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.
16
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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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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