The main goal of this paper is to define a new kind of economic indicator which can measure the evolution of inequalities in a given region during a time period, even when the dataset is incomplete or irregular. By using interpolation techniques and concepts related with poverty, we define an index for each structural unit. For the purposes of this paper, each considered unit is a different European country.

Of course, poverty and inequalities are different concepts. Poverty can be either an individual or a collective property of society, but inequality can only be considered as a collective property. Nevertheless, using a relative approach, we should consider the relationship between poverty and inequalities, because an individual can only be considered poor when he/she is compared to others.

Summarizing the methodology used, we generalize the Lorenz curves to give a bidimensional structure and a subsequent result quite similar to the well-known Gini index. With a low computational cost, we are able to include a variety of measures (obtained through the whole time period) in one single indicator, and we will see the major properties of the defined indicator.

Finally, the indicators will be applied to a region in Europe (Southern countries in the European Union). As one can check, the traditional Gini index is not valid when the dataset comprises different years or in the case of the database is incomplete, so it is worthwhile applying the new method to calculate a new, useful structure replacing the role that the Lorenz curve had in classic studies.