Although reducing poverty in the income or consumption perspective remains a top priority in the developing world, other dimensions are also critical to a decent life, such as health, education, and living conditions. However, one main challenge is to define an indicator that better reflects the multiple dimensions of capabilities or human needs in modern societies. Adriana Stankiewicz Serra (UNICAMP), Gaston Yalonetzky (Leeds University), and Alexandre Gori Maia (UNICAMP) have proposed new multidimensional poverty measures for Brazil, based on essential and policy-relevant well-being indicators that go beyond income needs. The authors highlight how the poor population may more than double if we consider non-monetary dimensions of poverty.

In the paper recently published in the journal Social Indicators Research (click here), the authors compared multidimensional poverty measures using two methods: i) the Alkire-Foster (AF) counting method, and ii) the Permanyer two-stage identification approach. The authors also compared the dynamics of multidimensional poverty between classes of rural/urban municipalities, defined mainly by demographic density and distance to the most important urban centers. 

The results highlight how multidimensional poverty is higher in remote municipalities than in municipalities close to a city. In other words, the distance to an urban center plays an essential role in the process of socio-economic development: the proximity to an urban center matters for both better opportunities of employment (and income) and better access to basic requirements for adequate living conditions and educational achievement. Nonetheless, multidimensional poverty declined most sharply in less developed areas, probably reflecting the effect of public policies targeted to the poorest localities, such as the rural electrification program. In turn, income poverty decreased faster in rural municipalities close to a city, probably also hinting at the role of market access in rural economic development. 

The authors also show that only one-quarter of the population identified as poor based on either monetary and non-monetary poverty perspective is simultaneously poor in both of them. The diversity and lack of coordination of social policies targeted at the poorest in Brazil may explain this result. For example, cash transfers may reduce income poverty but may have little, if any, effect on other dimensions of poverty (education, for instance).