  Brazil is the 5th largest country in the world, despite of having a ``High
Human Development'' it is the 9th most unequal country. The existing Brazilian
micro pension programme is one of the safety nets for poor people. To become
eligible for this benefit, each person must have an income that is less than a
quarter of the Brazilian minimum monthly wage and be either over 65 or
considered disabled. That minimum income corresponds to approximately $2$
dollars per day. This paper analyses quantitatively some aspects of this
programme in the Public Pension System of Brazil. We look for the impact of
some particular economic variables on the number of people receiving the
benefit, and seek if that impact significantly differs among the 27 Brazilian
Federal Units. We search for heterogeneity. We perform regression and spatial
cluster analysis for detection of geographical grouping. We use a database that
includes the entire population that receives the benefit. Afterwards, we
calculate the amount that the system spends with the beneficiaries, estimate
values \textit{per capita} and the weight of each UF, searching for
heterogeneity reflected on the amount spent \textit{per capita}. In this latter
calculation we use a more comprehensive database, by individual, that includes
all people that started receiving a benefit under the programme in the period
from 2nd of January 2018 to 6th of April 2018. We compute the expected
discounted benefit and confirm a high heterogeneity among UF's as well as
gender. We propose achieving a more equitable system by introducing `age
adjusting factors' to change the benefit age.
