Estimating Lower Tail Dependence Between Pairs of Poverty Dimensions in Europe
提出一种半参数Copula方法，用于测量欧洲贫困维度对在极端低值处的相依性，并发现2009至2018年间多个欧洲国家的下尾相依性显著增强。
This article provides an innovative method for measuring the dependence between pairs of poverty dimensions using a semiparametric copula approach that permits us to account for the importance of extreme low values. The association between pairs of poverty dimensions at the lower tail is easily measured using the parameter estimates of the specified parametric copula, and no further calculations are needed. This approach is used to measure the bivariate lower tail dependence between the dimensions of the AROPE rate in Europe at two time points (2009 and 2018). The findings reveal a statistically significant increase in the lower tail dependence between 2009 and 2018 in several European countries.