MEASURING WELL-BEING IN A CONTINENT OF CONTRASTS

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A few days ago, Forbes magazine released the 2014 list of World’s billionaires. Seven Latin American billionaires made the top 100, with Mexican telecom tycoon Carlos Slim, in the second spot. In total, there are almost 100 billionaires in the continent and their combined fortunes add up to US$500 billion.  But on the other hand,  Latin America is still home of 160 million of poor, equivalent to 35% of the population in the region (World Bank data), despite intense governmental efforts to reduce poverty.

Furthermore, the OECD in the report How’s life in 2013 noted that countries, such as Mexico and Chile are way below the OECD average of GDP per capita and gini coefficient. However, the report also mentions that despite economic difficulties faced by the population, Brazil, Mexico and Chile have higher spreads of life satisfaction. In fact, out of range from 1 to 10, Mexico scored 7.3, Brazil got 6.7 and Chile scored 6.5 just below the 6.6 OECD average score.

The How’s life in 2013 report shows a new approach to quantify and understand poverty. At first well-being of population was measured only on the basis of material resources reflected on the GDP per capita. In the early 1990s, the UNDP Human Development Index (HDI) incorporated health and education. Today, several countries are shifting to more comprehensive forms of measurement. This new methodology seems to take on board the approach based on capabilities (functionings) that Amartya Sen fiercely defended.

In 2008, Mexico started using this method in its poverty measurements and included six basic social rights in the Law for Social Development. Also, Colombia, El Salvador and the Brazilian state of Minas Gerais have included multidimensional approaches to measure poverty. These governments sought to a better assessment of the capabilities and potential of citizens.

But what exactly is a multidimensional approach of poverty? Poverty itself has several aspects. Poverty measurements should include elements that could cause or further increase the situation of deprivation populations. El Salvador, for instance, identified eight dimensions to be observed and addressed as part of its poverty measurements: employment, housing, education, security, recreation, health, nutrition and income. Colombia chose to evaluate social and health conditions by measuring the following five conditions: education, childhood and youth, labour, health and access to household utilities. While Mexico selected educational, access to healthcare, social security, housing quality, access to basic services and nourishment. In turn, based on these elements the Mexican government classified deprivation in three categories: 1) food insecurity (extreme poverty), 2) obstacles to development of capabilities (access to education and health) and 3) material deprivation (access to adequate housing and transport).

This trend is not unique to Latin America; Bhutan, Malaysia and some areas in China have also adopted it. The most commonly known is the Gross National Happiness Index of Bhutan that includes nine dimensions.

The importance of a multidimensional poverty approach is based in the fact that it highlights aspects that are lagging behind and that require intervention. In other words, by having measurements of different dimensions of deprivation, decision-makers are able to identify elements that need immediate attention of public policies. Policy-makers can also observe progress of social policies and can reassess the continuation or reformulation of current strategies.

While developing countries have made significant efforts to better understand and find solutions to address poverty, results are meager and governments still face enormous challenges. The multidimensional index is a photographic representation of the reality of poverty. To change the socio-economic landscape of the continent of contrasts, coordinated public and private efforts, along with civil society engagement, are in most need to eradicate poverty and reduce inequality.

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Filed under Analysis, Countries / Regions, Development, Macroeconomics, Uncategorized

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