Measuring multidimensional demographic convergence with indices of multiple variability

We aim to test the demographic convergence of populations towards a common pattern, which is one of the focuses of both the First and the Second Demographic Transition theories (represented by, respectively, FDT and SDT). Many studies have used different statistical indices of variability, but have only focused on a one-dimensional perspective, testing the convergence of each variable one at a time. In fact, each population is characterized by all the different demographic phenomena, so it could be interesting to test the convergence in a multidimensional perspective, considering all variables together at the same time. We propose a new statistical method useful for this aim. Here, we consider the crude birth rate, the crude death rate, the infant mortality rate and the aging index, which are the variables involved in both the FDT and the SDT theories. In fact, the SDT theory also includes other variables, such as those related to migration and to the family formation. We define some suitable absolute indices of multiple variability and, with the aim of evaluating the degree of convergence, the corresponding normalized ones with values comprised between 0 and 1. We test the convergence of the populations belonging to the European Union for all the years from 1960 to 2007.