1 CHAPTER 1: INTRODUCTION 1.0 Chapter ... - DSpace@UM

4.5.2 Correlation Matrix 2 between Tax Fairness, Demographic factors and TaxComplianceResearch question 2:Do age, gender, educations level and employment status haveimpact on tax fairness and indirectly influence tax compliance.Table 4.8A shows the results of Correlations Matrix 2. Demographic factors; gender,age, education and employment status (in conjunction with tax fairness) when correlatedwith tax compliance, only education was found to be significantly correlated with r =0.123 at p< 0.05. However, Richardson (2006) stated that age and gender weresignificantly correlated. The reason could be that the sample was MBA students whowere with high education background. The earlier two significant tax fairness dimensionsin Matrix 1 still remained significant in the second Matrix model.In this Malaysian setting, demographic factors when applied (in conjunction with taxfairness dimensions) don’t show great impact on tax compliance. Thus research question2 is partially supported because only education was the only significant demographicfactor (in conjunction with tax fairness dimensions) on tax compliance. The data wasfurther explored using OLS multiple regressions to examine the four hypotheses H2 to H5which are discussed in the next section. For the purpose of correlation and regressionanalysis, factor scale score was used for each value of the dimension being tested as wasdone by Richardson (2006).Factor scale score is the regression weight of each item thatmakes up the dimension. In order to get the score for a dimension the items usingregression weights which were extracted from factor analysis were added up. The factorscore is then saved and used for further regression analysis.68