By Valentina Forero Gonzalez
November 30 of 2016 was a historical day for Colombia. After more than 50 years, the government of President Juan Manuel Santos and the Revolutionary Armed Forces of Colombia (FARC) signed a peace agreement that culminated the longest-running civil war in the world. The peace deal is an extremely controversial issue. Supporters of the agreement emphasize the urgency of reconciliation to prevent any more deaths and work towards less poverty, especially in the most afflicted rural sector. Meanwhile, opponents contend that the deal is too lenient and will not serve justice. However, the one argument both sides seem to agree on is that violence has to come to an end in order for the country to reduce poverty and inequality (Wyss, 2016).
The last report by the National Administrative Department of Statistics (DANE) on poverty concluded that, overall, poverty and inequality decreased in the country in 2017. According to Maria Alejandra Medina, columnist of one of the main newspapers in the country, in eight years, 4.3 million people overcame poverty based on their income. Yet, she explains, there are some figures of poverty that are still subject of concern. In order to understand why these figures are significant, it is necessary to first understand what they are (Medina, 2018).
People defined as poor live below some minimally acceptable level of well-being. Different poverty measures can lead to different conclusions about a population depending on the factors that are believed to influence the measurements. On a first level, poverty will be determined by the choice of well-being indicator. Therefore, whether the indicator is income, consumption, access to education, health, etc. will be key to define policy goals in the future. On a second stance, the choice of poverty line, that is, the choice of the minimally acceptable level of the indicators is essential to analyze the incidence and prevalence of poverty (Schaffner, 2013).
In the case of Colombia, the government measures poverty using two different approaches: the monetary and the multidimensional.
The monetary approach to poverty uses income per capita to calculate the incidence, depth, and severity of poverty. The governments has two different poverty lines: an extreme poverty line that delimits the income necessary to acquire a food basket that guarantees basic caloric needs; and a relative poverty line that defines the minimum income necessary to consume an acceptable level of goods and services. According to the DANE, an individual was considered extremely poor in 2017 if his/her income was below 116,330 COP per month (approximately 39 dollars per month or 1.3 dollars per day). The same report set the relative poverty line of the country at 250,620 COP per month (83 USD per month or 2.8 USD per day) (DANE, 2018). Furthermore, the DANE provides three different measures of poverty which can be calculated using the equation in Figure 1. The headcount ratio, which measures the incidence of poverty, gives the percentage of the population living below the poverty line (α=0 in equation). The poverty gap, which assesses the depth of poverty, calculates how far below the poverty line an individual is and the average shortfall in income (α=1 in equation). Finally, the squared poverty gap, which estimates the severity of poverty, provides an indication of inequality by giving each household or individual a weight depending on their income (α=2 in equation) (Development Initiatives, 2016). The results of the report will be further explained in the following section.
The second approach used by the DANE is the national Multidimensional Poverty Index (MPI). This indicator measures “the proportion of people who experience multiple deprivations and the intensity of such deprivations” (UNDP, 2015). It provides a more complete and complex indicator that allows for a better understanding of poverty and its possible causes and outcomes. Better measures of poverty at the same time will foster more targeted policies to end it. Compared to the monetary approach, the MPI uses ten indicators related to health, education, and living standards (Figure 2). To calculate the index, the deprivation of each person is weighted by the indicator’s weight and if the sum of the weighted deprivations is 33 per cent or more, then the person is considered to be multidimensionally poor (UNDP, 2015).
Figure 3 displays the headcount ratio over time for extreme monetary poverty, which went from 8.5% to 7.4% at the national level in 2017. The poverty gap registered was 2.7%, indicating that in average the income of the people living below the line is 2.7% lower than 1.3 USD per day. Finally, the severity of extreme poverty was 1.5%. Similarly, Figure 4 presents the graph for relative monetary poverty, which fell by 1.1 points to 26.9%. The poverty gap was 10.3% and the severity of poverty was 5.1% (DANE 2018).
Likewise, Figure 5 illustrates the MPI over time, which went from 17.8% to 17%. According to Mauricio Perfetti, director of DANE, “among the deprivations that presented the most significant improvement for the MPI are low educational attainment, critical overcrowding and illiteracy” (Medina, 2018).
All of the measurements of poverty decreased from 2016 to 2017. However, they also demonstrate the unequal reality of the country. Both the monetary and the multidimensional approaches prove that the rural regions present significantly higher poverty rates than urban centers. Extreme monetary poverty in rural regions more than triplicated that of the capitals and relative monetary poverty in rural areas was about twelve percentage points higher. Likewise, the MPI in rural regions was more than three times that of the urban centers.
How Can We Explain These Differences?
Colombia is one of the most unequal countries in the world. However, in 2017 the Gini coefficient, which “measures the extent to which the distribution of income among individuals within an economy deviates from a perfectly equal distribution,” decreased from 0.517 to 0.508. Although this decrease should be taken as a positive sign, truth is that the country has had approximately the same inequality levels since the 1940s (Figure 6).
The severe variation of poverty within Colombia has been studied by various economists. Nowadays, one of the main theses to explain inequality is the persistence of institutions. James A. Robinson in his essay “The Misery in Colombia” argues that “the extent and persistence of poverty and violence in Colombia” is a consequence of extractive political institutions in which a small group of elites exploit the rest of the population (2015). These political institutions, which include corruption, clientelism, and weak judicial systems, lead to inefficient economic institutions (such as lack of property rights) that only benefit those with power. This is consistent with the distribution of poverty in Colombia (Figure 7). The urban centers referred by Robinson as the core have significantly lower poverty rates today because elites have historically lived there. Therefore, they have implemented policies that make them more prosperous. The rural regions or the periphery, on the other side, have been exposed to extractive systems that uphold poverty and violence.
In her article “What data on poverty figures are still worrying?” Medina states that the main areas of concern are the cities of Quibdó, Riohacha, Florencia, and Popayán, where the highest incidence of monetary poverty occurs. Consistent with Robinson’s theory, these cities where poverty persists are located in the periphery (Figure 7. Look at arrows).
The end of the Colombian conflict marks a historical moment in the country. The end of violence is an essential component to foster stability in the country and will surely improve the lives of millions of Colombians. However, contemporary theories of development have proven that in order to decrease poverty and inequality, the underlying causes them must be targeted. This means that, even in the absence of violence, as long as the government keeps in place an extractive system of corruption, lack of accountability, and economic insecurity, we cannot guarantee the effects of the deal.
*The link to the translated article can be found in https://translate.google.com/translate?sl=auto&tl=en&js=y&prev=_t&hl=en&ie=UTF-8&u=https%3A%2F%2Fwww.elespectador.com%2Feconomia%2Fpese-buenos-resultados-que-datos-de-las-cifras-de-pobreza-aun-preocupan-articulo-745897&edit-text=&act=url
Departamento Administrativo Nacional de Estadística –DANE Marzo 22 de 2018 Boletín técnico Pobreza Monetaria y Multidimensional en Colombia Año 2017. Retrieved from https://www.dane.gov.co/files/investigaciones/condiciones_vida/pobreza/bol_pobreza_17.pdf
Development Initiatives (Jul. 2016). Definitions and Measures of Poverty. Devinit.org. Retrieved from http://devinit.org/wp-content/uploads/2016/07/Definitions-and-measures-of-poverty.pdf
Medina, M. A. (Mar. 22, 2018) ¿Qué datos de las cifras de pobreza aún preocupan? El Espectador. Retrieved from https://www.elespectador.com/economia/pese-buenos-resultados-que-datos-de-las-cifras-de-pobreza-aun-preocupan-articulo-745897
Robinson, J. (2015). The Misery in Colombia. Desarrollo y sociedad. 9-90. 10.13043/DYS.76.1. Retrieved from https://scholar.harvard.edu/files/jrobinson/files/the_misery_in_colombia.pdf
Schaffner, J. (2013). Development Economics: Theory, Empirical Research, and Policy Analysis. Chapter 5, page 85.
United Nations Development Programme UNDP (Mar. 2015). Training Material for Producing National Human Development Reports. United Nations Development Programme: Human Development Reports. Retrieved from http://hdr.undp.org/sites/default/files/mpi_trainingmaterial_mcc_mk_clean_june_2015.pd
Wyss, J. (Dec. 01, 2016). Colombia’s congress passes historic peace deal with guerrillas, but battles remain. The Miami Herald. Retrieved from http://www.miamiherald.com/news/nation-world/world/americas/colombia/article118192178.html