By: Lykke E. Andersen*
Two of the Sustainable Development Goals recently agreed by all the member states of United Nations are to reduce poverty and to reduce inequality, and for those goals to be realized, the incomes of the poorest 40% of the population have to increase. Designing policies to reduce poverty and inequality at the very least requires us to know where to find the target population. In this blog I will argue that they are probably not where you think they would be.
At INESAD we are in the process of writing a 10-year anniversary book called “El ABC del desarrollo en Bolivia” with 30 chapters on the different dimensions of development (Agua, Basura, Crimen, Desigualdad, Educacion, Felicidad, etc.). As part of this project we have estimated an Asset Index based on the information in the 2012 National Population and Housing Census. The basic idea is that households with more productive assets (water, electricity, education, computer, Internet, etc.) are probably better off than households with fewer productive assets. Based on this Asset Index, we have divided all Bolivian households into five quintiles (1: the poorest 20% of households; 5: the richest 20% of households). Finally, we have tagged all the people living in the households in Quintiles 1 and 2 as poor, and with that information we have calculated both the poverty rate and the number of poor people in each of the Bolivian municipalities.
Figure 1 shows that, paradoxically, there is a negative correlation between the number of poor people in a municipality and the poverty rate in the municipality (ρ = -0.29). Indeed, the five municipalities with the highest numbers of poor people all have some of the lowest poverty rates found in the country. For example, Santa Cruz de la Sierra has almost 220 thousand poor people, although the poverty rate is only 15% (the third lowest of all Bolivian municipalities). La Paz has the lowest poverty rate of any municipality (10%), but it still has the fourth highest number of poor people.
Figure 1: The inverse relationship between poverty rates and the number of poor people in Bolivian municipalities, 2012.
Source: Calculations made by Marcelo Cardona at INESAD based on the data from the 2012 National Population and Housing Census in Bolivia.
In contrast, the municipality with the highest poverty rate of all, Carangas with a poverty rate of 98.5%, has only 826 poor people – less than half a percent of the number found in Santa Cruz de la Sierra.
Thus, if you want to significantly reduce poverty and inequality in Bolivia, you have to pay less attention to poverty rates, and more attention to the poor, many of whom have wisely abandoned the rural areas with persistently high poverty rates and moved to one of the metropolitan areas of Bolivia in search of opportunities and a better future for their families. They should be supported in this quest, and an obvious, simple and cheap way to do this is to provide basic services at their destination rather than at their point of origin.
* Lykke E. Andersen is a Senior Researcher at INESAD. She greatly appreciates feedback on this post either in the comments below or directly to: firstname.lastname@example.org.
The views expressed in this article are those of the authors and do not necessarily reflect the views of Fundación INESAD.