenya; the resident households

are among cane out-growers in western Kenya of who up to 82.6% direly depend on extension

credit facility from public or private extension credit providers. After the financial crisis of the

90’s, mainstream Banks and extension capital moved their focus and products beyond the cane

Out-growers’ households, putting six million Kenyans dependent directly or indirectly on cane at

risk of financial exclusion. With the advent of M-Swhari has the cane farmer found access to a

means to fund this gap?

1.3 Objectives of the Study

1.3.1The General Objective

The general objective of this Study will be to assess the effects of M-Shwari on financial inclusion

amongst households in Muhoroni Sub-County, Kenya. The following specific objectives will

guide the study;

1.3.2 Specific Objectives

The specific objectives this study will be;

i. To assess the extent to which M-Shwari transactions affect financial inclusion amongst

cane out-growers households in Muhoroni sub-county, Kenya.

ii. To assess the effect of suitability of M-Shwari on financial inclusion amongst cane out-

growers households in Muhoroni Sub-County, Kenya.

iii. To assess the effects of procedural formality of M-Shwari on financial inclusion

amongst cane out-growers households in Muhoroni sub-county, Kenya.

iv. To assess the moderating effects of poverty level, cane income, fiscal and monetary

mix on financial inclusion amongst cane out-growers households in Muhoroni Sub-

County, Kenya.

10

1.4 Research Questions

The study ought to answer the following research questions;

i. Has M-Shwari transactions increased formal access among cane Out-growers’ households

in Muhoroni sub-county?

ii. Has M-Shwari been sufficiently suitable to increasing formal access among cane out-

growers’ households in Muhoroni Sub-County?

iii. Have procedural formalities of M-Shwari enabled increased formal access amongst cane

out-growers’ households in Muhoroni Sub-County?

iv. Has poverty levels, farm income and fiscal monetary mix affected increased formal access

among cane Out-growers’ households in Muhoroni sub-county?

1.5 Scope of the Study

The study restricted its focus on cane out-growers within one geographical area, Muhoroni sub-

county in Kenya because of its unique segmented credit market. The study formulated a conceptual

model guided by financial intermediation, financial growth, and modern development theories.

The control variables encompassed three independent variables; M-Shwari transactions, suitability

of M-Shwari, and M-Shwari procedural formalities Moderated by poverty and government policy.

What are their possible patterns of influence on each other and the dependent variable?

1.6 Significance of the Study

Given the importance of the financial services particularly in the rural set up, the findings of this

study will be significant to various groups. Firstly, the cane out-growers’ households in Muhoroni

will get insight on how to go about increased formal credit. Secondly, the government will direct

monetary and fiscal policies aimed at enhancing financial inclusion largely in the rural areas.

Financial institutions will also be able to use the findings to undertake expansion by establishing

similar or better products than M-shwari to reach a wider population. Further research will also be

aided by the findings so that a more holistic understanding of the issues pertaining to coordination

of product development, implementation and practice can be established. The study will in addition

assist the regulators in their desire to create and facilitate favourable credit and investment policies

for cane out-growers’ households.

11

1.7 Operational Definition of Terms

Cane Contract farming:

Cane Out-growers’ Households:

Financial Inclusion:

M-Shwari transactions:

Procedural formality:

Suitability of product:

Poverty level:

Agreement between cane farmers and cane

buyers under forward agreements, frequently

at pre-determined prices for the production

and supply of cane.

Cane out-growers with a shared residence.

Percentage H/HS who have accessed an M-

Shwari account.

Percentage H/HS finding M-shwari

transactions accessible

Percentage H/HS finding M-shwari

procedures, terms and conditions preferable

Percentage H/HS finding M-shwari a

preferable product

Lower quartile income level of H/H in the

sub-county

12

CHAPTER TWO: LITERATURE REVIEW

2.1 Theoretical Review

2.1.1 Financial Intermediation Theory

Fama, (1980), developed the financial intermediation theory based on premise that Banks are

financial intermediaries that issue deposits and use the proceeds to purchase securities. When

banking is competitive, these portfolio management activities in principle fall under the

Modigliani-Miller theorem on the irrelevance of pure financing decisions. It follows that there is

no need to control the deposit creation or security purchasing activities of banks to obtain a stable

general equilibrium with respect to prices and real activity. In practice, however, banks are forcibly

involved in the process by which a pure nominal commodity or unit of account is made to play the

role of numeraire in a monetary system.

The study was guided by this theory; in assessing the suitability of such a nominal commodity and

whether by hedging appropriately such intermediary have created products that are particularly

valuable to some intermediaries' customers.

2.1.2 Finance Growth Theory

King, (1993), developed a finance growth theory on the premises that financial systems evaluate

prospective entrepreneurs, mobilize savings to finance the most promising productivity-enhancing

activities, diversify the risks associated with these innovative activities, and reveal the expected

profits from engaging in innovation rather than the production of existing goods using existing

methods. Better financial systems improve the probability of successful innovation and thereby

accelerate economic growth. Similarly, financial sector distortions reduce the rate of economic

growth by reducing the rate of innovation.

The study was guided by this theory; in assessing whether access to safe, easy and affordable

finance is a pre-condition for enabling economically and socially excluded people to integrate

better into the economy and protects themselves against economic shocks.

13

2.1.3 Modern development theory

Merton, (1977), developed the modern development theory on the observation that it was common

to include as part of the financial package a guarantee of the loan by a third party, in the

arrangement of a loan the theory states that “The issuing of a guarantee imposes a liability or cost

on the guarantor.”

The study was be guided by this theory; in assessing whether provision of basic services through

more efficient product to those who are completely excluded is a means to improve access and the

importance of effects on financial development.

2.2 Empirical Literature Review

2.2.1 Access to Transactions

According to a study by Mol, (2014), on extent of financial inclusion among rural households in

Kerala, India. The major findings of the study were; that 99% of the rural households in terms of

access to bank accounts are included in formal financial systems, while 76% of rural households

accessed saving accounts for children’s’ education, uncertainty related to health, households’

needs and investing in business. 24% of respondents didn’t save regularly because of lack of

money and awareness of services. Out of the total respondents 30% did not have access to formal

credit due to collateral security and guarantee problem.

Income and savings habit of rural Kerala households are related, wealth leads to increase in the

savings habit of the rural households. Most of the respondents’ access to formal credit indicated

that low income households are dependents on formal financial system for credit. This is reflected

by the financial inclusion index indicating Kerala is highly on formal financial system on various

aspects of financial inclusion such as banking penetration, availability of banking services and

usage of the banking system.

The study in terms of access to credit revealed that most of the rural households are included in

formal financial system, however to induce the saving habit among rural households and to extend

credit through an awareness programme. The study recommended financial institutions should

change and extend a helping hand with regard to financial aspect and existing policy changes given

14

that the services at the door by the banks influences the rural households borrowing from the formal

sector.

Data collection was by both secondary and primary data. Data presentation and analysis was by

tables and chi-square test at 5% significance level. The study collected secondary data from

published articles, journals, reports, books and websites. Primary data was collected from the rural

households by interview guide in Malappuram district. The study differs from the current study as

the objectives focused on; the extent to which rural households access saving and credit facility,

and identifies the reason for not saving as well as not borrowing, and finally if a relationship exist

between income and saving and credit. The current study will focus on a specific product control

factors for financial inclusion in Muhoroni sub-county.

Matoke, (2012) assessed the extent to which agent banking enabled the low income communities

of Kibera slums to access cash deposit and withdrawal services, credit and saving banking facilities

through agent banking. The key findings from this research were; Agent banking has had a

significant impact in including the low income households in the financial mainstream: There was

no significant effect of agent banking on the savings of the low income households; Mere opening

of a bank account does not have an automatic effect on the access to micro-credit among the low

income households: Access to bank deposits and withdrawals for low income households was not

sufficient to positively impact the finances of the low income households.

The study adopted descriptive research using questionnaire containing both closed ended and open

ended questions. The statistical package for social sciences and Excel was used to facilitate

analysis of the data. Unlike the current study the objectives were; to assess the extent to which

agent banking has enabled the residents of Kibera slums to access cash deposit and withdrawal

services, to establish if agent banking has enabled the residents of Kibera access saving facilities

with the banks, to establish if agent banking has played a role in enabling the residents of Kibera

access micro-credit.

15

2.2.2: Product Suitability

A study by Afande, (2015), examined the factors that affect accessibility to credit services by small

scale sugarcane farmers in Bungoma County. Whereas this study focused on responses from the

management of the commercial banks that extend credit to small-scale sugar cane farmers in

Bungoma County, the study did not allow for the exploration of the informal lenders’ perspectives

and but the current study will focus on the cane out-growers themselves whom access to formal

credit has been cumbersome.

A field survey was conducted in which primary data were collected using a structured

questionnaire. A total of 10 Credit managers from the various commercial banks in Bungoma

County that extend credit to Small-scale sugar cane farmers were interviewed. Data was analyzed

by use of descriptive statistics such as percentages, mean scores and standard deviations. Statistical

Package for Social Sciences (SPSS) was used as an aid in the analysis since it reduces lots of data

into simpler summary.

The results showed that most enterprises had not used credit before. Out of those who had, the

majority had used informal sources mainly due to lack of information about credit and required

security. The use of specific credit sources, either formal or informal, was justified as the only

source available. This may indicate the inability of the financial markets to meet the existing credit

demand and reinforces the argument that small-scale rural based enterprises do not have access to

the financial resources of the formal financial sector. In both formal and informal markets, personal

savings was the dominant source of finance, especially for initial capital.

Loan rationing in the informal credit market is attributed to the limited resource base, while for

the formal sector it is due to the lending terms and conditions. A comparison of household and

enterprise characteristics between those who had used credit and those who had not, as well as

between those who used formal sources and those who used informal sources, showed that the

differences were not significant in both cases. However, the loan terms and conditions all differed

significantly between formal and informal credit sources. It is argued that the limited credit use is

due to an inadequate credit market, which means that enterprise characteristics may not be

16

important in determining the use of credit. Limited access to credit is therefore seen as a result of

supply-side constraints, and not the demand side.

The fact that those who did not seek credit because they had relatively higher wealth values may

not necessarily mean that they did not need credit. Rather, it may mean that the type of loans they

require do not exist, implying that the credit market does not serve the needs of enterprises seeking

to expand their business. The result is, therefore, a credit gap capturing those enterprises too big

for the informal market, but not served by the formal market. This is because although informal

finance provides easier access to credit, informal credit is confined to specific activities and at

lower levels of income, thus limiting its use.

A study by Kalunda, (2014) sought to find out the level of financial inclusion in terms of access

and usage and its impact on small scale tea farmers in Nyeri County, Kenya. The relationship

between gender and age on the demand and use of financial services was also investigated using

the Pearson Chi square method. The findings reveal that the level of inclusion is high and usage in

terms of credit access is also high.

The relationship between gender and age on the demand and use of financial services under the

Pearson’s Chi square method yielded inconclusive results. The study recommends that financial

counselling and education should be offered to the farmers to enable them to appropriately use the

financial products and services offered through financial inclusion initiatives. Unlike the current

study it targeted Small scale tea farmers in Kenya, impact of financial inclusion initiatives.

2.2.3: Procedural Formalities

A study by Hoope, (2013) aimed at the following specific objectives to compare accessibility of

M-Pesa financial service to other non-mobile financial services, to establish M-Pesa transactions

costs and compare with other non-mobile microfinance services and to study M-Pesa user-

friendliness and compare to other microfinance services available locally. The major findings are

that Vodacom is the leader in the money market services since it is 100% accessible at the village

centers and small sub-centers.

17

The transaction costs as compared to other non-mobile services is lower since the sender is charged

some money and the receiver is charged a certain percent around 0.4% of the money received. The

M-pesa service menu is user friendly as compared to other microfinance services as revealed in

the number of people who joined the service automatically upon registration for the first time. The

Government and Non-Governmental organization can create supportive environment to improve

microfinance service in the study area.

According to the study, research has shown that the most effective way to significantly expand

poor people’s access to formal financial services is through digital means. In addition to cost

savings, digital financial services offer a wide array of benefits: They connect poor people to the

formal financial sector and enable them to become customers and suppliers within the wider

economy, financial flows can be accurately tracked, resulting in safer and speedier transactions

and less corruption and theft, providers can use financial histories to develop products that are

better suited to customers’ needs, cash flow, and risk profiles, including fee-for-service offerings

and smaller-unit transactions, direct deposits (including wages and government assistance) allow

money to “bypass” the home, helping users save rather than spend and often giving women more

financial authority within the family, and automatic reminders, positive default options, and other

choices offered via mobile phone menus offer convenience and save time.

A cross sectional research design was adopted. Multi-stage sampling technique was used from

selected wards and villages. The study was carried out in two phases. On the first phase the

reconnaissance survey carried out, selecting sample villages and pre-testing research instruments.

The current study differs in its conceptual frame work from this study as well in objectives.

Lundqvist, (2014), assessed the impact of mobile phone penetration on economic growth based on

a sample of 44 African countries during the period 2000-2011, the relationship between mobile

phone penetration, measured as the number of mobile phone subscribers per capita, and economic

growth was examined. Using a dynamic panel data model, a System GMM estimator was applied

to address any issues of endogeneity.

18

The findings suggested that policy promotions and regulations should be targeted towards further

utilization of the great potential for inclusive growth that higher mobile phone penetration reveals.

Moreover, there is a growing demand for formal financial services since the absolute incomes at

the bottom of the pyramid in many of the world’s poorest countries are rising, implying that more

people are moving away from incomes at subsistence levels to have some disposable surplus. The

current study differs in its objectives and methodology.

Kimani, (2013), established that; central bank rate, cash reserve ratio, open market operation and

uncertainty caused by possible outcomes due to monetary policy changes influences lending

behaviour by commercial banks in Kenya. The study concluded; that cash reserve ratio has an

effect on bank lending behaviour, holding some funds in excess reserves provides enhanced

liquidity which smoothen operation of payment system, the higher the banks’ reserve requirement

is set means less funds will be loaned out. Finally lending and payment systems in the commercial

banks concerned are influenced by reserve requirements: e.g. low interest rate lowers the cost of

borrowing and therefore banks attract new loans demands.

The study employed a descriptive research design and its target population was drawn from Kenya

five most profitable commercial banks. Respondents from credit and lending department were

selected from each commercial bank using purposive sampling. A content analysis and descriptive

analysis on both primary and secondary data was employed. The general objective was to establish

the effect of uncertainty arising from expected change in monetary policies on lending behavior of

commercial banks in Kenya. Specific objectives based on Lending Behaviour of Commercial

Banks in Kenya, sought to assess effects of Monetary Policies, determine the impact of central

bank rate on, establish the effects of cash reserve ratio, and find out the extent to which open

market operations affect lending behavior of commercial banks in Kenya. This study looks at a

product of one commercial bank (CBA).

2.4 Review of Knowledge Gap

Research undertaken focuses primarily on formal lenders’ perspectives extending SMEs’ credit in

Kenya, ignoring informal lenders’ perspectives and borrowers’ perceptions considered crucial in

exploring and establishing variances needed to seal leakages in financing SMEs.

19

2.5 Conceptual Framework

The study conceptualised, Financial Intermediation Theory, Finance Growth Theory, Modern

development theory and financial inclusion scenario amongst Out-growers’ households in

Muhoroni Sub-county in Kenya. Figure 2.5 below demonstrates the derivation of the relationship

into a multiple regression with financial inclusion amongst Out-growers’ households in Muhoroni

Sub-county as the dependent (outcome) variable. The independent variables used in this study

include; M-Shwari transactions, suitability of M-Shwari, and M-Shwari procedural formalities.

The role of moderating variables; Monetary and fiscal policy mix which are Government control

tools for velocities and prices of money in circulation and gross income as an indicator of poverty

effect.

The Conceptual Framework

Independent variables Moderating variables Dependent variable

Figure 2.5 Conceptual Framework

Source; Author 2015

M-Shwari

transactions

Suitability of M-

Shwari

Procedural

formalities of

M-Shwari

-Poverty level

-Farm income

-monetary and

fiscal policy mix

Financial

inclusion

among cane

out-growers’

households

in Muhoroni.

20

CHAPTER THREE: RESEARCH METHODOLOGY

3.1 Research Design

This study adopted descriptive survey design which according to Churchill, (1991) is appropriate

where the study seeks to describe the characteristics of certain groups, estimate the proportion of

people who have certain characteristics and make predictions. The study will aim at collecting

information from cane out-growers within the four administrative zones; Chemelil ward, Fort

Tenan ward, Koru ward and Muhoroni ward on the effects of M-shwari product on financial

inclusion amongst households in the years 2013 and 2014 in Muhoroni sub county, Kenya.

According to Mugenda and Mugenda, (1999), the purpose of descriptive research is to determine

and report the way things are. Descriptive research helps in establishing the current status of the

population under study. They are useful for describing, explaining or exploring the existing status

of two or more variables, (Mugenda et al., 1999). Orodho and Oyugi, (2003), asserted that surveys

are self-reports study that requires the collection of quantifiable information from the sample.

The use of questionnaire as an instrument of research gave respondents adequate time to provide

well thought responses in the questionnaire items and enables large samples to be covered within

a short time, Sinclair, Mchard, Dobbie, Cooper and Donald, (2008).

3.2 Target Population

Target population is the collection of elements that possess the information sought for by a

researcher to support the study, Oso and Onen, (2009). Table 5 show the distribution of 5000 cane

out-growers within the Sub-County.

3.3 Sampling Procedures and Sample Size

3.3.1 Sampling Procedures

The study was carried out in Muhoroni Sub-County in Kisumu amongst sugarcane out-growers’

households. Stratified proportionate random sampling technique was used to determine strata

sample size of households; without probability sampling error estimates could not be constructed

Glenn, (1992). Proportional allocation to each strata size (ward) is determined in accordance with

Table 6: this allows for equal opportunity for selection, (Kothari, 2004).

21

3.3.2 Sample Size

The sample size of respondents was 370, this has been determined from, Table 3, at 5% margin

of error (degree of confidence) using 95% confidence level of a target population of 5000 out-

growers households, an optimal sample size that fulfils the requirements of efficiency,

representativeness, reliability and flexibility, Kothari, (2007). Strata sample size has been

determined by the formula from Figure 3.3.1; Simple random sampling allows the population as a

whole to have an equal probability chance of being selected, (Kothari, 2004).

3.4 Data Collection Procedure

A total of 370 respondents were targeted, out of which a pre-test sample of a tenth of the total

sample size i.e. 37 respondents were exempted from the study. Therefore, the study distributed

408 questionnaires, an additional 10% per each ward, according to (Singh et al., 2014) it is

customary in a survey to add an extra 10% to compensate losses. The researcher obtained an

introductory letter from Laikipia University; the researcher proceeded and obtained all necessary

authorization documents as evidenced in the appendices below. The researcher personally visited

and coordinated the pre-test and data collection process in all the wards. The researcher throughout

was guided by Table 5 and Table 6. Whist liaising with the various representatives from

administrative divisions; Chemelil, Fort Tenan, Koru and Muhoroni wards.

The data collected was entered into excel and exported to SPSS version 21 for facilitating data

analysis in combination with Secondary data guided by Electronic codebooks which will greatly

facilitated the review of relevant CBA reports, journals. The objectives of the study were the bases

on which items on the questionnaire were developed. The high response rate was due to enthusiasm

as a result of familiarity amongst neighbours with the team and the non–personal natures of the

survey. All questionnaires apart from nine were immediately collected after being filled by

respondents.

22

3.5 Validity and Reliability

Validity of an instrument is the degree to which an instrument measures what it is intended to

measure, (Mugenda et al., 1999). Whereas as Reliability refers to the consistency of scores

obtained by the same persons when they are re-examined with the same test on different occasions

or with different sets of equivalent items, or under other variable examining conditions, Anastasi

and Urbina, (2002).

A pre-test sample of a tenth of the total sample size, 37 respondents, with homogeneous

characteristics is appropriate for a pilot study, (Mugenda et al., 1999). The reliability coefficient,

Pearson Product-Moment Correlation Coefficient (r), was determined between the scores obtained

by the same persons on the two administrations of the test. The value of "r” was obtained and fells

at 0.98, this was acceptable as indicated by the informal interpretation shown in Table 4

3.6 Data Analysis and Presentation

The data collected was analyzed with the aid excel and Statistical Package for Social Science

(SPSS) – version 21.0. The findings are presented as per the objectives and research questions of

the study. Data cleanup involved editing, coding, and tabulation in order to detect any anticipated

anomalies in the responses and assign specific numerical values to the responses for further

analysis. Frequency tables, percentages and means are used to present the findings. The responses

from the open-ended questions were listed to obtain proportions appropriately; the response are

then be reported by descriptive narrative.

Descriptive statistics are common interpretation of raw scores by reference to norms and are

conversion into some relative reference or “standard” score such as mean and standard deviation,

Brock, (2000), will be used. Tables, pie-charts, and graphs will also be used to present responses

and facilitate comparison. Content analysis is a technique for making inferences by systematically

and objectively identifying specific characteristic of messages and using the same approach to

relate trends. According to Kothari (2004), content analysis uses a set of categorization for making

valid and replicable inferences from data to their context.

23

The study results are presented in chapter four as two sections, namely: Results and Discussion.

The first stage involved reporting all the information related to each of the respondents’ personal

profiles and data analysis and discussed in relation to the research objectives outlined in chapter

one. Descriptive analysis was done to report on the respondents including the results of the

measurement variables. Finally, the results of regression to test the relationships between

constructs are reported in detail. This chapter concludes by highlighting the main findings obtained

from the quantitative data. The next section presents the results of the empirical analysis, discusses

the findings and interpretations.

3.6.1 Conceptual Model

This study formulated a conceptual model based three independent variables; M-Shwari

transactions, suitability of M-Shwari and M-Shwari procedural formalities their possible patterns

of influence on each other and eventually on effects of M-Shwari on financial inclusion among

out-growers’ households. These variables as intervened by monetary policy, fiscal policy, Out-

growers income and poverty level. This structural model below is determined in the next chapter.

Y = F(X1, X2, X3, X4)

3.6.2 Analytical Model

Regression analysis was used to analyze data. Regression analysis is a statistical process for

estimating the relationships among variables. It is used to understand which among the

independent variables are related to the dependent variable, and to explore the forms of these

relationships, (Mugenda et al., 1999).

The following analytical model was used to analyze data by estimating a linear equation in the

regression equation below:

Y= α+ β1X1+β2X2+ β3X3 + β4X4 + 𝜀

Y: Dependent variable; the percentage of household heads having used an M-Shwari account.

α: Constant, the intercept of the model.

β1: Coefficient of the X1, β2: X2, β3: X3 independent variables and β4: X4 moderating variable.

X1: Independent variable, the percentage of household heads finding M-Shwari transactions

accessible.

24

X2: Independent variable, percentage H/HS finding M-shwari a preferable product

X3: Independent variable, the percentage of household heads finding M-Shwari procedures

preferable.

X4: moderating variable, the lower quartile level of H/HS incomes.

𝜀: Error term

25

CHAPTER FOUR: RESULTS AND DISCUSSIONS

4.1 Muhoroni Cane Out-growers’ Households and Increased Financial Access

Increased financial access among the sugar cane out-growers’ households of Muhoroni sub-county

and the role of m-shwari being the core theme: the study materialized in the sugarcane settlement

of Muhoroni sub-county. Pearson’s correlation, r (“69”) = “.98”, p <.0.001”, correction of the

questionnaire wasn’t necessary.

The study distributed 408 questionnaires, an additional 10% per each ward, according to (Singh et

al., 2014) it is customary in a survey to add an extra 10% to compensate losses. Out of 408

respondents who participated in the study, 366 respondents completed their questionnaires

successfully. Therefore eliciting 98.9% of the targeted sample (370) and 89.7% of the distributed

questionnaires (408). The assumption of normal population, precision of (E) 5% was met for the

5000 targeted population, Appendix 1. This return rate was still acceptable because it was above

60% return rate recommended by Amin (2005). The response rate of 98.9% was thus sufficient for

analysis and reporting.

A Pie chart, figure 4.1, on increased formal access is used in interpreting the respondents’

responses. Evaluation indicated that the majority of respondents (56.6%) responded “yes” meaning

M-shwari had enabled them to increased formal access while 34.4% responded “no” meaning

otherwise. Data collected separately in each stratum guided by Table 6 was used so as to be

representative of the four administrative wards namely Chemelil, Forte Tenan, Koru, and

Muhoroni wards that make the Sub-County. Survey questionnaires as the primary level assessment

requiring individual head of households’ level estimation, respondents were to indicate by (1)-yes

or (2)-no whether they had increased formal access since the inception of M Shwari.

This is similar to a study by Mol, (2014), who revealed that 99% of the rural households in Kerala,

India in terms of access to bank accounts are included in formal financial systems, while 30% of

the total respondents did not have access to formal credit. Matoke, (2012), also who found that a

bank account does not have an automatic effect on the access to micro-credit. According to (Mburu

et al., 2012), rural households may be unaware of other resources available to them.

26

Figure: 4.1 Percentage Pie Chart on Inclusion

Source: Researcher 2016

4.1.1 Demography and Financial Inclusion

The study sought to assess whether there’s a relationship between increased formal access and the

socio economic factors. The study presents cross tabulations on demographic factors before

attending to Regression analysis for the four underlying variables namely access to transactions,

suitability of M-shwari and procedural formalities of M-shwari among Out-Growers Households

in Muhoroni sub-county.

Cross tabulations (contingency tables) in SPSS display the relationship between two or more

categorical (nominal or ordinal) variables, Field, (2009). The size of the table is determined by the

number of distinct values for each variable, with each cell in the table representing a unique

combination of values, (Field, 2009). These variables describe socio-economic factors and aspects

involved in the sanctioning of credit and the suitability preferences to the borrower. Respondents’

score assigning each of the variables accordingly has been analyzed below in Table 4.2 under

respective sub-themes:-

56.60%

34.40%

STATUS OF INCREASED FORMAL ACCESS

YES

NO

27

4.1.2 Households' Profile

Households are the primary unit of analysis and to understand the effect of M-Shwari on increased

formal access among Households, it was appropriate to look into household characteristics of the

study area on the basis of information elicited through the primary survey. (See Table 4.1)

Table 4.1: Residential Wards (Percentage)

Incr

ease

d F

orm

al A

cces

s

Chemelil Forte

Tenan

Koru Muhoroni N

Sample Sizes 127 118 61 102 408

Full-Responses 114 106 54 92 366

Yes 32.4% 30.9% 12.6% 24.2%

56.6%

no 29.6% 26.4% 17.6% 26.4% 43.4%

Total 31.1% 29.0% 14.8% 25.1% 98.9%

Mean 1.41 1.40 1.52 1.46 1.43

Std. Deviation .494 .491 .504 .501 .496


Figure: 4.1.2 Chart on Increased Formal Access across Wards

Source: Researcher 2016:

58.80% 60.40%

48.10%

54.30%

41.40% 39.60%

51.70%

45.70%

30.80%28.60%

14.60%

24.90%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

Chemelil Forte Tenan Koru Muhoroni

Per

cen

tage

Wit

hin

war

ds

Respondents' Wards Ditribution

Household Inclusion Strata

Yes No Total Linear (Yes)

28

Evaluation of mean scores and std. deviation showed that majority of wards had were well rated

however Koru ward was underrated. It was seen that majority of respondents were distributed

among Chemelil ward (32.4%) and the least in Koru (12.6%).

According to Table 4.1.2; fathers (61.8%) were the majority of out-growers benefiting while single

parents were least benefited (5.3%). A study by (Osieko, 2013) showed that majority of sugarcane

farmers are mainly male who form part of household heads and are likely to have more authority over land

ownership as compared to females of the sample.

Table 4.1.2: Parental Status of Household Heads (Percentage)

incr

ease

d f

orm

al a

cces

s Father Mother Step-parenting Single-parenting Total Mean 1.77

Yes 61.8% 20.3% 12.6% 5.3% 56.6% Std. Deviation 0.945

No 37.1% 40.9% 10.7% 11.3% 43.4%

Total 50.5% 28.9% 11.6% 7.8% 100% Mode 1

Mean 1.32 1.61 1.40 1.62 1.43

- Std.

Deviation .466 .491 .495 .494 .496


Evaluation of family size of the sample out-growers’ households showed that majority of

households (see Table 4.1.3) was highest (58.5%) among family members between 6 and 10 and

least (41.5%) among family members less than 6.

Table 4.1.3: Family Size of Out-Growers Households (Percentage)

incr

ease

d f

orm

al a

cces

s

6 and

below 10 >6 16>10 Total Mean 1.53

Yes 41.5% 58.5% - 56.6%

0.500 No 50.0% 37.6% - 43.4%

Total 47.0% 53.0% - 100.0% Mode 2

Mean 1.50 1.38 - 1.43 -

Std. Deviation .501 .486 - .496


Evaluation of age of household heads of out-growers households was done (see Table 4.1.4)

(30.9%).

29

Table 4.1.4: Age of Household Heads (Percentage) in

crea

sed

fo

rmal

acc

ess

25>17 35>25 50>35 above 50 Total Mean 2.60

Yes 17.4% 28.0% 30.9% 23.7% 56.6%

Std.

deviation

1.039

No 18.2% 29.6% 27.7% 24.5% 43.4%

Total 17.8% 28.7% 29.5% 24.0% 100.0%

Mode 3

Mean 1.45 1.45 1.41 1.44 1.43

-

Std. Deviation .501 .500 .494 .500 .496


Findings showed that majority of Households with increased formal access, were HOH between

50 and 35 years of age while the least (17.4%) fell between 25 and 17 of age. A study by (Osieko,

2013) revealed that most of the sugar cane farmer were within the age category of 40-50 years.

4.2.1 Socio-Economic Factors

To understand the effect of socio-economic factors namely HOHs’ education level, annual acreage

set aside for cane, status of out-growers and attitude on M-Shwari representing fiscal and monetary

perspective on increased formal access the study elicited respondents opinion of the sample under

this sub-themes, in Table 4.2.1.

Table 4.2.1: Education Background (Percentage) Distribution of Sample Households according to

Primary secondary tertiary or

professional Total Mean

2.22

yes 8.7% 45.9% 45.4% 56.6% Std.

Deviation

0.708

no 26.4% 44.0% 29.6% 43.4%

Total 16.4% 45.1% 38.5% 100.0% Mode 3

Mean 1.70

1.42

1.33

1.43

- Std.

Deviation .462

.496

.473

.496


Evaluation showed that increased formal access was predominant (45.9%) among HOHs’ within

the category secondary leavers and least among primary school leavers (8.7%) of the sample.

30

According to Table 4.2.2: 36.7% of out growers’ contracting status free-lance out growers while

the least (15.9%) were leaseholders or sub-contracting out growers.

Table 4.2.2: Out growers’ contracting status (Percentage)

Contracted Joint-

Contracted

Sub-Contracted

freelancing Total Mean 2.64

yes 22.2% 25.1% 15.9% 36.7%

56.6%

Std.

Deviation

1.171

no 22.6% 25.8% 20.1% 31.4% 43.4% Mode 4

Total 22.4% 25.4% 17.8% 34.4% 100.0%

Mean 1.44 1.44 1.49 1.40 1.43

- Std.

Deviation .499 .499 .504 .491

.496


To gauge the perception respondents on monetary and fiscal policies the study sought their

opinion on M-Shwari, since it is virtually a monopoly in the credit market of mobile agent

banking in Kenya, to represents governments policy. (See Table 4.2.3)

Table 4.2.3: perception of M-Shwari (Percentage)

lender-

advantaged

borrower-

indifferent

borrower-

advantaged

borrower-

disadvantaged Total Mean 2.33

yes 43.0% 40.1% 5.3% 11.6% 56.6% Std.

Deviation

1.181

no 17.6% 15.1% 21.4% 45.9% 43.4%

Total 32.0% 29.2% 12.3% 26.5% 100.0% Mode 2

Mean 1.24 1.22 1.76 1.75 1.43 -

Std.

Deviation .429 .419 .435 .434 .496


The Attitude of out-growers’ according to Table 4.2.3, 43.0% thought that M-Shwari was lender

advantaged while 15.9% thought that M-Shwari was borrower-advantaged of the sample.

To Access gross income as an indicator of the effect of poverty level on increased formal access,

the study sought to document the annual acreage set aside for cane by the out-growers. (See Table

4.2.4).

31

Table 4.2.4: Annual Acreages Cane (Percentage)

13 or less 25>13 50>25 Above 50 Total Mean 2.47

yes 33.3% 13.5% 23.2% 30.0% 56.6% Std.

Deviation

1.218

no 32.7% 18.2% 22.6% 26.4% 43.4%

Total 33.1% 15.6% 23.0% 28.4% 100.0% Mode 4

Mean 1.43 1.51 1.43 1.40 1.43

- Std.

Deviation .497 .504 .498 .493 .496


Evaluation showed that increased access was highest (33.3%) among those with13 or less acres of

cane annually. increased access was least (13.5%) among with between 25 and 13 of the sample.

Figure: 4.1.3 Gross income (annual cane Turnover)


The predominance of joint- contractors implies either the need to meet terms for contract status or

terms for credit from extension agencies. According to, (Prathap, 2011) terms and conditions are

attributes of the lenders that affect demand or non-demand of credit. While, (Mol, 2014),

conceptualizes that income and savings habit of rural households are related, wealth leads to

increase in the savings habit of the rural households.

57.00%

49.10%

57.10%59.60%

43%

50.90%

42.90%40.40%

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

13 or less 25>13 50>25 Above 50

incr

ease

d a

cces

s in

Per

cen

tage

s

Annual Acreages Set For Cane

Out-growers access with cane outlays

Yes No Linear (Yes)

32

4.3 Assessing the Effects of M-Shwari on Financial Inclusion

4.3.1 Access to Transactions and financial inclusion

The study sought respondents’ opinion on the effects of M-Shwari’s access to transactions on

financial inclusion among Out-growers’ Households in Muhoroni sub-county Kenya. Seven

variable were done one tailed ANOVA test to identify the underlying commonality behind the

preference of borrowers for factors of access to transactions.

Table 4.3 presents the comparison in interpreting the respondents’ responses as the primary level

assessment requiring individual head of households’ level estimation in percentages and means of

M-shwari’s access to transactions. Evaluation should that availability of agent float or cash,

availability of network accessibility, transaction fees and risk perception were well rated. But

proximity of agent operators’ procedural hassles were underrated. Variability test showed that.

Availability of Agent Float or Cash F (1, 365) = 105.541, P <0.001, η2 = 105.541, availability of

network and F (1, 365) = 82.298, P <0.001, η2 = 27.193 and procedural hassles F (1, 365) = 75.254,

P <0.001, η2 = 16.511.

33

Table 4.3.1: Access to Transactions

Underlying

Factors

Independent

Variables

V.A

(1)

A

(2)

F.A

(3)

P.A

(4)

I.A

(5

Mean Std.

deviation

Access to

transactions

Availability of

Agent Float or

Cash

6.0% 79.0% 10.7% 3.8% 0.5%

2.14

.592

proximity of

agent operators 5.7% 9.6% 79.8% 4.4% 0.5%

2.84

.606

Availability of

network 6.6% 81.4% 6.6% 4.1% 1.4%

2.12

.636

Accessibility

across networks 0 0 0 0

100% 5.00

.000

Transaction fees 4.4% 85.5% 7.9% 1.9% 0.3%

2.08

.467

Procedural

hassles 0.8% 4.1% 83.6% 8.7% 2.7%

3.08

.514

Awareness, usage

indicators

v.s S f.s Ps. Mean Std.

deviation

Risk Perception 75.7% 8.5% 15.6% 0.3% 1.40

.755

V.A Very Accessible, A, Accessible, F.A, Fairly Accessible, P.A Poorly Accessible,

I.A, Inaccessible, *S Secure


Proximity assessed whether the distance covered to access bank services and the associated time

and cost of transport are real incentives to alter the customer decision whether to visit the bank or

the agent. According to (Kithuka, 2010) distance does not influence the frequency of customer

transactions. (Matoke, 2012) revealed that access to bank deposits and withdrawals for low income

households was not sufficient to positively impact the finances of the low income households.

However, (Ndungu and Njeru, 2013), showed that agency banking is bringing the banking services

closer to the customers and thus positively influencing adoption of agency banking.

34

4.3.2 Suitability of Product and Financial Inclusion

The study sought respondents’ opinion on the effects of Suitability of Product on Financial

Inclusion among Households in Muhoroni sub-county Kenya. The results are as indicated in the

Table 4.3.2 below. .

Table 4.3.2: Suitability of M-Shwari

Respondents’ Score Assignment to Variables Percentages

Under

lyin

g

Fac

tor Independent

Variables(Banking-

usage preference)

Yes

(1)

No

(2)

No Opinion

(Indifferent)

(3)

Mean

Std.

Deviation

Suitability of

M-Shwari

Rate of Interest 59.3% 39.3% 1.4%

1.42

0.521

Usage Preference to

Extension Agencies 74.9% 23.8% 1.4%

1.27 0.472

Usage Preference to

Friends and relations 52.2% 45.6% 2.2%

1.50 0.543

Suitability of needs 57.1% 40.2% 2.7% 1.46 0.551

access Preference to

Extension Agencies 58.7% 35.2% 6.0%

1.47 0.609

access Preference to

Friends and relations 69.9% 29.2% 0.8% 1.31 0.480


Evaluation Suitability of M-Shwari showed variability of preference. Extension agencies, friends

and relations were well rated by the majority. But rate of interest, Suitability of product were

averagely rated. A six variable one tailed ANOVA test to identify the underlying commonality

behind the preference of borrowers for factors of access to transactions. Suitability of product

F (1, 365) = 1670.671, P <0.001, η2 = 90.978, Rate of interest F (1, 365) = 1569.838, P <0.001,

η2 = 80.530, and Usage preference to Friends and relations F (1, 365) = 1129.035, P <0.001, η2 =

81.292. However this contrasted (Kalunda, 2014), revealed that products may be financially

unsuitable.

35

4.3.3 Procedural Formalities and Financial Inclusion

The study also sought respondents’ opinion on the effects of M-Shwari’s access to transactions on

Financial Inclusion among Households in Muhoroni sub-county Kenya. The results are as

indicated in the Table 4.3.3 below.

Table 4.3.3: Procedural Formalities Evaluation


Pro

cedura

l F

orm

alit

ies

of

M-S

hw

ari

Very

preferable

preferable indifferent unpreferable Very

unpreferable

Mean Std.

deviation

Application

fee 77.0% 13.1% 6.0% 2.2% 1.6% 1.38 .828

Collateral

value 40.7% 38.0% 12.0% 9.0% 0.3% 1.90 .952

Application

Period 67.5% 23.5% 5.5% 1.9% 1.6% 1.47 .819

Terms of

Repayment

period

66.1% 22.1% 10.1% 0.5% 1.1%

1.48 .786

Procedural

hassles 41.3% 33.6% 16.7% 8.2% 0.3% 1.93

.964


Evaluation of Procedural Formalities showed variability with Application fee, Application Period

and Terms of Repayment period being well rated. But Collateral value Procedural hassles were

underrated. A five variables, one way ANOVA test to identify the underlying commonality behind

the preference of borrowers for factors of access to transactions. Collateral value F (1, 365) =

426.748, P <0.001, η2 = 178.341, Repayment period F (1, 365) = 355.942, P <0.001, η2 = 111.439,

and Procedural hassles F (1, 365) = 276.587, P <0.001, η2 = 146.374. However this contrasted

(Kalunda, 2014), who found procedural formalities cumbersome.

36

4.3.4 Moderating variables

The study also sought respondents’ opinion on the effects of M-Shwari’s access to transactions on

Financial Inclusion among Households in Muhoroni sub-county Kenya. The results are as

indicated in the Table 4.3.4 below.

Table 4.3.4: Moderating variables


Underlying

Factor

scores 13 or less

(1)

25>13

(2)

50 or >25

(3)

50 or above

(4)

Mean

Std.

Deviation

Moder

atin

g v

aria

ble

s

Annual acreage

set aside 33.1% 15.6% 23.0% 28.4% 2.47 1.218

Scores

lender-

advantaged

(1)

borrower-

indifference

(2)

borrower-

advantaged

(3)

borrower-

disadvantaged

(4)

Mean

Std.

Deviation

Perception of

M-Shwari 32.0% 29.2% 12.3% 26.5% 2.33 1.181


Evaluation showed that Perception of M-Shwari was well rated. But annual cane acreage set aside,

was rated (33.1%) well by small scale, lower quartile, farmers and least (15.6%) by medium sized

farmers. A two variable one way ANOVA test to identify the underlying commonality behind the

preference of borrowers for factors of access to transactions. Perception of M-Shwari

F (1, 365) = 99.095, P <0.001, η2 = 108.989, and annual cane acreage set aside F (1, 365) = .296,

P >0.05, η2 = .440.

4.4 Multiple Regression in SPSS

A multiple regression equation contains coefficients (b) for each prediction, if all the other

predictor values are held constant, and the estimates for these b- values indicates their individual

contribution of each predictor to the model, (Field, 2009). A SPSS stepwise regression output

contains summaries of estimated b-values of each predictor it is considering to enter or remove

into the model depending on whether it is forward or backward method respectively at that point.

Stepwise forward method enters the highest t-statistic in sequence with p< 0.05 while backward

method removes lowest t-statistic in sequence with p> 0.05 and or with the least betas values.

37

More so, (Field, 2009), the b-values tell us the degree each predictor affects the outcome. .A

positive b-value indicates a positive relationship between the predictor and the outcome. A

negative b-value indicates a negative relationship between the predictor and the outcome. An

associated standardized beta, error, tell us how many standard deviations the outcome will change

with each standard deviation change in each predictor, (Field, 2009). A t-test associated with a b-

value if P< .05 means a significant prediction. The output also contains a corresponding t-test and

significance for each predictor in the model.

4.4.1 Model fitting in regression analyses

This is a statistical test of the model’s ability to predict the outcome variable (increased formal

access) i.e. the F test, but also the value of multiple R, the value R, and the corresponding R2, and

the adjusted R2 , Field, (2013). The R square change is a measure that provides a useful the unique

contribution of new predictors to the explanatory variance in the outcome. The accompanying t-

test and significance tell us whether b-values differs significantly from zero, (Field, 2013).

4.4.2 Model Summary

Table 4.4.1: Coefficients from SPSS output

Model Unstandardized Coefficients Standardized

Coefficients

B Std. Error Beta

1

(Constant) .410 .046

Availability of agent float or

cash -.126 .027 -.151***

Suitability of needs .771 .031 .856***

Collateral value .092 .024 .177***

Perception of M-Shwari -.001 .012 -.003****

2

(Constant) .409 .046

Availability of Agent Float or

Cash -.127 .027 -.151

Suitability of needs .771 .031 .856

Collateral value .091 .022 .175

Note. R2 = .832 for step 1: Δ R2=-.000 for step 2. (ps< .05). ***p< 001, ****p> .90 N = 366

a. Dependent Variable: Increased formal access.

Source: Author (2016).

38

The model summary contains model 2, following forward stepwise method in SPSS on increased

forma access. I.e. Y = F(X1, X2, X3,). Suitability of the product showed a significantly higher level

of effect on increased formal access. F (1,363) =1670.671, p < .001, η2 = 73.839, procedural

formalities showed an F (2,364) =853.945, p < .001, η2 = 37.082, and Access to transaction a least

effect F (3,365) =599.409, p < .001 η2 = 24.952, (one-tailed test). While fiscal/monetary policy

showed no statistically significant effect on increased formal access. The equation becomes Y=

α+ β1X1+β2X2+ β3X3 + β4X4 + 𝜀

Table 4.4.2: Means and Standard Deviations of Usage and Product Indicators

Model Increased formal

access

Availability of Agent

Float or Cash

Suitability of

product

Collateral

value

N

366

Mean 1.43 2.14 1.46 1.90

Std.

Deviation

.496

.592

.551

.952

Source: Author (2016).

Table 4.4.2 show the means are larger than Std. Deviation an indication of the assumption of

independence.

4.5 Discussion

According to the study the most effective way to significantly expand “bottom of the pyramid”

peoples access to formal financial services is through digital means i.e. the results indicate

significance influence of access to transactions components to increased formal access namely;

availability of agent float or cash availability, availability of network and procedural hassles. It is

clear that M-Shwari has availed proximal and available agent banking formal transaction among

out growers of Muhoroni sub-county. This is indicated by the agent’s float highest “F value” and

low “p value” among transaction indicators.

This consistent with earlier findings of (Mol, 2014), that low income households of Kerala are

highly on formal financial system on various aspects of financial inclusion such as banking

penetration, availability of banking services and usage of the banking system. A key findings from

39

(Matoke, 2012) research was that agent banking has had a significant impact in including the low

income households in the financial mainstream.

Another attraction to M-Shwari was suitability of product. This component scored highest among

the significance t-test of all underlying factors namely; access to transactions, procedural

formalities and fiscal/monetary policies or income effect. M-Shwari has availed has provided out

growers with a tailor made product. This indicates that M-Shwari has filed a gap that needed filling

among cane out growers of western Kenya.

As a study by (Afande, 2015) revealed that the loan terms and conditions is as a result of supply-

side constraints, meaning that the type of loans they require do not exist, implying that the credit

market does not serve the needs of out-growers. Resulting in a credit gap not served by the formal

market. According to, (Prathap, 2011), conditionality for loan and loan product features were

preferred from semi-formal and informal sources and not from formal sources in rural Karala

households.

Procedural formalities results indicate significance influence of its components to increased formal

access namely; Collateral value, Repayment period and Procedural hassles showed statistical

significant, however collateral value had the highest score. Procedural formalities of M-Shwari

was preferable by most households. This shows that M-Shwari is user-friendly compared to other

microfinance services available locally.

(Hoope, 2013) revealed that Vodacom’s M-Pesa service menu (M-Shwari) is comparably user-

friendly with lower transaction costs than its competitors and is 100% accessible at the village

centers and small sub-centers. Therefore technologies needed to deepen financial inclusion among

these people are claimed to already be in place, (Lundqvist, 2014).

Perception of fiscal/ monetary mix were stepwise not significant, ΔR2 equaled zero showing that

this variable does not fit our model. This is consistent with a study by (Kalunda, 2014) that showed

this component is not statistically significant. (Kimani, 2013) showed that the higher the banks’

reserve requirement is set meant that less funds will be loaned out.

40

CHAPTER FIVE: CONCLUSIONS AND RECOMMENDATIONS

5.1 Conclusion

We quantify by comparing F-statistic to its null sampling distribution which is the specific F-

distribution which has degrees of freedom matching the numerator and denominator of the F-

statistic as “large”. The study generalized the outcome that M-Shwari has gained much usage by

Out-growers. Respondents' Residential wards, HoH age bracket, Out-growers' status and Annual

cane acreage set aside Households’ family size did not show influence on financial inclusion

whereas HoH Parental status, educational background of HoH, Perception of M-Shwari showed

significant influence on financial inclusion among the households.

Suitability of the product showed prominent significance followed, procedural formalities and

least by access to M-Shwari transactions that led to filling an existing credit gap among the

households however moderating variables did not contribute to our model. More so education was

not a necessary criteria for being able to cope with technological advances. According to (Ndungu

et al, 2013), high quality of agency and system availability contributes to service reliability which

in turn increases the adoption of agency banking.

5.2 Recommendation

It is suggested that M-Shwari should stress more on terms and conditions and loan product quality

so that saving on an individual basis is promoted with a view to increase the preference associated

with the present form of the product among cane Out-growers’ households in Muhoroni sub-

county. For example, The PMJDY gives preference to the lady of the household offering her

overdraft facility up to Rs.5000/- that can be withdrawn after 6 months. If the owner pays back the

loan on time then this amount is increased by Rs.15,000/- offering her overdraft facility up to

Rs.5000/- with households only requiring a letter issued by a gazette officer, with a duly attested

photograph of the person to open an account in any bank branch or Business Correspondent (Bank

Mitr) outlet, (PMJDY, 2016).

Appropriate differences in financial Reporting due to differences in sizes of entities, and ways of

raising capital (publicly or privately) applies the cost constraint assessments based on a

combination of quantitative and qualitative information cause of the inherent subjectivity as noted

41

by IFRS, (2015). The physical and cost barriers to access approach to measuring access and usage

has produced promising results. These data generated by a survey of users allows researchers to

measure financial access across sub-groups. However few such surveys exist for households, and

there are problems with cross-country compatibility of the data sets.

5.4 Suggested Areas for Further Study

The following areas are suggested for further study:

i. The fishing households as they suffer similar fate of irregular and declining incomes.

ii. Budget tracking and social audits on extension and agency banking as a monitor of the

funds flow process should be conducted by government agencies and civil society, to trace

leakages in fiscal and monetary policy implementation.

iii. A study to establish whether the findings on M-Shwari can be generalized to other areas

of Kenya,

iv. A to investigate the factors which influence rural households’ perception of monetary

policy.

42

WORK PLAN

Table 1: Work plan

Dates

Work activity

May 2013-August 2014 Proposal writing

January 2015 Defense in department

February 2015 Correction, data consolidation and resubmission to school

March 2015 Defense in school

June 2015 Correction, data consolidation and Defense in school

July 2015 Submission of; Book, certificate abstract, budget and work

plan.

July 2015 Piloting, Data-collection, Data-analysis and thesis writing

August 2015

Consolidation writing and Submission of final document;

Defense, Correction and resubmission

August 2015 Publication

43

BUDGET

Table 2: Budget

Proposal

preparation

UNIT-

COSTKSH

Batch TOTAL COST

KSH

Typesetting

Proposal

Printing

Travelling

Photocopy

Library, internet

search.

2000

600

2500

120

100

1

600 х6

2500 х5

120х6

-

2000

3600

12500

720

100

Sub-total 18920

Piloting

Typesetting

questionnaires

Printing

Photocopy

Travelling

Meals

2000

50

2*5

2500

300

1

50 х115

10 х115

1

1

2000

5750

1150

2500

300

Sub-total 11700

Data collection

Typesetting

questionnaires

Printing

Photocopy

Travelling

Meals

2000

5

2*5

5000

1500

1

5х6

10х25х370

5000х3

1500х3

2000

30

92500

15000

4500

Sub-total 114030

Thesis preparation

Typesetting Book

Printing

Photocopy

Publication

3000

5000

2*500

16000

1

5000*6

1000*6

1

3000

30000

6000

16000

Sub-total 55000

TOTAL 199650

Inflation@ 10% 19965

GRAND TOTAL 219615

44

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49

APPENDICES

APPENDIX: I

Table 3: sample size selection

SAMPLE SIZE (N) PRECISION (E) OF:

Size of population + 3% + 5% + 7% 10%

500 A 222 145 83

600 A 240 152 86

700 A 255 158 88

800 A 267 163 89

900 A 277 166 90

1000 A 286 169 91

2000 714 333 185 95

3000 811 353 191 97

4000 870 364 194 98

5000 909 370 196 98

6000 938 375 197 98

7000 959 378 198 99

8000 976 381 199 99

9000 989 383 200 99

10000 1000 385 200 99

15000 1034 390 201 99

20000 1053 392 204 100

25000 1064 394 204 100

50000 1087 397 204 100

100000 1099 398 204 100

>100000 1111 400 204 100

Source: Glenn, D. Israel (1992). a = assumption of normal population is poor, the entire population

should be sampled.

50

Table 4: Pearson Product-Moment Correlation Coefficient (r)

R Interpretation

Less than 0.20 Slight, almost no relationship

0.21-0.40 Low, correlation; definite but small relationship

0.41-0.70 Moderate correlation; substantial relationship

0.71-0.90 High correlation; strong relationship

0.91-1.00 Very High correlation; very dependable relationship

Source: Guilford (1956); an informal interpretation of the value r.

Table 5: Target population’s distribution

Administrative Division Target Population

Chemelil Ward 1550

Fort Tenan Ward 1450

Koru Ward 730

Muhoroni Ward 1270

Totals out-growers household

Population

5000

Source: Osieko, (2013).

51

Proportional Allocation formula

nx=n*Px................................(I)

n the total sample size

The proportion of each ward (Px)

Px=𝑁 ͓

𝑁................................... (II)

Where Nx is strata is size

N is target population size

Figure 3.3.1: Proportional Allocation formula

Table.6: Strata Proportional sampling

Administrative Division Px=𝑁

𝑁 Strata

Sample Size

Chemelil Ward 0.31 115

Fort Tenan Ward 0.29 107

Koru Ward 0.15 55

Muhoroni Ward 0.25 93

Sum of probability 1 370

Calculation; Authors (2015)

52

APPENDIX: I I:Transmittal Letter

MR. LAWI.O.OKUMU

LAIKIPIA UNIVERSITY

P.O. BOX 1100-20300

NYAHURURU, KENYA.

TEL: +254-(0) 20 2671985;

Cell: +254 713-552761/ (0)736-299961

[email protected]; www.laikipia.ac.ke

September , 2015

Dear Sir/Madam,

RE: ASSESSING THE EFFECTS OF M-SHWARI ON FINANCIAL INCLUSION AMONG

SUGARCANE OUT-GROWERS’ HOUSEHOLDS IN MUHORONI SUB-COUNTY, KENYA

You are invited to participate in a study, designed for the above topic, which is being conducted

as a requirement toward the degree Master of Business Administration of Laikipia University. The

usefulness and potential positive outcomes of the study will depend upon the honesty and care

with which you answer the questions.

This is an anonymous questionnaire, requiring about 15 to 20 minutes for completion. No

personally identifiable information will be collected from you. Participation in this project is

entirely voluntary. Please read the instructions for each section carefully. Choose a response that

gives the best indication of how you would typically think, feel and experience. All data will be

aggregated prior to presentation and treated with the strictest confidence and will only be used for

the purposes of this study.

Thank you in advance for your co-operatio

Yours faithfully

Lawi Okumu

53

APPENDIX: III: Questionnaire

LAIKIPIA UNIVERSITY

QUESTIONNAIRE SURVEY ON:

RE: ASSESSING THE EFFECTS OF M-SHWARI ON FINANCIAL INCLUSION AMONG

SUGARCANE OUT-GROWERS’ HOUSEHOLDS IN MUHORONI SUB-COUNTY, KENYA

This is an anonymous questionnaire. Please read the Information Letter carefully as it provides

details of the project. By completing the questionnaire, you are consenting to take part in this

survey. You are not required to provide your name as part of the survey. Your reply to the survey

will be strictly confidential. You have a chance to give any comments or suggestions at the end of

this questionnaire.

Thank you.

This questionnaire has five sections (Section A to E). Please answer all the questions.

SECTION A

This section seeks general information about your Farming household. Please tick a relevant box

to indicate what you belief is true.

i). My residential ward is: Chemelil [ ] Forte Tenan [ ] Koru [ ] Muhoroni [ ].

ii). I head this Household as; Father [ ] Mother [ ] step parenting [ ] Single parent [ ].

iii). The family members; 6 and below [ ] 10>6 [ ] 16>10 [ ] Above 16 [ ].

iv). My age bracket is; 25>17[ ] 35>25 [ ] 50>35 [ ] above 50[ ].

v). My level of education is; Primary; [ ] secondary [ ] tertiary or professional [ ].

vi). we grow cane as; contracted [ ] Joint contracted [ ] Subcontracted [ ].N/A [ ]

vii). Annual cane acreage is; < 5 [ ] 6-13 [ ] 14-25 [ ] >25 [ ].

viii) We have increased formal access since accessed M-shwari. Yes [ ] No [ ]

54

SECTION B

This section seeks information M-shwari Transactions effects to formal access via M-Pesa over

the past two years (2013-2014).

2) Please indicate by choosing your response on a scale of 1 to 5the extent to which you believe

M-shwari Transactions have led to formal access.

Table 7: Access to M-shwari Transactions

Access to M-shwari Transactions

Ver

y A

cces

sib

le

Acc

ess

ible

Fair

ly A

cce

ssib

le

Po

orl

y A

cces

sib

le

Inac

cess

ible

Agents float (Money) 1 2 3 4 5

Proximity of Agent operators 1 2 3 4 5

Network transaction facility 1 2 3 4 5

Across network transactions 1 2 3 4 5

Transaction fees 1 2 3 4 5

Other cost (specify) 1 2 3 4 5

Risks assessment criterion

Ver

y

secu

re

sec

ure

Fair

ly

secu

re

Po

orl

y

secu

re

inse

cure

We believe our money with M-Shwari is 1 2 3 4 5

54

SECTION C: This section seeks information on Suitability of M-Shwari.

3) Please choose your response on a scale of 1 to 5.the extent to which you find M-Shwari Suitable

Table 8: Suitability of M-Shwari

Suitability of M-Shwari

Yes

No

Indif

fere

nt

Transactions facility offered by M-Shwari enables us to access credit previously not

available due to interest charges. 1 2 3

Transactions facility offered by M-Shwari enables us to access credit previously only available from extension agencies.

1 2 3

Transactions facility offered by M-Shwari enables us to access credit previously only

available from friends or relatives. 1 2 3

product offered by M-Shwari is Suitable 1 2 3

Product Offered By M-Shwari is Preferable to Extension Agencies 1 2 3

Product Offered By M-Shwari is Preferable to Friends and relations 1 2 3

SECTION D : This section seeks information on procedural formalities

4) Please compare the M-Shwari procedural formalities with that of other creditors

Please choose your response on a scale of 1to 5.

Table 9: M-Shwari procedural formalities

PROCEDURAL FORMALITIES

Ver

y P

refe

rab

le

Pre

fera

ble

Nei

ther

Pre

fera

ble

no

r

Un

Pre

fera

ble

No

n-P

refe

rab

le

Un

-p

refe

rab

le

Application Fees 1 2 3 4 5

Collateral Value 1 2 3 4 5

Application Period 1 2 3 4 5

Repayment Period 1 2 3 4 5

Other procedures (specify) 1 2 3 4 5

Do you have increased access to finance with M-Shwari? Yes [ 1 ] No[ 2 ]

We think M-Shwari is;

Lender advantage [ 1 ] indifference [ 2 ] borrower advantaged [ 3 ] borrower disadvantaged [4 ]

THANK YOU FOR YOUR RESPONSE.

55

APPENDIX: IV:SPSS Output

Table A-1: coefficients

Model Unstandardized Coefficients

Standardized Coefficients

t Sig. 95.0% Confidence Interval for B

Collinearity Statistics

B Std. Error

Beta Lower Bound

Upper Bound

Tolerance VIF

1

(Constant) .246 .031 7.899 .000 .184 .307 Suitability of product

.816 .020 .906 40.874 .000 .777 .856 1.000 1.000

2


.452 .037 .502 12.212 .000 .379 .525 .218 4.594

Rate of itnterest .435 .039 .457 11.124 .000 .358 .512 .218 4.594

3


.382 .036 .424 10.501 .000 .311 .454 .200 4.994

Rate of itnterest .294 .042 .309 6.932 .000 .211 .377 .165 6.065 Usage preference to Friends and relations

.230 .034 .251 6.763 .000 .163 .297 .237 4.226

4


.425 .035 .471 12.260 .000 .357 .493 .194 5.144


.244 .032 .267 7.652 .000 .182 .307 .236 4.242

Application fee -.097 .014 -.161 -7.151 .000 -.123 -.070 .564 1.773

5

(Constant) -

9.264E-005

.028

-.003 .997 -.055 .055

Suitability of product

.372 .033 .413 11.175 .000 .307 .438 .185 5.409


.237 .030 .259 7.907 .000 .178 .296 .235 4.247

Application fee -.172 .017 -.287 -

10.400 .000 -.204 -.139 .333 3.005

Usage preference to Extension Agencies

.200 .028 .190 7.096 .000 .144 .255 .353 2.833

56

6

(Constant) -.021 .027 -.758 .449 -.074 .033 Suitability of product

.341 .033 .379 10.346 .000 .276 .406 .178 5.625


Usage preference to Friends and relations

.181 .031 .198 5.768 .000 .119 .242 .203 4.932

Application fee -.225 .019 -.375 -

11.558 .000 -.263 -.186 .226 4.417


.253 .030 .241 8.587 .000 .195 .311 .302 3.306

product preference to Extension Agencies

.161 .033 .197 4.811 .000 .095 .226 .142 7.031

7


.363 .033 .403 10.956 .000 .298 .428 .171 5.842


.172 .031 .188 5.540 .000 .111 .233 .201 4.968

Application fee -.192 .021 -.321 -9.007 .000 -.234 -.150 .182 5.496 Usage preference to Extension Agencies

.255 .029 .242 8.753 .000 .197 .312 .302 3.306


.169 .033 .208 5.132 .000 .104 .234 .141 7.074

Transaction fee -.085 .025 -.080 -3.399 .001 -.134 -.036 .419 2.389

57

8


.344 .034 .382 10.260 .000 .278 .410 .164 6.098


.180 .031 .197 5.834 .000 .119 .241 .199 5.019


.246 .029 .234 8.487 .000 .189 .303 .299 3.345


.169 .033 .207 5.153 .000 .104 .233 .141 7.075

Transaction fee -.090 .025 -.085 -3.627 .000 -.139 -.041 .416 2.403 Educational background of HOH

-.030 .011 -.043 -2.723 .007 -.052 -.008 .894 1.119

9


.346 .033 .384 10.447 .000 .281 .411 .164 6.100


.180 .030 .196 5.896 .000 .120 .240 .199 5.019


.243 .029 .231 8.504 .000 .187 .300 .299 3.348


.174 .032 .214 5.394 .000 .111 .238 .141 7.095


-.039 .011 -.056 -3.466 .001 -.062 -.017 .845 1.184

Annual cane acgreage set aside

-.022 .006 -.053 -3.337 .001 -.034 -.009 .877 1.140

58

10


.313 .034 .348 9.251 .000 .247 .380 .152 6.593


.195 .030 .213 6.421 .000 .135 .254 .195 5.123


.228 .029 .216 7.978 .000 .172 .284 .291 3.434


.186 .032 .228 5.809 .000 .123 .249 .139 7.172


-.038 .011 -.054 -3.410 .001 -.060 -.016 .844 1.185


-.037 .008 -.090 -4.763 .000 -.052 -.022 .597 1.676

Respondents' Residemtial wards

.029 .008 .068 3.480 .001 .013 .045 .569 1.756

11


.290 .034 .322 8.547 .000 .223 .357 .146 6.842


.177 .030 .193 5.854 .000 .117 .236 .190 5.262


.203 .029 .193 7.037 .000 .146 .260 .275 3.635


.198 .032 .243 6.254 .000 .136 .260 .138 7.253


-.051 .012 -.072 -4.396 .000 -.073 -.028 .766 1.305


-.037 .008 -.090 -4.827 .000 -.052 -.022 .597 1.676


.034 .008 .081 4.150 .000 .018 .051 .550 1.820

Repayment period

.091 .025 .145 3.603 .000 .042 .141 .128 7.787

59

12


.269 .034 .298 7.812 .000 .201 .337 .139 7.178


.201 .031 .220 6.468 .000 .140 .263 .176 5.697


.193 .029 .183 6.695 .000 .136 .250 .271 3.693


.175 .032 .214 5.393 .000 .111 .238 .129 7.748


-.055 .012 -.079 -4.803 .000 -.078 -.033 .751 1.332


-.039 .008 -.096 -5.169 .000 -.054 -.024 .589 1.699


.040 .008 .093 4.717 .000 .023 .056 .523 1.914

Repayment period

.074 .026 .117 2.866 .004 .023 .125 .121 8.246

product preference to Friends and relations

.084 .030 .081 2.843 .005 .026 .142 .248 4.025

60

13


.252 .034 .279 7.381 .000 .185 .319 .137 7.309


.178 .031 .195 5.720 .000 .117 .239 .169 5.924


.166 .029 .158 5.701 .000 .109 .224 .255 3.922


.183 .032 .225 5.756 .000 .121 .246 .128 7.789

Transaction fee -.070 .024 -.066 -2.974 .003 -.116 -.024 .399 2.503

Educational background of HOH

-.061 .011 -.087 -5.346 .000 -.083 -.039 .738 1.355


-.059 .009 -.146 -6.491 .000 -.077 -.041 .388 2.578


.052 .009 .122 5.866 .000 .035 .070 .452 2.214

Repayment period

.094 .026 .149 3.628 .000 .043 .145 .116 8.599


.116 .030 .112 3.838 .000 .057 .175 .229 4.363

Househlods familty size

.075 .020 .075 3.794 .000 .036 .113 .499 2.005

61

14


.244 .034 .271 7.122 .000 .177 .311 .135 7.426


Usage preference to Friends and relations

.178 .031 .194 5.726 .000 .117 .239 .169 5.925

Application fee -.233 .027 -.389 -8.656 .000 -.286 -.180 .096 10.385


.177 .030 .168 5.959 .000 .118 .235 .245 4.087


.183 .032 .224 5.754 .000 .120 .245 .128 7.789

Transaction fee -.077 .024 -.072 -3.226 .001 -.123 -.030 .390 2.567

Educational background of HOH

-.061 .011 -.087 -5.374 .000 -.084 -.039 .738 1.355


-.061 .009 -.149 -6.628 .000 -.079 -.043 .386 2.593


.053 .009 .125 6.008 .000 .036 .071 .449 2.229

Repayment period

.086 .026 .136 3.261 .001 .034 .137 .113 8.885


.111 .030 .107 3.652 .000 .051 .170 .227 4.408

Househlods familty size

.076 .020 .076 3.850 .000 .037 .114 .499 2.006

Application period

.041 .023 .068 1.777 .077 -.004 .086 .135 7.422

a. Dependent Variable: Increased formal access

assessing m-shwari and cane-farmers' households in muhoroni, kenya

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