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Table 1. Presentation of Demographic Summary of Accounts Respondents

Table 1 Presentation of Demographic Summary of Accounts Respondents

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Table 2. Descriptive Statistics of the level of EMA practices
Table 2. Descriptive Statistics of the level of EMA practices
Table 3. Level of EMA Techniques applied among Firms in Nigeria Multicollinearity Test for independent variables
Table 3. Level of EMA Techniques applied among Firms in Nigeria Multicollinearity Test for independent variables
Table 4. Mutlicollinearity Test for EMA, SIZ, LEV and GRW Prior to the regression analysis, the presence of multicollinearity was tested. Multicollinearity occurs when two or more independent variables are correlated making it exceedingly difficult to isolate the effect of each independent variable on the dependent variable (Mumbi, 2014). Variance Inflation Factor was used to measure the degree of collinearity. The VIF and tolerance statistics (with tolerance being 1 divided by VIF) are relevant for this test. If the largest VIF is greater than 10, it calls for concern (Myers, 1990; Bowerman & O’Connel, 1990); If the average VIF is substantially greater than 1 then the regression may be biased (Bowerman & O’Connel, 1990); Tolerance below .1 indicates a serious problem; Tolerance below .2 indicates potential problem (Menard, 1995). For the current model the VIF are far below 10 and the tolerance Statistics all well above 2; therefore we conclude that there is no collinearity within the data set and thus the regression analyses.
Table 4. Mutlicollinearity Test for EMA, SIZ, LEV and GRW Prior to the regression analysis, the presence of multicollinearity was tested. Multicollinearity occurs when two or more independent variables are correlated making it exceedingly difficult to isolate the effect of each independent variable on the dependent variable (Mumbi, 2014). Variance Inflation Factor was used to measure the degree of collinearity. The VIF and tolerance statistics (with tolerance being 1 divided by VIF) are relevant for this test. If the largest VIF is greater than 10, it calls for concern (Myers, 1990; Bowerman & O’Connel, 1990); If the average VIF is substantially greater than 1 then the regression may be biased (Bowerman & O’Connel, 1990); Tolerance below .1 indicates a serious problem; Tolerance below .2 indicates potential problem (Menard, 1995). For the current model the VIF are far below 10 and the tolerance Statistics all well above 2; therefore we conclude that there is no collinearity within the data set and thus the regression analyses.
Table 5. Results of regression using ROE
Table 5. Results of regression using ROE
Details of EMA Practices among Firms Sources: (Enahoro, 2009; Mumbi, 2014) Appendix 1. Parameters and measurement of EMA Practices
Details of EMA Practices among Firms Sources: (Enahoro, 2009; Mumbi, 2014) Appendix 1. Parameters and measurement of EMA Practices
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