Los medios de comunicación como agentes de socialización

Variance Inflation Factor (VIF) was used to detect the presence of multicollineaity.

The VIF measures how much the variances of the estimated regression coefficients are inflated as compared to when the independent variables are not related. Neter, Wasserman and Kutner (1990) suggested the use of VIF as a method of detecting the presence of multicollinearity. They suggested the value of 10 or more as an indication of the presence of severe multicollinearity. The formula is given as:

2

1 1 _k

k R

VIF 



Where:

2

Rk

= the squared multiple correlation for predicting the kth predictor from all other predictors.

The result in Table 5 shows that there is no multicollinearity between the independent variables in this research.

Table 6: Regression Results

Expected sign

Panel A Pooled coefficient

t-test

Panel B Fixed coefficient

t-test

Panel C Random coefficient

z-test

COMPit + .0402381 0.96 .1831796 4.28 .0965632 2.33

NPM_it + -.6875522 -7.35** -.7104689 -7.22*** -.6957037 -7.44

MGQL_it + -.1351595 -0.04 -.7476853 -0.23 -.3228714 -0.10

LDRit + .3128405 0.10 -.012861 -0.00 .2212651 0.07

CONSTANT .4308628 0.14 .9874056 0.30 .597227 0.19

R² 0.2747 0.2723 0.2744

N 150 150 150

F* 13.73 0.000* 13.46 0.000* 56.56 0.000*

Hausman Test - -

1.30 p-value 0.8606

Corr(Ui, X) - - -0.0766 - 0 -

Dependent variable: ETR.

Note: *, **, ***

Shows significance at 1%, 5% and 10% respectively Source: Appendix A16

To find the relationship between the dependent variable and the independent variables and the magnitude of the impact of the independent variables on the dependent variable, a pooled regression as well as fixed effects and random effects regressions were conducted.

1. The pooled regression from Panel A shows a 0.0402381 effect of COMP on ETR, the fixed effect in Panel B showed a 0.1831796 effect of COMP on ETR and the random effect in Panel C showed that COMP also impact on ETR by 0.0965632.

Based on the objective one of the study which is to determine the effect of competition on tax avoidance among the Nigerian deposit money banks, the approaches (the pooled, fixed and random effects) showed a positive effect of COMP on ETR. The pooled regression, the random and the fixed effects show significant effects respectively. This means that for every 1 point of increase in competition among deposit money banks in Nigeria effective tax rate will:-

a increase by 0.0402381 points in the pooled effect model and b increase by 0.1831796 points in the fixed effect model and c increase by 0.965632 points in the random model.

This implies that there is increase in government revenue hence, the absence of tax avoidance.

2. According to the pooled regression result in Panel A, the relationship between NPM and ETR is insignificant and negative with a coefficient of -0.6875522. The fixed effect estimation in Panel B shows that there is a negative relationship between NPM and ETR with a coefficient of -0.7104689. The random effects result in Panel C also shows an insignificant and negative relationship between NPM and ETR with a coefficient of -0.6957037. The negative effect of NPM in the models implies that ETR will decrease by 0.687 points for pooled regression

0.7104689 points for fixed effect and 0.70 approximately for random effects as a result of 1 point increase in NPM. From the results in all the models, as NPM rises, ETR fall: Thus, a rise in NPM means a rise in tax avoidance.

3. Result of the pooled regression from table 4 in Panel A shows that the relationship between MGQL and ETR is insignificant and negative with a coefficient of -0.1351595. The fixed effect in Panel B, the relationship between MGQL and ETR shows an insignificant and negative relationship with a coefficient of -0.7476853. The random effects measure of the relationship between MGQL and ETR in Panel C shows that the relationship is both insignificant and negative with a coefficient of -0.3228714. Based on the objective of the research, to determine how managerial efficiency affect effective tax rate, it shows that a 1 point increase in MGQL brings about more than 0.135 points reduction in ETR, implying an increase in tax avoidance for the pooled regression, a reduction by 0.7476 points for fixed effect and a reduction of 0.3228 points for random effects. Hence, there is an insignificant and negative relationship between MGQL and ETR among Deposit money Banks in Nigeria.

4. Another objective of this study is to evaluate the impact of non-performing loans on tax avoidance in the banks. From the pooled regression result in Panel A, the relationship between LDR and ETR is positive and insignificant with a coefficient of 0.3128405. The fixed effect result in Panel B, shows that LDR has an insignificant negative relationship as evidenced by a coefficient of -0.012861.

Also, the random effect in Panel C, shows that LDR has an insignificant positive impact on ETR. This means that a unit increase in the level of LDR will bring about an increase in the level of effective tax rate by more than 0.013 points in the

fixed effect, an increase of 0.3128 and 0.2213 points in the pooled model and random effect model respectively.

5. The robustness tests was conducted for the model, it has a correct functional form and the model‟s residuals are serially uncorrelated, normally distributed and homoskedastic. Therefore, the outcomes reported are serially uncorrelated, normally distributed and homoskedastic. Hence, the results reported are valid for reliable interpretation. The Hausman specification test shows that the random effects model is a better estimator than the fixed effects model since the Hausman test result shows a chi-square value of 1.30, with a p-value of 0.8606 at 5%

significance level.