A public micro pension programme in Brazil: Heterogeneity among states and setting up of benefit age adjustment

TL;DR

This study analyzes the heterogeneity of Brazil's micro pension program across states, examining economic impacts, geographical differences, and proposing age adjustment factors to improve equity.

Contribution

It provides a comprehensive quantitative analysis of heterogeneity in Brazil's micro pension system and proposes a novel age adjustment mechanism for fairness.

Findings

High heterogeneity among states in benefit distribution

Significant gender differences in benefit amounts

Geographical clustering of benefit recipients

Abstract

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.