I'm performing a principal component analysis (PCA) using some economic variables of a region. I have six variables and I want to reduce them to two principal components. Most of the variables have a larger value in either one of the first two principal components' eigenvectors. For example, they either have a large value in the first principal component [eigenvector] and near zero in the second, or vice versa.
However, I have one variable that has almost the same value in the eigenvectors of the first and the second principal components.
Does this tell me anything about this variable? Should I keep it or should I remove it from the analysis?