Upper tail dependence between rates of sexually transmitted diseases and rates of unemployment/poverty

In this work we estimate the upper tail coefficient between each one of the following three sexually transmitted diseases: Chlamydia, Syphilis and Gonorrhea and each one of the rates: (a) Unemployment and (b) Poverty. We use records coming from the 50 states of the United States and the District of Columbia, of the year 2016. To estimate the upper tail coefficient, we first model the dependence between each disease and each rate (a) and (b) through the Joe’s copula and by mean of a Bayesian approach. Our results point to evidences that could be valuable if we want to establish priorities between co-factors of economic nature, in the incidence of certain sexual diseases. For instance, when comparing the magnitud of the upper tail coefficients, for each desease with each rate: (a) and (b), we observe that in the case of Chlamydia and Gonorrhea, the Poverty shows a greater degree of dependence in the upper tail while for Syphilis the Unemployment shows greater dependence in the upper tail.