FACTORS AFFECTING TAX COMPLIANCE BY SMALL AND

MEDIUM ENTERPRISES IN SOTIK SUB-COUNTY IN BOMET

COUNTY IN KENYA

BY

MAUREEN CHEPKORIR BETT

UNITED STATES INTERNATIONAL UNIVERSITY- AFRICA

SUMMER 2020

ii

FACTORS AFFECTING TAX COMPLIANCE BY SMALL AND

MEDIUM ENTERPRISES IN SOTIK SUB-COUNTY IN BOMET

COUNTY IN KENYA

BY

MAUREEN CHEPKORIR BETT

A Research Project Report Submitted to the Chandaria School of

Business in Partial Fulfillment of the Requirement for the Degree

of Masters in Business Administration (MBA)

UNITED STATES INTERNATIONAL UNIVERSITY- AFRICA

SUMMER 2020

iii

STUDENT’S DECLARATION

I, the undersigned, declare that this is my original work and has not been submitted to any

other college, institution or university other than the United States International University-

Africa for academic credit.

Signed: …………………………………………. Date: ………………………………………

Maureen Chepkorir Bett

ID: 642804

This project has been presented for examination with my approval as the appointed supervisor.

Signed: …………………………………………. Date: ………………………………………

Timothy Okech, PhD

Signed: …………………………………………. Date: ………………………………………

Dean, Chandaria School of Business

iv

COPYRIGHT

All rights reserved. No part of this dissertation report may be photocopied, recorded or

otherwise reproduced, stored in retrieval system or transmitted in any electronic or mechanical

means without prior permission of USIU-A or the author.

©Copyright by Maureen C. Bett, 2020.

v

ACKNOWLEDGEMENT

I’d like to thank God for giving me the strength and energy to come up with this proposal.

Additionally, I’d like to thank my son, my parents and my extended family for their immense

support in my academic life. I would also like to acknowledge the USIU-Africa administration

and my colleagues in the ICT department for their material support and my fellow students for

their moral support. Special regard goes to my supervisor Prof. Okech for his continuous

guidance and support throughout this project.

Thank you all and may God bless you.

vi

DEDICATION

I dedicate this work to my beloved son Niall Cyril Kiprotich, my parents Mr. and Mrs. Julius

Lucina Bett, my other “mom” Anne Mwova, my siblings Mr. and Mrs. Emmanuel Linda

Langat, Mr. and Mrs. Nicholas Abigael Siele, Assumpta Chepkirui, Brigit Cherop and

Benedict Kipyegon, my nephews Kelby Kiprono and Luke Kiptoo and my friends Airen

Nyakundi, Vanice Morwabe, Annette Nakamya, Andrea Hernandez, Pinky Keerthi, Mike

Antipa, Eric Simechero and Hassan Mumin for their continuous support throughout my

studies. May God bless you abundantly.

vii

ABSTRACT

The purpose of this study was to explore the impact of several factors on tax compliance by

SMEs in Sotik Sub-county of Bomet County. The specific objectives of this study was to

assess the effect of the level of tax knowledge of SMEs in tax compliance, to establish the

impact of tax rates on compliance of SMEs in Sotik sub-county and to determine the effect of

fines and penalties on compliance of SMEs in Sotik county in Bomet county.

The research used a causal and explanatory survey design to investigate the relationship among

the independent variables which are level of tax knowledge, tax rates and fines and penalties

and compliance of SMEs as the dependent variable. Primary data collection was done via

questionnaire that was administered through a drop and pick of 120 questionnaires with both

open-ended and close-ended questions where 84 percent of the responses were recorded. The

study research used Pearson's correlation, regression analysis for each of the specific objectives

and data was analyzed by IBM SPSS. A multiple linear regression model was used to evaluate

the relationship between three independent variables which are level of tax knowledge, tax

rates and fines and penalties and the dependent variable which is SME compliance. The results

were presented in figures and tables.

Based on the specific objective of the study to assess the effect of the level of tax knowledge

on compliance of SMEs, the Pearson correlation results showed a positive relationship which

implies that the level of tax knowledge and compliance are positively correlated, and highly

statistically significant since the P-Value of 0.000, which is less than 0.05. This presents that

the level of tax knowledge and an SME’s compliance are directly related such that an increase

in the level of tax knowledge of SMEs leads to an increase in their compliance.

Secondly, based on the specific objective of the study to assess the extent to which tax rates

affect compliance, the result indicated a positive relationship between tax rates and

compliance, which implies that they are positively correlated and highly statistically significant

because the P-Value of 0.000, which is less than 0.05. This presents that SME compliance and

tax rates are directly related. This means that a change in the tax rated will cause a marked

change in the compliance of SMEs.

Thirdly, to assess the effect of fines and penalties on compliance of SMEs, the Pearson

correlation results showed a positive relationship, which implies that fines and penalties are

positively related, but not statistically significant since the P-Value of 0.157, which is greater

than 0.05. This presents that SME compliance with fines and penalties have a direct

viii

relationship in that, an increase in fines and penalties will increase compliance of SMEs, but

not by much.

The study concluded that increase in the level of tax knowledge leads to an increase in

compliance by SMEs. It showed that level of tax knowledge affected compliance of SMEs by

42.1 percent based on the R- Value. The research also concluded that when tax rates increased,

compliance also increase. Results showed that tax rates affect compliance by only 24 percent

based on its R-Value. Likewise, an increase in fines and penalties leads to an increase in

compliance by SMEs. Findings showed that fines and penalties affect compliance only by 2

percent according to the R-Value, which means that that their influence is not as significant as

of the other factors.

The study concluded that an increase in dissemination of tax information will improve

compliance by SMEs, especially when using the language locals understand and can relate to.

This is because, findings of this research showed that the more information available to SMEs,

the better their compliance. The study also concludes that a revision of tax rates will very much

encourage voluntary compliance. It recommends that the tax rates be such that SMEs don’t feel

oppressed. This will encourage compliance. The study further concludes that a revision of fines

and penalties and the interests that accrue from them will encourage compliance. The findings

of this research show that SMEs need a reminder of deadlines to avoid late payments that lead

to fines and penalties which in turn accrue interests.

The study recommends research using different methods like convenient sampling,

multivariate data analysis and vignette-based questionnaires for different results. It

recommends further research to compare compliance of SMEs in the other sub-counties in

Bomet namely, Chepalungu, Bomet East, Bomet Central and Konoin. It further recommends a

comparative research in Kericho County.

.

ix

TABLE OF CONTENTS

STUDENT’S DECLARATION .................................................................................................. iii

COPYRIGHT ............................................................................................................................... iv

DEDICATION ............................................................................................................................... v

ACKNOWLEDGEMENT ............................................................................................................ v

ABSTRACT .................................................................................................................................vii

TABLE OF CONTENTS ............................................................................................................. ix

LIST OF TABLES .......................................................................................................................xii

LIST OF FIGURES .................................................................................................................... xiv

ABBREVIATIONS ...................................................................................................................... xv

CHAPTER ONE ............................................................................................................................ 1

1.0 INTRODUCTION ............................................................................................................ 1

1.1 BACKGROUND OF THE STUDY ................................................................................. 1

1.2 STATEMENT OF THE PROBLEM .............................................................................. 4

1.3 GENERAL OBJECTIVES OF THE STUDY ................................................................ 5

1.4 SPECIFIC OBJECTIVES OF THE STUDY ................................................................. 5

1.5 IMPORTANCE OF THE STUDY .................................................................................. 5

1.6 SCOPE OF THE STUDY ................................................................................................. 6

1.7 DEFINITION OF TERMS .............................................................................................. 6

1.8 CHAPTER SUMMARY................................................................................................... 7

CHAPTER TWO ........................................................................................................................... 8

2.0 LITERATURE REVIEW ................................................................................................ 8

2.1 INTRODUCTION ............................................................................................................ 8

2. 2 LEVEL OF KNOWLEDGE OF THE TAX SYSTEM AND TAX COMPLIANCE 8

2.3 TAX RATES AND HOW TAX COMPLIANCE ......................................................... 12

2.4 FINES AND PENALTIES AND TAX COMPLIANCE ............................................. 16

x

2.5 CHAPTER SUMMARY................................................................................................. 18

CHAPTER THREE ..................................................................................................................... 20

3.1 RESEARCH METHODOLOGY .................................................................................. 20

3.2 INTRODUCTION .......................................................................................................... 20

3.3 RESEARCH DESIGN .................................................................................................... 20

3.3 POPULATION AND SAMPLING DESIGN ............................................................... 20

3.4 DATA COLLECTION METHODS .............................................................................. 23

3.5 RESEARCH PROCEDURES ........................................................................................ 24

3.6 DATA ANALYSIS METHODS .................................................................................... 24

3.7 CHAPTER SUMMARY................................................................................................. 25

CHAPTER FOUR ....................................................................................................................... 26

4.0 RESULTS AND FINDINGS .......................................................................................... 26

4.1 INTRODUCTION .......................................................................................................... 26

4.2 RESPONSE RATE AND DEMOGRAPHICS ............................................................. 26

4.3 THE EFFECT OF TAX KNOWLEDGE ON COMPLIANCE ................................. 30

4.4 THE EFFECT OF TAX RATES AND COMPLIANCE ............................................ 36

4.5 THE EFFECT OF FINES AND PENALTIES AND TAX COMPLIANCE ............. 39

4.6 CHAPTER SUMMARY................................................................................................. 45

CHAPTER FIVE ......................................................................................................................... 46

5.0 SUMMARY, DISCUSSION, CONCLUSION AND RECOMMENDATIONS ........ 46

5.1 INTRODUCTION .......................................................................................................... 46

5.2 SUMMARY ..................................................................................................................... 46

5.3 DISCUSSION .................................................................................................................. 48

5.4 CONCLUSION ............................................................................................................... 51

5.5 RECOMMENDATIONS................................................................................................ 52

REFERENCES ............................................................................................................................ 54

APPENDICES .............................................................................................................................. 61

APPENDIX I: RESEARCH LETTER ............................................................................... 61

APPENDIX II: NACOSTI PERMIT .................................................................................. 62

xi

APPENDIX III: COVER LETTER .................................................................................... 64

APPENDIX IV: QUESTIONNAIRE .................................................................................. 65

xii

LIST OF TABLES

Table 3.1 Target Population……………………………………………………………...23

Table 3.2. Sample Size……………………………………………………………...……26

Table 4.1: Highest Level of Education Attained by Owner or Employee……………….31

Table 4.2: How Long Have You Been in Operation or Worked for Your Company?......32

Table 4.3: What Is Your Main Business Activity?............................................................32

Table 4.4: Monthly Sales Level…………………………………………………...……. 33

Table 4.5: Size of Your Business in Terms of Employees…………………………….....33

Table 4.6: Tax Knowledge and Tax Compliance…………………………...…...…….…35

Table 4.7: Correlations on Tax Knowledge Level and Compliance……………….….…36

Table 4.8: Model Summary of Tax Knowledge Level and Compliance……………...….37

Table 4.9: ANOVA of Tax Knowledge Level and Compliance……………………........37

Table 4.10: Model Coefficients of Tax Knowledge Level and Compliance…………….38

Table 4.11: How Often Respondents Attended Taxpayer Education/Sensitization……...39

Table 4.12: Sources of Tax Information………………………………………………....40

Table 4.13: Tax Rates and Tax Compliance……………………………..………………41

Table 4.14: Correlations on Tax Rates and Compliance…………………………………42

Table 4.15: Model Summary of Tax Rates and Compliance…………………………….43

Table 4.16: ANOVA of Tax Rates and Compliance…………………………………….43

Table 4.17: Model Coefficients of Tax Rates and Compliance………………………….44

Table 4.18: Fines and Penalties and Tax Compliance…………………………………………….45

Table 4.19: Correlations on Fines and Penalties and Compliance……………………….46

Table 4.20: Model Summary of Fines and Penalties and Compliance…………………..47

xiii

Table 4.21: ANOVA of Fines and Penalties and Compliance…………………………...47

Table 4.22: Model Coefficients of Fines and Penalties and Compliance………………..48

Table 4.23: Reasons for Penalization…………………………………………………….49

Table 4.24: Model Coefficients……………………………………………….…………50

xiv

LIST OF FIGURES

Figure 4.1: Response Rate……………………………………………………………….30

Figure 4.2: Are You Employed or Own the Business?......................................................31

Figure 4.3: Presence of a Professionally Trained Accountant…………………………...34

Figure 4.4: Attendance of any Taxpayer Education/Sensitization……………………….39

Figure 4.5: Have You Ever Been Fined or Penalized for Failing to Pay Taxes?...............49

xv

ABBREVIATIONS

KRA- Kenya Revenue Authority

SME- Small and Medium Enterprises

VAT- Value Added Tax

CHAPTER ONE

1.0 INTRODUCTION

1.1 BACKGROUND OF THE STUDY

Small and medium-sized enterprises (SMEs) refer to a business or company that employs

fewer than 250 persons and has an annual turnover not exceeding 50 million euros and an

annual balance sheet not exceeding 43 million euros (E.U Law 2003/361). The SMEs

constitute a huge proportion of the national economy in most countries globally. In Europe,

there are approximately 23 million of them in the European Union, which account for 99% of

all enterprises and provide around 75 million jobs. (E.U Law 2003/361).

The importance of SMEs in the economic development of any country in recent years cannot

be underrated especially with regard to creation of employment, innovation, uplifting the

people’s standard of living and financial contribution to the growth of the country’s Gross

Domestic Product (Machira & Irura, 2012). Small and Medium Enterprises (SMEs) are

considered as a key engine of economic growth in developing and developed countries

(Nahida, Coop, Freudenberg, & Sarker, 2014). SMEs in Kenya are considered as sources of

employment generation, economic growth, and social transformation. A significant proportion

of the SMEs are formal, while majority fall within the informal economy based on their size,

location, ownership, status of formality and economic activity, together, as major job

providers, they produce a significant share of total value added, and provide a large segment of

the poor and middle-income populations with affordable goods and services (Kenya National

Bureau of Statistics MSME report, 2016).

It is noted by Tambunan (2008) that Small and Medium Enterprises (SMEs) play a vital

role in economic development, as they have been the main source of employment

generation and output growth, both in developing as well as in developed countries. He

also states that in developing countries, the role of SMEs becomes more crucial as they

have the potential for the improvement of income distribution, employment creation,

poverty reduction and export growth. It also leads to the development of entrepreneurship,

industry and the rural economy. It is important that they comply with government tax

policies. Kenya is ranked among countries with the low tax compliance as a result of

inefficient and ineffective tax administration (KRA, 2004).

Tax compliance is the taxpayers' ability and willingness to comply with the relevant tax laws

and regulations (Ayuba, Saad, & Ariffin, 2016). This is also referred to as the accurate

2

reporting of income and claiming of expenses in accordance with stipulated tax laws (Saipei &

Kasipillai, 2013). Tax collection has been a major concern among many governments all over

the world (Loureiro, 2014). Tax compliance is one of the major challenges facing small and

medium enterprises (SMEs). According to Pope and Abdul-Jabbar (2008), government

regulations, particularly taxation, are a major concern for the business sector throughout the

world. International experience demonstrates that regulatory burdens appear to fall

disproportionately on small and medium enterprises (SMEs). Businesses, in whatever form,

size and/or sector are required by law to comply with all relevant legislation, including

taxation.

In European countries, small and medium businesses play a significant role (Kaledin et al.,

2018). Faridy et al., (2014) state that in Bangladesh, 768 922 listed SME establishments

account for about 45% of the total value-added in manufacturing; 80% of industrial

employment; about 25% of the total labor force; and 90% of all businesses. They found that, in

terms of Bangladesh SME compliance with VAT law, the complexity of the law can influence

taxpayers’ ability to comply. They discovered that because of the complexity of the tax system,

some businesses (those who can afford it) may engage expert tax professionals to help them

with sophisticated tax planning to minimize tax payments. Additionally, they found that

negative perceptions about government policy and spending of tax revenue may contribute to

non-compliance. Other negative influences on compliance include perceptions of tax officers

being unfair, corrupt and abusing the discretionary power afforded to them.

SMEs in Malaysia are subject to income tax, either as individual (unincorporated businesses)

or as corporate taxpayers (incorporated businesses), depending on the business establishment

(Pope and Abdul-Jabbar 2014). The taxation of individual and corporate businesses is

governed by the ITA 1967, with almost similar tax provisions. Business taxpayers are required

by law to file an annual tax return correctly and in full, to keep sufficient records and

documentations and to observe other tax-related requirements. Additionally, businesses are

required to implement the Scheduler Monthly Tax Deduction Scheme and to furnish certain

returns on behalf of their employees. Businesses subject to indirect tax are further required to

comply with all applicable provisions under the respective acts. Besides direct and indirect

taxes imposed by the federal government, businesses are also required to comply with state and

local government taxes, including property taxes and various business permits and licensing.

Compliance to the above regulatory requirements is mandatory in nature. International

experiences often indicate the difficulties faced by SMEs in managing government laws and

3

regulations (Fernandez & Oats, 1998), particularly in maintaining proper records for

management and taxation purposes. The issues facing small businesses in relation to regulatory

costs are worldwide phenomena and almost identical in the US, UK, Australia and New

Zealand. These include a lack of understanding of the regulatory requirements and frequent

changes in regulations (Chittenden, Kauser, & Poutziouris, 2003).

In Malawi, over 52,000 SMEs contribute about 30% of total tax revenues (Malawi revenue

collection reports, 2011-2017). To mitigate risks associated with SME non-compliance, tax

administration in Malawi has implemented a number of strategies either as deterrence

measures or as a treatment to factors that encourage such behaviors. These include taxpayer

education, exemption from penalties for voluntary disclosure of underpayments, adoption of an

electronic fiscal device (EFDs) as risk management innovation, modernization of its systems.

There has been a minimal impact as SMEs are numerous, difficult to handle, therefore making

them risky group. Moreover, they are challenged with limited management skills and formal

education, access to credit, lack of technical know-how and inability to acquire skills and

modern technology. Further to this, SMEs lack access to credit (Basteri, 2016), a poor keeping

of business transactions leaving no audit trail (OECD, 2004). Despite all the initiatives taken

by tax administration in improving tax compliance in Malawi, SMEs overall compliance level

remains as low as 30% (2015/2016 MRA Annual Operations Report).

Kiwanuka (2004) posits that inadequate knowledge and skills about tax procedures are the

major qualities of most SMEs in Uganda, as most owners hire incompetent family members to

keep proper financial records. Many SME taxpayers do not know the domain of tax

professionals since they lack the independence and have no tax competency (European

Commission, 2007; Nakiwala, 2010). According to MoF & MoR (2007) one of the chief

features of SMEs is the lower level of the specialist tax expertise and greater owner-

involvement in day-today management and this call for them to search for assistance from

experts (Bertolini, Borgia, & Siegel, 2010). Consequently, Uganda is still characterized by the

low income tax compliance levels, in the face of the numerous advocacies for voluntary tax

compliance (Ayoki, 2008; Kangave, 2005; Bird, 2004). Therefore, the government has adopted

tax compliance administrative measures like penalties, rates and tax audits to ensure tax

enforcement instead of compliance (Kayaga, 2007), which have still failed to yield. Uganda’s

income tax compliance was very low at 38% by the end of 2005 (Ayoki, 2007).

4

In Kenya, 34.3% of the total economy is contributed by SMEs, which accounts for 77% of the

total employment statistics (Ouma et al, 2007). The government of Kenya has made attempts to

bring the underground economy into the tax net under the presumptive tax by introducing the

Finance bill of 2007 implemented in 2008. It was named the Turnover Tax (TOT). It is a

simple tax on the gross income of any resident person whose turnover from business does not

exceed Kshs.5 million during any year of Income. It was introduced by the Finance Act of

2007 through a provision of the Income Tax Act, Cap 470, and effective as from 1st January

2008. This is aimed at mobilizing revenue from the SMEs and improve their compliance

(Income Tax Act, Cap 470).

Ouma et al. (2007) opined that the TOT has however, failed to produce the desired results

because the SMEs in Kenya are fond of tax evasion because most of them are not registered by

the government through the proper process, and therefore remain undetected and pay no tax.

He says that those registered have tendencies of under-declaring their taxable income which

misrepresents their expenses, thereby translating into lower tax burden for them. Tax

compliance has been a major concern among many governments all over the world (Loureiro,

2014; Ayuba, Saad and Ariffin, 2016). According to Agbadi (2011), history has shown that

there has always been a reluctance to pay tax by SMEs. Again, statistical evidence has proven

that the contribution of income taxes to the government's total revenue by SMEs remained

consistently low (Chebusit et al., 2014). Over the last forty years, tax compliance in Kenya,

experienced large fluctuations when measured as a ratio of actual tax share of gross domestic

product (Waris, Kohonen, Ranguma and Mosioma, 2009). Most SMEs do not pay the taxes

and tax evasion among SMEs remains far above the ground, with a tax gap of about 35% and

33.1% in 2011 and 2012 respectively (KRA, 2015).

From the Kenya National Bureau of Statistics SMEs report 2016, Bomet County has 14,000

licensed SMEs. 95.9% of these are micro while the rest are small.

1.2 Statement of the Problem

SMEs are important players in a country’s tax system because they remit taxes. Hanlon (2007)

opines that, though the evidence is not unequivocal, most research suggests that traders who

are small business owner are more likely to cheat and not comply than other groups of

taxpayers. Small business owners are considered a high risk group in terms of tax compliance

by the Organization for Economic Co-operation and Development (OECD). In many cases

though, it is impossible to prove noncompliance (Kircher, 2007).

5

Karingi (2005) opines that tax plays an important role in the growth of any economy, so tax

compliance is useful to the economy because tax evasion hampers government revenue

collection, thus inefficiency in government spending as it diminishes the capacity of the state

to mobilize domestic revenues, resources that are needed for investments. He says that in 2010

for example, the amount lost to tax evasion represented about twice the amount the country

spent on health care. He posits that tax evasion also damages the country's growth capacity by

discouraging both local and foreign investors. According to Karingi, the high tax rate and

burden in Kenya, which is related to the high levels of tax evasion, is the leading disincentive

to business activity. There has been hostility between the taxpayers and tax collectors on issue

relating to tax compliance in Kenya (Makori, 2013). Most SMEs do not pay the taxes and tax

evasion among SMEs remains far above the ground, with a tax gap of about 35% and 33.1% in

2011 and 2012 respectively (KRA, 2015).

It is for this reason that research need to be undertaken to identify the impact of tax compliance

among SMEs in Sotik sub-county. It is also instructive to note that while extensive research

that has been done in this area, there has been none in Bomet county or even Sotik sub-county

specifically. In this context, there should be an understanding on the impact of tax compliance

to enable the county government to improve on its tax collection among the SMEs in Sotik

sub-county.

1.3 General Objectives of the Study

The objective of this study is to evaluate the impact of tax compliance on performance of small

and medium enterprise within Sotik sub-county of Bomet county in Kenya.

1.4 Specific Objectives of the Study

1.4.1 To assess how the level of tax knowledge affects compliance of SMEs in Sotik sub-

county of Bomet county in Kenya.

1.4.2 To assess the extent to which tax rates affect tax compliance among SMEs in Sotik

sub-county of Bomet county in Kenya.

1.4.3 To assess the effect of fines and penalties on tax compliance of SMEs in Sotik sub-

county of Bomet County in Kenya.

1.5 Importance of the Study

1.5.1 To the county and sub-county administrations

The findings of this research is of significance to the county administration as it will help them

to come up with better tax and licensing policies which will hopefully reduce compliance

6

costs, fines, penalties, tax knowledge, the complexity of tax system and tax compliance for the

SMEs.

1.5.2 SMEs in Sotik sub-county of Bomet County in Kenya

The findings of this study will also be useful to the SMEs in the sub-county. It will help them

come up with ways of overcoming their challenges on tax compliance and hence adhere to tax

policies more.

1.5.3 Researchers

The findings of this study will hopefully advance the existing literature on taxation, which will

be of significance to researchers as part of their empirical studies.

1.5.4 Traders

This study seeks to examine the determinants of tax compliance by SMEs including

supermarkets, retail stores, financial and money transfer services, small restaurants and hotels

and other SMEs in Bomet County in Kenya. The study will sample the employees and owners

of the SMEs in the county.

1.6 Scope of the Study

This study will primarily focus on micro, middle and small enterprises in the Sotik sub-county

of Bomet County in Kenya. The sub-county is divided into 5 wards namely Ndanai, Chemagel,

Kipsonoi, Kapletundo and Rongena. There are 400 SMEs in the sub-county and a sample of

30% that is, 120 SMEs will be taken for this study. SMEs from each ward will be investigated.

The research will be done starting September 2019. Questionnaires and interviews will be used

to gather data, which will then be analyzed using SPSS.

1.7 Definition of Terms

1.7.1 Tax

Aumeerun, Jugurnath, and Soondrum (2016) define tax as income which is paid to the

government in order to fulfill the need of the public. It is the revenue that government receives

as a percentage of each individual’s income. Besides being the major source of income to the

government, taxation is another way to achieve the macroeconomic aims of a country.

1.7.2 Tax Compliance

Ayuba, Saad and Ariffin (2016) define tax compliance as the ability and willingness of

taxpayers to comply with the relevant tax laws and regulations. Saipei and Kasipillai (2013)

define it as the accurate reporting of income and claiming expenses according to the stipulated

tax laws.

7

1.7.3 Small and Medium Enterprises

According to E.U Recommendation 2003/361, small and medium enterprises (SMEs) are

business companies that employs fewer than 250 persons and has an annual turnover not

exceeding 50 million euro and an annual balance sheet not exceeding 43 million euros.

1.8 Chapter Summary

This chapter provides the background information on tax compliance of SMEs. The problem

statement further explains the gaps in research done in Bomet County in Kenya. The general

and specific objectives which will guide the research have been clearly articulated. They are: to

to assess how the level of tax knowledge of SME owners and operators affect tax compliance

by SMEs in Bomet county in Kenya, to assess how tax rates affect compliance by SMEs in

Sotik sub-county of Bomet county and to assess the effect of fines and penalties on tax

compliance of SMEs in Bomet County in Kenya. The scope and justification of this research

have been highlighted. The next chapter will be the literature review of past researches done in

this field based on the specific objectives. The third chapter will outline the methodology to be

used in for data collection and analysis. Chapter four will present the findings of the research

in tables and charts. Chapter five will contain conclusions from the findings of the study and

will also include recommendations.

8

CHAPTER TWO

2.0 Literature Review

2.1 Introduction

This chapter presents the theoretical background to the study by objectives. It looks at the tax

rate, knowledge of tax systems and fines and penalties in relation to tax compliance by SMEs.

Finally, this chapter looks at the research gaps and summary of the whole chapter.

2. 2 Level of Knowledge of the Tax System and Tax Compliance

A Research done by Kamleitner et al. (2012) argues that knowledge specific to tax is necessary

for small business owners to willingly comply. According to Kirchler (2014), compliance of

tax has a significant relationship with one’s general level of education. He opines that one

fundamental way of increasing compliance is by raising public awareness to boost knowledge

of taxpayers. SMEs did not pay their obligations because they did not understand the tax law

requirements (Lumumba, 2010). Tax knowledge is closely related to the ability of taxpayers to

understand and comply with tax regulations and laws (Palil, 2011). A contrary research by

Ranharamak (2014) opined that increasing tax knowledge did not have a significant impact on

perceptions of fairness and tax compliance attitudes among SMEs.

Taxpayer education can be described as a method of educating the people about the whole

process of taxation and why they should pay tax (Aksnes, 2011). It assists taxpayers in meeting

their tax obligations to the government. This means that the primary existence of taxpayer

education is to encourage voluntary compliance amongst taxpayers. According to Misra

(2004), the main objective of tax payer education is in three folds: impart knowledge as regards

tax laws and compliance; change taxpayer’s attitude towards taxation and increase tax

collection through voluntary compliance. Tax compliance in pure administrational terms

therefore includes registering or informing tax authorities of status as a taxpayer, submitting a

tax return every year, if required and following the required payment time frames (Mohd et al.,

2011). In contrast, the wider perspective of tax compliance requires a degree of honesty,

adequate tax knowledge and capability to use this knowledge, timeliness, accuracy, and

adequate records in order to complete the tax returns and associated tax documentation.

2.2.1 Knowledge of Tax Systems and Compliance of SMEs Globally

A study conducted by Normala (2007) to examine the influence of tax education, as a

procreative approach to enhance the voluntary tax compliance, among the taxpayers, in

Malaysia. Using questionnaires administered to the taxpayers and the tax officials, the

9

respondents confirm the increase in the tax knowledge increase the level of voluntary tax

compliance. The statistical findings confirm that there is a significant relationship between the

level of tax education and voluntary tax compliance. Another study was carried out by Rasshid

and Noor (2004) to evaluate the influence of tax knowledge on the tax compliance behavior

among the taxpayers in Malaysia. The objective of the study was to investigate the effect of

the presence of tax knowledge and understanding, on the level of tax compliance behavior.

Analyzing the data collected using questionnaires to compare the compliance behavior of

taxpayers with significant level of tax knowledge with those without tax knowledge. Statistical

findings confirmed that those with tax knowledge had higher level of compliance than those

without, which indicated a significant relationship between the level of tax knowledge and the

level of tax compliance.

Another study by Cyrlje (2015) to investigate the effects of tax literacy as an instrument of

combating and overcoming tax system complexity, low tax morale and tax non-compliance in

Croatia concluded that tax literacy in the financial dimensions possesses specific tax oriented

financial knowledge on accounting and numeracy skills required for managing tax calculations.

Tax literacy was intended to help individuals receive information about taxes, to explain those

taxes within a domestic system as well as regional and international system. The aim of this

paper was to stress out that the complexity of the taxation system as well as some other

problems like those that low tax morale and low tax compliance might be combated through

promotion and implementation of tax literacy initiatives and programs. By acquiring basic

knowledge of taxation and public expenditures, individuals become able to efficiently manage

their personal finances and understand the basic logic of possible effects of fiscal policy. On

the other side, if individuals are not taught the basic concepts of taxation, and never acquire

needed numeracy skills, they might be more prone to problems like indebtedness or non-

compliance of their tax obligations. Another study conducted a study to determine how

enhanced tax knowledge and tax attitudes affect the compliance behavior among the taxpayers

in New Zealand concluded that the compliance behavior of the taxpayers after acquiring the

tax knowledge did not have significant relationship with tax compliance behavior (Lin and

Carrol, 2000).

Findings of a research done by Mukhlis et al. (2013) show that tax knowledge is strongly

influenced by the education level of the taxpayers. Their research concluded that basically the

SME sector businesses can understand their tax obligations when there is the aspect of justice

and tax benefit can be received in real terms by businesses in the SME sector in East Java. A

similar research done by Mukasa (2011) gave the result that the tax knowledge and perceived

10

fairness taxes have a causal relationship with tax compliance. Therefore, it is important to

analyze the role of education as far as the role of the tax, the tax knowledge and a sense of

justice taxpayer to tax compliance businesses, especially SMEs crafts field in East Java.

In areas of taxation laws and the role of tax in national development, it is necessary to increase

public awareness through knowledge of the tax system, especially to explain where and how

the money collected is spent by the government (Rizal, 2010). Heightened awareness would

encourage people to register as taxpayer. Most citizens do not have much understanding of

what tax laws mean and why the tax system is structured and administered as it is. Knowledge

is related to the ability of a taxpayer to understand and comply with taxation laws. Information

on opportunities to evade tax and the general understanding of tax laws and regulation is the

aspect of knowledge that is related to compliance. Enhancement of tax knowledge improves

one’s attitude towards compliance, and hence reducing one’s inclination to evade tax (Eriksen

and Fallan, 1996).

2.2.2 Knowledge of Tax Systems and SME Compliance in Africa

Previous studies by Kirchler & Maciejovsky (2001) and Park & Hyun (2003) found that

reduced complexity and greater tax knowledge increases tax compliance. Furthermore, based

on the slippery slope framework, Kirchler et al. (2008) concluded that subjective tax

knowledge and participation in the use of taxes has a positive relationship with trust, whereas

low understanding has a negative relationship with trust. Therefore, higher knowledge

regarding taxes leads to higher compliance. Studies by Newman and Nokhu (2018) to find out

if lack of tax knowledge contributed to high levels of tax non-compliance amongst SMEs in

Zimbabwe used a quantitative research approach with a sample of 35 SMEs and 40 tax

officials. The study found out that while the SMEs had basic tax knowledge, they did not

deeply understand it. For instance, the difference between presumptive and income-based

taxation. However, this did not influence their compliant behavior significantly. The study

further found out that tax rates and corruption need to be addressed for tax knowledge to have

any positive influence on compliance of SMEs.

A study by Carroll (2011) on taxation among SMEs in the informal sector in Ghana found out

that despite the fact that more than half (65 per cent) of the SMEs surveyed were aware that

they have to pay taxes, more than half were not well informed as to why they paid tax and

more than 50 per cent did not enjoy the benefits of paying it. However, he opines that tax

education alone cannot guarantee continued tax compliance. Studies done by Machogu and

Amayi (2013) on the effect of taxpayer education on voluntary tax compliance among SMEs in

11

Mwanza city in Tanzania concluded that level of taxpayer education affected the tax

compliance of the SMEs.

According to Mo (2003), complicated tax legislation and ongoing changes of the tax code

confuse tax administrators and taxpayers alike. This produces ample opportunity for tax

avoidance and non-compliance. Furthermore, it results in tax evasion which is not intentional,

but occurs due to lack of knowledge. In extreme cases, tax evasion and avoidance even become

inevitable when the tax system becomes too complex and/or contradictory to follow. Studies

by Errard (1998) showed that standard models assume that tax payers are fully informed in all

the aspects that cover the tax reporting processes, which is just a strong assumption and not the

case usually. Research shows that degree of information is an important factor on the behavior

of tax payers and that it influences tax evasion. Taxpayers with little education are not exposed

to tax compliance information very much, and hence are more prone to evasion. Some tax

payers find the complexity of tax information a little more difficult to understand compared to

others, which may lead to unintentional non-compliance if tax payers encounter problems

when filling tax returns.

2.2.3 Effect of the Level of Tax Knowledge on SME Compliance in Kenya

According to Muiru (2012), businesses contemplating significant transactions are often faced

with the problem of not knowing, with some degree of certainty, what the tax outcome of those

transactions would be. This uncertainty could sometimes mean a deal is aborted because an

adverse tax treatment could make it commercially non-viable. The situation is further

complicated by the complexity of our tax laws and the fact that they are subject to change from

time to time. Tax education should start at primary level with an emphasis on promotion of

voluntary compliance. The non-compliance may be unintentional, where the taxpayer is not

aware of his/her tax obligations or fails to fulfill his/her tax obligations due to ignorance of tax

laws and procedures or may be intentional due to the compliance attitudes. Future studies that

investigate the impact of informal and formal education could be useful to compliance of

taxpayers (Alasfour, Samy & Bampton, 2016).

With Kenya Revenue Authority (KRA) as the main tax authority in Kenya, Taxpayer

Education Unit was formed in the year 2005. It was formerly known as Taxpayer Services

under the Commissioner for Corporate Support Services. It then moved to the Marketing &

Communication Division in 2008 as a section mandated with internal and external education.

Its function is compiling and disseminating effective practices through advocacy programs to

stakeholders and taxpayers.

12

Regression results on the effect of tax payers’ knowledge and tax rates on tax compliance

amongst SMEs in Nakuru county in Kenya conducted by Aondo and Sile (2018) revealed that

tax payers’ knowledge has a positive and significant effect on tax compliance amongst SMEs

in Nakuru County Kenya. This means that an improvement in tax payers’ knowledge leads to

an improvement in tax compliance. The findings were that tax learning had positively huge

effect on tax compliance. Prescription that legislature ought to energize tax payers’ information

about assessment laws and standards, in this way making mindfulness for the common

advantages of the administration and the taxpayers.

2.3 Tax Rates and Tax Compliance

Tax compliance will increase when the tax rate rises. This is according to a study done by

Hashimzade et al. (2012). Although increasing marginal tax rates would likely encourage

taxpayers to evade taxes (Torgler, 2007; Witte & Woodbury, 1985), reducing tax rates does not

necessarily increase tax compliance (Kirchler, 2007). The tax rate is an important factor in

determining tax compliance behavior, although the exact impact is still unclear and debatable

(Kirchler, 2007). Furthermore, raising marginal tax rates will likely encourage taxpayers to

evade tax further (Ali, Cecil, & Knoblett, 2001; Torgler, 2007), whereas lowering the tax rates

does not necessarily increase tax compliance (Kirchler, 2007). In line with Kirchler (2007),

Inasius (2015) also indicates that the perception of the tax rate has no significant impact on tax

compliance. Although the impact of tax rates is debatable, Kirchler et al. (2008) and

McKerchar and Evans (2009) suggest that the degree of trust between taxpayers and the

government has a major role in ascertaining the impact of tax rates on compliance. When trust

is low, taxpayers perceive a high tax rate as unfair and when trust is high, taxpayers might

consider the same level of tax rate as contributing to the community (Kirchler et al., 2008).

2.3.1 How Tax Rates Affect Compliance of SMEs Worldwide

A study was conducted by Helhel and Ahmed (2014) in Sana’a, the capital city of Yemen to

evaluate and rank the factors that reduce taxpayer compliance. The results indicated that, high

tax rates and unfair tax system are the two most crucial factors associated with low

compliance. Furthermore, insufficient tax auditing, little deterrent effects of tax penalties and

tax amnesties enacted frequently have impact on taxpayers’ compliance decision. According to

Allingham and Sandmo (1972), a key comparative static result is that when the tax rate goes

up, competing income and substitution effects might lead to more or less tax compliance. The

substitution effect encourages evasion since the marginal benefit of cheating goes up with the

tax rate. On the contrary, the income effect tends to suppress evasion since a higher tax rate

13

makes the taxpayer with decreasing absolute risk aversion feel worse-off, and thus decrease

risk-taking. Therefore, the net effect is ambiguous.

According to Mungaya (2012), whenever prices increase due to increase in tax rates, there is a

drop in the consumption rate and a decrease in sales volumes which leads to retarded growth of

SMEs. Tax payment is among the outflows of cash from the business which reduce the

purchasing power of an enterprise. This is due to the fact that a large amount of cash collected

is used to pay taxes rather than to expand the business. The study showed that the purchasing

power of an enterprise drops immediately it pays taxes. It is generally agreed that high tax rates

increase tax burden, therefore lowering taxpayer’s disposable income (Chipeta, 2002). Aside

from the tax rate, the overall tax system greatly influences one’s decision to pay taxes. If an

individual is faced with what they consider a high tax rate, they may decide to declare only a

part of their taxable income, despite the fact that the tax rates on corporate profits are relatively

low. Some companies can use tax loopholes to pay little tax, and hence emphasize the

unfairness of the system that is perceived. This shows that the disposition of a taxpayer to

avoid and evade tax is greatly impacted by how the overall tax system is structured.

2.3.2 Tax Rates and SME Compliance in Africa

Research by Mas’ud et al. (2014) examined the correlation as well as the effect of tax rate on

tax compliance in Africa using cross-country data. The findings showed that there is significant

negative correlation between tax rate and tax compliance. In South Africa, studies conducted

by economy watch dog on tax burdens on SMEs revealed that tax requirements procedures

acted as stumbling blocks to tax compliance. A majority of SMEs experience their tax liability

as an increasing burden since they lack enough skilled staff to handle tax compliance issues

and are therefore, forced to incur “extra‟ tax costs. Most SMEs do not even recognize the tax

incentives and services available to them. The study also noted that changes in tax policies

sometimes result in an even more complex tax system. A clear finding was that elaborate tax

incentive schemes which require sophisticated systems and skilled staff would often result in

increasing compliance costs rather than provide real tax relief. As a result, small businesses

(and probably other taxpayers as well) would prefer simple cuts in tax rates and penalties.

A study conducted by Atawodi and Ojeka (2012) in North-Central Nigeria to evaluate the

factors that affect tax compliance of SMEs found that most SMEs attributed their non-

compliance to high tax rates and complex filing procedures. They recommended that Small and

Medium Enterprises should be levied lower amounts of taxes so that they will have enough

14

funds for other activities that will lead to business growth. Furthermore, they opined that it

would help SMEs get better equipped to survive in a competitive market.

In Ghana, tax policies and reforms have been instituted to ensure compliance to taxes. For

example, the Internal Revenue Service (IRS) and the Custom Exercise and Preventive Service

(CEPS) were merged into the Ghana Revenue Authority (GRA) to enhance the payments of

taxes and to improve efficiency in tax systems. Furthermore, the e-government project was

introduced in November 2011 by the government of Ghana to link the GRA to the Registrar

General’s Department (RGD) in order to electronically keep tabs on the payment of taxes from

registered businesses. In Ghana, most SMEs’ perception of tax policies is quite unappealing.

SMEs’ perception on tax policies may not only stem on the imposition of taxes but also the

rate of illiteracy of the SMES. It can be noted that most owners of SMES in Ghana are mostly

market women who may have little or no knowledge on tax policies. Complex tax systems

distort the development of SMES and often result in the morphing of groups that offer a lower

or no tax burden hence resulting in tax systems that levies high expenses on the economy. The

efficiency of tax policies depends on the designing of appropriate and rational tax rates,

reducing tax burden of the indigent people and intensifying the fight against the corruption and

the evasion of taxes. The complex nature of tax policies such as multiple taxes, high ports

charges etc. can exert serious burden on SMES. Such complexity in tax policies may results in

SMES hiring agents to explain tax policies which result in additional cost for SMES.

2.3.3 Effect of Tax Rates on Compliance of SMEs in Kenya

According to OECD (2010), fairness of the tax system for all businesses translates into

increased tax compliance. The taxpayer deems the tax system unfair if their business has been

subjected to higher tax burden than other business. As a consequence, taxpayers will evade

paying taxes or under declare taxes as they fall due. Kirchler et al. (2007) affirm that perceived

fairness of the tax system by the taxpayer, translates into increased voluntary compliance as

there is mutual trust between the government and the taxpayer. The heavy taxation is a subject

of worry not only in developed countries like USA but also in Kenya and other less

industrialized countries in Africa and Latin America. For instance, taxes in Kenya confront the

large manufacturing sector in different shapes and shades like import duties, export and excise

duties, sales, VAT, withholdings, income taxes and PAYE and others (KRA, 2011). It is for

most part trusted that a high tax rate is the primary driver of tax evasion. Motivating forces to

sidestep tax rely upon the minimal rates of tax collection on the grounds that these oversee the

increases from evasion as a total of the total sidestepped. One noteworthy evasion of tax is

15

high individual income rate of taxation which tend to direct taxpayers to dodge tax.

Excessively numerous and confounded standards and directions forced by the administration

tend to prompt tax evasion. Organizations discover it by and large troublesome frequently not

beneficial to work together lawfully (KRA, 2011).

Kenya has a complex tax system that makes it expensive for taxpayers to comply with an

increased cost of doing. A tax system that is more complex is costlier to administer, and hence

is more expensive for taxpayers to comply. Corporate income tax rate is 30 percent, personal

income tax rate ranges between 10 percent and 30 percent, VAT rate is 16 percent and while

withholding tax rates begin from 3 percent and depend on income source and whether one is a

Kenyan or not (Government of Republic of Kenya, 2012). Thiga and Muturi (2015) conducted

a study on Factors That impacts Tax Laws compliance amongst Kenyan SMEs and found tax

rates and tax compliance expenses are highest tax compliance contributing factor.

Studies done by Sile and Aondo (2018) revealed that tax payers’ knowledge, tax rates had

positive and significant effect tax compliance amongst SMEs in Nakuru County Kenya. This

means that an increase in tax payers’ knowledge and tax rates led to an improvement in tax

compliance. A study conducted by Mwangi (2014) on factors influencing tax compliance

among SMEs in Nairobi’s Industrial Area concluded that SMEs feel that tax rates for the

already several tax heads, that is, corporate tax, VAT and Pay as You Earn (PAYE) are either

high or very high. A high tax rate erodes taxpayer’s earnings and disposable incomes thus will

have a negative effect on consumption and investments. It will also encourage tax avoidance

and evasion as the opportunity cost to evade is high. This may be an expected reaction from

taxpayers as no single taxpayer can rate a tax rate as 'low'. There is also the problem of

defining the line between 'high', 'low' and 'fair'. The findings of this study do therefore agree

with those of other researchers as discussed in the literature review. As interest rates go higher,

the opportunity cost to evade becomes higher and thus taxpayers get tempted to evade.

(Friedland, 1978). Kenya’s tax rates compare favorably with that of her neighbors, Uganda and

Tanzania, who charge the same rates for corporate tax, withholding tax and VAT. However,

given the large percentage of respondents who feel that they are high, there is need to revise

these rates and make them more attractive to them. This will enhance tax collection by

reducing evasion and enhance investments. For PAYE, a revision of tax bands should be

pursued in addition to reducing tax rates which will also reduce the poverty level.

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2.4 Fines and Penalties and Tax Compliance

Fines and penalty rates may substitute each other due to their multiplicative linkages as long as

neither of them is set to zero (Kirchler et al 2007). Higher fines simply make evading taxes

more hazardous for taxpayers and should deter them from evasion. Empirically, the deterrent

effect of fines could not always be supported. The observed effects were weaker than expected

and some studies even suggest that an increase of penalties can have undesirable effect and

result in more tax avoidance (Kirchler et al, (2007). Alm et al., (1992) supports the evidence

that fines do affect tax compliance though the impact was virtually zero. Despite non-

compliance often being perceived as socially acceptable (Kirchler, 1998; Song and Yarbrough,

1978), people, including small business owners (Adams and Webley, 2001; Hite et al., 1992)

are significantly more compliant than predicted by neoclassical economists who assumes that

compliance depends predominantly on audit probability and fines (Andreoni et al., 1998).

According the records in the Bible, taxation dates back from the times of Jesus Christ, defiance

of tax laws also dates back to the same time. Most People have always had a hostile attitude

towards tax ever since the introduction of tax. “During the Roman Empire, in 60A.D, Boadicea

queen of East Anglia led a revolt that can be attributed to corrupt taxation. In Great Britain, the

100-year war (1337-1453) between England and France was renewed in 1369 by among other

key factors, the rebellion of the nobles of Aquitaine over the oppressive tax policies of Edward,

The Black Prince and in Post-Revolution America; Tax Act of 1864 was challenged several

times” (Director, Tax world Organization, 1999).

2.4.1 Effect of Fines and Penalties on Compliance of SMEs Around the World

A study was conducted by Christina, Deborah and Gray (2003) to determine the economic

and behavioral factors affecting tax compliance among taxpayers in the United States of

America. The objective of the study was to determine the economic and behavioral factors,

affecting the tax compliance among tax payers, in the Arkansas City tax penalty amnesty

system. Arkansas City had announced an amnesty system, whereby the non-compliant traders

were waived of the penalties and fines provided that they were ready to pay their tax liability

supposed to be paid and they did not pay. Tax penalties and auditing were not considered as

adequate deterrent forces by respondents. Some studies reported that the effect of the penalty

rate of increase on voluntary tax compliance was minimal & insignificant. On this basis, it can

be said that if tax penalties are not supported by auditing, they don’t create a significant effect

(Alm et all. 1990). Therefore, it is necessary to reorganize tax laws in order to apply tax

penalties under the strict auditing conditions (Tuay & Güvenç, 2007).

17

In Malaysia, the tax structure, consisting of tax rate, audit rate and penalty rate, is apparently

influential on taxpayers’ compliance behaviors as evident in an experimental study involving

two groups of undergraduate students (Loo, 2006b). A mixed-methods study (a survey and an

experiment) also demonstrated the same findings except for tax audit which was found to be

less effective for salaried taxpayers (Loo, McKerchar, & Hansford, 2009). This may be

because the scheduler tax deduction is imposed on the majority of salaried taxpayers in

Malaysia. However, the penalty rate appeared to be the most influential tax compliance

determinant of tax compliance attitudes in a comparison study of taxpayers’ compliance

attitudes before and after the implementation of the SAS (Loo, 2006a). Despite the tax

structure being evident to deter the non-compliance behavior of taxpayers, the enforcement of

the rules was viewed to be rather loose which may reduce the integrity of the IRBM in the eyes

of taxpayers. Overall, the threat of punishment remains significant in deterring the negative

intentions or attitudes of taxpayers.

Fines and penalty rates may substitute each other due to their multiplicative linkages as long as

neither of them is set to zero (Kirchler et al 2007). Higher fines simply make evading taxes

more hazardous for taxpayers and should deter them from evasion. Empirically, the deterrent

effect of fines could not always be supported. The observed effects were weaker than expected

and some studies even suggest that an increase of penalties can have undesirable effect and

result in more tax avoidance (Kirchler et al, (2007).

2.4.2 How Fines and Penalties Affect Compliance of SMEs in Africa

A research done by Nyamwanza, et.al. (2014) shows that penalties have been found to be the

most effective in enforcing compliance in Zimbabwe. SMEs are struggling to meet their

ZIMRA (The Zimbabwe Revenue Authority) obligations, which is made worse by the heavy

penalties charged by the authorities. Authorities take a number of measures in enforcing

compliance such as garnishing orders, closure of business premises, confiscation, and

penalties. These measures were rated by research respondents in terms of their effectiveness as

follows: penalties (42%), closure of businesses (29%), garnishing orders (12%), and

confiscation (12%).

According to Fishlow and Friedman (1994), tax fraud and evasion are also a result of a weak

judiciary. Addressing revenue shortfalls needs to go hand in hand with legislative reforms

strengthening the rule of law. This includes insufficient punishment and prosecution of

violators which can only be tackled when detected tax criminals face stricter penalties that are

effectively executed by courts. Higher penalties act as a deterrent and help to improve tax

18

compliance. To achieve this goal, governments have to strengthen the rule of law and develop

capacities of investigation authorities.

2.4.3 Fines and Penalties and SME Compliance in Kenya

A study carried out in Kitale town in Kenya on factors affecting tax compliance among small

and medium enterprises by Chebusit et al. (2014) shows that there is a positive effect of fines

and penalties on compliance cost and tax compliance. This indicates that an increase in fines

and penalty the tax compliance improves. Potential to evade tax is usually discouraged by high

penalties and the probability of being edited. The study finds strong support for the argument

that fines and penalties impacts highly on tax compliance, thus there should be moderate levels

of fines and taxes to employ. This way, SMEs will be encouraged to comply since they will

keep accurate records for taxation purposes in order to avoid fines and penalties. Regression

results on the effect of tax payers’ knowledge and tax rates on tax compliance amongst SMEs

in Nakuru county in Kenya conducted by Aondo and Sile (2018) revealed that taxation

penalties had inconsequential positive effect on compliance. A study conducted in Bomet town

concluded that a simple tax regime had the greatest effect. Online tax filing came second, and

tax payers’ education and training was third while stringent tax penalties had the least effect on

the SMEs turn over tax compliance (Kirui et al., 2017). The study also found that all the SMEs

and their employees had been adequately trained by KRA staff on how to file tax returns and

also understood well the dangers/penalties of failure to make returns on or before the maturity

date. Research done by Chebusit et al. (2014) on factors affecting tax compliance among SMEs

in Trans Nzoia concluded that there was a positive effect of fines and penalties on compliance

cost and tax compliance. This indicated that an increase in fines and penalty the tax compliance

improves. The observed effects were weaker than expected and some studies even suggest that

an increase of penalties can have undesirable effect and result in more tax avoidance (Kirchler

et al, 2007). On one hand, fines should be high enough to decrease the expected value of tax

evasion and to assure its deterrent effect on tax payers. The study found a strong support for

the argument that fines and penalties impacts highly on tax compliance, thus they

recommended employment of moderate levels of fines and taxes. This way, SMEs will be

encouraged to comply since they will keep accurate records for taxation purposes in order to

avoid fines and penalties.

2.5 Chapter Summary

This chapter gave a brief introduction of what is expected to be covered in the literature

review, an in-depth coverage of the existing literature on independent variables and dependent

19

variables as elaborated in the specific research objectives. It elaborates the various researches

done worldwide on how tax knowledge affects the tax compliance of SMEs, how tax rates

affect compliance and how threat of punishment by fines and penalties make SMEs comply

with taxes. Chapter three shows the research methodology and research design employed in

this research. Chapter four presents the research findings in tables and figures. Chapter five

features the conclusions drawn from the research as well as recommendations.

20

CHAPTER THREE

3.0 RESEARCH METHODOLOGY

3.1 Introduction

The methodology to be used for this study will be detailed in this chapter. The population of

the study and the sampling design alongside with the data collection methods, research

procedures and data analysis methods will be discussed and explained in detail. The purpose of

this study is to investigate the factors affecting tax compliance of SMEs in Sotik sub-county of

Bomet county in Kenya.

3.2 Research Design

The plan and structure of investigation planned to give answers to the research questions is

referred to as the research design (Cooper, 2008). The plan is the overall scheme or program of

the research. It includes an outline of what the investigator will do from writing hypotheses and

their operational implications to the final analysis of data. Cooper (2008) further opines that

the research design shows the research problem, that is the framework as well as the

organization, how the variables of a study relate and how empirical evidence of those

relationships will be obtained.

Research design can be further defined as the blueprint for collecting, measuring and analysing

data. It is the plan or strategy and structure of the research process, that provides a logical

sequence creating a connection between the research questions, the empirical data that will be

collected and the conclusion thereof (Cooper & Schindler, 2014).

Research design can also be defined as the glue that holds together the research project. A

design is used to structure the research, to show how all of the major parts of the research

project, the samples or groups, measures, treatments or programs, and methods of assignment,

work together to try to address the central research questions. Sachdeva (2009) defined the

research design as how the collections for data collection and analysis are arranged with the

aim of giving relevance to the research purpose with economy in the procedure. This is the

definition adapted for this research. This is because it clearly shows how we intended to carry

out the research.

3.3 Population and Sampling Design

3.3.1 Population

Population is defined as a set of elements of interest in a particular study (Anderson, 2015).

Many situations require information about a large group of elements (individuals, companies,

21

voters, households, products, customers, and so on). But, because of time, cost and other

considerations, data can be collected from only a small portion of the group. The larger group

of elements in a particular study is called the population, and the smaller group is called the

sample.

According to Creswell (2014), population is a group of individuals or entities with some

common characteristic that the researcher plans to study with the aim of generalizing the

findings about the target population.

Population refers to the total collection of elements about which the researcher wishes to make

inference. It is the universe of people, place or things to be investigated (Saunders, Lewis and

Thornhill, 2016).

The focus of the study was on Medium and Small Taxpayers operating within Sotik sub-county

of Bomet county. The population of interest for this study comprised of 400 registered SMEs.

Table 3.1 Target Population

Categories Population Percentage

Supermarkets 11 2.7%

Shops and retail stores 200 50%

Financial and money transfer services 65 16.3%

Small restaurants and hotels 60 15%

Private education institutes 55 13.7%

Petrol stations 9 2.3%

Total 400 100%

Source Bomet County Revenue Office (2019)

3.3.2 Sampling Design

According to Gass (2011), the basis of generalizability is the particular sample selected. Group

of participants will be drawn randomly from the population to which we hope to generalize.

Thus, in considering generalizability, we need to consider the representativeness of the sample.

What this means is that each individual who could be selected for a study has the same chance

of being selected as does any other individual. To understand this, we introduce the concept of

random sampling.

According to Cooper (2008), sampling design is a design, or a working plan, that specifies the

population frame, sample size, sample selection, and estimation method in detail. Objective of

the sampling design is to know the characteristic of the population. It is easier to take

22

information from a sample because collecting information from every member of the

population is impossible because of time, cost and convenience challenges. Information

collected from a sample is often adequate and easier to obtain.

Since we make conclusions about a population based on the information obtained from a

sample, it is important that the units in the sample are representative of the entire population.

The sampling design, which is the method chosen to select the sample from the overall

population, has important consequences. Poor sampling designs can yield misleading

conclusions. A sampling method is biased if it systematically favors certain outcomes (Calder,

2016).

3.3.2.1 Sampling Frame

The source material or device where a sample is drawn from is defined as a sampling frame

(Anderson, 2015). It is a list of those within the population of study who can be sampled. It

includes individuals, households and institutions.

The listing of the accessible population from which the researcher draws their sample is called

the sampling frame. This research was conducting a survey and selecting SMEs from the list of

registered SMEs in Sotik sub-county of Bomet county. The Sotik sub-county list of registered

SMEs is the sampling frame. That ideally was not a great way of doing it, as not all listed

companies were easily accessible, in which case the researcher needed to identify an SME and

randomly investigate their tax compliance behavior. They then drew their using one of the

many sampling procedures. The group that actually completed the study was a sub-sample of

the sample. It did not include non-respondents or dropouts.

3.3.2.2 Sampling Technique

According to Sachdeva (2009), in most surveys, access to the entire population is nearly

impossible, however, the results from a survey with a carefully selected sample will reflect

extremely close results as if provided by the population. Sampling method therefore was a very

important part of this research process. If a researcher surveyed using an appropriate sampling

technique, they can be confident that their results will be generalized to the population in

question. If the sample were biased in any way, it will be inadvisable to make generalizations

from the findings. The two essential types of sampling methods are probability and non-

probability sampling.

This study employed stratified sampling. This is a variant of simple random and systematic

methods and is used when there are a number of distinct subgroups, within each of which it is

23

required that there is full representation. Sachdeva (2009) says that a stratified sample is

constructed by classifying the population in sub-populations (or strata), based on some well-

known characteristics of the population, such as age, gender or socioeconomic status. The

selection of elements is then made separately from within each.

3.3.2.3 Sample Size

This study used a sample of 120 SMEs in Sotik sub-county of Bomet County. The sample was

30% of the population, which conforms to the recommendation by Mugenda and Mugenda

(2006). Stratified and simple random sampling methods were used to select a sample for the

study. Stratified sampling was used to group the SMEs in various categories or strata based on

the type of the SMEs and then simple random sampling method used to select the respondents

from each stratum. Stratified sampling method ensured that sub-groups in the population were

represented in the sample while simple random sample gave each respondent a random chance

of being included in the study.

Formula for sample size= category * 100

Total population

Table 3.2: Sample Size

Categories Population Sample size

Supermarkets 11 3

Shop and retail stores 200 60

Financial and money transfer services 65 20

Small restaurants and hotels 60 18

Private educational institutions 55 16

Petrol stations 9 3

Total 400 120

3.4 Data Collection Methods

The data collected was then organized systematically for analysis, which was done using

qualitative and quantitative methods. It was then evaluated and comparison made so as to

select the most accurate information from the respondents. The quantitative data was analyzed

and presented in tables and figures.

Primary data was collected using a structured questionnaire that had four sections. The first

section had data on the respondent, while the other three sections each answered questions

based on the three research objectives highlighted earlier. The questionnaire had both close and

open ended questions as the researcher needed to collect additional information that the close

24

ended questions might not have covered. A five-point Likert scale was used to measure

responses in the second, third and fourth sections. A commentary section under each section of

the research objective questions was included to cater for any other additional information that

was required for this research. Collection of data was done using drop and pick method of

administering a structured questionnaire to respondents. According to Ghayri and Gronthug

(2015), the questionnaire is among the most popular data collection methods in business

studies. The success strategies used included recruiting and training a research assistant, pre-

survey contact during where the aim of the study was explained and elaborated to respondents,

printing of the questionnaire, precise delivery, follow ups and timely collections.

3.5 Research Procedures

A questionnaire was developed and organized according to the specific objectives of the study.

This was done to ensure relevance to the research problem.

A research assistant was carefully selected, trained and engaged in the administration of the

questionnaire to selected respondents. He ensured that distribution of the questionnaire was

done within the appropriate time to allow the respondents time to properly complete the

questionnaire.

3.6 Data Analysis Methods

According to Blumberg (2014), data is a collection of figures and facts relating to a particular

activity under study. For data to be useful, it must provide answers to the research questions.

Data obtained from the field was systematically organized to facilitate analysis. The data

collected was analyzed using the Statistical Package for the Social Sciences (SPSS) software,

version 26 to retrieve results, which was then evaluated and comparisons made so as to select

the most accurate information from the respondents. The quantitative data was then analyzed

using the Statistical Package for the Social Sciences (SPSS) software, version 26 to retrieve the

results which were then presented in tables and figures.

Dependent variable is the variable that is measured, predicted or monitored and is expected to

be affected by manipulation of an independent variable. It attempts to indicate the total

influence arising from the effects of the independent variable and varies as a function of the

independent variable. In this study, SME compliance is the dependent variable, denoted by

“Y”. Factors that affect compliance are the independent variables denoted by “X”. These are

the variables that the researcher manipulates to determine their effects or influences on the

dependent variable and predict the amount of variation that occurs.

25

Other control variables in the study were ownership, level of education, years of operation,

main business activity, monthly sales level, size of the business in terms of employees and the

presence of a professionally trained accountant denoted as bx1, bx2, bx3…………... bxi

A multi linear regression model was used in the data analysis. The model is in the form:

Y = a+bX1+bX2+bX3+…………...bXi+e; Where

Y- dependent variable (SME compliance)

X1- independent variable (Level of Tax Knowledge)

X2- independent variable (Tax Rates)

X3- Independent variable (Fines and penalties)

a Is the constant and b Slope/ intercept and e Margin of error

3.7 Chapter Summary

This chapter covered the research methodology, which is a detailed description of the process

that the researcher used to conduct field survey. The research methodology is presented in

terms of; research design, population and sampling, sampling design sampling frame, sampling

technique, sample size, data collection methods, research procedure and data analysis methods.

The next chapter will deal with data presentation and analysis. Chapter four presents the

findings of the research in tables and charts. Chapter five has conclusions drawn from the

findings of the research and recommendations.

26

CHAPTER FOUR

4.0 Results and Findings

4.1 Introduction

This section presents the data assembled from the questionnaires by the respondents with

subsequent interpretation of the results in relation to the study. The presentation will use tables,

charts and graphs for the representation of the findings. The study will use Pearson’s

correlations to draw the statistical relationship between the independent variables, which

included the factors that affect tax compliance, and the dependent variable is the compliance of

owners and employees of SMEs in Sotik sub-county of Bomet county.

4.2 Response Rate and Demographics

4.2.1 Response Rate

A total of 120 questionnaires were distributed to the respondents for their participation the

factors affecting tax compliance of SMEs in Sotik sub-county of Bomet county. Figure 4.1

shows the response rate. 120 questionnaires were distributed, and 101 responses collected. This

represents an 84% response rate. This is consistent with Mugenda and Mugenda (2006), who

suggest that a 70% response rate signifies a representative sample for the study, and hence is

sufficient for data analysis. The N Value in this study is 101 (N=101).

Figure 4.1: Response Rate

4.2.2 Responses on if the Respondent was the Owner or Employee

The data in figure 4.2 represents the ownership distribution among the respondents of the

study. The results in figure 4.2 indicate that, majority of the participants, about 66% owned and

27

ran their businesses, whereas about 34% were employed. The study makes a finding that

majority of the SMEs are operated by their owners. The results indicate that most people prefer

to run and operate their own businesses instead of employing someone to do it.

Employee34%

Owner66%

Employee Or Owner?

Employee Owner

Figure 4.2: Owner or Employee

4.2.3 Response on the Highest Level of Education Attained by Owner or Employee

Table 4.1 represents the highest level of education attained by the owners or the employees

who run the SMEs. Most of those who own or run SMEs in Sotik sub-county finished high

school but did not get to graduate level.

Table 4.1: Highest Level of Education Attained by Owner or Employee

Frequency Percent

Cumulative

Percent

Primary Or Below 10 9.9 9.9

Secondary Level 33 32.7 42.6

Above Secondary But Not

Graduate 39 38.6 81.2

Graduate And Above 19 18.8 100.0

Total 101 100.0 N/A

4.2.4 Responses on Years of Operation of the Business

Table 4.2 shows the number of years the SMEs that responded have been in operation. It shows

that majority of them have been in existence for more than 10 years at 35.6%. This shows that

the economic environment of Sotik sub-county encourages businesses to grow.

28

Table 4.2: Period of Operation of the Business

Frequency Percent

Cumulative

Percent

Less Than 3 19 18.8 18.8

3-5 Years 23 22.8 41.6

5-10 Years 23 22.8 64.4

Over 10

Years 36 35.6 100.0

Total 101 100.0 N/A

4.2.5 Responses on the Main Business Activity

Table 4.3 shows the main business activity of the SMEs that responded. Majority are shops and

retail stores including hardware stores and chemists at 46.5%. This means that they are the

majority of taxpayers.

Table 4.3: Main Business Activity

Frequency Percent

Cumulative

Percent

Supermarket 3 3.0 3.0

Shop And Retail Stores 47 46.5 49.5

Financial And Money Transfer

Services 17 16.8 66.3

Small Restaurants, Hotels And

Bars 17 16.8 83.2

Private Education Institutes 14 13.9 97.0

Petrol Stations 3 3.0 100.0

Total 101 100.0 N/A

4.2.6 Responses on Monthly Sales Level

Table 4.4 shows the monthly sales level on the SMEs that responded. It shows that majority of

the SMEs that responded earn between KES 50,0001 and KES 100,000.

29

Table 4.4: Monthly Sales Level

Frequency Percent

Cumulative

Percent

Less Than KES 50,000 30 29.7 29.7

KES 50,000 To KES 100,000 52 51.5 81.2

KES 100,001 To KES 200,000 13 12.9 94.1

KES 200,001 To KES 300,000 2 2.0 96.0

KES 400,001 To KES 500,000 1 1.0 97.0

Over KES 500,000 3 3.0 100.0

Total 101 100.0 N/A

4.2.7 Responses on the Size of Business in Terms of Employees

Table 4.5 shows how big the SMEs that responded are in terms of the number of employees

they have. It shows that most of them, at 77.2% have less than 10 employees.

Table 4.5: Size of Your Business in Terms of Employees

Frequency Percent

Cumulative

Percent

0-10 78 77.2 77.2

11-20 13 12.9 90.1

21-30 9 8.9 99.0

Over 30 1 1.0 100.0

Total 101 100.0 N/A

4.2.8 Responses on the Presence of a Professionally Trained Accountant

Figure 4.3 shows the responses given by SMEs about the presence of a professionally trained

account. 68% of the SMEs interviewed do not have a professionally trained accountant. This

means that they either they do their own book-keeping or they hire someone to do it for them.

30

yes32%

no68%

Presence Of A Professionally Trained Accountant

yes no

Figure 4.3: Presence of a Professionally Trained Accountant

4.3 The Effect of Tax Knowledge on Compliance

The findings in table 4.6 present the findings on how knowledge of tax system and

administration affects tax compliance of SMEs. A scale of 1-5 was used where: 1= Strongly

agree, 2= Agree, 3= Uncertain, 4= Disagree and 5=Strongly Disagree. The study makes a

finding that respondents having enough information on tax and tax procedures at a mean of

2.98 and a standard deviation 0.916 and understanding all types of taxes the respondent is

supposed to comply with at a mean of 2.98 and standard deviation of 0.872 have the biggest

influences on compliance by SMEs. This indicates that, majority of the respondents have

sufficient information on tax and tax procedures and know the types of taxes they are supposed

to comply with and this points towards compliance.

Another factor that greatly influences compliance is awareness of how the tax system is

structured and administered with a mean of 2.77 and standard deviation 0.893. This indicates

that majority of the respondents highly agree that SME owners and employees are aware of

how the tax system is structured and administered.

Encountering problems while filing returns with a mean of 2.75 and a standard deviation of

1.053 is also a great influence of compliance. This shows that owners and employees of SMEs

do not comply when faced with problems while filing returns.

The study implies that knowing how to declare actual income received from all sources to the

tax authority with a mean of 2.60 and standard deviation 0.928 also influences compliance.

The study makes a finding that, key factors as following: Perceived fairness of the tax system

with a mean of 2.58 and standard deviation of 0.983, understanding one’s tax obligations with

31

a mean of 2.49 and a standard deviation of 0.879, keeping up-to-date books of accounts for

one’s business with a mean of 2.45 and a standard deviation of 0.954, taxation rules being too

sophisticated for a non-professional to understand with a mean of 2.30 and a standard deviation

1.285, awareness of tax laws with a mean of 2.09 and a standard deviation of 0.680 and tax

officials no providing accurate advice on tax with a mean of 2.01 and a standard deviation of

1.136 have a strong role in ensuring compliance. The study makes a finding that, perceived

fairness of the tax system had means of 1.94 and a standard deviation of 0.957. This implied

that it did not have much impact on compliance.

32

Table 4.6: Tax Knowledge and Tax Compliance

N Mean Std.

Deviation

Variance Skewness

Statistic Statistic Statistic Statistic Statistic Std.

Error

Awareness of Tax Laws 101 2.09 .680 .462 1.058 .240

Awareness of How Tax

System is Structured And

Administered

101 2.77 .893 .798 -.047 .240

Rules On Taxation Are Too

Sophisticated For A Non-

Professional To Understand

101 2.30 1.285 1.651 .636 .240

Knowledge of How To

Declare Actual Income

Received From All Sources

To The Tax Authority

101 2.60 .928 .862 .416 .240

Understanding of Tax

Obligations

101 2.49 .879 .772 .587 .240

Record-keeping for the

Business

101 2.45 .954 .910 .688 .240

Adequacy of Information On

Tax And Tax Procedures

101 2.98 .916 .840 -.358 .240

Tax Laws Complexity Adds

To Incorrect Tax Returns

101 1.94 .957 .916 1.307 .240

The Tax Officials Do Not

Provide Accurate Advice On

Tax

101 2.01 1.136 1.290 1.067 .240

Encounter Problems When

Filing Returns

101 2.75 1.053 1.108 .357 .240

Perceived Fairness Of The

Tax System Encourages

Compliance

101 2.58 .983 .965 .276 .240

Understanding of all the

Types of Taxes Supposed To

Comply With

101 2.98 .872 .760 -.424 .240

4.3.1 Inferential Statistics

Correlation test helps in evaluating for the existence of statistical association between the

independent variable and the dependent variable. The tests also produce the significant factor,

33

which helps in estimating whether the findings of the study can be inferred for the target

population according to Mugenda, & Mugenda (2006).

4.3.1.1 Level of Tax Knowledge and SME compliance

The data in table 4.7, presents the results of the computation on the effect of the level of tax

knowledge on the compliance of SMEs in Sotik. The correlation establishes a positive

relationship between the level of tax knowledge and the compliance of SMEs. This implies

that, a positive change in the level of tax knowledge will trigger a strong change in tax

compliance of SMEs. The significance reflected at level 0.05, recording a p value of 0.000

which indicates that it is less than the significance. Thus, concluding that its positively

correlated and highly statistically significant (P-Value = 0.000 < 0.05, R-Value = 0.649).

Table 4.7: Correlations on Tax Knowledge Level and Tax Compliance

Compliance Tax Knowledge Level

Compliance Pearson

Correlation

1 .649

Sig. (2-

tailed)

0.000

N 101 101

The R value represents the simple correlation, which is 0.649. The R Square represents the

total variation in the dependent variable (SME Compliance) which can be explained by the

independent variable (Tax knowledge level). From the analysis, R Square value was 0.421,

which implies that 42.1% of the variation in SME compliance was caused by changes in the

level of tax knowledge as shown in table 4.8. The significance had a P value of 0.000 < 0.05,

thus the relationship is highly statistically significant.

Table 4.8: Model Summary of Tax Knowledge Level and Tax Compliance

Mode

l

R R

Square

Adjusted

R Square

Std. Error

of the

Estimate

Change Statistics

R

Square

Change

F

Chang

e

df

1

df

2

Sig. F

Chang

e

1 .649a 0.421 0.415 3.41496 0.421 71.877 1 99 0.000

a. Predictors: (Constant), Tax_Knowledge_Level

34

An ANOVA table shows how well the regression equation fits the data. An analysis was done

at 95% of confidence level. The F critical is 71.877 and the P value is 0.000. This analysis

confirmed that the level of tax knowledge has a relationship with compliance of SMEs as

shown in Table 4.9.

Table 4.9: ANOVA of Tax Knowledge Level and Tax Compliance

Model Sum of Squares df Mean

Square

F Sig.

1 Regression 838.222 1 838.222 71.877 .000b

Residual 1154.531 99 11.662

Total 1992.752 100

a. Dependent Variable: Compliance

b. Predictors: (Constant), Tax_Knowledge_Level

The coefficients table seeks to predict SME compliance from the level of tax knowledge, as

well as determine whether the level of tax knowledge contributes statistically significantly to

the model. The “B” column represents the constant figure to regression equation. According to

Table 4.9, the regression equation will be Y = 17.092 – 0.709 X1, where Y is the dependent

variable (SME compliance) and X1 is independent variable (Tax knowledge level) which

concludes that the level of tax knowledge is taking the constant SME compliance by 17.092

and an increase in the level of tax knowledge results into 0.709 increase in compliance by

SMEs. They are also highly statistically significant. The constant was significant (0.000) as per

Table 4.10 (p < 0.05).

Table 4.10: Model Coefficients of Tax Knowledge Level and Compliance

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std.

Error

Beta

1 (Constant) 17.092 1.670 10.238 0.000

Tax Knowledge

Level

0.709 0.084 0.649 8.478 0.000

a. Dependent Variable: Compliance

35

Figure 4.4 below shows that most SME owners and employees have not attended any tax

education or sensitization at 57%. This greatly affects their compliance.

Figure 4.4: Attendance of any Taxpayer Education/Sensitization

Table 4.11 below shows the frequency with which SME owners and employees have attended

tax education or sensitization events and forums. This is from the 57% who claimed to have

participated in them. The data shows that 31.7% attended annually.

Table 4.11: How Often Respondents Attended Taxpayer Education/Sensitization

Frequency Percent Cumulative

Percent

-1 58 57.4 57.4

Quarterly 3 3.0 60.4

Semi-Annually 8 7.9 68.3

Annually 32 31.7 100.0

Total 101 100.0 N/A

Table 4.12 below shows the sources of information for SME owners and employees. It shows

that there are several sources available for taxpayers, but most of them, at 29.5% get their

36

information from TV and radio. This could be because they are easily accessible and do not

require much effort as compared to written inquiry, which was only done by 2.9% of the

respondents. Only 2% of the respondents read brochures presented by KRA. 13.5% of the

respondents paid personal visits to KRA offices that are in Kericho and Bomet towns. 24.6%

of the respondents had access to newspapers and other print media and hence got their tax

information from. 20.5% of the respondents have access to the internet, mostly through their

mobile phones and hence got their tax information from there. Only 7% of the respondents

called KRA for information.

Table 4.12: Sources of Tax Information

Responses Percent of

Cases N Percent

Source Of Tax

Information

Personal Visit To KRA Offices 33 13.5% 32.7%

Written Inquiry 7 2.9% 6.9%

Brochures 5 2.0% 5.0%

Telephone 17 7.0% 16.8%

TV/Radio 72 29.5% 71.3%

KRA Website 50 20.5% 49.5%

Print Media (newspapers, etc) 60 24.6% 59.4%

Total 244 100.0% 241.6%

4.4 The Effect of Tax Rates and Compliance

The data on table 4.13 presents the mean and Standard deviation of tax rates and compliance of

SMEs in Sotik sub-county in Bomet county. A Likert scale of 1-5 was used where: 1= Strongly

Agree, 2= Agree, 3= Uncertain, 4= Disagree and 5= Strongly Disagree. The study makes a

finding that being able to determine accurately once income and liability is the greatest

influence in complying with a mean of 2.68 and a standard deviation of 0.871. This indicates

that, majority of the respondents comply because they are able to determine how much tax they

should pay. The study establishes that, the second most influential factor was that the rate of

turnover tax being higher that the profit margins of the SMEs with a mean of 2.47 and a

standard deviation of 1.171. This indicates that majority of the respondents highly agree that

the taxes they pay eat too much into the profits they make.

37

Thirdly, the study shows that the formula for calculating the tax is difficult with a mean of 2.26

and a standard deviation of 1.092. The study makes a finding that, key factors of tax rates

affect compliance as follows: the cost required for filing tax returns is high with a mean of 2.21

and a standard deviation of 1.061, the rate of turnover tax being prohibitive with a mean o

f2.09 and a standard deviation of 0.896, being registered with KRA for income tax with a mean

of 2.00 and a standard deviation of 0.600 and filing returns with a mean of 1.93 and a standard

deviation of 0.752. Complexity of tax laws adding to incorrect tax returns with a mean of 1.79

and a standard deviation of 0.887 and the tax rates being too high with a mean of 1.65 and a

standard deviation of 0.741 have a surprisingly low impact on the compliance of SMEs.

Table 4.13: Tax Rates and Tax Compliance

N Mean Std.

Deviation

Variance Skewness

Statistic Statistic Statistic Statistic Statistic Std.

Error

I File Returns 101 1.93 .752 .565 1.267 .240

I Am Registered With KRA For

Income Tax

101 2.00 .600 .360 1.417 .240

I Am Able To Determine

Accurately My Tax Liability And

Income

101 2.68 .871 .759 -.072 .240

The Tax Rates Are Too High 101 1.65 .741 .549 .960 .240

The Formula For Calculating The

Tax Is Difficult

101 2.26 1.092 1.193 .502 .240

Tax Laws Complexity Adds To

Incorrect Tax Returns

101 1.79 .887 .786 1.653 .240

The Cost Required For Filing

The Tax Returns Is High

101 2.21 1.061 1.126 .750 .240

The Rate Of Turnover Tax Is

Prohibitive

101 2.09 .896 .802 .760 .240

The Rate Of Turnover Tax Is

Higher Than Profit Margins

101 2.47 1.171 1.371 .199 .240

38

4.4.1 Inferential Statistics

4.4.1.1 Tax Rates and SME Compliance

The findings in below Table 4.14, present the correlation relationship between the effect of tax

rates on the compliance of SMEs. It indicates that there exists a positive relationship between

tax rates and compliance of SMEs in Sotik. This implies that, a positive change in tax rates will

trigger a strong change in tax compliance of SMEs. The significance reflected at level 0.05,

recording a p value of 0.000 which indicates that it is less than the significance. Thus,

concluding that its positively correlated and highly statistically significant (p= 0.000 < 0.05, R-

Value = 0.490).

Table 4.14: Correlations on Tax Rates and Tax Compliance

Compliance Tax Rates

Compliance Pearson

Correlation

1 .490

Sig. (2-

tailed)

0.000

N 101 101

The R value represents the simple correlation, which is 0.490. The R Square represents the

total variation in the dependent variable (SME Compliance) which can be explained by the

independent variable (Tax rates). From the analysis, R Square value was 0.240, which implies

that only 24% of the variation in SME compliance was caused by changes in the tax rates as

shown in table 4.15. The significance had a P value of 0.000 < 0.05, thus the relationship is

highly statistically significant.

Table 4.15: Model Summary of Tax Rates and Tax Compliance

Mode

l

R R

Squar

e

Adjuste

d R

Square

Std. Error

of the

Estimate

Change Statistics

R

Square

Change

F

Chang

e

df1 df2 Sig. F

Chang

e

1 .490a 0.240 0.233 3.91072 0.240 31.299 1 99 0.000

a. Predictors: (Constant), Tax_Rates

39

An ANOVA table reports how well the regression equation fits the data. An analysis was done

at 95% of confidence level. The F critical is 31.299 and the P value is 0.000. This analysis

confirmed that tax rates have a relationship with compliance of SMEs as shown.

Table 4.16: ANOVA of Tax Rates and Tax Compliance

Model Sum of

Squares

df Mean

Square

F Sig.

1 Regression 478.675 1 478.675 31.299 .000b

Residual 1514.078 99 15.294

Total 1992.752 100

a. Dependent Variable: Compliance

b. Predictors: (Constant), Tax_Rates

The coefficients table provides to predict SME compliance from the tax rate and also determine

whether the tax rates contribute statistically significantly to the model. The “B” column

represents the constant figure to regression equation. According to Table 4.17, the regression

equation will be Y = 23.556 – 0.711 X2, where Y is the dependent variable (SME compliance)

and X1 is independent variable (Tax rates) which concludes that the tax rates are taking the

constant SME compliance by 23.556 and an increase in the tax rates results into 0.711 increase in

compliance by SMEs. They are also highly statistically significant. The constant was significant

(0.000) as per Table 4.17 (p < 0.05).

Table 4.17: Model Coefficients of Tax Rates and Tax Compliance

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std.

Error

Beta

1 (Constant) 23.556 1.378 17.097 0.000

Tax Rates 0.711 0.127 0.490 5.595 0.000

a. Dependent Variable: Compliance

4.5 The Effect of Fines and Penalties and Tax Compliance

The data on table 4.18 presents the mean and Standard deviation of fines and penalties and

compliance of SMEs in Sotik sub-county in Bomet county. A Likert scale of 1-5 was used

where: 1= Strongly Agree, 2= Agree, 3= Uncertain, 4= Disagree and 5= Strongly Disagree.

40

The study makes a finding that escaping without any punishment after being detected for not

reporting one’s exact income is the greatest influence of compliance with a mean of 4.04 and a

standard deviation of 0.677. Affording to pay the penalty rates because they are low is another

influence to compliance with a mean of 3.95 and a standard deviation of 0.792. Fear of tax

audits and prosecution is a close third influence of compliance of SMEs with a mean of 2.00

and a standard deviation of 0.600.

Other key tax rate factors that influence compliance are as follows: Filing tax returns and

paying taxes on time to avoid fines and penalties with a mean of 1.97 and a standard deviation

of 0.714, Stiff fines and penalties for late filing with a mean of 1.97 and a standard deviation

od0.793, high chance of being detected for non-payment of taxes with a mean of 1.96 and a

standard deviation of 0.761 and failure to pay taxes leading to fines and penalties.

The study finds that fines and penalties do not have much influence on compliance.

41

Table 4.18: Fines and Penalties and Tax Compliance

N Mean Std.

Deviation

Variance Skewness

Statistic Statistic Statistic Statistic Statistic Std.

Error

I File My Returns And Pay Taxes

In Time To Avoid Fines And

Penalties

101 1.97 .714 .509 1.223 .240

Failure To Pay Taxes Leads To

Fines And Penalties

101 1.91 .550 .302 .316 .240

There Is A High Chance Of

Being Detected For Non-

Payment Of The Taxes

101 1.96 .761 .578 .345 .240

I Fear Tax Audits And

Prosecution

101 2.00 .775 .600 1.185 .240

Fines And Penalties Charged For

Late Filing Are Stiff

101 1.97 .793 .629 .544 .240

The Penalty Rates Are Very Low

And I can Afford To Pay The

Penalty

101 3.95 .792 .628 -.650 .240

If Detected Not Reporting My

Exact Income, I Believe The Tax

Authority Is Tolerant To Offence

And Most Likely I will Escape

Without Punishment

101 4.04 .677 .458 -.245 .240

4.5.1 Inferential Statistics

4.5.1.1 Fines and Penalties and SME Compliance

The findings in below Table 4.19, present the correlation relationship between the effect of

fines and penalties on the compliance of SMEs which indicates that there exists a positive

relationship between fines and penalties and compliance of SMEs in Sotik. This implies that, a

positive change in fines and penalties will trigger a strong change in tax compliance of SMEs.

The significance reflected at level 0.05, recording a p value of 0.142 which indicates that it is

more than the significance. Thus, concluding that its positively correlated and but not

statistically significant (p= 0.157 > 0.05, Correlation coefficient = 0.142).

42

Table 4.19: Correlations on Fines and Penalties and Tax Compliance

Compliance Fines and

Penalties

Compliance Pearson

Correlation

1 0.142

Sig. (2-

tailed)

0.157

N 101 101

The R value represents the simple correlation, which is 0.020 while the R Square represents the

total variation in the dependent variable (SME Compliance) which can be explained by the

independent variable (Fines and penalties). From the analysis, R Square value was 0.020,

which implies that only 2% of the variation in SME compliance was caused by changes in

fines and penalties as shown in table 4.20. The significance had a P value of 0.157 > 0.05. This

shows that the relationship is not statistically significant.

Table 4.20: Model Summary of Fines and Penalties and Tax Compliance

Mode

l

R R

Squar

e

Adjuste

d R

Square

Std. Error

of the

Estimate

Change Statistics

R

Square

Change

F

Chang

e

df1 df

2

Sig. F

Chang

e

1 .142a 0.020 0.010 4.44116 0.020 2.032 1 99 0.157

a. Predictors: (Constant), Fines_And_Penalties

An ANOVA table shows how well the regression equation fits the data. An analysis done at

95% of confidence level. The F critical is 2.032 and the P value is 0.157. This analysis

confirmed that the level of tax knowledge has a relationship with compliance of SMEs as

shown below.

43

Table 4.21: ANOVA of Fines and Penalties and Compliance

Model Sum of

Squares

df Mean

Square

F Sig.

1 Regression 40.083 1 40.083 2.032 .157b

Residual 1952.669 99 19.724

Total 1992.752 100

a. Dependent Variable: Compliance

b. Predictors: (Constant), Fines_And_Penalties

The coefficients table provides to predict SME compliance from fines and penalties and also

determine whether the they contribute statistically significantly to the model. The “B” column

represents the constant figure to regression equation. According to Table 4.22, the regression

equation will be Y = 23.196 – 1.310 X3, where Y is the dependent variable (SME compliance)

and X1 is independent variable (Fines and penalties) which concludes that fines and penalties

are taking the constant SME compliance by 23.196 and an increase in the tax rates results into

1.310 increase in compliance by SMEs. However, they are not statistically significant. The constant

was significant (0.157) as per Table 4.22 (p > 0.05).

Table 4.22: Model Coefficients of Fines and Penalties and Tax Compliance

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std.

Error

Beta

1 (Constant) 23.196 5.458 4.250 0.000

Fines and Penalties 1.310 0.919 0.142 1.426 0.157

a. Dependent Variable: Compliance

Figure 4.5 below shows the number of respondents who have ever been penalized for failing to

pay taxes. It shows that half of the respondents have been penalized for one of several reasons

that will be shown in Table 4.23.

44

50%50%

Ever Been Fined Or Penalized For Failing To

Pay Taxes?

Yes No

Figure 4.5: Ever Been Fined or Penalized for Failing to Pay Taxes

Table 4.23 shows the reasons respondents have been fined for due to failure to pay taxes. It

shows that most respondents have been fined for late filing of returns. The study showed that

they often forgot or weren’t aware of deadlines.

Table 4.23: Reasons for Penalization

Responses Percent of

Cases N Percent

Reasons For Fines Or

Penalties

Failing To Submit

Returns

19 27.5% 38.0%

Late Filing of Returns 34 49.3% 68.0%

Poor or No Record-

Keeping

12 17.4% 24.0%

Falsifying Records 4 5.8% 8.0%

Total 69 100.0% 138.0%

The regression equation demonstrated in Table 4.24 has shown that, taking all factors into

considerations and all other factors held constant, compliance of SMEs increase by 9.085. The

findings showed that, with all other variables held at zero, a unit change in the level of tax

knowledge would lead to an increase of 0.638 in SME compliance (Beta 0.584, P-Value <

0.05), and a unit change in tax rates would lead to positive change of 0.56 in SME compliance

(Beta 0.386, P-Value < 0.05), and a unit change in fines and penalties would result to a positive

increase of 0.603 increase in compliance by SMEs (Beta 0.065, P-Value > 0.05).

So, the equation will be:

45

Y = a+bX1+bX2+bX3+e

Where, 𝑌= 9.085 + 0.638 𝑋1 + 0.56 𝑋2 + 0.603 𝑋3

Y = SME compliance (%) - Dependent variable

a = The constant

𝑋1= Tax Knowledge Level (%) - Independent variable

𝑋2= Tax Rates (%) - Independent variable

𝑋3= Fines and Penalties (%) - Independent variable

e = Margin of error

There is no statistical significance between the level of tax knowledge, tax rates and fines and

penalties (P-Value < 0.05) as per Table 4.24.

Table 4.24: Model Coefficients

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std.

Error

Beta

1 (Constant) 9.085 3.856 2.36 0.02

Tax Knowledge Level 0.638 0.073 0.584 8.72 0

Tax Rates 0.56 0.098 0.386 5.7 0

Fines and Penalties 0.603 0.617 0.065 0.98 0.331

a Dependent Variable: Compliance

4.6 Chapter Summary

This section of the study covered the data presentation and analysis of the questionnaires. This

included the results and analysis of demographic data, descriptive statistics, correlations

results, simple linear regression, ANOVA table, and coefficients tables for significance tests to

assess the role of tax level knowledge, the effect of tax rate and the impact of fines and

penalties on the compliance of SMEs in Sotik sub-county of Bomet county. The next chapter

provides summary of the findings, discussion, conclusions and recommendations.

46

CHAPTER FIVE

5.0 DISCUSSION, CONCLUSION AND RECOMMENDATIONS

5.1 Introduction

This chapter covers the summary of the findings of the study. The section will then cover the

discussion on the findings, where the thematic association is made between the main findings

of this study and the past literature on the factors influencing tax compliance of SME owners

and employees in Sotik sub-county of Bomet county. The chapter will then show conclusions

drawn from the field study and offer recommendations based on the findings.

5.2 Summary

The purpose of this research was to analyze the factors affecting tax compliance of SMEs in Sotik

sub-county in Bomet county. The research had the following specific objectives: To assess how

knowledge of tax laws, policies and procedures affect compliance of SMEs, to assess the

extent to which tax rates affect tax compliance among SMEs and to assess the effect of fines

and penalties on tax compliance of SMEs in Sotik sub-county in Bomet county in Kenya.

The research used a causal and explanatory survey design to investigate the relationship among

the independent variables which are tax knowledge level, tax rates and fines and penalties and

SMEs as dependent variables. Primary data collection was used with a drop and pick of 120

questionnaires with both open-ended and close-ended questions where 84% of the responses

were recorded. The respondents were 66% owners and 34% employees of SMEs, which shows

that majority of respondents prefer running their own businesses. Most of the respondents went

above secondary school but not to graduate level at 38.6%. Most respondents have operated in

the area for more than 10 years at 35.6%, which shows that it is a conducive environment for

business. The study research used Pearson's correlation, regression analysis for each of the

specific objectives and data was analyzed by IBM SPSS. A multiple linear regression model

was used to evaluate the relationship between three independent variables which are level of

tax knowledge, tax rates and fines and penalties and the dependent variable which is the SME

owners and employees. The results were presented in figures and tables.

On the level of tax knowledge on the compliance of SMEs, the Pearson correlation results

showed a positive relationship as R-Value = 0.649 and P-Value = 0.000. This implies that the

level of tax knowledge and compliance of SMEs are positively correlated and are highly

47

statistically significant since the P-value is less than 0.05. This presents that level of tax

knowledge has a direct relationship with SME compliance. According to regression analysis,

the adjusted R square value was 0.421 which implies 42.1% of the variation in compliance by

SMEs was caused by change in the level of tax knowledge. An ANOVA analysis and

coefficient done at 95% confidence level confirmed that it is highly statistically significant

since the F critical is 71.877 and P value is 0.000.

On the role of tax rates on compliance of SMEs, the Pearson correlation results indicated a

positive relationship as R-Value = 0.490 and P-Value = 0.000. This implies that SME

compliance and tax rates are positively correlated and highly statistically significant since the

P-value is less than 0.05. This shows that, compliance of SMEs has a direct relationship with

tax rates. Regression analysis showed that the R square value was 0.240, which implies that

only 24% of the variation in compliance by SMEs was due to variations in tax rates. An

ANOVA analysis and coefficient done at 95% confidence level and the F critical was 31.299

and the P value was 0.000, confirming that the relationship between tax rates and compliance

is highly statistically significant.

On the effect of fines and penalties on compliance of SMEs, the Pearson correlation results

showed a positive relationship as R-Value = 0.020 and P-Value = 0.157. This implies that fines

and penalties have a negative correlation with compliance and is not statistically significant,

since the P value is greater than 0.05. This shoes that fines and penalties have a direct

relationship with compliance. From the regression analysis, the adjusted R square value is

0.010, which implies that 0nly 1% of the variation in SME compliance is caused by variations

in fines and penalties. An ANOVA analysis and coefficient done at 95% confidence level and

the F critical was 2.032 and the P value was 0.157, showing that the relationship between

compliance and fines and penalties is not statistically significant.

A multiple linear regression analysis done between the dependent variable (SME compliance)

and the independent variables (tax knowledge level, tax rates and fines and penalties) showed

that there is a positive correlation between the independent and dependent variables (R-Value

= 0.760, P-Value= 0.759). This implies that the independent variables and the dependent

variables are positively correlated but have no significant correlation since the P- value is

greater than 0.05. The adjusted R square value is 0.577. This implies that only 57.7% of

variation in compliance by SMEs is caused by variations in the level of tax knowledge, tax

rates and fines and penalties.

48

5.3 Discussion

5.3.1 Effect of the Level of Tax Knowledge on SME Compliance.

The research sought to find the effect of the level of tax knowledge on compliance by SMEs. It

showed that there was a positive impact on compliance by SMEs (r= 0.649 P-value= 0.000).

The analysis implied that the level of tax knowledge and compliance by SMEs have a direct

relationship and are highly statistically significant, which is in line with studies done by Inasius

(2015) where he opines that tax knowledge becomes the strongest predictor affecting tax

compliance. He concludes that there is a significant relationship between tax knowledge and

tax compliance and that greater tax knowledge increases compliance. Taxpayers who are not

very educated are not very exposed to tax compliance information and, hence are more prone

to non-compliance.

The complexity of tax information is difficult for some taxpayers to understand, which leads to

unintentional non-compliance if taxpayers encounter problems while filing returns. SMEs

generally find the information given by KRA fairly inadequate to enable them complete the tax

returns expected from them. Some find the process to be complicated, requiring too much

information thus a waste of time and resources. It is thus clear that there is a strong case for

improvement of the information available.

Rizal (2010) opines that knowledge of tax system is necessary to increase public awareness,

especially on taxation laws, the role of tax in national development, and to explain how and

where the money collected is spent by the government. This study is in agreement with these

findings. Awareness by the society would encourage people to fulfill their obligations. Most

citizens do not have much understanding of what tax laws mean and why the tax system is

structured and administered as it is. Knowledge, as one of the factors in compliance, is related

to the taxpayers’ ability to understand taxation laws and their willingness to comply. The

aspect of knowledge that relates to compliance is the general understanding about taxation

regulations and tax systems. Attitude towards compliance can be improved through the

enhancement of tax knowledge.

A study conducted by Inasius (2015) in Indonesia concluded that tax knowledge has significant

correlation to compliance of taxpayers as long as they deem the tax system to be fair. However,

tax compliance was solely based on tax knowledge, the probability of being audited and the tax

rate perception. These findings are in line with the findings of this similar study done in Sotik

sub-county.

49

Taxpayer education will provide the necessary tax knowledge to comply with the tax matter

and change the perceptions and attitudes towards tax-compliance by creating more positive

attitudes. This was confirmed in a study carried out in Mwanza, Tanzania by Machogu and

Amayi (2013). Their findings agree with the results of this study carried out in Sotik sub-

county in Kenya.

A study conducted by Newman and Nokhu (2018) in Zimbabwe confirmed that SMEs lack

knowledge of tax requirements leading to the non-compliance behavior as postulated by

Akinboade (2012), which agrees with the findings of this research done in Sotik sub-county in

Kenya.

Majority of the respondents are in agreement that taxpayer education and seminars plays a

positive role in enhancing tax compliance. Taxpayer sensitization/education is one of the

powerful tools of enhancing compliance. In these forums, knowledge is passed to taxpayers

exhaustively and this enhances future compliance and through this knowledge the taxpayer is

able to know the various rights and obligations accruing from services offered by KRA.

Communication channels open up and this enhances friendly relations between the taxpayer

and the tax authority. Consequently, taxpayers also feel part and parcel of the policy making

process. KRA should strive to open ‘Help’ counters for taxpayers to seek help in dispensing

information. Well-trained and knowledgeable staff should man the counters. They should also

enhance taxpayer education and remove the ambiguities in the VAT and Income Tax Acts.

5.3.2 Effect of Tax Rates on SME Compliance

The study sought to establish the effect of tax rates on compliance by SMEs. It showed that

there was a positive correlation between tax rates and SME compliance (r = 0.490, P-value=

0.000). The research showed that there is a positive relationship between tax rates and

compliance by SMEs. The analysis showed that tax rates and compliance are positively

correlated and highly statistically significant. This contradicts a study done by Kirchler (2007)

which indicates that the exact impact of tax rates is still unclear, although it is an important

factor in determining tax compliance behavior of SMEs. A high tax rate erodes taxpayer’s

earnings and disposable incomes thus discouraging compliance. It will also encourage tax

avoidance and evasion as the opportunity cost to evade is high. This may be an expected

reaction from taxpayers as no single taxpayer can rate a tax rate as 'low'. There is also the

problem of defining the line between 'high', 'low' and 'fair'. Given the large percentage of

respondents who feel that they are high, there is need to revise these rates and make them more

attractive to them. This will enhance tax collection by reducing evasion and enhance

50

compliance. Kirchler et al, (2008) further suggests tax rates have mixed impact on tax

compliance, that is, decreasing tax rates does not necessarily always increase compliance and

also increasing tax rates will not necessarily always decrease compliance behavior.

A study done by Inasius (2015) indicated that perception of tax rates, influence of referent

group and the probability of being audited are not significant to tax compliance. This is unlike

the findings of this study which were that tax rates greatly influence compliance. With regard

to the perception of tax rates, findings of the study done by Inasius (2015) in Indonesia showed

that tax rates are not significantly correlated to tax compliance. This contradicts to this study

done in Sotik sub-county

The results of the study however agree with past researchers like Clotfelter, (1983) as a cited in

Chau and Leung (2009) opined that economic models of rational compliance decisions provide

either mixed predictions of the effect of the marginal tax rate on compliance, or predict that

increased tax rates would increase compliance.

Results of these study show that reducing tax rates is not the only way to prevent non-

compliance. Studies by Hashimzade et al. (2012), which concluded that compliance will

increase when the tax rate rises agrees with these findings. Although increasing marginal tax

rates would likely encourage taxpayers to evade taxes (Torgler, 2007).

Masúd et al. (2014) examined the correlation as well as the effect of tax rates on compliance in

Africa using cross-country data. The findings showed that there is significant negative

correlation between tax rates and tax compliance. This contradicts the findings of this study

which showed a significant positive correlation between tax rates and compliance of SMEs in

Sotik.

5.3.3 Effect of Fines and Penalties on Compliance

This research showed a positive relationship between fines and penalties and compliance (r =

0.142, P-Value =0.157). The analysis showed that fines and penalties and SME compliance are

positively correlated, but not statistically significant. Penalties and interest from them arise out

of late filing of returns, non-payment of taxes and non-disclosure of taxable income which is

discovered during audit. These fines, penalties and any interests arising from them are

specified in the respective Acts. Because these are legislative requirements, KRA can only act

to reduce through regular education/sensitizations and audits. The other available option is to

change the law to reduce the fines and penalties. This research shows that high fines and

51

penalties only marginally encourages compliance of SMEs in Sotik sub-county, which agrees

with other studies done by past researchers.

A research done by Chebusit et al. (2014) in Trans Nzoia county in Kenya found out that fines

and penalties were rated average in influencing SMEs tax compliance. Their results showed a

positive effect of fines and penalties on compliance, meaning that an increase in fines and

penalties led to an increase in compliance. This is in line with the findings of this study carried

out in Sotik that showed that fines and penalties positively affect compliance but not by much.

A study by Alm et al. (1990) reported that the effect of the penalty rate on increase of

voluntary compliance was minimal and insignificant. This might mean that if tax penalties and

fines are not supported by auditing, they don’t create a significant effect on compliance. This is

in line with the findings of this research.

Another study by Evans et al. (2005) examines the relationship between record-keeping

practices of SMEs and their potential compliance problems. The study found out that record-

keeping has a direct impact on compliance. This study done in Sotik sub-county found out that

poor record-keeping often led to poor reporting and hence exposed respondents to fines and

penalties and any interests arising from them.

5.4 Conclusion

5.4.1 Effect of the Level of Tax Knowledge on SME Compliance

Past studies have shown that the level of tax knowledge greatly influences compliance by

SMEs. For SMEs in Sotik sub-county in Bomet county, findings of this research have shown

that their compliance is influenced the level of tax knowledge they have. It shows that the more

information they have, the more inclined to compliance they are. The respondents are willing

to attend tax sensitization and education forums. They are requesting KRA to organize and

invite them and to also be more accessible and friendly and to use their local language that they

better understand and relate to.

5.4.2 Effect of Tax Rates on SME Compliance

Results from this research concluded that tax rates and compliance by SMEs have a positive

relationship. Specifically, tax rates greatly influence compliance of SMEs in Sotik sub-county

in Bomet county. An increase in the tax rates shows a marked increase in compliance by

SMEs. However, the government should consider increasing tax incentives and exemptions to

encourage voluntary compliance.

52

5.4.3 Effect of Fines and Penalties on Compliance

Results from the research recognized that fines and penalties positively influenced compliance

by SMEs in Sotik, but not by much. SME owners and employees are affected by fines and

penalties and the interest that accrues, but not immensely, which the government should

consider extending deadlines and alerting them through various communication channels to

boost compliance.

5.5 Recommendations

Based on the findings of this study, the researcher came up with several recommendations.

5.5.1 Recommendations for Improvement

5.5.1.1 Effect of the Level of Tax Knowledge on SME Compliance

The findings in this study showed positive relationship that is highly statistically significant.

This means that there is credible evidence that the level of tax knowledge of an SME owner or

employee greatly influences their compliance, and some proof that it does. Further studies can

be done using convenience sampling, non-parametric (Mann-Whitney and Kruskal-Wallis)

tests, multivariate data analysis, and vignette-based questionnaire for looking at exactly what

level of tax knowledge will ensure total compliance.

5.5.1.2 Effect of Tax Rates on SME Compliance

The findings in this study showed positive relationship that is highly statistically significant.

This means that there very credible evidence that tax rates influence compliance of SMEs and

some proof that it does. Further studies using data with convenience sampling, non-parametric

(Mann-Whitney and Kruskal-Wallis) tests, multivariate data analysis, and vignette-based

questionnaire for looking at the right tax rates that will ensure total compliance.

5.5.1.3 Effect of Fines and Penalties on Compliance

The research recommends that use of other research design models such as online surveys,

telephone surveys, and statistical tests such as Chi- square, t-test analysis, ordinary least

squares analysis, independent sample t test, bivariate data analysis, discriminant analysis, open

analysis, fixed-effect regression, Kolmogorov-Smirnov test, and multivariate regression for

further study as the findings in this study showed a positive but not statistically significant

relationship between fines and penalties and compliance. This means there is reliable evidence

that the influence of fines and penalties on compliance by SMEs, but that there is no proof that

it will not affect it.

53

5.5.1.4 Recommendations for Further Research

This study mainly focused on investigating the effect of a few factors on compliance of SMEs

in Sotik sub-county in Bomet county. The study recommends that the future researchers should

look into compliance patterns of the other three sub-counties in the greater Bomet county and

compare them to Sotik SMEs. Future researchers should approach the topic with different

method of research methodologies.

54

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APPENDICES

APPENDIX I: RESEARCH LETTER

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APPENDIX II: NACOSTI PERMIT

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APPENDIX III: COVER LETTER

MAUREEN CHEPKORIR BETT

USIU-Africa

P. O. BOX 14634 - 00800,

NAIROBI, KENYA

Dear Respondent,

I am carrying out a research on the impact of tax compliance on the performance of SMEs in

Sotik sub-county in Bomet county. This is in partial fulfilment of the requirements for the

award of the degree of Master of Business Administration at USIU-Africa. This study intends

to use data from small and medium-sized enterprises, of which you are part of the selected

sample of respondents whose views we seek on the above mentioned matter.

Attached is a questionnaire, of which you’re kindly requested to answer all the questions

accordingly. All information given in the questionnaire will be treated with strict

confidentiality and used for the purpose of this dissertation only.

A copy of the final report will be availed to the respondents/firms upon request.

Thank you for taking your time to fill in the questionnaire.

Thank you in advance,

Yours sincerely,

Maureen C. Bett

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APPENDIX IV: QUESTIONNAIRE

My name is Maureen Chepkorir Bett, a graduate student at United States International

University- Africa pursuing Master’s degree in Business Administration (MBA). As part of the

requirement towards the fulfillment of the requirements of the degree, I am required to write a

research project. In this regard, I have designed a questionnaire to collect information on the

effect of tax compliance on the performance of medium and small taxpayers in Sotik sub-

county of Bomet county. The information obtained will only be used for academic purposes

and shall be treated in utmost confidence. You are requested to complete this questionnaire as

honestly and objectively as possible. Note that you are not required to indicate your name

anywhere on the questionnaire.

Thank you for your co-operation.

SECTION A: DEMOGRAPHIC

1. Are you employed or own the business? (Tick one)

(0= Employed 1= Owner)

Employed ( ) Owner ( )

2. Which of the following best estimates the highest level of education attained by the

owners of the enterprise? (Tick one)

(0= Primary or below 1= Secondary level 2= Above secondary but not

graduate 3= Graduate and above)

Primary level or below ( ) Secondary level ( )

Above secondary but not graduate ( ) Graduate and above ( )

3. How long have you been in operation or worked for your company in years? (Tick one)

(0= Less than 3 1= 3-5 2= 5-10 3= Over 10)

Less than 3 ( ) 3-5 ( ) 5-10 ( ) Over 10 ( )

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4. What is your main business activity? (Tick one)

1. Supermarkets

2. Shops and retail stores

3. Financial and money transfer services

4. Small restaurants, hotels and bars

5. Private education institutes

6. Petrol stations

5. What is the sales level of your business per month? (Tick one)

(0= Less than 50,000/- 1=50,000/- to 100,000/- 2=100,001/- to 200,000/-

3= 200,001/- to 300,000/- 4= 300,001/- to 400,000/- 5= 400,001/- to 500,000/-

6= Over 500,000/-)

Less than 50,000/- ( ) 50,000/- to 100,000/- ( )

100,001/- to 200,000/- ( ) 200,001/- to 300,000/- ( )

300,001/- to 400,000/- ( ) 400,001/- to 500,000/-

Over 500,000/- ( )

6. What is the size of business in terms of employees? (Tick one)

(0= 0-10 1= 11-20 2= 21-30 3= over 30)

0-10 ( ) 11-20 ( ) 21-30 ( ) over 30 ( )

7. Do you have a professionally trained accountant? (Tick one)

(0= Yes 1= No)

Yes ( ) No ( )

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SECTION B: TAX KNOWLEDGE LEVEL

This section is concerned with determining impact of tax knowledge among the SMEs on

tax compliance level. Please check (×) in the box which best depicts your level of

concurrence or non-concurrence with the statement.

Strongly Agree=1, Agree = 2, Uncertain=3, Disagree=4 and Strongly Disagree=5

Index Statement 1 2 3 4 5

1 I am aware of tax laws.

2 I am aware of how the tax system is

structured and administered.

3 Rules on taxation are too sophisticated for a

non-professional to understand.

4 I know how to declare actual income received

from all sources to the tax authority.

5 I understand my tax obligations.

6 I keep up to date books of account for my

business.

7 I have enough information on tax and tax

procedures.

8 Tax laws complexity adds to incorrect tax

returns.

9 The tax officials do not provide accurate

advice on tax

10 I encounter problems when filing returns.

11 Perceived fairness of the tax system

encourages compliance

12 I understand all the types of taxes I am

supposed to comply with

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13. Have you ever attended any taxpayer education/sensitization on tax compliance?

(0= Yes 1= No)

Yes ( ) No ( )

14. If yes, how often do you attend? (Tick one)

(0= Every month 1= Quarterly 2= Semi-annually 3= Annually)

Every month ( ) Quarterly ( )

Semi-annually ( ) Annually ( )

15. How do you obtain information on tax matters? (Tick the ones that apply)

(0= Personal visit to KRA offices; 1= Written inquiry; 2= Brochures; 3= Telephone;

4= TV/Radio; 5= KRA Website; 6= Print media)

Personal visit to KRA offices ( ) Written inquiry ( )

Brochures ( ) Telephone ( ) TV/Radio ( ) KRA Website ( )

Print media (newspapers, etc) ( )

16. Please give suggestion(s) of how knowledge of tax system can be improved to boost

compliance amongst SMEs.

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SECTION C: TAX RATES

This part is concerned with determining effect of tax rates among the SMEs on tax

compliance level. Please check (×) in the box which best depicts your level of concurrence

or non-concurrence with the statement.

Strongly Agree=1, Agree = 2, Uncertain=3, Disagree=4 and Strongly Disagree=5

Index Statement 1 2 3 4 5

1 I file returns.

2 I am registered with KRA for income tax.

3 I am able to determine accurately my tax

liability and income.

4 The tax rates are too high.

5 The formula for calculating the tax is

difficult.

6 Tax laws complexity adds to incorrect tax

returns.

7 The cost required for filling the tax returns

is high.

8 The rate of turnover tax is prohibitive

9 The rate of turnover tax is higher than

profit margins

10. Please give suggestion(s) of how tax rates can be improved to boost compliance

amongst SMEs

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SECTION D: FINES AND PENALTIES

This part is concerned with determining effect of fines and penalties among the SMEs on

tax compliance level. Please check (×) in the box which best depicts your level of

concurrence or non-concurrence with the statement.

Strongly Agree=1, Agree = 2, Uncertain=3, Disagree=4 and Strongly Disagree=5

Index Statement 1 2 3 4 5

1 I file my returns and pay taxes in time to

avoid fines and penalties.

2 Failure to pay taxes leads to fines and

penalties.

3 There is a high chance of being detected for

non-payment of the taxes.

4 I fear tax audits and prosecution.

5 Fines and penalties charged for late fillings

are stiff.

6 The penalty rates are very low and I can

afford to pay the penalty.

7 If detected not reporting my exact income, I

believe that the tax authority is tolerant to

my offence and most likely I will escape

without punishment.

8. Have you ever been fined or penalized for failing to pay taxes?

(0= Yes 1= No)

Yes ( ) No ( )

If yes, what were the reasons for penalization? (Tick the ones that apply)

(0= Failing to submit returns; 1= Late filing of returns; 2= Poor or no record-keeping;

3= Falsifying records)

Failing to submit returns ( )

Late filing of returns ( )

Poor or no record-keeping ( )

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Falsifying records ( )

9. Please give suggestion(s) of how fines and penalties can be revised to boost compliance

amongst SMEs.

Suggest other strategies that can be used to improve tax compliance of SMEs