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Therefore the chances are underreporting will increase and honest tax reporting willdecrease. This creates an inverse relationship between self interest and tax compliance.Spicer & Becker (1980) used taxpayer’s tax rate and the tax rates of other taxpayers’ tooperationalize tax fairness. The results were evasion increased (decrease) when thesubjects were informed that their tax rate is higher than (less than) the tax rates of theothers. These results also were not consistent because other studies by Milliron (1985a)and Kaplan & Reckers (1985) found no relationship between tax rate and evasion.2.5 Demograhic Factors and Tax FairnessThe taxation literature has statements that demographic dimensions have impact on taxcompliance e.g. Andreoni et al. (1998) stating types of income affects compliance rate.The study also reported noncompliance was higher among taxpayer over 65 years old.Another by Feinstein (1991) stating the rate and degree of noncompliance is less withhouseholds who are over 65 years old. Data from Taxpayer Compliance MeasurementProgram (TCMP) used by IRS of the US shows types of income affects compliance rates(US GAO, 1990). Dubin & Widle (1998) based the study on data from TCMP and censusstated noncompliance is greatest where a non-white population is high. Baldry (1987)based data from TCMP and census and found age and gender affect compliance rate.According to Chan et al. (2000) demographic variables indirectly affect tax complianceon three aspects; attitudes, perceptions and noncompliance opportunity.40
Jackson & Milliron (1986) found that gender has an influence on tax compliance;younger, single males are more likely to evade. Other previous studies that showedsignificant differences between male and female as indicated in the literature are (Kinsey& Grasmick, 1993; Mason & Calvin, 1978; Porcano, 1988; Vogel, 1974; and Wenzel,2002). Age is another demographic factor found to have a positive link with taxcompliance. Researchers of tax compliance studies like (Vogel, 1974 and Mason et al,1975) have stated that older taxpayers’ are more compliant. However, as mentioned byMcGowan (2000), generally studies do not show clear systematic patterns of howdemographic factors affect taxpayers’ perception on fairness.Richardson (2006) has used demographic factor as a control variable also. Researchersfelt that demographic variables affect tax compliance through indirect means such as theattitudes and noncompliance opportunity. For the purpose of this study demographic datawas collected to consider the impact on tax compliance behaviour directly and alsoindirectly (age and gender).Prior studies mostly have tested the direct associationbetween demographic factor with tax compliance and as compared with those that havetested the association of the impact of tax fairness on demographic factors that ultimatelyaffects tax compliance behaviour.Jackson & Milliron (1986) were the first to consider the impact of demographic factor ontax compliance by looking at the direct impact of demographic factors such as age,gender, education, income level, income source, marginal tax rate, fairness, complexity,and revenue authority and tax morale. Richardson (2006) reported that older taxpayers41
Page 4: noncompliance which means not repor
Page 10 and 11: individuals that push for tax fairn
Page 12 and 13: Following from hypothesis H1 - H5,
Page 14 and 15: 1.6 Limitations of the StudyThe fin
Page 16 and 17: CHAPTER 2: LITERATURE REVIEW2.0 Cha
Page 18 and 19: compliance research and numerous ta
Page 20 and 21: stated crime is an industry where m
Page 22 and 23: 2.2 Definition of Tax FairnessThe l
Page 24 and 25: Distribution in tax fairness refers
Page 26 and 27: elief, and evaluation between pragm
Page 28 and 29: elief that unfairness in the tax sy
Page 30 and 31: elevance of knowing the attitudes o
Page 32 and 33: It has been admitted by many resear
Page 34 and 35: significant results. The reasons gi
Page 36: unfair and also their exchange with
Page 39: (vertical equity) or in other words
Page 43 and 44: differences. Therefore the findings
Page 45 and 46: study education which is a noncompl
Page 47 and 48: CHAPTER 3: METHODOLOGY3.0 Chapter O
Page 49 and 50: Table 3.1: Reversed Coded Items on
Page 51 and 52: 3.2 Sampling DesignA non probabilit
Page 53 and 54: correlations and multiple regressio
Page 55 and 56: the four Federal Territory IRB bran
Page 57 and 58: analysis was carried out. Firstly,
Page 59 and 60: Table 4.3: Mean and Standard Deviat
Page 61 and 62: factor analysis was considered appr
Page 63 and 64: paid is fair to himself). Based on
Page 65 and 66: dependent variables but having the
Page 68 and 69: 4.5.2 Correlation Matrix 2 between
Page 70 and 71: 4.6.1 H1: There is a positive assoc
Page 72 and 73: The second predictor which was sign
Page 74 and 75: analyzed in Model 3a and 3b to know
Page 76 and 77: Model 3a band 3b was specifically t
Page 78 and 79: CHAPTER 5: CONCLUSIONS AND RECOMMEN
Page 80 and 81: taxes they pay, and may not be payi
Page 82 and 83: in the pay statements and they have
Page 84 and 85: service announcements such as, tele
Page 86 and 87: BIBLIOGRAPHYAllingham, M., & Sandmo
Page 88 and 89: Fallan, L. (1999), “Gender, expos
Page 90 and 91:
Mazur, M. .J. & Plumley. A. (2007),
Page 92 and 93:
Singh, V. (2003), “Tax Compliance
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