Tests for causality were not undertaken as it is difficult to be sure that all underlying hypotheses of the models are true and that all confounding variables are controlled for. As the dataset is extremely rich in quantity and representativeness of observations, and quality and diversity of explanatory variables, the statistical power of the results is naturally increased. The use of control variables also enhances the accuracy of the measures for participation decision by women. As the subject of study is of great complexity, any method/approach has its strengths and weaknesses and can provide at most provisional, partial, and conditional explanations. Therefore, the robust relationships can only be clarified through an overview of the research in the area in question and the confluence of the diverse streams of evidence.