----------------------------------------------------------------------------- Effect of Personal and Non-personal Factors on Tax Evasion Among Small and Medium Enterprises in Nairobi County, Kenya RUTHNDICHU MBA/46618 sn,·.- ~ T l- iiJu~-~ --:- -·- l ... . 1 \ ,,.fo, ·""I : .' L! BRA R y ~ , sPECIAL coLLF:cno."-'-" n ---..:· Submitted in partial fulfillment of the requirements for the award of a Master's in Business Administration (MBA) Degree Strathmore Business School MAY 2019 This dissertation is available for Library use on the understanding that it is copyright material and that no quotation from the thesis may be published without proper acknowledgement. DECLARATION I declare that this work has not been previously submitted and approved for the award of a degree by this or any other university. To the best of my knowledge and belief, the dissertation contains no material previously published or written by another person except where due reference is made in the thesis itself. © No part of this thesis may be reproduced without the pem1ission of the author and Strathmore University Ruth Ndichu May 2019 Approval The dissertation of Ruth Ndichu was reviewed and approved by: Dr. David Mathuva (Supervisor) Strathmore University Dr. George Njenga Dean, Strathmore Business School Prof. Ruth Kiraka Dean, School of Graduate Studies Strathmore University 11 ABSTRACT Tax evasion affects various sectors of an economy and heaps adverse effect on an economy as a whole. This study assessed the effect of personal and non-personal factors on tax evasion among SMEs in Nairobi County. The specific objectives of the study were to establish the effect of tax rates on tax evasion among SMEs in Nairobi County; the effect of economic factors on tax evasion among SMEs in Nairobi County; and the effect of demographic factors on tax evasion among SMEs in Nairobi County, Kenya. The study adopted a descriptive research design. This study collected primary data from the field using questimmaires. Descriptive analysis was done where measures of central tendencies (frequencies, means and percentages) were used to carry out the analysis. Inferential statistics including coiTelational analysis and regression analysis were also used. It was established that tax rate has moderate, positive and significant effect on tax evasion. Economic factors have strong, positive and significant effect on tax evasion. Demographic factors have strong, positive and significant effect on tax evasion. The study concluded that tax rate, economic factors and demographic factors are key drivers of tax evasion among SMEs. The study recommends that the Kenya Revenue Authority (KRA) should come up with im10vative ways of collecting revenue without necessarily raising the rates. The govemment should come up with sound economic policies (including macro and micro economic policies) which would increase the taxpayers ' incomes hence more taxes. KRA should consider the male and female attributes when designing taxation policies. Penalties for noncompliance may be more stringent to men as compared to women due their differences in willingness to comply with taxes. 111 TABLE OF CONTENTS DECLARATION ............................................................................................................... ii ABSTRACT ...................................................................................................................... iii TABLE OF CONTENTS ................................................................................................ iv LIST OF FIGURES ......................................................................................................... vi LIST OF TABLES ......... ..................................... ............................................................ vii DEFINITION OF TERMS ............................................................................................ viii LIST OF ACRONYMS .................................................................................... ............... ix ACKNOWLEDGMENTS ................................................................................................. x DEDICATION ........ .......................................................................................................... xi CHAPTER ONE: INTRODUCTION .............................................................................. ! 1.1 Background of the Study ... ... .. ..... ... ..... ... ....... ........ ............ ..... .. ... .. .... ..... ....... ........... .. 1 1.1.1 Personal and Non-Personal Factors .................................. ... .... ... ... ... .... ....... ..... . .2 1.1.2 Tax Evasion .......... ...... ..... ... .... ....... ...... ......... ... ..: ..... ..... ... ... .. ....... ..... .. ... ....... .. .... 3 1.1.3 Small and Medium Enterprises ....... .. ... ........... ... ..... .... .. .. ..... .... .. ..... .... ......... .. ... ..6 1.2 Statement of the Problem ........... ..... ..... .. .. ...... ....... ..... .. ...... ...... ....... .............. ... .. .. .. .... 7 1.3 Research Objectives .... ................... ... .. .. .... ......... .. .... .. .. ... ...... ... ....... .. ..... ... ................ .9 1.3.1 General Objective ..... ......... .... .. .. ..... .... .. .. ...... .... .. .. .... ... .. ...... ... .. ... ... ...... .... .... .. .... 9 1.3.2 Specific Objectives .. .. .... .. .... ... ............ .. .. .... .. .... .. ... .......... ..... .. ............ .. .. ............ 9 1.4 Research Questions .. ....... ..... ... ............... ....... .. ...... ... -..~ .......... .... .... ... .. ... ... ...... ... .. .. ..... 9 1.5 Scope of the Study .. .. .... ... ....... ... .......... ·. .... .. .. ..... ...... ...... ... ... ..... .. .. ....... ... ... .... ..... .. ... .. 9 1.6 Justification of the Study ... ......... .......... .... ... ............................. ... .. ......... ...... .. .. .. .. ... 10 1. 7 Significance of the Study ... ........ ...... ........ ........ .. ... ..... ........... ... ... ........ .... ... ........ ... .. . 10 1.8 Organization of the Thesis .. ............ ..... .. ......... ...... .. .. ..... ..... .... .... ..... ..... .. ... ......... .... . 10 CHAPTER TWO: LITERATURE REVIEW ............................................................... 12 2.1 Introduction .. ...... ........ ..... .. .. ........ ... ...... .......... ...... ... ....... .. ..... .......... .......... ..... ........ .. 12 2.2 Theoretical Framework .... ... .. ........ .......... ........ ..... ...... .... .. ............ ..... ... ... .... ..... .... .... 12 2.2 .1 Economics of Crime Model .... .... .... .......... ... ...... ...... ........ .. .. .... ...... ... ................ 12 2.2 .2 Prospect Theory .. .... .. ...... ... .... .............. .. ......... .. ................... .... .. .. ... ..... .. ...... ..... 13 2.2.3 Social Identity and Self Categorization Theory ..... ... .... ... ...... ...... ... ....... ...... ... .. 14 2.3 Empirical Review .. ....... ....................... .. .. ... ......... ..... ...... ............................. ..... .. ..... . 15 2.3.1 Effect of Tax Rate on Tax Evasion .. ... .... ..... .. ................... ... .. ... ...... .. ... .. .... ... .. . .15 2.3.2 Effect of Economic Factors on Tax Evasion ....... .... ............ ... .... ....... .. ... .. .... ... . 17 2.3.3 Effect of Demographic Factors on Tax Evasion .. ................... .. .. ..... ... ......... .. .. .18 2.4 Su1mnary and Research Gap ...... ............ .. ...... ... .... ... ... ....... ................. .......... .. ....... ..2 0 2.5 Conceptual Framework .... .. ..... .. .. ....... ... ..... ......... .. ........ .. ...... ....... .. ..... ... .... ...... .. ...... 20 2.6 Operationalization of Variables ... ........ .. ... ............ .......................... .. ...................... .21 2.7 Chapter Sunu11ary .. ... ... .... ..... ... ....... .. ...................... .. .. .. ... ....... ...... ..... ....... .... .... .... .... 22 CHAPTER THREE: RESEARCH METHODOLOGY .............................................. 23 3.1 Introduction ....... ... .. ..... ............ .. .. .. .... .. ... .... .. ... ........ ....... ........ ...... .. ........ ... ... .... ...... .. 23 3.2 Research Design ...... .. .... ............ ..... ..... .. ... ... ......................................... .... .............. .. 23 3.3 Target Population ...... ... ............. ........... ... ..... ............... .. .. .. ................ ...... .............. .. .2 3 lV 3.4 Sampling Techniques .... ..... .. ................ ........ ....... ......... ... .... ..... .. ... .. .. .. ...... ...... ..... ... . 23 3.5 Data Collection Instrument .. ..... ... .... ......... .. ........... ...... ...... ................ ........... ... ..... ... 24 3.7 Research Quality ............ ... .. .. .. .. .... .. ........ ...... ..... ...... .... .. .... ....... .... ....... ..... ............... 24 3.7.1 Validity .. .. ... .... .. ...... ..... .... .. ... .. ... ........... .... ......... .. .. ............. ..... ...... ................... 25 3.7.2 Reliability .. .. ... .... .. ...... .. .. .... ..... ... ........... .. .... ..... ... ........ ... ..... ... ..... ...... ..... ........... 25 3.7.3 Objectivity. . ..... .. .. ... .... ... ... ........ .. ........ .. ..... ....... ........... : .... .......... ... .. .... ....... ....... 26 3.8 Data Analysis and Presentation ....... ... .......... ..... ... .. ..... .. ~ ........... .. ... .... ......... ...... .. .. .. 26 3.9 Ethical Consideration ..... .. ...... ...... ..... .. .. .. .... ....... .. ... ..... ......... .. ............ ....... ....... ....... 27 CHAPTER FOUR: PRESENTATION OF RESEARCH FINDINGS ....................... 28 4.1 Introduction ........... .. ..... .. ... ........ ...... .............. ......... .......... ................................ ... ..... 28 4.1 .1 Response Rate .. ..... ............ .. .. ................................. ... ........... .. .... .... .... ..... ..... ..... 28 4.2 General Infonnation ....... ...... ... .. ..... .... .. .. ... .... ......... .. ......... ... ... ....... .... .. ....... .. .... ..... .. 28 4.2.1 Gender of Respondents ....... .... ... ..... .... ....... ... ......... ... ..... .......... ........ .... ........... .. 28 4.2.2 Age of Respondents .. .... ... .. .. ................ ... ......... ... ... .............. ..... .. .... ..... ..... .... .... 29 4.2.3 Level of Education of Respondents ..... ... ... ... ... .... ... .... .... .. .. ............ ... ........ ..... .. 29 4.2.4 Length of SME Operation ......... .......... ......... .. ..... .... .... ....... .. .... .... ... ...... ....... .. .. .3 0 4.2.5 Whether Tax Evasion is a Key Concem .............. ............. ................................ 30 4.3 Descriptive Analysis ...... ... .. .. ......... .. .. .... .. .......... ....... ..... .... ..... ...... ..... ..... ........ .. ...... .3 1 4.3.1 Tax Rate and Tax Evasion ... ......... .. ......... .. ... ..... .. .... .... .... ........ ...... .. ... ......... .. .. .3 1 4.3 .2 Economic Factors and Tax Evasion ... ..... ...: ... .. .. ... ....... ... ..... .. ...... ... ..... ......... .... 33 4.3.3 Demographic Factors .......... :. .. ... ............... ... ....... ...... ... ........ ... ... ... ..... ............. .. 34 4.3.4 Tax Evasion ....... ...... .. ... .. ....... ....... .. .. ...... .... .. ...... ... ... .... ..... ... ........... ............. .... 35 4.5 Inferential Statistics ............... .. .......... .. ............ ........ .... ...... .. ............ ........ ..... ..... ..... .3 6 4.5.1 Correlation Analysis .. ... .. .. ...... .. ............... .... ...... .... .. ..... .. ........ ... .. ...... ........... .. .. 36 4.5.2 Regression Results ..... .. ..... ... ............................... ... .... ............. ......... ... .............. 37 CHAPTER FIVE: DISCUSSIONS, CONCLUSION AND RECOMMENDATIONS ............................................................................................................................................ 40 5.1 Introduction ................ ...... ........ .. ......... ... ...... ...... .......... ... .... ..... ..... ... ...... ... ...... ... .. .... 40 5.2 Discussions ......... ..... ..... ... ..... ... ... ........ ...... ....... .......... .... .. ... ... ..... ..... .... ... ........ ....... ..4 0 5.2.1 Tax Rate and Tax Evasion .... ............. ....... .. ............................. ...... ...... ..... ... .. .. .40 5.2.2 Economic Factors and Tax Evasion .... ... ... ..................... ...... ............ .. .. ............ .41 5.2.3 Dernographic Factors .. ......... .. .... .... ....................................... .. ......... ... .. ..... ...... .4 2 5.3 Conclusion ......... ..... ...... .. .............................. ...... .. ... ... ... .. ... .... ............ ...... ............. ..4 3 5.4 Recommendations of the Study ..... ........ .... ...... .... .. .... .. ...... ...... ... .. .... .. .. ... .... .. ... ..... . .44 5.5 Contribution of the Study to Knowledge ... ... .. ........ ...... ... .... ... ... ...... .. .. ........ .. ......... .45 5.6 Suggestions for Further Studies ...... .. ...................... ........... ..... ...... .. .. .. .. ....... ......... .. .46 REFERENCES .................... ................................ .. ........................................................... 47 APPENDICES .... ,. .................................................. : ......................................................... 53 APPENDIX 1: APPROVAL LETTER. ........... ................ ..... ... .. ... .... .... .. ... ............... .. 53 APPENDIX II: QUESTIONNAIRE .... ... ........... .. , .... ... .. ... ....... .... .. ... .... .. ..... .......... ... .5 4 v LIST OF FIGURES Figure 1.1 : Conceptual Framework .... ... .. ........... .............................. ...... .......... ............... 21 Vl LIST OF TABLES Table 2.1: Operationalization ofVariables ... .... .. .... .............. .. ...... ... ............................. .... 21 Table 3.1: Reliability Results .. .... ...... ............................. ... ..................... ..... ..... ........ ..... .... 25 Table 4.1: Gender of Respondents .......... .. ......... ......... .... .. ... ........... .................. ..... ........ ... 28 Table 4.2: Age of Respondents .............. .. ............... .. ... .................. .... .. ............. ....... .... ... .. 29 Table 4.3: Level of Education of Respondents ...... ....... ... ..... .. ........... .. .................... ........ . 29 Table 4.4: Length of SME Operation .. ...... .. ..... ..... ... .... ....... ... ........................ .. ..... ... ....... . 30 Table 4.5: Whether Tax Evasion is a Key Concem .... .. ... ..... ....... ........ .... ...... ........ .......... . 30 Table 4.6: Tax Rate and Tax Evasion ... .............. ..... ............... .. ..... ..... .................. ........... . 32 Table 4.7: Economic Factors and Tax Evasion ......... ........ ..... ..... ..... .................. .. .... ........ 33 Table 4.8: Demographic Factors ............. .... .... .. .. .... ..... ........... ............... ...... ....... ... ......... .. 34 Table 4.9: Attitudes towards Tax Evasion ...... ..... ........................... ...... .......... .. ................ 35 Table 4.10: Correlation Analysis ... .. ...... ..... ................ ..... .. .................. .... .......... ... ..... ... ... . 37 Table 4.11: Model Sunm1ary .......... ... ........ ... .............................. ........................ .... .......... 38 Table 4.12: Analysis of Variance ....... .. ... : ... .. .................................. .................. ...... .......... 38 Table 4.13: Regression Coefficients .. ............. .. ... ..... .................................. ....... .. .......... ... 38 Vll DEFINITION OF TERMS Demographic factors- This include the income level of the SMEs that will enable them to pay the tax Economic factors - High rate imposed on taxes for the SMEs to pay. Tax evasion - illegal ways that people employ to avoid paying taxes and these include undeJTeporting income, profit or over reporting the amount of tax deductions. Tax rates - the ratio (usually expressed as a percentage) at which a business or person is taxed. Vlll LIST OF ACRONYMS GDP Gross Domestic Product KRA Kenya Revenue Authority PAYE Pay as You Eam SME Small and Medium Enterprise VAT Value Added Tax lX ACKNOWLEDGMENTS 1 wish to extend my heartfelt thanks to: 1. God the almighty, for giving me life, good health, the strength, wisdom and opportunity to undertake my studies. Without his blessings, this achievement would not have been possible. 11. My Supervisor, Dr. David Mathuva, for his wise and impactful guidance. 111. My dad Harun, my mum Jane, and the rest of our family (Damaris, Virginia, Davie, Boniface, Ken, Angel, the late Ruby and Lydia) for their love, supp011 and understanding. IV. My wonderful friend Samuel (and countless others) for your support, words of encouragement and making it possible. v. All businesspeople who responded to my survey. v1. Moses (PhD finali-st) for his guidance through statistical analysis. v11. Evei·yone who' s encouraged, aided, or guided me along the jmnm!y. God bless you! X DEDICATION I dedicate this research to God, my family, friends, all the respondents, my professors, and to all the people who made this study possible. Most especially, I dedicate this to my family, we have walked this joumey together and they represent those who have influenced my life profoundly. God bless you. XI CHAPTER ONE: INTRODUCTION 1.1 Background of the Study The amount of money spent by the govenunent in provision of health, education, security and infrastmcture facilities and therefore economic growth is generally referred as public expenditure (Fagbemi, Uadiale & Noah, 2014). Taxation is a major source of finance for this public expenditure. Taxation of any country form the fiscal policies which are tools used by the govemment in achieving economic growth and stability. Taxation refers to the levy charged by the state to citizens in order to coilect revenue for economic growth and development. According to the World Bank (2013), taxes are a compulsory transfer of resources to the govemment from the rest of the economy. The major challenge with tax systems and economies today is -an increasing trend in tax evasion. Tax ~vasion is illegal and negatively affects the growth of an economy (Serem, Robert & Phillip, 2017). Most tax authorities are unable to meet revenue collection targets because of the increased trend in tax evasion among taxpayers across the world (John, Kamau & Nzioki, 2018). In Kenya for instance, the Kenya Revenue Authority (a govenunent tax agent) failed to meet the planed revenue collection targets by Kshs. 50 billion and Kshs. 172.4 billion for the financial years 2016/201 7 and 2017/2018 respectively (KRA, 2017) . Most economies today are characterized by an increasing trend of tax evasion where businesses are exploring all loopholes within the tax systems that help them either to declare less income as actually reported, fail to file retums in time or ' doctor' the financial statements in their favor. Since tax evasion is a crime, the whole concept can best be illustrated by the economics of crime model theory (Agago, Nittala & Tirfe, 2015). Although this increased trend in tax evasion has received great attention by scholars and academicians, much emphasis of the literature has focused on establishing factors behind this trend in different contexts. Little attention has been paid in relating personal as well as non-personal! factors with tax evasion. 1.1.1 Personal and Non-Personal Factors Personal factors shape one' s personality and determine the undertaken actions and their outcomes by people. Agago et al. (20 15) identified personal factors to include the age, occupation, level of income and education qualifications. Rodriguez-Justicia and Theilen (20 18) summed up personal factors into demographic components like gender categories, gender, levels of education, the type of one' s occupation and marital status. All these factors shape and determine people ' s personalities. Non-personal factors on the other hand cover a wide range of aspects like the interest rate, inflation, exchange rate, the prevailing tax systems that detennine the tax rates and tax bases in the country. More specifically, Litina and Palivos (20 16) identified non-personal factors as comprising of the tax rate and the economic factors prevailing in the economy. Personal and non-personal factors have been used to explain different behavior including tax compliance as well as noncompliance (tax evasion) (Pui-Yee, Moorthy & Choo-Keng Soon, 2017). According to Hofmann, Voracek, Bock and Kirchler (2017), taxpayers with high level of education are deemed to be more knowledgeable on the importance of paying taxes and thus have greater compliance which lowers tax evasion. On the contrary, Kasper, Kogler and Kirchler (20 15) indicates that the more educated the taxpayers are, the higher the degree of tax evasion since they have more knowledge on loopholes and flaws within the tax systems which they can capitalize on to evade taxes. According to Abdixhiku, Pugh and Hashi (2018), males tend to evade taxes more as compared to female taxpayers. Brink and Porcano (2016) indicates the people who are employed are economically empowered and thus would have low tax evasion as compared to the unemployed people. Aim (20 19) argues that less educated people have little or no knowledge on the need to pay taxes or file retums hence would evade tax as compared to the educated people. According to Basheer, Ahmad and Hassan (20 19), the prevailing economic factors like inflation, high interest rates, labor costs and a general decline in the levels of income all motivate taxpayers to evade taxes. 2 According to According to Dalu, Maposa, Pabwaungana and Dalu (2012), tax evasion among small business is affected by economic factors, tax rates and demographic factors. Tax rates have been widely recognized as the most primary determinant of tax evasion. Economic factor includes income level which is another important detenninant. It usually refers to the adjusted gross income or total positive income of a taxpayer. Gender of the taxpayer has been revealed to be significant in past studies. Vogel (2014) shows that the compliance levels of female taxpayers are higher than for males. It ' s against this backdrop that the study seeks to identify the effects of some of the personal and non-personal factors among tax payers while complying or not complying with taxes. Specifically, the study will examine the effect of non-personal factors, specifically tax rates and economic factors on tax evasion. Further, the study will also examine the effect of demographic factors on tax evasion, specifically the gender and age of a tax payer. 1.1.2 Tax Evasion Tax evasion affects various sectors of an economy and heaps adverse effect on an economy as a whole (Pickhardt & Prinz, 2014). Evasion of taxes tampers on the accuracy of microeconomic statistics thus leading to the misallocation of resources needed to stimulate the growth of an economy. Additiop.ally, the evasion of taxes alters the distribution of income in an arbitrary and erratic way. Increment in the propensity to evade taxes renders most govenunents unable to deliver it obligations and responsibilities in terms of improvement in standard of living to its citizens. Several countries have experienced loss in tax revenues due to tax evasion (Hashimzade, Myles & Tran-Nam, 2013). The United Kingdom estimates loss in tax revenues to be $21 billion per year (Slemrod, 2.016), Greece estimates showed loss in tax revenues to be $30 billion per year (Murphy & Higgins, 2014). In developing countries, overall tax revenues loss due to tax evasion is estimated at $285 billion per year (Khlif & Achek, 2015). The noncompliant behaviors of 3 citizens have forced most govenunents in raising tax revenues thereby heaping most burdens on individuals with favorable compliance behaviors. However, increment in such burdens towards the few citizens complying with taxes may not be economically viable on the basis of moral issues as well as social and cultural characteristics (Oz Yalama & Gumus, 2013). In Ghana, one of the many problems facing tax administration is tax evasion. Tax evasion is rampant due to lack of appropriate monitoring strategies in tracking tax revenues from tax officials and taxpayers (Adebisi & Gbegi, 2013). Several media platforms in Ghana headlines tax evasion as a massive hit in the Ghanaian economic. In 20 12, an additional $36 million shipped abroad mostly to non-taxable offshore accounted on the blind side of tax authorities. In October 2013, a giant media platforn1 known as peace online reported that the presidential taskforce uncovered over ·$367 million was lost in Ghana as a result of the tax evasion. In December 2014, it was reported that about $140 million in taxes were lost to the state in the mining sector alone between 2005 and 2007. Due to the massive airwave reports on tax evasion, tmst issues have been a problem in combating the evasion of taxes in Ghana (Casaburi & Troiano, 2015). Taxpayers are often of the view that tax officials hold the key to tax evasion by engaging in several cormpt practices such as issuing fake tax payment receipts to taxpayers among others. Aside the tmst issues, there are several non-economic and economic factors affecting tax evasion in Kenya. Tax rates, tax audits, penalties, are factors driving the evasion of taxes in Kenya. Therefore, it is important to investigate the drivers of tax evasion in Kenya. Kenya has established jurisdictions concerning administration of tax for example the Kenya Revenue Authority (KRA) in Kenya (KRA, 2017). Tax compliance indicates the ability of citizens in a country to honor their tax obligations in timely and convenient way. Tax compliance is the adherence to the established mles and regulations governing tax in a country. The tax rate charged by law is unsustainable for some SME businesses and this forces such businesses to adopt tax evasion strategies so as to remain competitive in the 4 marketplace. In Kenya, the applicable taxes are corporation tax at 30%, Value Added Tax (VAT) at 16%, Capital Gains Tax, Custom Duty at Excise duty ranging between 0% and 25% depending on the goods, gaming taxes at 15% and withholding tax ranging from 5% to 20%. Further the rates of penalties and interest levied under the Tax Procedure Act, 2015 are generally high with penalties being 20% of unpaid tax and 2% monthly interest on outstanding taxes. For an SME paying corporate tax at 30% as well as VAT at 16%, the rates would be to too high given all other operating cost of a business (KRA, 201 7). The judicial systems of a country will help in reduction of the tax evasion as it administers legal suits by the perpetrators of tax evasions (Pope, Rupe11 & Anderson, 2014). Generally, existence of severe penalties and higher audit probabilities significantly leads to tax compliance. Probability of detection indicates the chances or likelihood that · non-compliant individuals will be discovered by the tax authorities. People would like to entirely evade their tax liabilities and the only reason they might not do that is presence of non-zero probability of being caught i!1 tax evasion (Wallace, 2015). High tax rates and complex tax legislations significantly add up to tax evasion among businesses (Murphy & Higgins, 2014). Tax compliance costs are incurred by business entities so as to meet the requirements set out for compliance with certain tax levels and structures. Cost of compliance include accounting costs; economic costs; lobbying costs; training costs and lost revenue from the system. Businesses pay for time spent by intemal staff in understanding and applying the rules, payment of extemal experts, record-keeping costs, developing systems and related incidental costs. Further, some tax retums are to be submitted monthly, and committing human resources to these can lead to cash flow problems, since there would be less activity chasing after business related activities like debt collection. For purposes of this study, focus will not be placed on the compliance-related psychological costs (stress and anxiety of owners and their staff) (Rametse, 2009), but on the administrative workload and its relationship with the performance of the business. 5 1.1.3 Small and Medium Enterprises There has been no consensus on the definition of SMEs and researchers have given various definitions. For example, Kinjanjui (2016) defined SME's as finns employing between 1 and 150 persons. Soderbom (20 14) defined SMEs in Kenya as businesses employing between 10 and 100 employees. The definition varies from country to country. The broad Kenyan definition of SMEs includes micro enterprises. As per the International Finance Corporation (IFC) definition, SMEs implies any business in the private sector which employs between 50-300 employees. For purposes of this paper we shall go as per the IFC definition of an SME. An SME is an entity that does not have public accountability or publishes general purpose financial statements for external users e.g. owners not involved in day to day management; Kenya Revenue Authority; existing and potential creditors; credit rating agencies and whose debt and equity instmments are not traded in the public market (A domestic or foreign stock exchange or over the counter market) and does not hold funds in a fiduciary capacity for a broad group of outsiders as one of its primary businesses such as banks, credit unions, insurance companies, securities brokers/dealers, mutual funds and investment banks (ICP AK.com). SMEs play an imp01tant role in economic development of Kenya. For instance, majority of the firms enrolled in the Kenya Association of Manufacturers (KAM) fall under this category (Schaltegger & Wagner, 2017). Global statistics indicate that SMEs account for more than 70% of business enterprises. For instance, about 80 to 90 percent of business enterprises in the United States are SMEs with similar statistics for Canada. It is a recognized fact that majority of the large global corporations around the world like Ford, Acer Computer, Bata International, and Seagrams were started by founders who later developed business empires (Leonidou, Leonidou, Fotiadis & Zeriti, 2013). SMEs have traditionally operated in domestic markets, but increasingly find themselves obliged to internationalize, in order to survive in a market that is becoming more and more globally competitive. SMEs have attracted increasing attention in recent years in light of concrete evidence of the importance of new business creation fOi economic 6 growth and development (Somsuk & Laosirihongthong, 2014). SMEs in particular are attracting the attention of policy makers and researchers because it has been recognized during the last decade as an important and untapped source of economic growth. There are several sources of income, for example, corporate profits, individual incomes, employees ' salaries and commodities in the market. Corporate bodies pay corporate tax, goods and commodities attract VAT (Kogler, Batrancea, Nichita, Pantya, Belianin & Kirchler, 2013). Properties for instance transfer of title in land attract stamp duty as a source of revenue for the govemment and capital gains tax. Pay as You Eam (PAY E) is levied on employee income on a graduated scale on a monthly basis. Tax evasion in Kenya, especially among the small and medium enterprises is generally very high. Kenya is actually_ ranked among low-income countries or low compliance countries with hard task of ensuring efficient and effective tax administration. The Ethics and Anti-Corruption Conunission is recently investigating Darasa Investment that evaded paying Kshs. 2.5 billion taxes (EACC, 20 19). ln another recent case, Kenya Revenue Authority charged two business people (Mr. Kevalkumar Navin Maisura and Ms. Arti Jagdiesh Bakrania) with tax evasion amounting to Kshs. 7 billion. Hence, there is need to examine the effect of personal and non-personal factors on tax evasion among SMEs in Kenya which informed the study. 1.2 Statement of the Problem Tax evasion prevalence is vast and greatly impairs taxation's macro- economic objectives thus creating a gulf between actual and potential govenunent tax revenue raising many issues which need urgent attention and solutions. However much the govenm1ent endeavors to exercise its sovereign right to collect taxes, nobody likes paying taxes although there is great appreciation that taxes need to be paid and this drives some people into tax evasion making the govenunent constantly fail to raise targeted tax revenue (Brink & Porcano, 2016). 7 Tax evasion remains one of the challenges facing the tax administration for businesses in Kenya despite the fact that KRA perfom1s monthly taxpayer education progranm1es so as to improve tax compliance (KRA, 2011). Although there has been significant growth in tax collection, by over 300% (2003-2011), the contribution by SMEs has been very iow (KRA, 2013). Tax evasion has been a major issue for policies among different scholars although different reactions have been sought. In Nigeria, Atawodi and Ojeka (2012) studied factors affecting compliance of tax among the small and medium enterprises (SMEs) and established that high tax rates and complex filing procedures are the most crucial factors causing non-compliance of SMEs. This study was carried out in Nigeria and not in Kenya creating a knowledge gap. Macharia (2014) examined the effect of tax evasion on tax revenues in Kenya and established that tax evasion negatively but significantly affects tax revenue. Mukabi (20 14) examined · factors influencing turnover tax compliance in the Kenya_Revenue Autho1ity domestic taxes department and est.ablished that perceptions of taxpayers towards the tax system greatly determine the level of compliance for turnover tax. The study did not focus on tax evasion but rather on tax compliance which creates knowledge gap. Karanja (2014) sought to establish factors affecting voluntary tax compliance on rental income and revealed that attitude factors, high tax rate, unfair tax system, social norms, gender and level of education are significant and play a great role towards the compliance or non- compliance of Kenyan taxpayers on rental income. The study also focused on tax compliance and not specifically on tax evasion which create gaps. Thus, based on the aforementioned studies, it can be seen that some of them were done in different countries like Nigeria and not in Kenya. Other studies focused more on tax compliance and not tax evasion. This creates research and knowledge gaps that the current study sought to fill by examining the effect of personal and non-personal factors on tax evasion among SMEs in Nairobi County, Kenya. 8 1.3 Research Objectives 1.3.1 General Objective The purpose of this study was to the effect of personal and non-personal factors on tax evasion among SMEs in Nairobi County, Kenya. 1.3.2 Specific Objectives 1. To examine the effect of tax rates on tax evasiOn among SMES 111 Nairobi County, Kenya. 11. To assess the effect of economic factors on tax evasion among SMES in Nairobi County, Kenya. 111. To investigate the effect of demographic factors on tax evasion among SMES in Nairobi County, Kenya. 1.4 Research Questions 1. What is the effect of tax rates on tax evasion among SMES in Nairobi County, Kenya? n. What is the effect of economic factors on tax evasion among SMES in Nairobi County, .Kenya? 111. What is the effect of demographic factors on tax evasion among SMES in Nairobi County, Kenya? 1.5 Scope of the Study The study sought to establish the effect of personal and non-personal factors on tax evasion among SMEs in Nairobi County, Kenya. The study investigated the effect of tax rate, economic factors and demographic factors on tax evasion among SMEs in Nairobi County, Kenya. The study was canied out in Nairobi since there are many SMEs in Nairobi County. The study was conducted using primary data which was collected using questi01maires. The study was carried out in the month ofFebruary 2019. 9 1.6 Justification of the Study Taxation can have significant effects on the economy, including impacting on SME creation and the growth of SMEs in Nairobi. A 2017 National Economic Survey report by the Central Bank of Kenya (CBK) indicate that SMEs constitute 98 percent of all business in Kenya, create 30 percent of the jobs ammally as well as contribute 3% of the GDP. An exploration of the relationship between tax administration and perfonnance of SMEs is necessary and significant towards the development and growth of SMEs. If businesses are to grow and contribute to economic and social upliftment, the tax obstacles must be identified, and the path eased. - 1.7 Significance of the Study The findings o,f the study would be important to the management team of the SMEs, the Kenya Revenue Authority and the future scholars and academicians. To the management of the SMEs, the findings would establish the best way of enhancing compliance in taxation for the growth of the economy. The KRA would rely on the fmdings of the study to come up with best policies and guidelines for regulating tax evasion among businesses in Kenya. Through the findings of the study, the KRA would be able to understand the various factors affecting tax evasion in the country. The study would add to the existing literature and infom1ation on tax evasion in different contexts. This would help future scholars and academicians to carry out similar studies in future. The study would also reconm1end areas in future that studies should focus on and this would grow the available literature. 1.8 Or·ganization of the Thesis Chapter one outlines the background of the study, statement of the problem and research objectives. It also has sections on significance and scope of the study. Chapter two 10 provide an in-depth review of academic research on themes of the study. The theoretical framework is discussed. The section also covers empirical literature. It has a section on conceptual framework, drawing the relationship between the independent and dependent study variables. It also covers the summary of the literature and the research gap. Chapter three provides a brief overview of the research design, population and sampling frame of the study. In addition, it discusses the instruments, data collection and data analysis methods alongside ethical considerations which will be used in the study. Chapter four presents the findings of the analysis while chapter five gives a summary, conclusion and recommendations arising from these findings. 11 CHAPTER TWO: LITERATURE REVIEW 2.1 Introduction This chapter reviews relevant literature to the study as conducted by other different scholars. The chapter reviews the theories forming the basis of the study, the empirical literature, and critique of the literature, research gaps and the conceptual framework. 2.2 Theoretical Framework This study was infom1ed by the Economics of Crime Model, Prospect Theory and Social Identity and Self Categorization Theory. 2.2.1 Economics of Crime Model The Economics of Crime Model was- fonnulated by Becker (1968) when working on the problem on how to stop criminals from committing crimes and whether stopping crime is even desirable. Allingham and Sandmo· (1972) were first people to apply the Economics of Crime Model in compliance research. According to Osoro ( 1995), a rational consumer seeks to maximize the expected utility of tax evasion gamble, by balancing the benefits accruing from successful cheating against risks of likely sufferings from detection in the fonn of punishment. This school of thought holds that compliance is largely dependent on audit verifications and severity of penalties spelt out to perpetrators. This model is relevant to this study because it helps give a clear comparative analysis on declared income increases following an increase either in likelihood of been detected and the number of likely audits and verification which may lead to discovery of any form of tax malpractices. It is relevant for this study because it helps put into perspective the likelihood of individuals seeking compliance instead of evading tax compliance (Draca & Machin, 2015). A purely economic analysis of the evasion gamble suggests that most rational individuals should either undeiTeport income not subject to source withholding or over claim deductions not subject to independent verification because it is extremely unlikely that such cheating will be caught and penalized. This theory is relevant in 12 explaining the best way which tax evasion can be solved. From the theory, it can be infeiTed that an increase in penalties would make it costly for taxpayers to evade. The resultant effect would be to reduce tax evasion and thus increasing the amount of collected tax revenues. 2.2.2 Prospect Theory This theory was developed by the psychologists Kahneman and Tversky (1979). According to Prospect Theory, making of decisions under conditions of uncertainty is seen as a choice between gambles or prospects. Decisions that are made in relation to risks signify a choice made between different altematives that have close association with given gambles or prospects. According to Yitzhaki (1974), when fines are charged on tax evaded and of the preferences of the taxpayer satisfies the assumption of decreasing absolute risks aversion, then a negative relationship between taxes and tax evasion is predicted. According to the Prospects Theory, the losses and the gains of carrying out a ce1iain action are differently valued. However, people make their decisions based on perceived gains rather than perceived loss. The general idea behind this theory is that when individuals are presented with two choices (both equal) but one with has potential Joss and the other one with potential gains, the latter choice will be chosen as opposed to the fanner choice (He & Zhou, 2011 ). The theory is relevant to the current study since tax evasion is a risky action. Tax evaders therefore evaluate the perceived gains of evading tax and the potential losses of the same. The decision to evade tax is shaped by the potential gains of evasion as opposed to potential losses of evasion. Potential gains from tax evasion would be in the fonn of increased cash at the disposal of ' the business for investment, purchase of stock or distribution to the investors. On the other hand, potential loss would be penalties, interest or impriso1m1ent is a tax payer is caught evading tax. 13 2.2.3 Social Identity and Self Categorization Theory This theory was expressed put forth by scholars by the names Henri Tajfel and John Turner at the beginning of the 1970s and the 1980s. According to the theory, social identities are reflections of the social categories, groups, as well as the networks that an individual may belong. The core function of the assemblage to its members is its utility in increasing self-esteem and ego, internalized stereotypes as well as the nonns are advanced in a manner that they advantage the in-group. The theory also posits that the process of singling out the group by stereotype apportionment and the allocation of the cogi1itive frameworks is christened the "categorization" process Jackson (2004) defines social category diversity as dissimilarity 111 social category membership. For instance, it can happen if members . of the group vary in relation to gender, age or if they come from different etlmic groups. As a result of these differences, a team would achieve a low level of cohesiveness and sati sfaction . A relationship- oriented conflict will have a harmful effect on perfonnance if a team fails to control its differences, (Williams & O'Reilly, 1998; Tjosvold, 2003) . In accordance to social identity theory, personal idei1tity develops among people according to the group to which they fit in (Hogg, Ten-y & White, 1995). Being a member of a particular group happens when persons stereotype themselves by attributing to them behaviors, attitudes and other characteristics. Self-categorization is defined as the process of seeing oneself as a member of a group (Kulik& Bainbridge 2006). Social identity theory can be tern1ed as a theory of people belonging to a particular membership and portraying similar behavior (Hogg, 1995). It is how individual make sense and understand themselves in social settings and circles. This theory links the differences in demographic factors of tax payers like age, gender and levels of education and their influence on tax compliance or evasion. 14 2.3 Empirical Review 2.3.1 Effect of Tax Rate on Tax Evasion The relationship between tax cuts and increment in tax rates in curbing tax evasion has attracted numerous researches around the world. Allingham and Sandmo (20 13) argue that tax cuts may broaden tax base and improve compliance behaviors of citizens. However, Goh, Lee; Lim and Shevlin (20 16) asserted that increment in tax rates will exett fear into taxpayers' hence encouraging tax compliance. The study adopted descriptive survey design and employed the use purposive sampling method. Tax rates increase will result in an increase propensity to evade taxes. An upsurge in tax rates shifts the burden of tax payments to few individuals complying with taxes. According to Dyreng, Hanlon and Maydew (2018), such upsurge in tax rates will eventually compel taxpayers to adopt noncompliant behaviors hence affecting tax revenues needed to fund public expenditures. Mazzolini, Pagani and · Santoro (20 16) state that when tax rates are that high, nobody is going to pay, business will find a way to get out The study employed a descriptive survey design. High-end clients in New York are holding onto stocks and avoiding selling their business for fear of being bulldozed by a giant capital gains tax bill. The increase in the tax rates will lead to increase in the size of underground economy. Hanlon, Maydew and Thomock (20 15) further argues that there should be a reduction in tax rates in the legal sector; increase the punislunent for patticipation in the illegal activities and legalizing currently illegal activities such as gambling and use of manJuana. Fisman and Wei (20 13) were interested in fleshing out a widely held notion that higher tax rates will encourage greater evasion with a study that could assess the magnitude of the effect. Data was collected using stmctured questionnaires and purposive sampling technique was employed from thirty (30) respondents as a sample size used to collect data from the respondents. So, they decided to examine detailed statistics on a range of 15 goods expmied from Hong Kong to China, paying specific attention to the value and quantity reported by Hong Kong versus what was reported by China. The study indicated that, higher tax rates provoke tax evasion. The author captured this phenomenon in some detail when they look at how importers in China responde.d to high tariff rates by engaging in a rash of evas_ive behaviors . They find the reaction in that country to be so intense that tax increases may even produce a reduction rather than an increase in tax revenues. Carrillo, Pomeranz and Singhal (2017) opines that there are widespread practices of undenepmiing unit value of the imports and mislabeling higher-taxed products as lower taxed products. Kukaj, (20 16) analyzed the effect of tax rates on tax evasion by using aggregate US data - for the period 1941-1981. The study employed both descriptive and inferential statistics for data analysis. The study focused on the importance of inflation. It seems clear that inflation can .affect the decision to evade. Inflation erodes the real value of nominal disposable income and this induces taxpayers to restore their purchasing power through tax evasion. A change in the tax rate exe1is two opposing effects on the taxpayer. According to Dyreng, Hanlon, Maydew and Thornock (20 17 ), an increase in the tax rate induces greater evasion since it increases the marginal return to successful evasion. Reducing disposable income, a higher tax rate generates an additional effect (the income effect) which may lead to more or less evasion depending on the individual attitude towards risk. To the extent that an individual is less willing to take risk as his/her after- tax income declines, he/she will be less inclined to evade taxes when the tax rate mcreases. CaroB (2013) analyzed the reaction of taxpayers resulted from increasing tax rate. The research investigates a taxpayer panel to evidence the income declared in response of a tax rate change. The study embraced a descriptive research. The study concluded that increasing tax rate causes lowering the declared income for tax purposes. The research shows that income tax rate increasing during 2013 reduced the income gathered from tax administration with 39% at most and 13% at least. 16 From the reviewed literature, a negative relationship is predicted between tax rates and tax evasion. Most of the reviewed studies suggest that an increase in tax rate would lead to reduction in amount of taxes declared (tax evasion). However, some of these studies were done in advanced economies including United States of America while others collected data from secondary sources which creates knowledge gaps. 2.3.2 Effect of Economic Factors on Tax Evasion Income level fluctuations have had an impact on taxpayers evading behaviors. It is widely asserted that higher income level attracts higher compliance while lower-income taxpayers cormote lower compliance (Kasper, Kogler & Kirchler, 20 15). High income eamers are expected to exhibit wealth by complying to taxes while low income earners are expected to hide their actual income from tax officials (Donohoe, 20 15). An argument made by Birskyte (20 13) emphasized that income components is a major driving force in curbing tax evasion. Further, the researcher asseried that income source solely from wages and salaries minimizes tax evasion to an appreciable level (Basheer, Ahmad & Hassan, 2019). Nevertheless, works have also proven that there exists no statistically significant relationship between tax evasion and income. Mason and Lowry (2013) find that middle income taxpayers are generally compliant with tax laws, while low income level taxpayers and high-income level taxpayers are relatively non-compliant with tax laws. Income source usually refers to the type or nature ofthe taxpayer's income. Schmolder's (2013) show that when a large par1 of a country's labor force is engaged in agriculture and small trading, income and profit taxation is unsuccessful. The greatest opportunity to evade income tax exists from those who derive their income from agriculture, independent trades or self-employment, whereas the least opportunity exists for those taxpayers whose source of income is dependent on wages or salaries subject to withholding, such as from the services sector (Lefebvre, Pestieau, Riedl & Villeval, 20 15). 17 According to a study done by Carfora, Pansini and Pisani (20 17) the 1ssue IS the relationship between tax evasion and economic stability. The study embraced a descriptive research. Increase in the size of the underground activities implies that there is less reported taxable income which means that the government may confront a budget deficiency. Balafoutas, Beck, Kerschbamer and Sutter (20 15) point out that higher unofficial activities will decrease the legal GOP which can be interpreted as a sign of recession and increase the uncertainty and the risk of investment. Therefore, tax evasion leads to instability of the economy. Hence, it is expected that the increase in the amount of tax evasion causes the economy to become more instable. Alabede, Ariffin and Idris (2013) investigated individual taxpayers ' attitude and compliance behavior in Nigeria. The study adopted an exploratory research design. The study recognized that several factors may be responsible for low compliance in income tax.._administration in Nigeria. However, taxpayers ' attitude was identified as one factor that play important role in influencing tax compliance behavior. Data for the study were collected through a survey of individual taxpayers ' opinion, meanwhile the analysis was carried out using moderated multiple regression. The result of the study indicated that taxpayer's attitude towards tax evasion is positively related to compliance behavior due to the low income. Abdixhiku, Pugh and Hashi (2018) indicate that taxpayer' s risk preference has strong negative moderating impact on the relationship between mcome level towards tax evasion and compliance behavior. The reviewed literature established that economic factors affecting tax evasion include the level of incomes and presence of underground economies and they have an influence on tax evasion. Some of the studies reviewed however, were carried out in other countries including Nigeria, which points out the need for similar studies in Kenyan context. 2.3.3 Effect of Demographic Factors on Tax Evasion Gender of the taxpayer has been revealed to be significant in past studies. Calvin (2013) show that the compliance levels of female taxpayers are higher than for males and argue 18 that this compliance gap is shrinking over time as new generations of liberated women emerge. The study used descriptive research design where secondary panel data was collected. Demographic factors effect on tax evasion cannot be underestimated. On the account of gender, female taxpayers are more compliant than their male counterparts (Vogel, 2014). Evasion of taxes is more unacceptable behavior to female taxpayers than their male counterparts . The ·emergence of more independent non-traditional generation seems to be lowering the compliance gap between male and female taxpayers. With respect to age, Cyan, Koumpias and Mm1inez-Vazquez (20 16) note that it is believed that the aging taxpayers tend to be more compliant than the younger taxpayers. According to Eckel and Grossman (2013), younger taxpayers are more risk seeking and less sensitive to penalties. It is also argued that taxpayers who are 65 years and above comply more to taxes. Descriptive research design was adopted, and a questi01maire used __ to collect data. With regards to ethnicity, minimal research has been unde1iaken in accounting for the impact of etlmicitY on tax compliance: Benk, Budak, Yiizba!?I and Mohdali (2016) note that men and women significantly differ in their willingness to comply with their taxes across countries and conditions. These differences are remarkably large and are consistent across a wide variety of institutional choices. Simply put, women appear to be much more tax compliant than men in every country and under every condition. The evidence regarding gender differences, however, is somewhat contradictory. Wallace (20 15) has shown that men and women behave differently even when facing abstract choices. For example, women tend to be less competitive and less certain of the quality of their performance (Preece & Stoddard, 2015). Eckel and Grossman (2013) have demonstrated in a variety of experiments that women are more altruistic, but others have shown men to be more willing to conhibute to the public good. Men and women also appear to have different attitudes and behavior when it comes to taxation specifically. Besley, Jensen and Persson (20 19) found out that in contrast to men, women tend to think that the tax code is fairer, the likelihood of getting caught for evasion is greater, and they 19 overestimate the penalties for evaswn. In tenns of behavior, several tax compliance experiments have also shown women to be more compliant than men. The studies reviewed established some of the demographic factors affecting tax evasion as to include the age and education of taxpayers and their gender categories. The studies concur that as compared to men, women are more tax compliant. None of the studies, however, was done in the Kenyan context which brings in the research as well as knowledge gap that the sought to fill. 2.4 Summary and Research Gap Fisman and Wei (2013) investigated whether tax rates will encourage greater evasion in China; this study had a different contextual setting since it was done outside Kenya. Alabede, Ariffin and Idris (2013) investigated individual taxpayers ' attitude and compliance behavior in Nigeria, this study had a different contextu~l setting since it was done outside Kenya. Kukaj , (2016) analyzed the effect of tax rates on tax evasion by using aggregate US data, these studies were conducted outside Kenya, a different contextual therefore, the finding may not be reflected in the current study. Carol! (2013) analyzed the reaction of taxpayers resulting from increasing tax rate: the study only looked at the reactions and failed to look at the detenninant. Carfora, Pansini and Pisani (20 17) investigated the relationship between the tax evasion and economic stability; the study did not look at the detem1inants. Eckel and Grossman (2013) investigated why younger taxpayers are more risk seeking and less sensitive to penalties, the study only concentrated on age. 2.5 Conceptual Framework A conceptual framework is a model of relationship where researchers present the relationship between variables in a study and show the relat\onship graphically or diagrammatically. It gives an idea of the variables to be covered by the study. The dependent variable was tax evasion of SME whose indicators were revenue collection 20 and filled retum. The independent variables are to be examined to find out their level of effects on the dependent variable are: economic factors , tax rate and demographic factors. Independent Variable [ Dependent Variable J Economic Factors • Income level Tax Evasion Tax Rate • Revenue Collection • Penalties and interest • Cost of compliance L--------;1 • Payment of tax • Correct Filed Retums • Period of extension Demographic Factors • Age • Gender • Level of Education Figure 1.1 Conceptual Framework 2.6 Operationalization of Variables Table 2.1 gives a summary of bow the study variables were operationalized. Table 2.1: Operationalization of Variables Objective (s) Type of Type of Scale Indicators Type of Variable analysis To examine the effect ll1dependent Ordinal scale • Penalties • Descriptive of tax rates on tax tax rates and interest statistics evasion among SMES • Cost of • Inferential in Nairobi County, compliance statistics Kenya • Period of -extension To assess the effect of ll1dependent Ordinal scale • ll1come • Descriptive economic factors on economic level statistics tax evasion among factors • Inferential SMES in Nairobi statistics 21 County, Kenya To investigate the Independent Ordinal scale • Age • Descriptive effect of demographic demographic • Gender statistics factors on tax evasion factors • Level of • Inferential among SMES in Education statistics Nairobi County, Kenya Tax evasion among Dependent Ordinal scale • Revenue • Descriptive SMES in Nairobi tax evasion Collection statistics County, Kenya • Payment of • Inferential tax statistics • Conect Filed Returns 2.7 Chapter Summary The chapter has reviewed the economics of crime model, prospect theory and social identity and self-categorization theories that provided anchorage to the whole study. In addition to these theories, literature on personal and non-personal factors affecting tax evasion has also been extensively reviewed. The conceptual framework showing the variables of the study and their measurement is also well presented. 22 CHAPTER THREE: RESEARCH METHODOLOGY 3.1 Introduction This chapter presents the research methodology, the data collection process and data analysis, research design, the location of the study, the target population and sampling method to be used, the data collection instrument, data collection procedure, analysis and ethical considerations. 3.2 Research Design The study adopted a descriptive research design. This design is appropriate for this study as respondents of the study were expected to provide a description of the different drivers of tax evasion and how they affect the amount of revenue collected (Creswell , 20 13). Descriptive research design was appropriate for this study because, this research design concems itself with collecting infonnation on the respondents understanding, perception and opinion (Yin, 2013). It answers the question on where, what, how and where of a phenomenon or event. The descriptive design is the description of state of affairs as they exist at present. 3.3 Tar·get Population Population refers to the entire subjects that the researcher wants to study. According to Yin (2013), the population consists of the aggregate of the observable items which the researcher is interested in. The study targeted 2017 top 100 SMEs in Kenya witmer list, since they were deemed to be more experienced in matters of taxation (Bizna-Kenya, 20 18). The respondents of the study comprised of one director from each of these 100 SMEs hence making up 100 respondents. 3.4 Sampling Techniques Sampling is the process of selecting a group of subjects within the targeted population, who represent the larger population group. The study adopted purposive sampling 23 picking only the managing directors. Since the targeted population was relatively small , census was employed and thus 100 respondents were all included in the study. According to Lewis (20 15), a census gives valid data as all the population used in the study and there was no generalization of findings . Yin (2017) opines that a census is ideal whenever the population elements are less than 200. 3.5 Data Collection Instrument This study collected primary data tl·om the field with the help of questiom1aires that contained of close ended questions. Questiom1aires were used since they were relatively quick and easy to develop code and interpret.. The questionnaire covered the demographic infonnation and each of the four study variables (tax rate, economic factors, demographic .factor and tax evasion). The questionnaire used the five Point Likert scale to explain the extent of agreement in each of the study variables. The study applied self-administration method while issuing respondents with thequestionnaires. This was meant to raise the response rate of the study. The questimmaires were issued to the respondents at the place of work; respondents were allowed one week to fill the questionnaire before the researcher collected them for analysis. At the point of issuing the questionnaire, contact information of the researcher were given in order to respond to any queries that would arise while filling the questimmaire. 3. 7 Research Quality Before data collection conm1enced, the researcher took consideration of the elements that made up a good research in ten11S of validity, reliability and objectivity. This was done to ensure the information that would be collected would be free of bias and would be correct. To ensure research quality, the research instruments were subjected to pilot testing. The study used 5 respondents from 5 SMEs within Nairobi that have are not inclusive of the top-1 00 SMEs for catTying out pilot testing. The SMEs to take part in the pilot study were purposively selected. 24 3.7.1 Validity Validity refers to the extent to which the research instrument measures what it was expected to measure. Validity ensures that the data is reliable, tme and accurate (Pickard, 2012). To determine validity, the study engaged the supervisor in reviewing the questionnaires to make sure that the items measure the underlying construct in theories and the conceptual framework. At the end of tllis review, questions found to be invalid were completely removed from the questi01maires . 3.7.2 Reliability Reliability refers to consistency in the results obtained and it nom1ally is obtained using the test-retest reliability method (Bemard & Bernard, 2012) . To increase reliability, Yin (2013) noted that the similar items for testing need to be increased or testing diverse types of samples of people or events_ or units using unifonn testing procedure. To detennine reliability, all the piloted questionnaires were coded into SPSS and the Cronbach Alpha coefficient values were computed. According to Yin (2015), Cronbach alpha coefficient of 0.70 and above implies that the study instruments are reliable. The findings of reliability analysis are shown in Table 3.1. Table 3.1: Reliability Results Variable Number of Items Cronbach Alpha Coefficient Remark · Tax rate 8 0.765 Reliable Economic factors 6 0.874 Reliable Demographic 6 0.739 Reliable factors Tax evasion 14 0.760 Reliable Source; Research Data (2019) From Table 3.1, all the items have Cronbach Alpha coefficients above 0.7, showing that the instruments were reliable. This finding is in lined with Yin (20 15) who recommended a Cronbach Alpha of over 0.7 as adequ.ate for inferring that the instruments are reliable. 25 3.7.3 Objectivity The researcher ensured there was no bias during the process of data collection and analysis . This was done by first verifying that the data collection instruments were functional before the actual study commences. The discussions and conclusions were drawn from the study findings and were made free of personal perceptions, assumptions, ·. '· ' ·. ':1 . impressions, feelings and beliefs . :. . '. ;: .. ~: ·.. . . 3.8 Data Analysis and Presentation The data collected was measured to ensure that it confonns to the research objectives. The collected data was sorted to ensure that all the questionnaires are filled. The sorted questionnaires were coded into SPSS Version 23.0 for analysis and presentation. Data was then analyzed by use of descriptive and inferential statistics. Descriptive statistics were presented inf01111 of mean~ and standard deviation. Inferential statistics were presented by use of correlation analysis and multiple regressions. The multiple regression analysis was specified as follows; Where, Y it =Tax evasion X11 =Tax rate X21= Economic factors X3t= Demographic e;t = is the error tenn Whereby: ~o = the minimum Y when the rest of the variables are held at a constant zero The analyzed data was presented inform of figures and tables. 26 3.9 Ethical Consideration The researcher aimed at keeping ethics of research while conducting this study. The researcher sought pem1ission from the management of each SME before commencement of data collection (Flick, 20 15). The researcher sought permission from the Strathmore University- Institutional Regulatory Board (SU- IRB) to collect data. Confidentiality was maintained by ensuring the names of the respondents were not indicated anywhere, individual responses were grouped to get an overall opinion that was generalized to the study findings . The researcher endeavored to maintain anonymity of the respondents. 27 CHAPTER FOUR: PRESENTATION OF RESEARCH FINDINGS 4.1 Introduction Once data had been collected from the field, it was cleaned and populated in the Statistical Package for Social Sciences (SPSS). The analysis was then conducted on the data as presented in this chapter. For ease of presentation, the chapter is divided into sections starting with the infon11ation on respondents and the variables of the study. The inferential statistics covering correlation and regression analysis is also detailed in this chapter. The essence of the inferential statistics was to detem1ine relationship and the effect of the identified factors on tax evasion. 4.1.1 Response Rate A total number of 100 questi01maires were distributed to managing directors of the 2017 top 100 SMEs companies in Kenya. From these questionnaires, 79 . of them were completed by the respondents hence giving a response rate of 79%. The response rate was adequate and conquered with Yin (2017) who opines that for presentation and interpretation, good response rates should be over 70%. 4.2 General Information The general infon11ation on the respondents and the studied SMEs were collected and presented as shown in this section. 4.2.1 Gender of Respondents The gender distribution of respondents who took part in the study is shown in Table 4.1. Table 4.1: Gender of Respondents Frequency Percent Male 58 73.4 Female 21 26.6 Total 79 100.0 Source; Research Data (2019) 28 The findings in Table 4.1 indicate that while 73.4% of the respondents were male, 26.6% were female. This shows that both male and female respondents were involved in the study hence representative findings were sought on effect of personal and non-personal factors on tax evasion. 4.2.2 Age of Respondents The age brackets of respondents who took part in the study are as shown in Table 4.2. Table 4.2: Age of Respondents Frequency Percent 20-30 Years 5 6.3 31-40 Years 11 13.9 41-50 Years 47 59.5 Above 5 I Years 16 20.3 Total 79 100.0 Source; Research Data (2019) From Table 4.2, most of the respondents 59.5% were 41-50 years, 20.3% were over 51 years, and 13.9% were 31-40 years while 6.3% were 20-30 years. This implies that respondents who took part in the study were adults who probably understood tax evasion. Hence, the information they gave on tax evasion was reliable as presented herein. 4.2.3 Level of Education of Respondents The study sought to understand the highest level of education of the respondents as a way of predicting their knowledge and ability to read, write and interpret the research questions as shown in Table 4.3. Table 4.3: Level of Education of Respondents Frequency Percent Certificate 7 8.9 Diploma 18 22.8 Undergraduate Degree 42 53 .2 Post Graduate Degree 12 15.2 Total 79 100.0 Source; Research Data (2019) 29 The study established that 53.2% of the respondents had undergraduate degrees, 22.8% had diplomas, and 15.2% had post graduate degrees while 8.9% had a certificate. This shows that respondents of the study were generally learned and thus could read and interpret the research questions properly. They were also knowledgeable on matters of tax evasion as sought by the study. 4.2.4 Length of SME Operation The findings on the number of years that the studied SMEs had been in operation are summarized in Table 4.4. Table 4.4: Length of SME Operation Frequency Pucent Less than 3 Years 5 6.3 4-6 Years 29 36.7 7-9Years 28 35.4 Above 10 Y-ears 17 21.5 Total 79 100.0 Source; Research Data (2019) As indicated in Table 4.4, majority of the SMEs top 100 SMEs in 2017 had been operation for 4-6 years, 35.4% for 7-9 years, 21.5% for over 10 years an 6.3% for less than 3 years. Thus, most SMEs studied had been in operation for a relatively long period of time hence suitable for case studies. 4.2.5 Whether Tax Evasion is a Key Concern The study sought to detennine whether tax evaswn IS a key concern 1ssue and the findings are reported in Table 4.5 . Table 4.5: Whether Tax Evasion is a Key Concern Frequency Percent Yes 58 73.4 No 21 26.6 Total 79 100.0 Source; Research Data (2019) 30 Table 4.5 shows that most of the respondents 73.4% believed that tax evasion is a key concem. This is probably because it is illegal and attracts heavy penalties and fines once caught up. The finding is consistent with Pickhardt and Prinz (2014) who established that tax evasion affects various sectors of an economy and heaps adverse .e ffect on the economy as a whole. Hashimzade eta!. (2013) also points out that several count1ies have experienced loss in tax revenues due to tax evasion. 4.3 Descriptive Analysis The study had three specific objectives which were; to examine the effect of tax rates on tax evasion among SMES in Nairobi County, to assess the effect of economic factors on tax evasion among SMES in Nairobi County and to investigate the effect of demographic factors on tax .evasion among SMES in Nairobi County, !