Multicollinearity Multicollinearity is one of the common problems in spatial regression analysis. Sometimes some or all of the explanatory variable are highly correlated in the sample data, which means that it is difficult to tell which of them is influencing the dependent variable (Barrow, 2009, p. 306). Hence, to check whether the independent variables are correlated with each other, a correlation matrix for the three indicators was measured using excel. The correlation matrix in table 2 (see below) shows the correlation coefficients between the indicators. This was done to increase the efficiency of the analysis by checking for spurious correlations. Thus, the correlation matrix indicates that none of the indicators are strongly correlated
