Poverty and Migration From The Northern Triangle: It All Boils Down to The Lack of Poverty Data
Figure 1 - The Northern Triangle of Central America. A term used to refer to the countries of Guatemala, Honduras and El Salvador.
Credit: User:Cobaltous, CC BY-SA 4.0, via Wikimedia Commons.
The number of people living in extreme poverty globally declined steadily from 36% in 1990 to 10% in 2015 [1]. Before the pandemic, the World Bank estimated that the percentage of people living on less than $1.90 a day would decline to 7.9% in 2020 [2]. However, a year later, after the outbreak of COVID-19, the World Bank has confirmed a rise in poverty that would affect between 9.1 and 9.4 percent of the world's population [3]. This is the first increase since 1998 and represents a decade-long setback in global progress towards reducing poverty and achieving the Sustainable Development Goals (SDGs) [4].
When assessing progress towards achieving these SDGs, defining how global poverty is measured is fundamental. Regrettably, researchers have not always agreed on a standard technique, resulting in wildly disparate figures [5]. This article identifies poverty and the absence of data to measure it, as the primary cause of migration from the Northern Triangle. The Northern Triangle is a term mainly used by the United States government to refer collectively to Guatemala, Honduras, and El Salvador (Fig. 1). According to the 2019 census, the region has a population of nearly 33 million people, with El Salvador being the most densely populated of the three [6].
Before 2010, poverty was only defined in monetary terms. Today, measuring poverty includes the reality of people’s experiences and the deprivation they face. For example, the Multidimensional Poverty Index (MPI) examines deprivation across ten indicators in three equally weighted dimensions: health, education, and standard of living (Fig. 2). According to this index, 1.3 billion people, 22% of the global population, live in multidimensional poverty [8].
Figure 2 - The Global Multidimensional Poverty Index. 3 dimensions of poverty by 10 indicators. Figure constructed by Author, based on Ref [9].
When assessing multidimensional poverty at a national level, countries sometimes include additional dimensions and indicators. Illustratively, El Salvador oversees the housing, habitat, and employment, adding indicators like housing overcrowding and crime incidence to the list [9]. Unfortunately, the Northern Triangle lacks comparative evaluation and indicators to measure poverty in the region. For example, according to the National MPI, 59% of Hondurans were Multidimensionally Poor in 2018 [10]. Similarly, El Salvador's latest 2017 assessment reports 33.4% as Multidimensionally Poor [9]. Guatemala's latest report dates from 2014, recording that, unfortunately, 61.6% of the population is Multidimensionally Poor [11]. Given the disparity of poverty measurements and reporting, this article examines how governments and policymakers could use technology and data collection to detect the factors contributing to poverty, and consequently migration, to address the crisis from the source.
The Lack of Poverty Data
For over 35 years, the World Bank has set the standards for poverty data collection using the same method for tracking poverty: going from house to house to collect data and measure consumption [12]. To do so, the World Bank works with 155 countries, of which 96% are developing countries [12]. Out of these countries, 77 countries do not have adequate poverty data [13]. The gaps in data collection range from no data to infrequent data collection that does not portray the country’s direction in reducing poverty [13].
Unfortunately, gathering household consumption data takes two hours per household [12]. Furthermore, for the sample size to represent the country, at least 2,000 homes need to be surveyed. To illustrate the magnitude of time and resources spent to collect poverty data, let's look at the example of Nigeria. For such a large country to be accurately assessed, 100,000 households need to be surveyed, which would take 8,334 days [12]. Given the substantial effort required, 77 nations, including Korea, Cuba, and Tanzania, still lack adequate poverty data gathering [14].
In addition to collecting consumption data, the World Bank's team gathers information on correlates of poverty like employment opportunities, access to education, and reception of social assistance [12]. Thus, the goal is to count people suffering from poverty and identify what barriers they face. Unfortunately, this is only possible when frequent and timely data comparable over time is available [14]. While defining a reasonable time-frame continues to be a challenge, the General Data Dissemination System (GDDS) recommends updating poverty statistics in at least three to five-year intervals [12]. Hence, as Senior Economist Umar Serajuddin notes, a more attainable goal for SDG 1: No Poverty could be eradicating poverty data deprivation by 2030 [13].
Poverty and Migration
Since gaining independence from Spain, the Northern Triangle has faced a long history of autocratic rule and an uneven transition to democracy. Over the past decade, the region became the transshipment corridor for Transnational Organized Crime (TOC) groups [15]. These are primarily Mexican drug trafficking syndicates that are thought to be associated with state entities from Venezuela and Iran. Consequently, homicide rates rose rapidly in the 2000s as the region became the primary transit corridor for South American narcotics bound for the United States [7].
These issues only begin to highlight the complexity of poverty in the region, where the percentage of people living with less than $3.10 a day in 2014 ranged from 11 to 30% [16]. The 2014 World Bank poverty report is the most recent for this area, highlighting the need for frequent data for policy-making [16]. Without poverty data, stakeholders cannot understand the magnitude of the problem, nor identify root causes in order to begin drafting solutions. Moreover, this deficiency prevents comparison between countries and causes countries to fail to replicate successful poverty-eradication strategies. Such consequences may seem secondary, considering that collecting poverty data is a way of giving voice to those suffering from it.
Figure 3 - Apprehensions of migrants encountered at Southwest border in thousands. Showing that there were more nationals from the Northern Triangle arriving at the border through the first half of 2021 than there were in the first half of 2020. Figure constructed by Author, based on Ref [7].
This environment has created the perfect ecosystem for human trafficking to become a booming business model for smugglers and TOCs [17]. In addition, after Biden's administration took office in January 2021, false rumors of an "open border" permitting free movement of migrants across it have spread in violent and poverty-stricken communities [17]. These rumors led to an influx of more foreign nationals from the Northern Triangle at the Southern Border during the first half of 2021 than there were in 2020 (Fig. 3) [18].
The primary triggers of migration include security concerns, poor governance characterized by corruption and oppression of the opposition, and global warming leading to prolonged droughts and back-to-back hurricanes [15, 18]. Above all, the main reason youth migrate is the lack of economic and training opportunities that limit their employability [19]. As Michael, a 17-year-old migrant of Honduras, recognized:
“I left my mom, my wife, and all my family behind [18]. ”
Such training opportunities may include technical, vocational, and soft skills. Unfortunately, the initiatives mentioned above to increase education and empowerment opportunities for youth might not slow down the migration influx. In the Northern Triangle, this crisis started in the late 80s after the conclusion of a period of civil wars sparked by the Cold War [20]. Consequently, migration recurrence in the region is self-reinforcing over time since families seek reunification. For instance, more than 80% of unaccompanied minors traveling in 2021 already have a family member in the U.S. [21]. Moreover, those who leave their communities serve as examples of resilience and strength; sharing their experiences and resources with those who remain behind, ultimately encouraging migration.
By the end of President Trump's administration, every migrant, including asylum seekers, attempting to enter the U.S. anywhere other than at an official port of entry was detained and criminally prosecuted [22]. Consequently, close to 4,000 children were separated from their families [23]. In contrast, in January 2021, President Biden announced that children would no longer be separated from their families or become subject to immediate public health expulsions, leading to a boom in unaccompanied minors at the border [15]. In the meantime, while their relatives, children stay at detention centers for months at a time [21]. Recent BBC coverage uncovered detention centers' allegations of cold temperatures, sickness, and neglect through a series of interviews with children and staff [21]. As of May 2021, these detention sites held more than 20,000 migrant children [21]. Most of them are teenagers from the Northern Triangle, but some are reported to be as young as 6 years old [24]. As psychiatrist Amy Cohen notes:
“Even after weeks in these conditions, these children are at greater risk of developing major psychiatric illnesses later in life, at greater risk of substance abuse and a greater risk of suicide [21]. ”
While the conditions of the detention centers in Texas or U.S. policy to prevent migration are not a major point of discussion for this article, they are still vital to implore that poverty is not just statistics and numbers: it is real people facing real issues.
A Cross-Border Effort: Prioritizing Mobile Data Collection Technologies
Cellular phone communication technology has proven to reduce the time and cost of collecting household survey data without compromising data quality [25]. Despite the innovation, such initiatives do not intend to replace traditional household surveys. However, when better integrated, they can prove to be a formidable set of tools for data collection to provide the best evidence to policymakers. Through a collective effort by the three nations of the Northern Triangle, integrating mobile data collection technologies could have relevant results in improving the wellbeing and development of migrant communities; such advancements might be witnessed in the three areas listed below.
1) Data points of people prone to migrate:
Current demographic data of at-risk communities in gang-dominated or hurricane danger zones, where a higher risk of migration is present, is rarely available [16]. Such data points are as simple as the head-count of families, schooling and profession, or the number of relatives in the U.S., yet they are simply non-existent. Having this information could speed up designing policy and solutions to address the root cause of migration.
2) The design of a mobile application to fight rumors on U.S. border policy that encourages migrant caravans:
To fight misinformation, the U.S. could design a mobile app to provide the daily number of families receiving asylum, the number of people let into the U.S., the number of free beds in migrant shelters across the route, and the average waiting time in Tijuana shelters. Before starting their journey, some migrants do not know there is a waiting list to request asylum. Illustratively, recent BBC coverage shared testimonials of migrants along the route that believed crossing the border with an asylum status would be an immediate process [18]. In reality, some families waited over a year in Tijuana to enter the U.S. [17]. Having access to this information could help individuals considering this journey grasp the risks and could encourage them to stay home.
3) The wellbeing of undocumented individuals:
For undocumented migrants already in the U.S., technology can significantly impact their livelihood, making access to health, education, and employment easier. For example, Everest, the world's only device-free, globally accessible payment solution platform, allows refugees to identify public services, thus enabling them to claim their social and economic rights and making them self-sufficient in the long term.
Everest exemplifies how the above-outlined applications can downsize the resources of poverty data collection while speeding up the process. This way, stakeholders can have quicker access to poverty data and better understand the magnitude of the problem, while prioritizing the root causes when drafting solutions. More importantly, these platforms give voice to those suffering, allowing stakeholders to view the problem from the perspective of those most affected. Unfortunately, the U.S. lacks strong diplomatic relationships with the Northern Triangle, leaving the current administration with few feasible partners in the region. There is diplomatic tension and open conflict with the presidents of Honduras, El Salvador, and Nicaragua. Thus, it is essential to note that no monetary investment will be enough without cooperation and cross-country integration.
While it is true that the pandemic put an abrupt break to our work towards the SDGs, it is encouraging to recognize that the important achievements in the field happened before digitalization and technology. Consequently, through data science, and the dialogue and cross-border cooperation that technology allows, we can do more to get closer to reaching the SDGs.
References
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