poverty and education

You are using an outdated browser. Please upgrade your browser or activate Google Chrome Frame to improve your experience.

Thanks for signing up as a global citizen. In order to create your account we need you to provide your email address. You can check out our Privacy Policy to see how we safeguard and use the information you provide us with. If your Facebook account does not have an attached e-mail address, you'll need to add that before you can sign up.

This account has been deactivated.

Please contact us at [email protected] if you would like to re-activate your account.

Lack of access to education is a major predictor of passing poverty from one generation to the next, and receiving an education is one of the top ways to achieve financial stability.

In other words: education and poverty are directly linked.

Increasing access to education can equalize communities, improve the overall health and longevity of a society , and help save the planet .

The problem is that about 258 million children and youth are out of school around the world, according to UNESCO data released in 2018.

Children do not attend school for many reasons — but they all stem from poverty.

Here are all the statistics, facts, and answers to questions you might have that shed light on the connection between poverty and education.

How does poverty affect education?

Families living in poverty often have to choose between sending their child to school or providing other basic needs. Even if families do not have to pay tuition fees, school comes with the added costs of uniforms, books, supplies, and/or exam fees.

Countries across sub-Saharan Africa, where the world’s poorest children live, have made a concerted effort to abolish school fees . While the ratio of students completing lower secondary school increased in the region from 23% in 1990 to 42% in 2014, enrollment is low compared to the 75% global ratio. School remains too expensive for the poorest families. Some children are forced to stay at home doing chores or need to work. In other places, especially in crisis and conflict areas with destroyed infrastructure and limited resources, unaffordable private schools are sometimes the only option .

Why does poverty stop girls from going to school?

Poverty is the most important factor that determines whether or not a girl can access education, according to the World Bank. If families cannot afford the costs of school, they are more likely to send boys than girls. Around 15 million girls will never get the chance to attend school, compared to 10 million boys.

Read More: These Are the Top 10 Best and Worst Countries for Education in 2016

Gender inequality is more prevalent in low-income countries. Women often perform more unpaid work, have fewer assets, are exposed to gender-based violence, and are more likely to be forced into early marriage, all limiting their ability to fully participate in society and benefit from economic growth.

When girls face barriers to education early on, it is difficult for them to recover. Child marriage is one of the most common reasons a girl might stop going to school. More than 650 million women globally have already married under the age of 18. For families experiencing financial hardship, child marriage reduces their economic burden , but it ends up being more difficult for girls to gain financial independence if they are unable to access a quality education.

Lack of access to adequate menstrual hygiene management also stops many girls from attending school. Some girls cannot afford to buy sanitary products or they do not have access to clean water and sanitation to clean themselves and prevent disease. If safety is a concern due to lack of separate bathrooms, girls will stay home from school to avoid putting themselves at risk of sexual assault or harassment.

Read More: 10 Barriers to Education Around the World

An educated girl is not only likely to increase her personal earning potential but can help reduce poverty in her community, too.

“Educated girls have fewer, healthier, and better-educated children,” according to the Global Partnership for Education.

When countries invest in girls’ education, it sees an increase in female leaders, lower levels of population growth, and a reduction of contributions to climate change.

Can education help break the cycle of poverty?

Education promotes economic growth because it provides skills that increase employment opportunities and income. Nearly 60 million people could escape poverty if all adults had just two more years of schooling, and 420 million people could be lifted out of poverty if all adults completed secondary education, according to UNESCO.

Education increases earnings by roughly 10% per each additional year of schooling. For each $1 invested in an additional year of schooling, earnings increase by $5 in low-income countries and $2.5 in lower-middle income countries.

Read More: 264 Million Children Are Denied Access To Education, New Report Says

Education reduces many issues that stop people from living healthy lives, including infant and maternal deaths, stunting, infant and maternal deaths, vulnerability to HIV/AIDS, and violence.

How can we end extreme poverty through education?

There are more children enrolled in school than ever before — developing countries reached a 91% enrollment rate in 2015 — but we must fully close the gap.

World leaders gathered at the United Nations headquarters to address the disparity in 2015 and set 17 Global Goals to end extreme poverty by 2030. Global Goal 4: Quality Education aims to "end poverty in all its forms everywhere."

Read More: How We Can Be the Generation to End Extreme Poverty

The first step to achieving quality education for all is acknowledging that it is a vital part of sustainable development. Citizens, governments, corporations, and philanthropists all have an important role to play. Learn how to ensure global access to education to end poverty by taking action here .

Global Citizen Explains

Defeat Poverty

Understanding How Poverty is the Main Barrier to Education

Feb. 7, 2020

About . Click to expand section.

Our History
Team & Board
Transparency and Accountability

What We Do . Click to expand section.

Cycle of Poverty
Climate & Environment
Emergencies & Refugees
Health & Nutrition
Livelihoods
Gender Equality
Where We Work

Take Action . Click to expand section.

Attend an Event
Partner With Us
Fundraise for Concern
Work With Us
Leadership Giving
Humanitarian Training
Newsletter Sign-Up

Donate . Click to expand section.

Give Monthly
Donate in Honor or Memory
Leave a Legacy
DAFs, IRAs, Trusts, & Stocks
Employee Giving

How does education affect poverty?

For starters, it can help end it.

Aug 10, 2023

Nancy Masaba recently finished secondary school in Nairobi, Kenya, and now plans to go to university.

Access to high-quality primary education and supporting child well-being is a globally-recognized solution to the cycle of poverty. This is, in part, because it also addresses many of the other issues that keep communities vulnerable.

Education is often referred to as the great equalizer: It can open the door to jobs, resources, and skills that help a person not only survive, but thrive. In fact, according to UNESCO, if all students in low-income countries had just basic reading skills (nothing else), an estimated 171 million people could escape extreme poverty. If all adults completed secondary education, we could cut the global poverty rate by more than half.

At its core, a quality education supports a child’s developing social, emotional, cognitive, and communication skills. Children who attend school also gain knowledge and skills, often at a higher level than those who aren’t in the classroom. They can then use these skills to earn higher incomes and build successful lives.

Here’s more on seven of the key ways that education affects poverty.

Go to the head of the class

Get more information on Concern's education programs — and the other ways we're ending poverty — delivered to your inbox.

1. Education is linked to economic growth

Ali* pictured in a Concern-supported school in the Sila region of Chad

Education is the best way out of poverty in part because it is strongly linked to economic growth. A 2021 study co-published by Stanford University and Munich’s Ludwig Maximilian University shows us that, between 1960 and 2000, 75% of the growth in gross domestic product around the world was linked to increased math and science skills.

“The relationship between…the knowledge capital of a nation, and the long-run [economic] rowth rate is extraordinarily strong,” the study’s authors conclude. This is just one of the most recent studies linking education and economic growth that have been published since 1990.

“The relationship between…the knowledge capital of a nation, and the long-run [economic] growth rate is extraordinarily strong.” — Education and Economic Growth (2021 study by Stanford University and the University of Munich)

2. Universal education can fight inequality

A 2019 Oxfam report says it best: “Good-quality education can be liberating for individuals, and it can act as a leveler and equalizer within society.”

Poverty thrives in part on inequality. All types of systemic barriers (including physical ability, religion, race, and caste) serve as compound interest against a marginalization that already accrues most for those living in extreme poverty. Education is a basic human right for all, and — when tailored to the unique needs of marginalized communities — can be used as a lever against some of the systemic barriers that keep certain groups of people furthest behind.

For example, one of the biggest inequalities that fuels the cycle of poverty is gender. When gender inequality in the classroom is addressed, this has a ripple effect on the way women are treated in their communities. We saw this at work in Afghanistan , where Concern developed a Community-Based Education program that allowed students in rural areas to attend classes closer to home, which is especially helpful for girls.

Four ways that girls’ education can change the world

Gender discrimination is one of the many barriers to education around the world. That’s a situation we need to change.

3. Education is linked to lower maternal and infant mortality rates

Concern Worldwide staff member with mother and young child

Speaking of women, education also means healthier mothers and children. Examining 15 countries in sub-Saharan Africa, researchers from the World Bank and International Center for Research on Women found that educated women tend to have fewer children and have them later in life. This generally leads to better outcomes for both the mother and her kids, with safer pregnancies and healthier newborns.

A 2017 report shows that the country’s maternal mortality rate had declined by more than 70% in the last 25 years, approximately the same amount of time that an amendment to compulsory schooling laws took place in 1993. Ensuring that girls had more education reduced the likelihood of maternal health complications, in some cases by as much as 29%.

4. Education also lowers stunting rates

Concern Worldwide and its partner organizations organize sessions with young girls and adolescents in Rajapur High School in Shoronkhola. In the session, girls receive information about menstrual hygiene and the importance of hygiene, including nutrition information. During the session, girls participate in group discussion and often gather to address their health-related issues related to menstrual taboos and basic hygiene. This project runs by the Collective Responsibility, Action, and Accountability for Improved Nutrition (CRAAIN) programme. (Photo: Mohammad Rakibul Hasan / Concern Worldwide)

Children also benefit from more educated mothers. Several reports have linked education to lowered stunting , one of the side effects of malnutrition. Preventing stunting in childhood can limit the risks of many developmental issues for children whose height — and potential — are cut short by not having enough nutrients in their first few years.

In Bangladesh , one study showed a 50.7% prevalence for stunting among families. However, greater maternal education rates led to a 4.6% decrease in the odds of stunting; greater paternal education reduced those rates by 2.9%-5.4%. A similar study in Nairobi, Kenya confirmed this relationship: Children born to mothers with some secondary education are 29% less likely to be stunted.

What is stunting?

Stunting is a form of impaired growth and development due to malnutrition that threatens almost 25% of children around the world.

5. Education reduces vulnerability to HIV and AIDS…

Denise Dusabe, Vice Mayor of Social Affairs in Gisagara district, presents at an HIV/AIDS prevention and family planning event organized by Concern Rwanda. Five local teams participated in a soccer championship, with government representatives presenting both speeches and prizes. Local health center staff also offered voluntary HIV testing, distributed free condoms, and helped couples with selecting appropriate family planning methods.

In 2008, researchers from Harvard University, Imperial College London, and the World Bank wrote : “There is a growing body of evidence that keeping girls in school reduces their risk of contracting HIV. The relationship between educational attainment and HIV has changed over time, with educational attainment now more likely to be associated with a lower risk of HIV infection than earlier in the epidemic.”

Since then, that correlation has only grown stronger. The right programs in schools not only reduce the likelihood of young people contracting HIV or AIDS, but also reduce the stigmas held against people living with HIV and AIDS.

6. …and vulnerability to natural disasters and climate change

Concern Protection staff Nureddin El Mustafa and Fatma Seker lead an information session with the community committee at Haliliye Community Centre following the February 2023 earthquake in Türkiye and Syria

As the number of extreme weather events increases due to climate change, education plays a critical role in reducing vulnerability and risk to these events. A 2014 issue of the journal Ecology and Society states: “It is found that highly educated individuals are better aware of the earthquake risk … and are more likely to undertake disaster preparedness.… High risk awareness associated with education thus could contribute to vulnerability reduction behaviors.”

The authors of the article went on to add that educated people living through a natural disaster often have more of a financial safety net to offset losses, access to more sources of information to prepare for a disaster, and have a wider social network for mutual support.

Climate change is one of the biggest threats to education — and growing

Last August, UNICEF reported that half of the world’s 2.2 billion children are at “extremely high risk” for climate change, including its impact on education. Here’s why.

7. Education reduces violence at home and in communities

Concern and Theatre For Change working with students of Chigumukire Primary School and their parents to help highlight the dangers and challenges of school-related gender-based violence as part of Right to Learn

The same World Bank and ICRW report that showed the connection between education and maternal health also reveals that each additional year of secondary education reduced the chances of child marriage — defined as being married before the age of 18. Because educated women tend to marry later and have fewer children later in life, they’re also less likely to suffer gender-based violence , especially from their intimate partner.

Girls who receive a full education are also more likely to understand the harmful aspects of traditional practices like FGM , as well as their rights and how to stand up for them, at home and within their community.

Fighting FGM in Kenya: A daughter's bravery and a mother's love

Marsabit is one of those areas of northern Kenya where FGM has been the rule rather than the exception. But 12-year-old student Boti Ali had other plans.

Education for all: Concern’s approach

Concern’s work is grounded in the belief that all children have a right to a quality education. Last year, our work to promote education for all reached over 676,000 children. Over half of those students were female.

We integrate our education programs into both our development and emergency work to give children living in extreme poverty more opportunities in life and supporting their overall well-being. Concern has brought quality education to villages that are off the grid, engaged local community leaders to find solutions to keep girls in school, and provided mentorship and training for teachers.

More on how education affects poverty

6 Benefits of literacy in the fight against poverty

Child marriage and education: The blackboard wins over the bridal altar

Project Profile

Right to Learn

Get emails with stories from around the world.

You can change your preferences at any time. By subscribing, you agree to the Terms of Use and Privacy Policy.

A World of Hardship: Deep Poverty and the Struggle for Educational Equity

Learning in the Time of COVID-19 blog series art

This post is part of LPI's Learning in the Time of COVID-19 blog series, which explores evidence-based and equity-focused strategies and investments to address the current crisis and build long-term systems capacity.

One day you get out there and actually see where the children you serve on a daily basis come from. Several teachers came back after delivering food and broke down in tears telling me what they saw. A student was living in a home with no roof; they’ve got a tarp for a roof kept on by bricks and tires. Homes didn’t have doors. —Principal of a rural high-poverty elementary school

As this quote powerfully conveys, families living in deep poverty face profound material, social, and emotional hardships. Households in deep poverty suffer from food shortages, unemployment, unstable housing, inadequate medical care , electrical shutoffs, and isolation.

Children living in households in deep poverty are often “invisible” to more affluent community members—and likely to many educators as well. Too often, the plight of students living in deep poverty is subsumed under the broad definition of poverty, which does not reveal the unique hardships that are endured by those families and children with virtually no material resources . For those of us who believe in educational equity, making the invisible visible is the first step in overcoming deep disadvantage.

The U.S. Census Bureau defines deep poverty as living in a household with total cash income that is below 50% of the poverty threshold. As the National Center for Children in Poverty map below indicates, no state is without children living in deep poverty. Although the percentage varies considerably across states, all states have at least 5% of their children living far below the poverty line. In total, more than 5 million children in the United States live in deep poverty, including nearly 1 in 5 Black children under the age of 5.

With the explosion of the health and economic crisis caused by the COVID-19 pandemic, households living in deep poverty have been pushed to the edge of survival: Nearly 4 in 10 Black and Latino households with children are struggling to feed their families . These numbers will no doubt grow as job losses mount, as do the numbers of children and adults of color who are contracting—and, in a disproportionate number of cases, dying from—COVID-19.

Why Deep Poverty Matters for Educators

Recently, Stanford researcher Sean Reardon and his colleagues conducted a national study on racial segregation and achievement gaps. In describing the findings he noted, “While racial segregation is important, it’s not the race of one’s classmates that matters, per se. It’s the fact that in America today, racial segregation brings with it very unequal concentrations of students in high- and low-poverty schools.” Another recent study of poverty and its effects on learning determined that levels of poverty matter in the abilities of students to succeed in school. According to the authors, “The experiences of children living in families with incomes just below the poverty line are likely quite different from those living in extreme poverty. Parents’ struggles to provide sufficient food and shelter for children may affect child academic achievement.”

The authors go on to note that the “depth of the poverty” matters both for the day-to-day life of students and families, and for public policy. “To determine appropriate subsidy levels and the types of services needed by children and families, policymakers need detailed data about the depth of family poverty. Studies have shown that simply classifying people as ‘in poverty’ or ‘not in poverty’ is not sufficient. The diversity in access to economic resources due to the depth of poverty helps explain the gaps in family investment in children’s education.”

The impact of poverty on children’s ability to learn is profound and occurs at an early age. A recent study of the neurological effects of deep poverty on young children’s development found that “poverty is tied to structural differences in several areas of the brain associated with school readiness skills, with the largest influence observed among children from the poorest households…. As much as 20% of the gap in test scores could be explained by maturational lags in the frontal and temporal lobes.” These effects were found to be associated with the consequences of living in deep poverty at an early age, some of which include premature and low-birthweight babies; poor nutrition and living without sufficient food; exposure to toxins, such as lead paint or contaminated drinking water; and lack of access to early learning opportunities.

If we are to educate the whole child , regardless of their family’s income, it is essential to provide an array of academic and social services that ensures that equity of opportunity reaches those students living in deep poverty.

The Importance of Accurately Determining Eligibility for Increased Services

In May 2020, the Learning Policy Institute published Measuring Student Socioeconomic Status: Toward a Comprehensive Approach . This report analyzes the limitations of the current methods used by school systems for measuring students’ socioeconomic status for purposes of allocating resources to meet their needs. Noting the limitations of determining a student’s level of poverty by her or his eligibility for free and reduced-price lunch—even when this measure is enhanced through direct certification of eligibility for other poverty-related programs—the report concludes that the development of new student poverty measures is urgently needed.

Blog Series: Learning in the Time of COVID-19

This blog series explores strategies and investments to address the current crisis and build long-term systems capacity. View all blogs >

The report also notes that researchers have suggested alternative measures of student poverty, some of which include parental education, student mobility, and community income as proxy measures. These strategies, however, do not appear to be capable of capturing the depth of an individual student’s poverty with the accuracy required to create and maintain academic and social programs designed and funded to meet the needs of students living in households in deep poverty. A more robust, reliable, and valid measure of students experiencing deep poverty is needed.

For several years, researchers at the Bendheim-Thomas Center for Research on Child Wellbeing at Princeton University have felt the pressing need to “move beyond income-based measures of poverty, ” according to Center Co-Director Kathryn Edin. She and her colleagues are currently utilizing measures of hardship that are more likely to reveal depth of poverty beyond income measures alone.

While there are a number of measures that identify deep poverty, perhaps the most direct, reliable, and valid measure available is a survey of a household’s ability to take care of the basic necessities of life. Households in deep poverty regularly experience food and housing insecurity, often can’t pay their bills, and are unable to access health care when they need it. At a time when access to the internet is essential for a student’s ability to learn online, families living in deep poverty often have their electricity shut off for lack of payment.

One of the most valid and reliable of these “material hardship” types of surveys has been used by the Survey of Income and Program Participation (SIPP) and, later, the Fragile Families Challenge . Material hardship measures ask direct questions about forgone consumption—that is, what families have had to do without when they may have to live on as little as two dollars a day .

Generally, surveys of material hardship consist of 10 or more questions. Below are some of the types of questions that might be included in a school-based survey to better understand the day-to-day realities for students and families:

In the past 12 months, were you ever hungry, but didn’t eat because you couldn’t afford enough food?
In the past 12 months, did you move in with other people even for a little while because of financial problems?
In the past 12 months, was there anyone in your household who needed to see a doctor or go to the hospital but couldn’t go because of the cost?
In the past 12 months, did you receive free food or meals?
In the past 12 months, did you not pay the full amount of a gas, oil, or electricity bill?

These measures do not replace income measures; they supplement them in order to get a fuller understanding of the lived experience of families living in deep poverty. For example, as a supplementary measure, a survey of material hardship could be incorporated into the free and reduced-price lunch forms sent to families to determine their eligibility to receive meals at school. When the material hardship surveys are returned, school administrators would have a clear indication of which students are living in deep poverty.

This recommendation can be seen as a first step in a more comprehensive approach to measuring deep poverty of students. Undocumented or mixed-status families might hesitate to complete government forms for fear of deportation; some families might not complete the material hardship survey due to privacy or other concerns. Some of these concerns could be addressed in community school settings, where the ties between families and the school are often close and continuous. The establishment of trust is a bond that can help to overcome the fear of government.

More From the Blog Series

In the Fallout of the Pandemic, Community Schools Show a Way Forward for Education
School-Based Health Centers: Trusted Lifelines in a Time of Crisis
County-Level Coordination Provides Infrastructure, Funding for Community Schools Initiative

To some busy school administrators, adding any survey might seem burdensome, but the returns on a short material hardship survey are very high. With this information, schools and school systems will be able to tailor programs to meet the needs of children and young adults living in families in deep poverty. These programs should support students’ health and well-being, as well as include academic enhancement and enrichment. In the context of the COVID-19 crisis, waiting for the perfect measure could result in increased hardship for students trapped in deep poverty.

Toward Educational Equity

Since the 1990s, the social safety net has been basically shredded. As a result, in many communities, the local public school system is often the only entity situated to meet the needs of students from families in deep poverty by providing meals as well as a safe place to be during the day. Early intervention programs, such a free and high-quality early childhood programs , are a very promising approach to mitigating the effects of deep poverty on young children. Community schools , which provide students and families with a range of supports and services to mitigate the impact of deep poverty—from health and mental health care to before- and after-school care and social service supports—are another promising example. Ensuring that these services are available to children in deep poverty can literally mean the difference between life and death—and between a chance in life and none—for many of these young people.

These are just two examples of how information about students’ level of poverty can lead to improved and expanded services and supports to meet their needs. Of course, schools alone cannot reverse the impact of deep poverty on children, families, and communities. But without well-financed schools with the targeted resources needed to enable students’ learning, the negative effects of deep poverty on children will remain, now and in the future.

Sign up for our mailing list

Featured Topics

Featured series.

A series of random questions answered by Harvard experts.

Explore the Gazette

Read the latest.

‘Could I really cut it?’

For this ring, I thee sue

Cass R. Sunstein (left) speaks with Benjamin Eidelson, Professor of Law, on his new book "Campus Free Speech."

Speech is never totally free

Robert Sampson, Henry Ford II Professor of the Social Sciences, is one of the researchers studying the link between poverty and social mobility.

Rose Lincoln/Harvard file photo

Unpacking the power of poverty

Peter Reuell

Harvard Staff Writer

Study picks out key indicators like lead exposure, violence, and incarceration that impact children’s later success

Social scientists have long understood that a child’s environment — in particular growing up in poverty — can have long-lasting effects on their success later in life. What’s less well understood is exactly how.

A new Harvard study is beginning to pry open that black box.

Conducted by Robert Sampson, the Henry Ford II Professor of the Social Sciences, and Robert Manduca, a doctoral student in sociology and social policy in the Graduate School of Arts and Sciences, the study points to a handful of key indicators, including exposure to high levels of lead, violence, and incarceration as key predictors of children’s later success. The study is described in an April paper published in the Proceedings of the National Academy of Sciences.

“What this paper is trying to do, in a sense, is move beyond the traditional neighborhood indicators people use, like poverty,” Sampson said. “For decades, people have shown poverty to be important … but it doesn’t necessarily tell us what the mechanisms are, and how growing up in poor neighborhoods affects children’s outcomes.”

To explore potential pathways, Manduca and Sampson turned to the income tax records of parents and approximately 230,000 children who lived in Chicago in the 1980s and 1990s, compiled by Harvard’s Opportunity Atlas project. They integrated these records with survey data collected by the Project on Human Development in Chicago Neighborhoods, measures of violence and incarceration, census indicators, and blood-lead levels for the city’s neighborhoods in the 1990s.

They found that the greater the extent to which poor black male children were exposed to harsh environments, the higher their chances of being incarcerated in adulthood and the lower their adult incomes, measured in their 30s. A similar income pattern also emerged for whites.

Among both black and white girls, the data showed that increased exposure to harsh environments predicted higher rates of teen pregnancy.

Despite the similarity of results along racial lines, Chicago’s segregation means that far more black children were exposed to harsh environments — in terms of toxicity, violence, and incarceration — harmful to their mental and physical health.

“The least-exposed majority-black neighborhoods still had levels of harshness and toxicity greater than the most-exposed majority-white neighborhoods, which plausibly accounts for a substantial portion of the racial disparities in outcomes,” Manduca said.

“It’s really about trying to understand some of the earlier findings, the lived experience of growing up in a poor and racially segregated environment, and how that gets into the minds and bodies of children.” Robert Sampson

“What this paper shows … is the independent predictive power of harsh environments on top of standard variables,” Sampson said. “It’s really about trying to understand some of the earlier findings, the lived experience of growing up in a poor and racially segregated environment, and how that gets into the minds and bodies of children.”

More like this

Cities’ wealth gap is growing, too

Racial and economic disparities intertwined, study finds

The study isn’t solely focused on the mechanisms of how poverty impacts children; it also challenges traditional notions of what remedies might be available.

“This has [various] policy implications,” Sampson said. “Because when you talk about the effects of poverty, that leads to a particular kind of thinking, which has to do with blocked opportunities and the lack of resources in a neighborhood.

“That doesn’t mean resources are unimportant,” he continued, “but what this study suggests is that environmental policy and criminal justice reform can be thought of as social mobility policy. I think that’s provocative, because that’s different than saying it’s just about poverty itself and childhood education and human capital investment, which has traditionally been the conversation.”

The study did suggest that some factors — like community cohesion, social ties, and friendship networks — could act as bulwarks against harsh environments. Many researchers, including Sampson himself, have shown that community cohesion and local organizations can help reduce violence. But Sampson said their ability to do so is limited.

“One of the positive ways to interpret this is that violence is falling in society,” he said. “Research has shown that community organizations are responsible for a good chunk of the drop. But when it comes to what’s affecting the kids themselves, it’s the homicide that happens on the corner, it’s the lead in their environment, it’s the incarceration of their parents that’s having the more proximate, direct influence.”

Going forward, Sampson said he hopes the study will spur similar research in other cities and expand to include other environmental contamination, including so-called brownfield sites.

Ultimately, Sampson said he hopes the study can reveal the myriad ways in which poverty shapes not only the resources that are available for children, but the very world in which they find themselves growing up.

“Poverty is sort of a catchall term,” he said. “The idea here is to peel things back and ask, What does it mean to grow up in a poor white neighborhood? What does it mean to grow up in a poor black neighborhood? What do kids actually experience?

“What it means for a black child on the south side of Chicago is much higher rates of exposure to violence and lead and incarceration, and this has intergenerational consequences,” he continued. “This is particularly important because it provides a way to think about potentially intervening in the intergenerational reproduction of inequality. We don’t typically think about criminal justice reform or environmental policy as social mobility policy. But maybe we should.”

This research was supported with funding from the Project on Race, Class & Cumulative Adversity at Harvard University, the Ford Foundation, and the Hutchins Family Foundation.

Share this article

Harvard releases race data for Class of 2028

Cohort is first to be impacted by Supreme Court’s admissions ruling

Parkinson’s may take a ‘gut-first’ path

Damage to upper GI lining linked to future risk of Parkinson’s disease, says new study

High doses of Adderall may increase psychosis risk

Among those who take prescription amphetamines, 81% of cases of psychosis or mania could have been eliminated if they were not on the high dose, findings suggest

Get involved

The transformative power of education in the fight against poverty

October 16, 2023.

Zubair Junjunia, a Generation17 young leader and the Founder of ZNotes, presents at EdTechX.

Zubair Junjunia

Generation17 Young Leader and founder of ZNotes

Time and again, research has proven the incredible power of education to break poverty cycles and economically empower individuals from the most marginalized communities with dignified work and upward social mobility.

Research at UNESCO has shown that world poverty would be more than halved if all adults completed secondary school. And if all students in low-income countries had just basic reading skills, almost 171 million people could escape extreme poverty.

With such irrefutable evidence, how do we continue to see education underfunded globally? Funding for education as a share of national income has not changed significantly over the last decade for any developing country. And to exacerbate that, the COVID-19 shock pushed the level of learning poverty to an estimated 70 percent .

I have devoted the past decade of my life to fighting educational inequality, a journey that began during my school years. This commitment led to the creation of ZNotes , an educational platform developed for students, by students. ZNotes was born out of the problem I witnessed first-hand; the inequities in end-of-school examination, which significantly influence access to higher education and career opportunities. It is designed as a platform where students can share their notes and access top-quality educational materials without any limitations. ZNotes fosters collaborative learning through student-created content within a global community and levels the academic playing field with a student-empowered and technology-enabled approach to content creation and peer learning.

Although I started ZNotes as a solo project, today, it has touched the lives of over 4.5 million students worldwide, receiving an impressive 32 million hits from students across more than 190 countries, especially serving students from emerging economies. We’re proud to say that today, more than 90 percent of students find ZNotes resources useful and feel more confident entering exams , regardless of their socio-economic background. These globally recognized qualifications empower our learners to access tertiary education and enter the world of work.

Sixteen-year-old Zubair set up a blog to share the resources he created for his IGCSE exams. Through word of mouth, his revision notes were discovered by students all over the world and ZNotes was born.

In rapidly changing job market, young people must cultivate resilience and adaptability. World Economic Forum highlights the importance of future skills, encompassing technical, cognitive, and interpersonal abilities. Unfortunately, many educational systems, especially in under-resourced regions, fall short in equipping youth with these vital skills.

To address this challenge, I see innovative technology as a crucial tool both within and beyond traditional school systems. As the digital divide narrows and access to devices and internet connectivity becomes more affordable, delivering quality education and personalized support is increasingly achievable through technology. At ZNotes, we are reshaping the role of students, transforming them from passive consumers to active creators and proponents of education. Empowering youth through a community-driven approach, students engage in peer learning and generate quality resources on an online platform.

Participation in a global learning community enhances young people's communication and collaboration skills. ZNotes fosters a sense of global citizenship, enabling learners to communicate with a diverse range of individuals across race, gender, and religion. Such spaces also result in redistributing social capital as students share advice for future university, internship and career pathways.

“Studying for 14 IGCSE subjects wasn't easy, but ZNotes helped me provide excellent and relevant revision material for all of them. I ended up with 7 A* 7 A, and ZNotes played a huge role. I am off to Cornell University this fall now. A big thank you to the ZNotes team!"

Alongside ensuring our beneficiaries are equipped with the resources and support they need to be at a level playing field for such high stakes exams, we also consider the skills that will set them up for success in life beyond academics. Especially for the hundreds of young people who join our internship and contribution programs , they become part of a global social impact startup and develop both academic skills and also employability skills. After engaging with our internship programs, 77% of interns reported improved candidacy for new jobs and internships.

ZNotes addresses the uneven playing field of standardized testing with a student-empowered and technology-enabled approach for content creation and peer learning.

A few years ago, Jess joined our team as a Social Impact Analyst intern having just completed her university degree while she continued to search for a full-time role. She was able to apply her data analytics skills from a theoretical degree into a real-world scenario and was empowered to play an instrumental role in understanding and developing a Theory of Change model for ZNotes. In just 6 months, she had been able to develop the skills and gain experiences that strengthened her profile. At the end of internship, she was offered a full-time role at a major news and media agency that she is continuing to grow in!

Jess’s example applies to almost every one of our interns . As another one of them, Alexa, said “ZNotes offers the rare and wonderful opportunity to be at the center of meaningful change”.

Being part of an organization making a significant impact is profoundly inspiring and empowering for young people, and assuming high-responsibility roles within such organizations accelerates their skills development and sets them apart in the eyes of prospective employers.

On the International Day for the Eradication of Poverty, it is a critical moment to reflect and enact on the opportunity that we have to achieving two key SDGs, Goal 1 and 4, by effectively funding and enabling access to quality education globally.

Global Education Monitoring Report

Reducing global poverty through universal primary and secondary education

The eradication of poverty and the provision of equitable and inclusive quality education for all are two intricately linked Sustainable Development Goals (SDGs). As this year’s High Level Political Forum focuses on prosperity and poverty reduction, this paper, jointly released by the UNESCO Institute for Statistics (UIS) and the Global Education Monitoring (GEM) Report, shows why education is so central to the achievement of the SDGs and presents the latest estimates on out-ofschool children, adolescents and youth to demonstrate how much is at stake. At the time of writing, the out-of school rate had not budged since 2008 at the primary level, since 2012 at the lower secondary level and since 2013 at the upper secondary level.

The consequences are grave: if all adults completed secondary school, the global poverty rate would be more than halved.

The impact of poverty on educational outcomes for children

Hb ferguson.

1 Community Health Systems Resource Group, The Hospital for Sick Children

2 Department of Psychiatry, Psychology & Public Health Sciences, University of Toronto, Toronto, Ontario

Over the past decade, the unfortunate reality is that the income gap has widened between Canadian families. Educational outcomes are one of the key areas influenced by family incomes. Children from low-income families often start school already behind their peers who come from more affluent families, as shown in measures of school readiness. The incidence, depth, duration and timing of poverty all influence a child’s educational attainment, along with community characteristics and social networks. However, both Canadian and international interventions have shown that the effects of poverty can be reduced using sustainable interventions. Paediatricians and family doctors have many opportunities to influence readiness for school and educational success in primary care settings.

Depuis dix ans, l’écart des revenus s’est creusé entre les familles canadiennes, ce qui est une triste réalité. L’éducation est l’un des principaux domaines sur lesquels influe le revenu familial. Souvent, lorsqu’ils commencent l’école, les enfants de familles à faible revenu accusent déjà un retard par rapport à leurs camarades qui proviennent de familles plus aisées, tel que le démontrent les mesures de maturité scolaire. L’incidence, l’importance, la durée et le moment de la pauvreté ont tous une influence sur le rendement scolaire de l’enfant, de même que les caractéristiques de la communauté et les réseaux sociaux. Cependant, tant au Canada que sur la scène internationale, il est possible de réduire les effets de la pauvreté au moyen d’interventions soutenues. Les pédiatres et les médecins de familles ont de nombreuses occasions d’agir sur la maturité et la réussite scolaire dans le cadre des soins de premier recours.

Poverty remains a stubborn fact of life even in rich countries like Canada. In particular, the poverty of our children has been a continuing concern. In 1989, the Canadian House of Commons voted unanimously to eliminate poverty among Canadian children by 2000 ( 1 ). However, the reality is that, in 2003, one of every six children still lived in poverty. Not only have we been unsuccessful at eradicating child poverty, but over the past decade, the inequity of family incomes in Canada has grown ( 2 ), and for some families, the depth of poverty has increased as well ( 3 ). Canadian research confirms poverty’s negative influence on student behaviour, achievement and retention in school ( 4 ).

Persistent socioeconomic disadvantage has a negative impact on the life outcomes of many Canadian children. Research from the Ontario Child Health Study in the mid-1980s reported noteworthy associations between low income and psychiatric disorders ( 5 ), social and academic functioning ( 6 ), and chronic physical health problems ( 7 ). Since that time, Canada has developed systematic measures that have enabled us to track the impact of a variety of child, family and community factors on children’s well-being. The National Longitudinal Survey of Children and Youth (NLSCY) developed by Statistics Canada, Human Resources Development Canada and a number of researchers across the country was started in 1994 with the intention of following representative samples of children to adulthood ( 8 ). Much of our current knowledge about the development of Canadian children is derived from the analysis of the NLSCY data by researchers in a variety of settings.

One of the key areas influenced by family income is educational outcomes. The present article provides a brief review of the literature concerning the effects of poverty on educational outcomes focusing on Canadian research. Canadian data are placed in the perspective of research from other ‘rich’ countries. We conclude with some suggestions about what we can do, as advocates and practitioners, to work toward reducing the negative impact of economic disadvantage on the educational outcomes of our children.

POVERTY AND READINESS FOR SCHOOL

School readiness reflects a child’s ability to succeed both academically and socially in a school environment. It requires physical well-being and appropriate motor development, emotional health and a positive approach to new experiences, age-appropriate social knowledge and competence, age-appropriate language skills, and age-appropriate general knowledge and cognitive skills ( 9 ). It is well documented that poverty decreases a child’s readiness for school through aspects of health, home life, schooling and neighbourhoods. Six poverty-related factors are known to impact child development in general and school readiness in particular. They are the incidence of poverty, the depth of poverty, the duration of poverty, the timing of poverty (eg, age of child), community characteristics (eg, concentration of poverty and crime in neighborhood, and school characteristics) and the impact poverty has on the child’s social network (parents, relatives and neighbors). A child’s home has a particularly strong impact on school readiness. Children from low-income families often do not receive the stimulation and do not learn the social skills required to prepare them for school. Typical problems are parental inconsistency (with regard to daily routines and parenting), frequent changes of primary caregivers, lack of supervision and poor role modelling. Very often, the parents of these children also lack support.

Canadian studies have also demonstrated the association between low-income households and decreased school readiness. A report by Thomas ( 10 ) concluded that children from lower income households score significantly lower on measures of vocabulary and communication skills, knowledge of numbers, copying and symbol use, ability to concentrate and cooperative play with other children than children from higher income households. Janus et al ( 11 ) found that schools with the largest proportion of children with low school readiness were from neighbourhoods of high social risk, including poverty. Willms ( 12 ) established that children from lower socioeconomic status (SES) households scored lower on a receptive vocabulary test than higher SES children. Thus, the evidence is clear and unanimous that poor children arrive at school at a cognitive and behavioural disadvantage. Schools are obviously not in a position to equalize this gap. For instance, research by The Institute of Research and Public Policy (Montreal, Quebec) showed that differences between students from low and high socioeconomic neighbourhoods were evident by grade 3; children from low socioeconomic neighbourhoods were less likely to pass a grade 3 standards test ( 13 ).

POVERTY AND EDUCATIONAL ATTAINMENT

Studies emanating from successive waves of the NLSCY have repeatedly shown that socioeconomic factors have a large, pervasive and persistent influence over school achievement ( 14 – 16 ). Phipps and Lethbridge ( 15 ) examined income and child outcomes in children four to 15 years of age based on data from the NLSCY. In this study, higher incomes were consistently associated with better outcomes for children. The largest effects were for cognitive and school measures (teacher-administered math and reading scores), followed by behavioural and health measures, and then social and emotional measures, which had the smallest associations.

These Canadian findings are accompanied by a large number of studies in the United States that have shown that socioeconomic disadvantage and other risk factors that are associated with poverty (eg, lower parental education and high family stress) have a negative effect on cognitive development and academic achievement, smaller effects on behaviour and inconsistent effects on socioemotional outcomes ( 17 – 19 ). Living in extreme and persistent poverty has particularly negative effects ( 18 ), although the consequences of not being defined below the poverty line but still suffering from material hardship should not be underestimated ( 20 ). Furthermore, American studies found strong interaction effects between SES and exposure to risk factors. For instance, parents from disadvantaged backgrounds were not only more likely to have their babies born prematurely, but these prematurely born children were also disproportionately at higher risk for school failure than children with a similar neonatal record from higher income families ( 18 ).

It is worth noting that international studies have consistently shown similar associations between socioeconomic measures and academic outcomes. For example, the Progress in International Reading Literacy Study (PIRLS) assessed the comprehensive literacy skills of grade 4 students in 35 countries. The Programme for International Student Assessment (PISA) assessed reading, math and science scores of 15-year-old children in 43 countries ( 21 ). At these two different stages of schooling, there was a significant relationship between SES and educational measure in all countries. This relationship has come to be known as a ‘socioeconomic gradient’; flatter gradients represent greater ‘equity of outcome’, and are generally associated with better average outcomes and a higher quality of life. Generally, the PISA and the NLSCY data support the conclusion that income or SES has important effects on educational attainment in elementary school through high school. Despite the results shown by the PISA and the NLSCY, schools are not the ultimate equalizer and the socioeconomic gradient still exists despite educational attainment. Test results can be misleading and can mask the gradient if the sample does not account for all children who should be completing the test. A study ( 13 ) completed by the Institute of Research and Public Policy demonstrated only small differences between low and high socioeconomic students when test results were compared in those students who sat for the examination. However, when results were compared for the entire body of children who should have written the examination, the differences between low and high socioeconomic students were staggering, mainly due to the over-representation of those who left school early in the low socioeconomic group.

Longitudinal studies carried out in the United States have been crucial in demonstrating some of the key factors in producing and maintaining poor achievement. Their findings have gone well beyond a model that blames schools or a student’s background for academic failure. Comparisons of the academic growth curves of students during the school year and over the summer showed that much of the achievement gap between low and high SES students could be related to their out-of-school environment (families and communities). This result strongly supports the notion that schools play a crucial compensatory role; however, it also shows the importance of continued support for disadvantaged students outside of the school environment among their families and within their communities ( 22 ).

A Human Resource Development Canada study ( 23 ) titled “The Cost of Dropping Out of High School” reported that lower income students were more likely to leave school without graduating, which agrees with international data. In a nonrandom sample for a qualitative study, Ferguson et al ( 24 ) reported that one-half of Ontario students leaving high school before graduating were raised in homes with annual incomes lower than $30,000. Finally, in Canada, only 31% of youth from the bottom income quartile attended postsecondary education compared with 50.2% in the top income quartile ( 25 ). Once again, the evidence indicates that students from low-income families are disadvantaged right through the education system to postsecondary training.

REVERSING THE EFFECTS OF POVERTY

The negative effects of poverty on all levels of school success have been widely demonstrated and accepted; the critical question for us as a caring society is, can these effects be prevented or reversed? A variety of data are relevant to this question, and recent research gives us reason to be both positive and proactive.

Early intervention

There is a direct link between early childhood intervention and increased social and cognitive ability ( 26 ). Decreasing the risk factors in a child’s environment increases a child’s potential for development and educational attainment. Prevention and intervention programs that target health concerns (eg, immunization and prenatal care) are associated with better health outcomes for low-income children and result in increased cognitive ability ( 27 ). However, it is the parent-child relationship that has been proven to have the greatest influence on reversing the impact of poverty. Both parenting style ( 28 ) and parental involvement, inside and outside of the school environment ( 29 ), impact on a child’s early development. Characteristics of parenting such as predictability of behaviour, social responsiveness, verbal behaviour, mutual attention and positive role modelling have been shown to have a positive effect on several aspects of child outcome. Parental involvement, such as frequency of outings ( 29 ) and problem-based play, creates greater intellectual stimulation and educational support for a child, and develops into increased school readiness ( 26 ).

Interventions act to advance a child’s development through a range of supports and services. Their underlying goal is to develop the skills lacking in children, that have already developed in other children who are of a similar age. There is general agreement that interventions should be data driven, and that assessments and interventions should be closely linked. A primary evaluation of a child and family support systems is, therefore, pivotal in the creation of individualized interventions to ensure success in placing children on a normative trajectory ( 30 ). Ramey and Ramey ( 30 ) determined that interventions have sustained success for children when they increase intellectual skills, create motivational changes, create greater environmental opportunities and/or increase continued access to supports.

Karoly et al ( 31 ) reported the magnitude of effects that early intervention programs have on children. Measured at school entry, they found a pooled mean effect size of around 0.3, with many programs having effect sizes between 0.5 and 0.97. This means that for many interventions, children in the program were, on average, one-half to a full standard deviation above their peers who were not in the program. Interestingly, they found that interventions that combined parent education programs with child programs had significantly higher effect sizes. Furthermore, interventions that continued beyond the early years showed significantly lower fade-out effects. The results strongly support the notion that early interventions should include the whole family and be continued beyond the early years. Constant evaluation of interventions should be completed to ensure that the benefits for children are maximized using these key components.

Highly regarded early interventions

The High/Scope active learning approach is a comprehensive early childhood curriculum. It uses cooperative work and communication skills to have children ‘learn by doing’. Individual, and small and large group formats are used for teacher-and-child planned activities in the key subject areas of language and literacy, mathematics, science, music and rhythmic movement. There has been ongoing evaluation of the approach since 1962 using 123 low-income African-American children at high risk of school failure ( 32 ). Fifty-eight children received high-quality early care and an educational setting, as well as home visits from the teachers to discuss their developmental progress. By 40 years of age, children who received the intervention were more likely to have graduated high school, hold a job, have higher earnings and have committed fewer crimes.

Similar positive effects of preschool intervention were found in the evaluation of the Abecedarian project ( 33 ). This project enlisted children between infancy and five years of age from low-income families to receive a high-quality educational intervention that was individualized to their needs. The intervention used games focused on social, emotional and cognitive areas of development. Children were evaluated at 12, 15 and 21 years of age, and those who had received the intervention had higher cognitive test scores, had greater academic achievement in reading and math, had completed more years of education and were more likely to have attended a four-year college. Interestingly, the mothers of children participating in the program also had higher educational and employment status after the intervention.

One of the oldest and most eminent early intervention programs is the Chicago Child Parent Center program. The intervention targets students who are between preschool and grade 3 through language-based activities, outreach activities, ongoing staff development and health services. Importantly, there is no set curriculum; the program is tailored to the needs of each child ( 34 ). One crucial feature of the program is the extensive involvement of parents. Multifaceted parental programs are offered to improve parental knowledge, their engagement in their children’s education and their parental skills. An evaluation of the Chicago Child Parent Center Program was completed by Reynolds ( 34 ) using a sample of 1106 black children from low-income families. They were exposed to the intervention in preschool, kindergarten and follow-up components. Two years after the completion of the intervention, the results indicated that the duration of intervention was associated with greater academic achievement in reading and mathematics, teacher ratings of school adjustment, parental involvement in school activities, grade retention and special education placement ( 34 ). Evaluation of the long-term effects of the intervention was completed by Reynolds ( 35 ) after 15 years of follow-up. Individuals who had participated in the early childhood intervention for at least one or two years had higher rates of school completion, had attained more years of education, and had lower rates of juvenile arrests, violent arrests leaving school early.

Later intervention

A common question concerns the stage at which it is too late for interventions to be successful. Recent findings (N Rowen, personal communication) from an uncontrolled community study in Toronto, Ontario, have suggested that a multisys-temic intervention as students transition to high school can produce dramatic results. The Pathways to Education project began because of a community (parents) request to a local health agency to help their children succeed in high school. The community consisted mainly of people from a public housing complex, with the majority of families being poor, immigrants and from visible minority groups. The Pathways project grew out of a partnership between the community, the health centre and the school board, and was funded by a variety of sources. The core elements of the program include a contract between the student, parents and project; student-parent support workers who advocate for the student at school and connect parents to the project and/or school; four nights a week of tutoring (by volunteers) in the community; group and career mentoring located in the community; and financial support, such as money for public transit and scholarship money for postsecondary education dependent on successful academic work and graduation. The Pathways project has been running for six years, and the results for the first five cohorts of students have been exciting. In comparison to a preproject cohort, the absentee and academic ‘at-risk’ rate (credit accumulation) has fallen by 50% to 60%, the ‘dropout’ rate has fallen by 80% to a level below the average for the board of education and the five-year graduation rate has risen from 42% to 75%. Of the graduates, 80% go on to college or university, compared with 42% before the Pathways project. While these initial results must be replicated in other communities, they suggest that, even at the high school level, interventions can be startlingly effective, even in a community with a long history of poverty, recent immigration and racism. As the proponents of Pathways move to replication, they will need to be careful to untangle the effects of community commitment, school board collaboration and the rich set of collaborations that have been a hallmark of this first demonstration project. Nevertheless, Pathways has made it clear that Canadian communities possess the capacity to change the education outcomes of their children and youth. While it takes resolve and resources to achieve such effects, initial analysis suggests that over the lifetime of the students, each dollar invested will be returned to Canada more than 24 times ( 36 )!

Schools make a difference

Canadian and international research on educational outcomes has revealed important data on the effects of schools and classrooms. Frempong and Willms ( 37 ) used complex analyses of student performance in mathematics to demonstrate that Canadian schools, and even classrooms, do make a difference in student outcomes (ie, students from similar home backgrounds achieve significantly different levels of performance in different schools). Furthermore, schools and classrooms differ in their SES gradients (ie, some schools achieve not just higher scores, but more equitable outcomes than others). These general findings were corroborated by Willms ( 38 ) using reading scores from children in grade 4 and those 15 years of age from 34 countries. Once again, it was demonstrated that schools make a difference and that some schools are more equitable than others. According to Thomas ( 10 ), activities other than academics, such as sports and lessons in the arts, have been shown to increase student’s school readiness despite SES. These activities should be encouraged in all schools to maximize school readiness. A key to making schools more effective at raising the performance of low SES students is to keep schools heterogeneous with regard to the SES of their students (ie, all types of streaming result in markedly poor outcomes for disadvantaged children and youth).

WHAT CAN WE DO?

Balancing the consistent evidence about the pervasive negative impact of poverty on educational outcomes with the hopeful positive outcomes of intervention studies, what can we do in our communities to attenuate the effects of poverty and SES on academic success? Here are some important actions:

Advocate for and support schools which strive to achieve equity of outcomes;
Advocate for and support intervention programs that provide academic, social and community support to raise the success of disadvantaged children and youth;
Make others aware of the short-, medium- and long-term costs of allowing these children and youth to fail or leave school;
Never miss a personal opportunity to support the potential educational success of the children and youth who we come into contact with;
Advocate for system changes within schools to maximize educational attainment (eg, longer school days and shorter summer vacations); and
Advocate for quality early education and care to minimize differences between children’s school readiness before entering school.

Paediatricians and family doctors have many opportunities to influence readiness for school and educational success in primary care settings. Golova et al ( 39 ) reported intriguing results from a primary care setting. They delivered a literacy promoting intervention to low-income Hispanic families in health care settings. At the initial visit (average age 7.4 months), parents received a bilingual handout explaining the benefits of reading aloud to children, literacy-related guidance from paediatric providers or an age-appropriate bilingual children’s board book. Control group families received no handouts or books. At a 10-month follow-up visit (mean age 17.7 months), there was no difference between groups on a screening test for language scores; however, intervention families read more often to their children, reported greater enjoyment of reading to children and had more children’s books in their homes. Given this suggestive finding, there are a number of points that paediatricians and family doctors should consider as they deliver primary care:

Observe and encourage good parenting – mutual attention and contingency of interaction (taking turns and listening to each other), verbal behaviour (amount of talking and quality), sensitivity and responsiveness (awareness to signs of hunger, fatigue, boredom and providing an appropriate response), role modelling and reading to their children;
Encourage parents to increase their knowledge of child development, particularly age-appropriate needs of and activities for their children. Explain to them, for instance, how ear infections can severely affect a student’s language development, and that good nutrition and hygiene can lower the frequency and severity of infections;
Encourage parents who do not have their children in institutionalized care to attend parent-child centres and programs. These programs usually do not charge fees and require no formal arrangements. Examples are the Ontario Early Years Centres, the Aboriginal Head Start Program in Northern communities, and programs related to the Alberta Children and Youth Initiative;
Indicate the importance of parental support and networks – keep a message board in your office and post a list of community-based organizations in your neighborhood; and
Keep in mind that poverty is not always obvious. One in five low-income families is headed by a parent who works full-time all year; thus, it is often difficult to tell if a family is in need ( 40 ).

Poverty's impact on educational opportunity

Fifty years ago, communities across America began efforts to make school districts more racially integrated, believing it would ease racial disparities in students’ educational opportunities. But new evidence shows that while racial segregation within a district is a very strong predictor of achievement gaps, school poverty – not the racial composition of schools – accounts for this effect.

In other words, racial segregation remains a major source of educational inequality, but this is because racial segregation almost always concentrates black and Hispanic students in high-poverty schools, according to new research led by Sean Reardon, a professor at the Stanford Graduate School of Education (GSE) and a senior fellow at the Stanford Institute for Economic Policy Research (SIEPR).

“The only school districts in the U.S. where racial achievement gaps are even moderately small are those where there is little or no segregation. Every moderately or highly segregated district has large racial achievement gaps,” said Reardon, the Professor of Poverty and Inequality at the GSE. “But it’s not the racial composition of the schools that matters. What matters is when black or Hispanic students are concentrated in high-poverty schools in a district.”

The findings were released on Sept. 23 in a paper accompanying the launch of a new interactive data tool from the Educational Opportunity Project at Stanford University, an initiative directed by Reardon to support efforts to reduce educational disparities throughout the United States.

Test scores as measures of opportunity

The Educational Opportunity Project gives journalists, educators, policymakers and parents a way to explore and compare data from the groundbreaking Stanford Education Data Archive (SEDA), the first comprehensive national database of academic performance.

The database, first made available online in 2016 in a format designed mainly for researchers, is built from 350 million reading and math test scores from third to eighth grade students during 2008-2016 in every public school in the nation. It also includes district-level measures of racial and socioeconomic composition, segregation patterns and other educational conditions.

Researchers have used the massive data set over the past few years to study variations in educational opportunity by race, gender and socioeconomic conditions throughout the United States. The data have also shown that students’ early test scores do not predict academic growth over time, indicating that poverty does not determine the effectiveness of a school.

Now, with an interactive tool on the Educational Opportunity Project’s website, any user can generate charts, maps and downloadable PDFs to illustrate and compare data from individual schools, districts or counties. (Visualizations also can be embedded elsewhere online so that users can access them directly from another site.)

The site provides detailed data on three measures of educational opportunity:

Average test scores, which reflect all of the educational opportunities children have from birth through middle school
Learning rates (how much students learn from one year to the next), which reflect the opportunities available in their schools
Trends in how much average test scores change each year, which reflect changes in the opportunities available to successive cohorts of children

“We can also break it down and look at how students are performing differentially by race, by ethnicity, by gender, by family income,” said Reardon. “That lets us understand not just how a community is providing opportunity for everyone, but whether it’s providing the same amount of opportunity for children from different backgrounds.”

Beyond learning about their own school or districts, users can also find and learn from comparable communities with fewer inequities. For instance, superintendents concerned about the achievement gap between students of different race and ethnicity in their district could use the tool to identify other districts around the country that are similar in size and demographics but have smaller achievement gaps – and then reach out to leaders in those communities to find out about the practices and policies that have been effective.

A better gauge of school quality

The information on learning rates is a key innovation of the site, Reardon said, because these trends provide a picture of educational opportunity that’s vastly different from what average test scores show.

By indicating how much students learn as they go through school, these rates are “a much better measure of school quality,” said Reardon. “If parents were to use the learning rate data to help inform their decisions about where to live, they might make very different choices in many cases.”

What’s more, data on learning rates are largely unavailable elsewhere. “Some states and websites provide some measure of learning rates for a community, but their data are typically based on one year of growth, and they aren’t comparable across states,” he said. “Our learning rates are based on eight years of data, so they’re much more reliable.”

Reardon acknowledged the limitations of measuring student achievement through reading and math scores. “Test scores certainly don’t measure everything we want for our kids,” he said. “We also want them to learn art and music, to learn to be empathetic and kind, creative and collaborative, and to have good friends and be happy – it’s not all about math and reading.”

He also cautioned that differences in average test scores do not reflect differences in students’ intelligence or abilities. “When we look at average test scores in a community, a school district or a school, what we’re measuring is really the amount of educational opportunity provided in those communities – not the average ability,” he said. “Average ability doesn’t vary from one place to another, but opportunity does.”

Identifying the effects of school segregation

In studying segregation in U.S. schools today, Reardon and colleagues sought to discover whether racial segregation has the same harmful effects that it did 50 years ago, when efforts to integrate Southern school districts began in earnest.

The research team used the data now available through the Educational Opportunity Project to investigate first how strongly segregation levels are associated with academic achievement gaps.

What they found was striking: Without exception, the level of segregation correlated not only with the size of the achievement gap, but also with the rate at which that gap grew as students progressed from third to eighth grade.

To determine what accounted for the correlation, they controlled for racial differences in school poverty and found that segregation no longer predicted the achievement gaps. That meant the association between racial segregation and the growth of achievement gaps operated entirely through differences in school poverty.

“While racial segregation is important, it’s not the race of one’s classmates that matters, per se,” said Reardon. “It’s the fact that in America today, racial segregation brings with it very unequal concentrations of students in high- and low-poverty schools.”

Educational epidemiology

With new, accessible evidence for the relationship between test score patterns and socioeconomic status, race and gender, the Educational Opportunity Project lays the groundwork for more targeted policies to address disparities.

Reardon sees the project as a kind of educational epidemiology. “In order to fix problems of inequality and improve schools, we need to have a good understanding of the landscape of the problem,” he said. “In some ways, that’s what epidemiologists do.”

By pinpointing where disparities exist, where they’re getting worse or better and the factors that correlate with local trends, the Educational Opportunity Project aims to bring both researchers and community members closer to understanding how to create more equitable learning opportunities, in and out of school.

Then, said Reardon, “we can get to a place where we can start to have targeted social and educational policy solutions that will really make a difference.”

The Educational Opportunity Project has been supported by grants from the U.S. Department of Education’s Institute of Education Sciences, the Spencer Foundation, the William T. Grant Foundation, the Bill and Melinda Gates Foundation and the Overdeck Family Foundation.

Co-authors of the research paper on school segregation are Ericka S. Weathers, PhD ’18, an assistant professor at Penn State College of Education; Erin M. Fahle, PhD ’18, an assistant professor at St. John’s University School of Education; Heewon Jang, a doctoral student at Stanford GSE; and Demetra Kalogrides, a research associate with the Center for Education Policy Analysis (CEPA) at Stanford GSE.

Can global supply chains be fixed?

Research Highlight
Global Development and Trade
Regulation and Competition

Presidential debate fact check: Analyzing Trump, Harris on abortion, immigration, more

Poverty Impedes Children’s Education Long Before They Enter The Classroom — Here’s How We Can Change That

Share to Facebook
Share to Twitter
Share to Linkedin

Written by Jordan Langs, Program and Development Associate, Moms Helping Moms Foundation

Within the United States, education is commonly regarded as an equalizer to opportunity and upward mobility. In reality, there are countless impediments in the system that exclude low-income children from reaping the full benefits of education long before they enter the classroom.

Education starts well before a child enters the classroom.

Education starts well before a child enters the classroom. Harvard University’s Center on the Developing Child noted that “brains are built over time, from the bottom up,” beginning before birth and continuing into adulthood. While development may continue into adulthood, the brain develops more during the first five years of a child’s life than at any other point, with more than 1 million new neural connections being made every second. In fact, 90% of the brain is developed by the time a child is five or six years of age. Growing research on early childhood development has confirmed the importance of supporting brain development during the early years. Thanks to studies conducted by organizations like The National Academies of Sciences, Engineering, and Medicine, we now know there is a direct connection between early childhood development and social, emotional, behavioral, and cognitive development outcomes, linking healthy development to school readiness and success in life . As noted by Harvard University’s Center on the Developing Child , “Healthy development in the early years provides the building blocks for educational achievement, economic productivity, responsible citizenship, lifelong health, strong communities, and successful parenting of the next generation.”

The ratio of age-appropriate books per child in low-income neighborhoods is 1 book per 300 children, compared to middle-income neighborhoods where the ratio is 13 books per child.

With critical learning and development occurring well before children enter a classroom, the responsibility to support early childhood development falls on parents and caregivers. This puts low-income students at a significant disadvantage, resulting in a substantial school readiness gap that has negative lifelong implications. Children from low-income households often lack access to books, sing-along toys, interactive games, and other early learning materials that support a child’s healthy development. To put it into perspective, the ratio of age-appropriate books per child in low-income neighborhoods is 1 book per 300 children, compared to middle-income neighborhoods where the ratio is 13 books per child.

When families lack access to these essential learning materials, children miss out on the many positive benefits of early literacy learning. When you read to your child, you teach them how to acquire, organize, and use knowledge . You foster their cognitive development by engaging them in thinking, exploring, and problem-solving. You enhance their language and literacy skills by introducing new words and stimulating their understanding and ability to use and comprehend those words. You expand their social, emotional, and behavioral skills by building their knowledge of the world through the narrative of a book, which develops listening skills, emotion management, and problem-solving skills. In sum, early literacy is an integral piece of a child’s brain development.

Other impediments, like the inexistence of universal child care , also stand in the way of low-income children’s healthy development and access to education. With the cost of child care programs averaging $14,117 annually per child , a rampant 41% increase compared to pre-pandemic prices, this service is unattainable for most low-income families, meaning that parents and caregivers must take on the role of an early educator in addition to the many roles they already assume as a parent. So, now not only do families need to have access to literacy materials to teach the child, but it means they also need to be able to devote time. Unfortunately, time is another unattainable factor for many low-income families, as parents and caregivers work extensive hours and multiple jobs to make ends meet. With less time to spend with their children, children consequently miss out on the high-quality, development-stimulating experiences their more affluent counterparts receive by attending child care. Stress can also be attributed to the various hurdles standing between low-income children and healthy development. While stress takes many forms, low-income families are, once again, disproportionately affected. New research has linked poverty to stress, uncovering the toxic consequences on early childhood development , including damage to the brain’s executive function and the regulation of emotion and attention.

“How do you become literate when there are no available resources?” Susan Neuman, New York University

The lack of access to learning materials extends beyond the household. There is a severe shortage of print materials available to the public in many low-income communities. Many do not have public libraries, and those that do are met with limited items and hours of operation. According to the U.S. Department of Education, a staggering 2.5 million children across the country are enrolled in districts where there are no libraries. However, the lack of print materials does not just refer to the free resources available at a public library; it also includes items available for purchase. This harsh reality for low-income communities is known as book deserts . Research shows that living in a book desert can impose severe constraints on school readiness. New York University childhood and literacy education researcher, Susan Neuman , encapsulates the harsh consequences of book deserts by proclaiming, “How do you become literate when there are no available resources?”

As we can see, poverty is a cement barrier standing between low-income families and their ability to stimulate healthy early childhood development so their children can reap the full benefits of education. Since raising a child costs roughly $14,846 per year , while the annual salary of a full-time minimum-wage worker receiving the federal minimum wage ( $7.25 ) is only $15,080, it’s nearly impossible for low-income families to stretch their budgets even further to include books, let alone child care. When compared to food, rent, utilities, and clothing, books become a luxury item forced to take a backseat. With 61% of low-income families not having any children’s books in their homes and only 48% of low-income children entering school prepared, the extent that poverty negatively impacts school readiness is clear. Unfortunately, when a child starts school behind, they are more likely to stay behind .

While this form of poverty is seemingly challenging to address, growing research in recent years has found effective interventions. A study on poverty’s impact on children’s cognitive, emotional, and brain development , in particular, has opened doors for potential policies that would support children in their early years. The New York Times reported that the study provided low-income mothers with monthly cash stipends of $333 for the first year of their child’s life. The findings were remarkable, revealing increased brain activity in babies, highlighting the sensitivity of children’s brains to their environment while offering direct evidence that poverty itself can hold children back from day one.

In addition to research, there are many things that we as a community can do at the local, state, and federal levels. Here are some ways that you can make a significant difference in a child’s life that will follow them for years:

1. Donate Books

Donating new and gently used books helps get books in the hands of those who need them most. Many human services organizations and nonprofits alike have created literacy programs to better support low-income families. Even organizations that you wouldn’t think accept books oftentimes do – food and diaper banks included. Other great places to donate new and used books are Head Start Programs, local libraries, and Community Family Resource Centers.

Donating new and gently used books and supplies helps get them into the hands of those who need them most.

Many organizations have expanded their services in recent years to help get books into low-income communities. Moms Helping Moms Foundation (MHM), founded in 2011 as a diaper bank, quickly expanded its operation to provide books and literacy materials when Founder and Co-Executive Director, Bridget Cutler, realized the potential MHM had to help families beyond diapers. Through its Early Literacy Program , MHM distributes literature in both English and Spanish to parents and caregivers throughout New Jersey. Items under this category include books, which MHM ensures each child served receives at least one with every wish list fulfillment, and early literacy learning materials that discuss the importance of early reading, talking, and singing with children. Since 2017, MHM has donated nearly 25,000 books along with literacy handouts to New Jersey residents in need. They rely on donations of books and literacy kits to provide these essential items. You can donate new and gently used children’s books by bringing or mailing items directly to their warehouse in Warren, New Jersey, or by purchasing them from their Amazon Wish List .

2. Get Crafty: Make Literacy Kits!

Literacy kits are also a great way to support a child’s early development and can be a fun craft opportunity for volunteers. Love Letters for Literacy helps families in need by donating handmade literacy packets to make teaching the letters of the alphabet easy and fun! By partnering with nonprofits around the country, like Moms Helping Moms Foundation, literacy kits are reaching low-income children in underserved communities. Visit their website to learn more!

Print materials are another great way to get literacy kits into these communities. Moms Helping Moms Foundation and diaper banks across the country have partnered with the National Diaper Bank Network and Too Small To Fail to provide informational handouts that families can use to support their child’s early development. This initiative, called Diaper Time Is Talk Time, aims to spread awareness, promote the importance of early brain and language development, and empower parents and caregivers with the tools to talk, read, and sing with their little ones. Learn more about the program and check out their free handouts here !

3. Host a Book Drive

Book drives are a fun and educational way to collect these much-needed items while simultaneously raising awareness in the community. Best of all, anyone and any group can host a book drive – individuals, schools, service groups, student organizations, local businesses – you name it. At Moms Helping Moms Foundation, they offer both in-person and virtual drive opportunities, as do many other organizations these days. Learn more about hosting an in-person or virtual book drive by visiting their website !

4. Start A Free Library!

While free libraries have been around for quite some time, the COVID-19 pandemic drew new attention to them as many communities found their local libraries and book shops shut down. Starting a free library is a simple and easy way to bring the community together while increasing the availability of free literacy materials. The “library” itself can take many different forms. The most common approach is to perch a cabinet-style box at the curb of your house or building, but you can practically makeshift it however you’d like.

Starting a free library is a simple and easy way to bring the community together while increasing the availability of free literacy materials.

The Little Free Library is a 501(c)(3) nonprofit organization based in Hudson, Wisconsin. Their vision is to have a Little Free Library in every community so every reader can have a book. With over 125,000 Little Free Libraries in 100+ countries, their global network is making an immense difference in communities across the globe. Get involved by starting your own, or supporting your local, free library! It’s simple, easy, and fun – and the Little Free Library has a step-by-step tool kit to help you get started.

5. Use Your Voice: Advocate and Raise Awareness

Growing research in recent years has opened doors for government intervention. Senator Elizabeth Warren introduced S.1398 The Universal Child Care and Early Learning Act to help promote school readiness for all young children by ensuring they have access to a supportive learning environment where they can stimulate healthy early childhood development. Use your voice to raise awareness of this bill by contacting U.S. Senators and asking for their support. The NCSL has an excellent letter template example that you can use to format your letter.

In addition to contacting government officials, you can use your voice in the community and on social media. TikTok user Araba Maze used TikTok to bring awareness of Baltimore's book deserts. Her journey started while reading to her nieces on their stoop in Baltimore, Maryland, when she noticed other little kids gathering around. She began hosting “Stoop Storytimes” every week and was eventually inspired to become a librarian. After realizing she still wasn’t reaching the children in her neighborhood, for there are many barriers to access, she entered the United Way’s Baltimore County Changemaker Challenge to help increase access with free book vending machines in everyday places like laundromats, convenience stores, and train stations. To help raise awareness, she posted a video on TikTok that quickly went viral, bringing in donations of books for the vending machines while inspiring viewers to get involved. After earning $20,000 in grant money and collecting donations through social media, Araba began partnering with local book banks to get the vending machines set up across the city and Baltimore County.

There are many other ways to get involved and make a difference! Check out the End Book Deserts resource guide, organized by state, to see what efforts are currently being made in your community.

This is a content marketing post from a Forbes EQ participant. Forbes brand contributors’ opinions are their own.

Editorial Standards
Reprints & Permissions

Ending poverty
Facts about poverty
Education & poverty

Global poverty and education

Facts & stats about world poverty and education.

Global poverty facts
Health & poverty
Empowerment & poverty
Employment & poverty
Giving & poverty
Technology & poverty
Hunger & poverty
Poverty in the U.S.
Poverty in Africa

The research is conclusive: When we reduce barriers to education, we set children up to thrive. It’s not only about knowledge and numbers, access to education reduces a child’s involvement in gangs and drugs, and lowers the amount of teen pregnancies. Education leads to healthier childhoods and, ultimately, to greater economic prospects as adults. Your sponsorship or gift helps provide children access to life-changing education programs in the communities we serve, as well as crucial health and dental services, life-skills and career-placement workshops, and more.

Sponsor a child Make a gift Learn about our Education Programs

Children who participate in early childhood development achieve higher education levels and make more money as adults.

In developing nations, 60% of 10 ten-year-olds suffer from learning poverty, unable to read/understand simple stories.

For every year a girl remains in school, her average lifetime income increases 10% and odds of an early marriage shrink.

A child’s survival beyond age 5 increases by 31% when a mother has a high school degree, compared to no education.

Despite the shrinking gender gap, 8% fewer girls complete lower secondary school than boys. 

The share of youth not employed or participating in education or job training rose to 23.3%, the highest increase in 15 years.

Global studies find there is a 9% increase in hourly earnings for every extra year of schooling a child receives. 

During COVID, children in Latin America and the Caribbean lost an average of 225 full days of school.

a woman sitting at a desk in front of a computer

Access to education

We believe providing children access to education and resources ushers them into a world of ideas and knowledge, and creates lasting change in their lives. Supporters provide access to tutoring, computer courses, libraries and more, setting children up for a lifetime of success.

WHO Youth Violence Research, 2009
UNICEF The State of the World’s Children, 2009
UNESCO, 2012
World Bank eLibrary. “Returns on Investments in Education,” 2002
UNESCO Global Education Monitoring Report, 2017
The World Bank 2015
The World Bank 2017
Globalpartnership.org, Education Data Highlights
Un.org, Education
Results.Org, World Poverty and What you Can Do About It
Lifewater.org, 9 Poverty Statistics that Everyone Should Know, January 28, 2020

This site uses cookies to improve your experience. You can restrict cookies through your browser; however that may impair site functionality.

Are you sure?

My order summary

Wednesday, September 18, 2024

INTER PRESS SERVICE

News agency, news and views from the global south .

Asia-Pacific
Latin America & the Caribbean
Middle East & North Africa
North America
Food & Agriculture
Humanitarian Emergencies
Poverty & SDGs
Financial Crisis
Green Economy
Natural Resources
Trade & Investment
Cooperatives
Advancing Deserts
Biodiversity
Climate Change
Water & Sanitation
Armed Conflicts
Crime & Justice
Indigenous Rights
Migration & Refugees
Press Freedom
Civilisations Find Alliances
Eye on the IFIs
Global Geopolitics
Globalisation
South-South
United Nations
Regional Alliances
Southern Aid & Trade
Active Citizens
World Social Forum
Conferences
Gender Violence
Women & Economy
Women & Climate Change
Women’s Health
Gender Identity
Women in Politics

Where Has Poverty Gone?

NEW YORK / OXFORD, UK , Sep 18 2024 (IPS) - Political polarization, the climate emergency, organized crime, migration, and low economic growth currently dominate the public debate in Latin America and the Caribbean (LAC), and rightly so. However, there is a significant structural challenge to human development and democracy itself that, along with inequalities, lies at the root of these crises: poverty.

Today, 181 million people, 29% of the region’s population, live in monetary poverty, and 33 million suffer from acute multidimensional poverty (considering only countries with available data). Advancing towards a prosperous and resilient LAC requires putting poverty in all its forms and dimensions back at the center of public debate and addressing new responses through public policy.

In past decades, the region significantly reduced poverty by taking advantage of economic growth driven by the commodities boom and the introduction of innovative public policies focused on solving this problem, such as conditional cash transfers—schemes where cash is given to households in poverty in exchange for specific investments in human development, such as ensuring school attendance or participation in vaccination campaigns-.

However, this trend began to reverse two years before the pandemic.

Revitalizing the poverty reduction agenda requires resuming this innovative capacity and political will. We have done it in the past, we must do it again, and it is possible. Brazil’s recent proposal to the G20 to promote a Global Alliance Against Hunger and Poverty is an excellent step in this direction.

To achieve this, it will be essential to better understand and measure the multiple forms and dimensions of poverty, ensure effective inter-institutional coordination for policy design and implementation, and refine the targeting and allocation of resources through new planning instruments. Given the context of low economic growth and limited fiscal space, efficiency is key to accelerating significant achievements.

Ensuring that people in poverty have the capabilities and opportunities to live the life they want requires tools that capture their realities and experiences, including the multiple deprivations that affect them in different dimensions of well-being and go beyond the lack of income.

Not having access to education, water, or health, among others, are significant deprivations that may or may not be correlated with having money—a person may have sufficient income to not be considered poor and yet not have access to healthcare because there is no hospital near his or her community.

The Global Multidimensional Poverty Index (MPI), launched by UNDP and OPHI in 2010, complements the measurement and analysis of extreme monetary poverty with information about people’s situation in multiple socioeconomic dimensions.

The MPI has been adopted by countries around the world as an official poverty measure, complementing income-based measures and focusing on each country’s priorities, turning them into effective public policy tools that allow for more precise identification of who and where the poor are, and how it varies by age, gender, territory, and ethnicity.

Latin America has been a pioneer in adopting national MPIs, with 12 countries and two major cities—Mexico City and Bogotá—and can once again be a reference for poverty reduction. The success of conditional cash transfers in the past meant a quantitative leap in the utility of monetary poverty data.

It is time to replicate this success by developing new transformative policies that have the same effect on the utility of multidimensional data, taking advantage of the planning, policy articulation, and monitoring possibilities provided by the rich information obtained from complementary use of both measures.

In Honduras, for example, multidimensional data was used to better identify the population with the greatest vulnerabilities as a result of COVID-19 and to more accurately guide cash supports.

On the other hand, a clear articulation between other national policies and poverty reduction goals will also be crucial to achieving greater impact. Policies like those related to productivity, energy, or climate change are often defined in a sectoral manner despite their potential to accelerate poverty reduction.

These links need to be formalized. It is also important to invite actors beyond the public sector to incorporate these analyses and actions to accelerate poverty reduction as part of their development strategies. For example, the Colombian natural gas producers’ association (Naturgas) created an index of strategic municipalities.

This explicitly incorporates an equity dimension through poverty-related variables alongside business variables usually used by private companies in their decision-making processes. This index generates incentives to invest in areas of greater poverty while respecting the natural profit-seeking of these companies.

If we want to get back on track towards eradicating poverty in all its dimensions, we must put poverty and inequality back on the public agenda, promoting spaces for dialogue, collaboration, and consensus around innovative and transformative public policies that allow us to move towards more equal and inclusive societies.

Only in this way we will be on track to achieve sustainable development in LAC. Let’s not wait any longer and make the leap that we need in public innovation for a well-being and human development that leave no one behind.

Michelle Muschett is Director, Regional Bureau for Latin America and the Caribbean of the United Nations Development Programme (UNDP); Sabina Alkire is Director of the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford.

IPS UN Bureau

Related Tags

Editors' choice, explainer: why venezuela needs to reduce its gas flaring.

This photo of the Caribbean Sea taken in 2021 is the above view of the western side of Venezuela's Paraguaná Peninsula. The smoke plume running across the middle of the image appears to originate at a gas flare (mechurrio) of the Paraguaná Refinery Complex. Credit: NASA

Most popular

How much is too much for mount everest isn’t it time for sagarmatha to rest, a un 2.0 needs robust people’s civil society participation, global community urged to help deliver quality, holistic education for ukrainian children, the deadly us weapons of civilian destruction, leaders can rise to the summit, together, the week with ips.

Latin America & the Caribbean
Middle East & North Africa
Reprint / Republish
Our Partners

IPS is an international communication institution with a global news agency at its core,raising the voices of the South and civil society on issues of development, globalisation, human rights and the environment Copyright © 2024 IPS-Inter Press Service. All rights reserved. - Terms & Conditions

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

View all journals
Explore content
About the journal
Publish with us
Sign up for alerts
Review Article
Open access
Published: 13 September 2024

Digitalisation and poverty in Latin America: a theoretical review with a focus on education

Jesús Plaza de la Hoz 1 ,
Zaida Espinosa Zárate ORCID: orcid.org/0000-0002-5217-2731 2 &
Celia Camilli Trujillo 3

Humanities and Social Sciences Communications volume 11 , Article number: 1194 ( 2024 ) Cite this article

Metrics details

Development studies
Science, technology and society

This theoretical review/metatheory examines different theoretical approaches to digitalisation. With a focus on education, it analyses how the digitalisation of Latin American populations in vulnerable contexts is understood in 87 documents published by Latin American institutions between 2000 and 2022 that met the inclusion criteria. An inductive coding analysis of their theoretical perspectives on ICT and digitalisation was conducted, yielding four categories as results: a tendency toward (1) a humanistic model of digitalisation, (2) with a social focus, (3) a sociocultural perspective, and (4) a communitarian-substantialist understanding of ICT. The implications of these theoretical perspectives for education are discussed in terms of the aims and expectations placed upon digitalisation and can serve as a theoretical basis for public educational policies seeking to advance development in Latin America, understood in human, not just economic, terms.

Scientometric analyses of digital inequity in education: problems and solutions

Inclusive education of refugee students with disabilities in higher education: a comparative case study

Digital transformation and digital literacy in the context of complexity within higher education institutions: a systematic literature review

Introduction.

The Economic Commission for Latin America and the Caribbean (CEPAL, 2022 ) reports that the number of people living in extreme poverty in this region increased to 86 million in 2021 as a consequence of the COVID-19 pandemic, with a 7.9% decrease in regional GDP in 2020. These figures reveal the devastating impact of the health crisis in this part of the Americas, which was already facing significant social and economic challenges. Much of the progress made in poverty reduction over the last two decades has been lost (World Bank, 2021 ).

Although many factors contribute to poverty in Latin America, digitalisation is considered one of the structural knots for development. The potential of information and communication technologies (ICTs) can be harnessed to benefit the poor, as they are creating new opportunities that can be leveraged to support human development and poverty reduction strategies. However, several requirements must be met for this potential to be realised. Public policies are needed not only to support the provision of accessible and low-cost infrastructure, but also to promote the demand for ICTs through contextualised information and local services for the most vulnerable. To foster this demand, investment in training and awareness campaigns is essential. As Solorio et al. ( 2023 ) point out, community participation, particularly that of vulnerable groups, in policy areas such as digitalisation and digital education is crucial for successful implementation. Therefore, there are both objective and subjective conditions that must be met for the digitalisation of the populations living in vulnerable conditions to be effective. Objective conditions include material, political and economic factors that enable or impede the shift from physical to virtual environments. Subjective conditions, both individual and social, are equally important. Individual subjective conditions refer to digital competence, encompassing the capabilities individuals must develop to be active digital citizens rather than passive subjects (Cortina, 2001 ). Social subjective conditions pertain to the social perception and assessment of digitalisation, which not only enable it—as is the case with objective conditions—but also legitimise it, making it desirable or even normative.

In addition, the contribution of digitalisation to poverty reduction depends on the theoretical perspectives that underlie the digitalisation process. In other words, the extent to which digitalisation can be harnessed to improve the lives of disadvantaged populations depends on the very understanding of digital technologies and how the digitalisation process is conceived in the region. Without a social understanding, digitalisation can perpetuate inequalities and further marginalise disadvantaged groups, distancing them from their rights as citizens. Therefore, as stated by Pick et al. ( 2007 ), the Latin American perspective on the problem of development is key for effectively approaching and understanding digitalisation and its institutionalisation. In this context, the contribution of this article is twofold: on one hand, it compiles and analyzes the educational articles that have been published on digitalisation and poverty by Latin American institutions since the turn of the century with the aim of directly listening to the voices of those involved, avoiding the imposition of alien understandings of the phenomenon and solutions that come from contexts foreign to the characteristics of this region (Gascó-Hernández et al., 2006 ). On the other hand, it focuses on the theoretical perspectives on digitalisation underlying those studies to critically analyse their actual potential to advance the development and their ambiguities.

Here development is understood from a human and not purely economic perspective based on Ignacio Ellacuría’s liberation project in the context of ‘the unlivable lives of the poor in El Salvador and other third world countries’ (Espinosa, 2022 , p. 2). Ellacuría’s philosophy of historical reality ( 1990a ) is an original theoretical contribution that emerges from the Latin American context and whose international significance is increasingly acknowledged. He understands history as the fundamental reality and conceives it as a complex dynamic totality that comprises various dimensions as structural moments (the material, the biological, the psychological, the personal, the social, the political, the ideological), in line with Zubiri’s philosophy ( 1995 ). Unlike Hegel, Ellacuría asserts that ‘it is not a logical reason that drives the development of historical reality in a predetermined teleological way, but human praxis’ (Espinosa, 2022 , p. 2). Thus, reality is open in its dynamism and demands a critical analysis of its objectified structures and the transformation of those that are not true , good and politically adjusted , in correspondence with the epistemological , ethical and praxical/political dimensions of reality.

Ellacuría’s thought can serve as a theoretical framework for identifying ideologizations (not just ideologies) within the digitalisation process that offers a distorted picture of reality and legitimize the current state of affairs, in which most of the population is unable to use ICTs for their social advancement. Those ideologizations hinder the potential contribution of technologies to the common good or, in Ellacuría’s terms, to a universalizable civilisation project that provides an opportunity for everyone’s humanisation. Ellacuría’s critical analysis of historical reality and its objectified structures can be applied to the theoretical perspectives underpinning digitalisation by posing the three questions he asks: To what extent are they true/right ? To what extent are they good/fair ? And to what extent do they adjust to their immediate context? Just as with social structures, the theoretical perspectives on digitalisation set certain limits to human praxis: they open up some options, enable the creation of some possibilities, and rule others out.

In this line, it is acknowledged that despite the centrality of metatheory to research and practice, research studies rarely have a strongly articulated philosophical foundation (Prestwich et al., 2014 ). However, when such a foundation is present, it is valuable to study the theoretical perspectives underlying these studies in and of themselves (Allana and Clark, 2018 ) to understand how digital inequality is ultimately explained. This is increasingly recognised as a crucial area for methodological advancement (Campbell et al., 2014 ).

In education, only a few theoretical reviews/metatheories regarding digitalisation can be found. Herrero-Diz et al. ( 2016 ) examine the theories that explain minors as creators of digital content. Martino and Spoto ( 2006 ) analyse the methodological and formal perspectives on social networks and their relationship with ICTs. López-Núñez et al. ( 2022 ) focus on how new methodologies positively influence the reduction of learning difficulties in primary school students and students with attention deficit hyperactivity disorder. While not a metatheory, the study by Ngwenyama and Morawczynski ( 2009 ) presents the factors affecting ICT expansion in five Latin American countries with an economic focus. However, none of these studies has focused on vulnerable populations, and only a few have taken Latin America as a reference point (Stratton and Nemer, 2020 ), which is the intention here.

Accordingly, the research questions that guide this study are the following: what are the theoretical perspectives on digitalisation of educational research published between 2000 and 2022 that focus on the population living in poverty in Latin America? What are the implications of these ways of understanding digitalisation for development? In other words, based on the goals attributed to technology and the expectations over it, how well do those theoretical perspectives serve as a framework for contributing to development? To answer them, the following objectives were pursued:

Identify scientific educational documents on the digitalisation of populations in vulnerable situations and describe their main contextual characteristics.

Examine the conceptualisation of digitalisation proposed in them based on the aims attributed to it, the expectations about it, and the understanding and importance given to both objective and subjective conditions for digitalisation.

Distinguish several categories that emerged from the analysis of the selected documents. These categories can be understood as different theoretical approaches to digitalisation, each serving human development to varying extents.

Study context

The present theoretical review focuses on Latin America and seeks to identify all the scientific educational articles published on the digitalisation of people living in disadvantaged contexts of this region between 2000 and 2022 with the purpose of understanding their theoretical perspectives on digitalisation.

The time frame between 2000 and 2022 was selected because this period encompasses significant legislative and policy developments in the field of digitalisation and digital education across Latin America. Since the early 2000s, many countries in the region have implemented national strategies and reforms promoting the digitalisation of education, such as Argentina’s Conectar Igualdad [Connect Equality] programme since 2010, which aimed to distribute laptops to students and teachers, enhancing digital literacy, or Colombia’s Computadores para Educar [Computers for Education] initiative since 2001. Additionally, key educational reforms, including Chile’s General Education Law of 2009 and Ecuador’s Organic Law of Intercultural Education of 2011, have incorporated specific guidelines for integrating ICT into their educational systems. This legislative and policy context justifies the selection of this time frame, allowing for a comprehensive analysis of the evolution of digitalisation and its conceptualisation in educational scientific articles across the region.

Study design

Theoretical reviews or metatheories are a type of systematic review that involves scrutinising the theoretical perspectives of a group of studies, including their epistemology, assumptions and contexts (Paterson et al., 2001 ; Thorne et al., 2004 ). For Nicholas et al. ( 2006 ), theoretical reviews explore the sociohistorical, paradigmatic, tangential and idiosyncratic perspectives inherent in understanding a topic at a given time and place. In other words, they analyse latent theories understood as broad perspectives, which make claims about the nature of reality and philosophically underpin research and practice in any field of study (Allana and Clark, 2018 ). While reviews of empirical data seek to minimise the bias of the methodological quality of the primary studies, theoretical reviews are not even certain that the concept of bias is substantially meaningful, as their main contribution is aimed at ‘opening up’ the reviewers’ thinking about the research topic and broadening the potential space for generating hypotheses for future effective interventions (Campbell et al., 2014 ).

The question that guided the present theoretical review was structured according to the Patient, Intervention, Comparison, Outcome (PICO) methodology (Page et al., 2021 ): How is the digitalisation of the populations living in vulnerable contexts in Latin America approached conceptually? Guided by broad inclusion criteria, it seeks to explore the theoretical approaches underlying the documents under study (Campbell et al., 2014 ).

Following the guidelines of the Cochrane Handbook for Systematic Reviews (Higgins et al., 2022 ), the following inclusion criteria have been used: empirical and theoretical studies; written in Spanish, English or Portuguese; published in scientific journals between 2000 and 2022 by Latin American institutions; referring to Latin American populations in a situation of vulnerability. Vulnerability is understood as conditions where individuals, due to certain social, cultural, economic, psychological, age, and/or gender factors, are helpless, defenceless, or in a fragile position regarding access to information and the ability to act as citizens through digital mechanisms (Helsper and Smahel, 2020 ).

The exclusion criteria eliminated systematic reviews and studies not related to the field of education, those that do not explicitly mention an interest in populations in contexts of poverty, and those conducted by Latin American organisations that do not take the population of this region as the study object.

The descriptors used to search the documents were ‘digital’ and ‘ICT’ combined with the Boolean operator AND for the terms ‘divide,’ ‘gap,’ ‘inclusion,’ ‘at risk,’ ‘inequality,’ ‘poverty,’ and ‘vulnerab*,’ all of which were searched for in the title, abstract or keywords (Fig. 1 ). These terms were chosen based on previous studies related to the topic (Camilli and Römer, 2017 ; González-Zabala et al., 2018 ; Martínez-Bravo et al., 2020 ).

Database search strings.

The literature review was carried out by consulting the general databases SCOPUS and Web of Science as well as specific education (ERIC) and communication (Communication & Mass Media Complete) databases, and DIALNET, which provides access to documents published primarily in Spanish or addressing Hispanic topics.

For the review process, which met the PRISMA criteria (Page et al., 2021 ), a coding manual (authors, publication year, title, journal, abstract, study objectives, research question, methodological design, main results, conclusions, limitations and outlook) was prepared in Excel and shared among the researchers. Of the 1495 manuscripts found, 374 were included in the first round, of which only 227 met the inclusion criteria in the second round. This number decreased to 156 in the third round, and in the fourth and final round, the total number of manuscripts selected was 87 (Fig. 2 ).

Data analysis modes and theories

The qualitative analysis of the theoretical perspectives was carried out in two phases. The first phase, exploratory in nature, involved a general description of the studies. The second phase consisted of a critical examination of the different frameworks for understanding the digitalisation of disadvantaged populations, aiming to reveal similarities and discrepancies within and between the studies (Paterson et al., 2001 ). This type of analysis, aligned with a more discursive synthesis approach, was characterised by a reflexive and iterative process in which the research production was assumed as a socially constructed reality, culturally linked to sociohistorical and geographical contexts (Thorne et al., 2004 ).

The analysis was carried out using the inductive (bottom-up) criterion, and thus, all the categories were emergent (Bingham and Witkowsky, 2022 ). Each researcher coded based on the most frequent topics related to the conceptualisation of digitalisation concerning disadvantaged populations. The main categories identified were then pooled together, allowing for the reduction, synthesis and comparison process to be accomplished. Atlas.ti8 was used in both phases.

General description of the studies

The 87 final documents, numbered in Appendix 1 , were published between 2004 and April 2022, although 64.29% of them are concentrated between 2015–2022, with a peak in 2020 and 2021. Between 2001 and 2003, and in 2005, there were no publications that met the inclusion criteria (Fig. 3 ).

Publication years.

The studies were conducted with the participation of universities and research centres from Mexico (1,8,11,13,14,18,31,34,35,42,46,48,51,58,60,63,67,72,80,84,85), Colombia (3,4,6,10,30,32,44,45,47,53,66,73,84), Brazil (16,17,22,33,39,55,64,65,68,74,75,76,79,86), Argentina (19,21,37,40,56,70,78,82), Chile (26,27,29,52,54), Peru (20,50,71), Uruguay (7,61), Bolivia (5,28), Ecuador (57,81,83,87), Costa Rica (69), Nicaragua (43), the Dominican Republic (9) and Venezuela (36). Collaboration with universities out of the Latin American context came from the USA (5.05%), Canada (2.02%) and Spain, Botswana, New Zealand, Turkey and the United Kingdom (1.01%); although 8,08% does not provide this information.

Theoretical perspectives on digitalisation

Four categories emerged from the analysis (Table 1 ). Each category represents a twofold understanding of digitalisation. Although these understandings are presented as binomials, they make up a continuum, and the articles’ theoretical perspectives lie somewhere along this continuum, sometimes revealing ambiguities. The articles highlight different aspects of these categories, thus showing some of their assumptions and committing to certain understandings of digitalisation. The explanation and discussion of these categories are approached in the next section. In this ‘Results’ section, the studies are classified under these theoretical perspectives, with evidence provided for this classification. Not all the studies are classified under all categories, as some articles focus on only some categories.

A humanistic vs. a capital model of digitalisation

Studies 10,26,27,31,34,36,40,41,50,53,65,68 move away from a capital model of digitalisation toward approaches that do not view it from a cost-benefit perspective. The rationale they present for ICTs access and use is not exclusively that of the homo economicus , linked to a utilitarian approach, although their socio-occupational impact is also acknowledged. Instead, ICT is presented as a realm for the expression and construction of individual identity and its recognition, which is subject to increasing digital mediation, and as a ‘sphere for the production of meaning’ (53, p. 119).

To illustrate this approach, studies 26 and 65 explain that the digital environment plays a role in supporting social and symbolic integration. Study 53 considers that ‘the appropriation of digital technology transcends the mere use of tools, involving a comprehensive process of cultural and social construction and interpretation’ (p. 123). As such, the transmedia context is presented as a scenario for the dynamic production of subjectivity (31,50,53). In this space, according to 31 regarding indigenous peoples—the youth must negotiate the perspectives of their communities of origin and their roots, redefining and reworking the representations of their ethnicity with an openness to the more numerous (in quantity) and heterogeneous (in quality) referents offered by the digital world.

In turn, 27 constructs a theoretical framework based on Sen ( 2000 ), whereby ICTs are conceived as contributing to development understood not only in economic terms but as an increase in people’s capabilities to achieve what they consider valuable. 36 advocates a model of technology in which ‘the social is above the economic’ (p. 714). In this regard, studies 10, 34 and 85 underline the urgent need for innovative moral leadership to connect technology with human development and make technological development sustainable. Similarly, 40 expands the term ‘digital literacy’ from the technical to the political-empowering, thus transcending an instrumental vision.

Study 35 is ambiguously situated within this first classification, as it analyzes the contribution of digitalisation to the social capital of migrants in different situations, i.e., to the creation of social networks of belonging, broadening the possibilities for their integration. It appears that the authors understand social capital in instrumental terms, referring to the security and support from a network of contacts that can be accessed through ICTs, which helps migrants better adapt to a foreign society.

In turn, in other studies, a capital model of digitalisation can be identified, as they associate this process with the achievement of different benefits of a material or economic kind and, therefore, the digital divide with exclusion from them (1,7,8,18, 20,23,26,33,34,35,39,41,42,47,70,72,73,76,77,85). Exclusion is, indeed, defined as the ‘impossibility of obtaining, leveraging, taking advantage of the benefits generated by ICTs’ (1, p. 94) that affects some population groups. 42 and 47 explain that the digital divide and digital poverty are two perspectives of the same problem: an inadequate distribution of the social gains of digitalisation, which has resulted in the social and educational poverty of certain populations and which has been exacerbated during COVID-19 (33,73,77,85). Study 35 also understands ICTs as ‘enablers and generators of different potential forms of capital’ (p. 63). Nevertheless, ‘benefits’ is sometimes understood in a broad sense, rather than exclusively in relation to the economic perspective.

From a critical perspective on a neoliberal model, 39 discusses capitalist techno-politics, and 47 is suspicious of the neutral conceptions of the digitalisation process, arguing that it is the privileged sectors that benefit from it, while others are excluded. In other words, it is only the former who, ‘by using them [ICTs], achieve a familiarisation that prepares them for the arrival of other new technologies,’ with the result that ‘the knowledge gap between these two segments is increasing’ (47, p. 141). Therefore, left to market forces and without intervention, the digitalisation process (or techno-totalitarianism, as 41 calls it) means that ICTs ‘reproduce and exacerbate social inequalities, becoming instruments for increasing differences and developing new forms of inequality’ (47, pp. 140–141).

A social vs. an individual function of ICTs

At first glance, one might expect a humanistic model to be associated with social dynamics or a social function of technology. In contrast, the capital model would be related to an individualist-instrumentalist perspective, i.e., understanding ICTs for the satisfaction of individual interests. However, this correlation is not always present in the analysed studies. Given their focus on disadvantaged populations, there is an emphasis on satisfying basic individual needs that facilitate a dignified life. Many of the articles that align more closely with a humanistic model of digitalisation explore how ICTs can be used to improve lives affected by poverty, starting with their most urgent individual needs (e.g., labour inclusion, integration in the case of emigration). Despite this, these studies assume that it is precisely the social aspect of ICTs (their capacity for connectivity, collaboration and the expression and recognition of identity) that contributes to advancing the life projects of the poorest, as opposed to purely consumerist or individual entertainment uses.

In this regard, these studies emphasise the risk of educational policies that focus narrowly on extending access to technologies, making them universal, namely: that the type of use that is ultimately made of them is limited to consumption, to the satisfaction of individual desires, which are sociologically and economically generated and can be manipulated. Thus, as 51 argues, it is possible to ‘achieve universal access without bringing about social change’ (p. 275) or, even worse, create greater inequality. To counteract this tendency observed in the digitalisation process, it is deemed necessary to adopt a ‘social vision of ICTs’, which is endorsed by articles 7,29,36,37,38,43,45,50,55,63,65,68,72,79. It means cultivating an appropriation of them for (universal) human development. In other words, students should become critical digital prosumers (37), to understand the technological process rather than merely being affected by it (55). This requires deep appropriation processes involving a range of differentiated activities that go beyond communicational and recreational uses to include informational, content creation, e-government and occupational uses. Engaging in this wide spectrum of activities requires accessing the Internet not only via mobile devices but also via computers, as the access device impacts the degree of development of digital competencies, as noted by study 29.

Study 63 presents examples of the social role that ICT can play in the political Latin American context through the various initiatives of the civic organisation Coding Mexico : App115 or Overthrowing the Mexican Tech Mafia, Explaining the Law, and Civic Challenges, among others. 45 describes the ‘ Kioscos vive digital ’ project intended to strengthen rural Colombian communities, while 50 sees the possibility of integrating ICTs into the cultural and social identity of indigenous groups for their own purposes as a community. These are examples of how to place digital technologies at the service of social inclusion and citizen empowerment, while also transcending a consumerist and passive use of them. Studies 36 and 43 also advocate a social approach to science and technology, but 47 expresses a discouraging vision: ‘As we move forward in… economics and technology, we move backward socially’ (p. 141).

A sociocultural vs. an individualist perspective on digitalisation

A sociocultural perspective on digitalisation, as opposed to an individual-focused perspective, is particularly prominent in studies 7,19,26,27,34,85, but is also mentioned in studies 4,21,25,40,49,58,68 as being key to the success of educational policies. According to these studies, adopting digital technologies does not result from a purely personal or individual decision once it becomes possible, but rather depends on contextual and sociocultural factors. In other words, even when the necessary conditions for adopting technology (objective material conditions such as infrastructure and connection, and subjective individual conditions such as personal competence) are met, there is no guarantee that technology will be adopted and, consequently, the digital divide may persist.

This challenges the notion that people adopt technology spontaneously, as soon as they are able to, purely as an exercise of individual freedom. In other words, even if they have the capability, they do not automatically desire to do so. This decision depends on contextual factors that shape the social perception and assessment of technology. These factors influence people’s attitudes and dispositions, such as openness to innovations or suspicion and distrust, thereby affecting their willingness to adopt technology, as 27 explains. There are thus vulnerable contexts with specific problems that make it difficult for young people to adopt certain uses of technology and develop the associated competencies. For example, the negative cultural connotation in border areas (8), the culture of rural versus urban areas, or being a victim of a conflict, as in Colombia (76), all represent barriers to adoption.

In this line, 25 analyses the causes of the low demand for ICTs among rural populations and finds out it has to do with an ‘insufficient awareness of the opportunities’ offered by technologies, which ‘reduced the potential success of the provision of infrastructure’ (p. 247). This points to the need for a bottom-up strategy that facilitates co-management and participation in highly marginalised contexts, listening to the voices and needs of stakeholders, along with education for the ongoing acquisition of ICT skills, the development and maintenance of infrastructure and the adoption of appropriate technologies.

Freedom to choose must, therefore, be understood in relation to a context rather than in a disembodied way, and this context is particularly important in the case of disadvantaged and isolated communities. To support this idea theoretically, 34 refers to Nussbaum’s ( 2011 ) theory of capabilities and, like 73, to Sen ( 2000 ): these capabilities are developed to varying degrees depending on the conditions of the context. In turn, studies 4 and 27 rely on Giddens’ Structuration Theory, according to which individuals have agency, but it is limited by the social structures that are reinforced and reproduced through collective action. Study 4 also underlines the importance of this sociocultural level by using the theoretical framework of ‘symbolic interactionism’: the interaction between subjects and, therefore, the culture they produce shapes the discourses justifying digitalisation, which act as mediators for individual interpretation. 49 emphasises the role this worldview plays in grounding the right to digital inclusion, as the demand for this right arises from a specific context defined by certain praxis and needs, which differ from those of other contexts. Therefore, according to the author, justification processes are relative to a given context and do not have so much to do with ‘the illusion of truth’ (49, p. 50), following Rorty.

In these studies, the influence of culture and community is manifested through the mediation of key community figures, who act as gatekeepers and facilitate the socialisation of technology: teachers (19,26,28,37,40,57,85), those responsible for access points (31) and, in isolated and aging populations, young people (8,21,26) play crucial roles in transmitting social values associated with technology, shaping perceptions of its usefulness, and setting expectations for its use. If this is the case, strictly speaking, ‘policies are not implemented; instead, the political text is subject to modifications and is reinterpreted by the central subjects of that practice’ (19, p. 101). In this regard, 39 adopts the critical perspective of the Frankfurt School (Adorno and Horkheimer, 2007 ) to analyse the emancipatory resistance to the technological cultural industry, which apparently seeks digital inclusion as an instrument of capitalist domination.

This mediation is particularly significant in the case of teachers, who are responsible for implementing educational policies for digital inclusion. Their influence on promoting a culture favourable to the appropriation of ICTs is acknowledged. For instance, 26 correlates technological appropriation by students (measured in terms of use and access) with teachers’ skills, frequency of access and expectations concerning the social and educational impact of the Internet. In its study of Argentine teachers in vulnerable schools, study 37 also concludes that they must become the driving force behind their students’ autonomous learning in the digital context. In Mexico, study 85 reveals that in the absence of government support, most teachers in rural schools take responsibility for their students’ digital learning. 20 also argues that technology ‘is wasted without the commitment from this educational actor’ (p. 49).

This emphasis on context should not diminish personal responsibility for adopting a critical perspective on both digitalisation and the culture that promotes it in specific ways. As 4 emphasises, practice ‘occurs within a temporal order’ (trajectory) and ‘a spatial order’ (framework) (p. 4), which influence action but do not determine it, as they are mediated by an interpretative process. Some studies advocate these internal factors of critical thinking and creativity as being crucial to civic and critical digital literacy (4,39,41,70), enabling individuals to make innovative or unprecedented uses of technology.

A liberal-proceduralist vs. a communitarian-substantialist model of digitalisation

It is possible to identify a liberal view of digitalisation in some of the studies, in which the digital space appears as a new means to exercise freedoms for individual self-determination. In this view, the emphasis is on removing (external) obstacles rather than on promoting specific uses of ICT for pursuing life projects deemed valuable, as such moral assessments are considered to belong to the private sphere (1,19,28,33,36,50,53,67,77). In this liberal perspective, ICTs are presented in their indeterminacy, as means, as open realities: as 36 indicates, ‘processes to be developed’ (p. 711), something to be done, not yet established or accomplished: ‘They are only a means, not an end in and of themselves’ (p. 713). Study 53 also understands them as ‘mediations’ whose valence is yet to be determined.

The emphasis on external factors—and, therefore, on the obstacles faced—is typical of the liberal perspective: high cost, lack of infrastructure, and limited training are the most recurrent themes in relation to the poorest populations—1,33,50,67,77—, including indigenous groups—1,50—and teachers in disadvantaged contexts—19,28—. For example, study 19 highlights the lack of adequate teacher training—a deficiency that became evident during the pandemic—and argues that the educational policies implemented have not created the minimum conditions necessary for teachers to use technological equipment effectively; then, ‘without warning, without training, without Internet, there is chaos in the school dynamics’ (19, p. 111). It is akin to ‘having cars and highways and not being able to drive because one does not know how’ (67, p. 101). Study 67 also points to the high costs of the Internet, which limit access, as well as the existence of more urgent realities (‘11.3% of Mexican households do not have potable water. Almost half of the households in towns with less than 2500 inhabitants use firewood or charcoal for cooking,’ and it is thus necessary to ‘close other gaps… to bridge the digital divide’ (p. 100)). A similar situation is reported by 65 in Brazil with the construction of telecenters, without first addressing the socioeconomic precarity of excluded youth.

However, other studies highlight a problem characteristic of modern societies: after rights and freedoms have been secured and barriers to access and training have been removed, the use of ICT often remains passive, instrumental and decontextualised; technology is not leveraged to enhance the individual’s personal life project. This problem is also found in developing societies, where Internet access is increasingly universal due to mobile devices. In this case, the obstacles are not external but internal, involving the challenge of making innovative use of ICTs that contribute to personal life projects.

Accordingly, from a communitarian perspective studies 4,7,19,20,27,29,30,40,45,47,63 and 70 advocate for viewing the user as an agent focused on specific goals and actively using technology to achieve them, rather than as a mere recipient of existing services. Based on this sense of agency and by relating technology appropriation to specific practices, these studies define technological appropriation as inherently tied to these practices. As 47 argues, discussing digital literacy requires reflecting on the goals, goods and values to which individuals aspire, transcending—as 27,40 and 70 indicate—an instrumental-proceduralist perspective. Study 19 also criticises the flaw of educational digital policies where ‘the focus is on the means rather than on the content’ (p. 110). Furthermore, 4 and 70 note that ‘it is not possible to speak about generalised uses of ICTs; social actors must make their own approach, as it is particular needs that determine appropriation processes’ (4, n.p.); in other words, a ‘situational approach’ is necessary (70, p. 103). In education, this means that it is necessary to ‘turn how each disciplinary field produces knowledge, carries out research and operates in an interweaving with technologies into a teaching object’ (70, p. 104). Therefore, the twofold dimension of abstention and provision involved in the right to digital inclusion (49) requires a concrete, specific provision focused on each of the actors and their particular aims for social transformation.

A growing interest in the most vulnerable

The analysis of the contextual characteristics of the studies demonstrates a substantial increase in publications on the digitalisation of Latin American communities in vulnerable conditions over the last decade, with a peak between 2020–2022 related to the effects of the pandemic on impoverished populations. The health crisis has served as a catalyst to reveal the digital inequality that particularly affects Latin America (Levi, 2021 ). Until COVID-19, the abundant bibliography on digitalisation and digital education stood in stark contrast to the limited research explicitly focused on analysing this process among the most vulnerable, who can be found in different contexts—rural, urban and border. This has been changing over the last decade and, ultimately, following the pandemic, when it is precisely the poorest sector of the population that has attracted the attention of researchers, not only in the international context (Mkhize and Davids, 2021 ; Noor et al., 2020 ; Reuge et al., 2021 ) but also in Latin America.

An incipient humanistic turn of the digitalisation process

Concerning the theoretical perspectives of the studies, the first category that emerged in the analysis identifies the ultimate aims (humanistic or capital-related (Regmi, 2015 )) attributed to digitalisation (Fig. 4 ). These aims to establish a horizon of meaning for it and reveal the assumptions and sociohistorical perspectives from which technology is viewed, enabling—and limiting—its potential to advance human development at a given time and place.

Aims attributed to digitalisation: From capital to humanistic models of digitalisation.

For Regmi ( 2015 ), the capital model views digitalisation as an ‘investment through which individuals, corporations and nations can maximise their economic growth’ (p. 134). This model is grounded on the theory of human capital, which, from a neoliberal approach, is based on three assumptions: competitiveness through the maximisation of individual freedom; privatisation (knowledge is understood as a private good); and human capital formation for the economic prosperity of the individual and her nation. Critics argue that this model has created ‘a narrow, market-based conception of education, skill and talent through which agents of neoliberal globalisation have benefited’ (Regmi, 2015 , p. 140).

In contrast, the humanistic model links digitalisation not only to economic growth but to the full development of the individual and the good of communities, connecting it to a social agenda pursuing justice and respect for human rights. This model is based on three assumptions: civic education (to foster active citizenship), building social capital (collaboration, coordination and cooperation) and improving capabilities for human development (Valdivia et al., 2021 ).

In the analysed papers, the capital perspective is present, since, for the populations living in vulnerable conditions, satisfying basic needs requires different types of capital that can be more efficiently accessed digitally. Nevertheless, the overall tone of the studies points in a different direction, suggesting a humanistic turn of technology. This aligns with recent studies (Henríquez, 2021 ; Loh and Chib, 2022 ; López-García, 2020 ), where the primary objectives of technology are improving relationships and nurturing common interests to provide humanly meaningful use of ICTs. This implies that the objectives attributed to them are not purely utilitarian, but involve expressive aims of human nature, which give them an intrinsic sense of purpose: they open up opportunities for the exercise of creativity and the expression and recognition of personal identity.

Indeed, many studies acknowledge that a mere instrumentalist perspective on technology fails to consider it appropriately and needs to be transcended. Thus, in the humanistic approach, ICTs are considered a field for imagination and human originality and, consequently, related to the individual goals that are desired. Instead of replicating already established uses, technology appropriation involves constructing one’s own representations and narratives that are often alternative, or at least complementary, to the hegemonic discourse. This is a way to ‘ “talk back” to structures of power that have erased or distorted [some people’s] interests and realities’, and resist an external imposition of identity, i.e., the reproduction of ‘images that are produced [and attributed] from the outside’ (31, p. 267). Therefore, those studies highlight the key role that ICTs play in contemporary processes of subjectivization, as a new ‘public space in which some fragments of identities are shared’ (31, p. 266) while they are being constructed.

From the satisfaction of ‘individuality’ to the cultivation of ‘personhood’: the social role of digitalisation

If the first category points to the fundamental aims attributed to digitalisation, the second focuses on the dynamics generated by it, i.e., how these aims are operationalised in everyday life (Fig. 5 ). In particular, the second category looks into the following question: does digitalisation contribute to advancing individualism and the fragmenting tendency characteristic of modern liberal societies (Bauman and Bordoni, 2016 ; Gozálvez-Pérez, 2011 ; Taylor, 2016 )? Or, on the contrary, does it counteract the atomism and disintegrative inclination of societies and facilitate the development of a sense of community, communication and belonging that contemporary physical communities are unable to confer (Keane et al., 2016 )? This is particularly important in the case of disadvantaged populations, who are usually marginalised and sometimes spatially isolated, and would undoubtedly benefit from (digital) solidarity structures. It is these structures, when institutionalised, that ensure that the common good is indeed common and that rights are universal, without becoming privileges (Aznar, 2019 ; Ellacuría, 1990b ).

The operationalisation of fundamental aims: From individual to social functions of digitalisation in everyday life.

Following Maritain’s ( 1984 ) distinction, it can be asked whether the selected studies present the digital space as a community of individuals or a community of persons; in other words, whether digitalisation is oriented toward the satisfaction of ‘individuality’ or the cultivation of ‘personhood,’ understanding that only the latter includes the possibility of fellowship. Only in the case of the latter does the digital environment represent a realm of empathy (Rifkin, 2009 ), of friendly relationality—both in the conventional sense of the word and in the civic sense of friendship (Nussbaum, 2014 ), where the good of the other is sought for its own sake rather than solely to obtain some return. When connected to the development of personhood, the social function of ICT is highlighted and thus the participation of everyone in it as a common good and for the common good, as opposed to passive-consumerist uses, such as the individual consumption of content or its production for the individual satisfaction of ‘citizens who accept the political and economic structures’ instead of exercising ‘active citizenship to bring about “political, economic, and social improvements” ’ (Regmi, 2015 , p. 141).

Gozálvez-Pérez ( 2011 ) warns against the risk of ‘digital endogamy’ that ICT may pose, a form of individualism that threatens democracy. In this regard, 65 draws on Freire ( 1994 ) to argue that the appropriation of technology should contribute to strengthening social ties, to ‘being more in communion with other consciousnesses’ (p. 27), rather than simply having more—which would reify relationships and people.

The role of culture in digital appropriation

Regarding the third category of the sociocultural and individual factors affecting digitalisation (Fig. 6 ), most studies suggest that the decision to adopt ICTs depends not only on political-economic material factors (infrastructure, connection) and individual subjective factors (digital competence). While these are necessary conditions, it is also essential to have a culture conducive to ICTs that places a positive value on them and integrates them into daily activity.

The factors affecting digitalisation: From individualist to sociocultural perspectives.

Many of the reviewed studies highlight that the adoption of ICTs is mediated by the group (its dynamics, hierarchy of values and practices), and consequently, for a digitalisation policy to be effective, it must affect this culture. This involves bringing about the ‘domestication of technology’ (35), or what 4 calls the ‘social’—as distinct from the individual—appropriation of it, by including it in the culture’s spaces, times, aesthetics and functioning. Then, the integration of ICTs into communities ‘should not only involve training activities but also actions that incorporate mechanisms for constructing and negotiating the expectations that communities themselves have regarding the Internet’ (26, p. 581). The key role of culture is related to meaning (Barón and Gómez, 2012 ; Fuentes, 2015 ; Paulhiac and Ortega, 2019 ). This points to the complexity of the multifactorial—not only economic, political, technological, or even cognitive, but also social and cultural—and multidimensional—access, use, appropriation—phenomenon of digital inclusion, which should be mirrored in its educational approach.

The sociocultural perspective on digitalisation is based on a social learning theory (Bandura and Walters, 1977 ), according to which people learn from one another (through observation, imitation and modelling). Thus, individuals gain an understanding of ICTs and the purposes they can serve through everyday interactions with others. As MacIntyre ( 1987 ) indicates, personal identity, and therefore freedom, is constructed based on connections with others, i.e., on the horizon provided by inclusion in a context. Recognising this cultural construction involves acknowledging its historical and evolving nature, as opposed to the ahistorical and apparently neutral—nonpolitical—nature of the individualistic perspective.

The influence of culture explains, at least in part, the persistence of the digital divide in subcultures such as indigenous communities. The characteristics of some places (geographically isolated), their population (aging), the economic activity carried out, as well as gender and literacy levels, are conditions that make it difficult for inhabitants to be exposed to external and heterogeneous references that include ICTs in their worldview. Consequently, their relevance and usefulness are not easily perceived. Although there are differences, something similar occurs with other population groups, such as the elderly, whose symbolic and cultural reality does not include ICTs but prioritises other values (e.g., face-to-face communication), and these cultural factors act as a barrier to digital inclusion. The same occurs in border populations, where the cultural connotations of the context (violence, police control and labour exploitation) hinder technological adoption.

Studies that focus exclusively on the lack of personal competence or the physical impossibility of access seem to assume that once the external obstacles limiting the use of ICTs have been overcome, i.e., given the objective conditions of access and connection and given the ability to use ICTs, adoption is a natural, spontaneous, immediate or automatic process, such that if a person can, they will. While this is true in many cases, it is so precisely because there are contextual factors that shape a culture or a symbolic imaginary aligned with the values associated with technology (immediacy, productivity, competitiveness, quantity/amplitude versus depth), which encourage adoption by positively representing digitalisation. Although its associated dangers and risks are also perceived, it is ultimately understood that the strengths and opportunities offered by digitalisation outweigh them.

The need to consider cultural elements in the design of public educational policies should not dilute the fundamental personal responsibility of becoming a digital citizen rather than merely a subject (Cortina, 2001 ). This entails, firstly, adopting a critical view of digitalisation as it is presented in each culture (as well as of the opposing conservative technophobic view) and, secondly, using ICTs not merely as passive consumers limited to receiving what is available in the environment, but rather as active producers seeking new uses that help transcend the current state of affairs. Although social contextual values influence desires, perceptions and assessments of reality, including ICTs, these cultural values do not determine them. Therefore, digital literacy must therefore be civic and critical, aimed at performing a ‘reading of resistance’ (Umaña, 2021 ; Walton, 2012 ) of the discourses in which digitalisation is presented as well as of the reality it affects. In this regard, Rivoir and Escuder ( 2021 ) warn that even being a ‘digital native’ does not ensure this appropriation, as, without motivation and sufficient skills, superficial recreational use of ICTs is perpetuated, which at most contributes to social integration.

From indeterminate ICTs in generalist training programmes to a communitarian-substantialist approach based on goods

The final category contrasts a liberal-proceduralist and a communitarian-substantialist approach to digitalisation (Fig. 7 ).

The politics of digitalisation: from liberal-procedimentalist to communitarian-substantialist approaches.

From the liberal perspective, the virtual environment is seen as another realm for exercising individual freedom, provided that the rights and freedoms of others are respected. Digital exclusion, in turn, is understood as a loss of negative liberties, as a reduction in a person’s sphere of action due to external impediments (lack of infrastructure, connection, training). Consequently, the liberal perspective focuses on eliminating these external obstacles, rather than promoting specific uses of ICTs for a life project considered good or valuable. In other words, it emphasises what ‘can’ be done (negative liberty) rather than the goods worth pursuing (positive liberty) (Carter, 2010 ), thus adopting an external perspective of ICT instead of addressing internal factors. This liberal view aligns with the procedural perspective of ICTs, which focuses on rights, as opposed to a substantialist conception that recognises certain goods and aspires to pursue them (Díaz and Barrientos, 2019 ; Sandia et al., 2019 ).

The liberal model acknowledges the substantial recognition of only two goods in relation to technology: (1) freedom of access to and use of ICTs, without specifying which uses are better than others (this question is left up to the private assessment of the individual); and (2) ICTs themselves. ICTs are recognised as a good (the fundamental axis of the digital knowledge society), as they provide an additional realm for exercising individual freedom alongside the physical one. Thus, ICTs appear as a means (to exercise freedoms) and as a right, and their absence implies a reduction in freedom. Insofar as they are not directed to specific objectives, because these are excluded from the public-political realm in the liberal model, ICTs are presented in an indeterminate manner, not directed toward any particular goal. They are not associated with the attainment of specific goods that would represent the good life, except for the fundamental values of freedom and nonviolence, which are the only substantive commitments of liberalism.

This liberal perspective on ICTs can be identified in some of the selected studies when they discuss appropriation without specifying its aims, purposes, and objectives. However, these factors should determine the appropriation process, as using technology for one purpose is not the same as using it for another. In response to this, many studies argue for the need to contextualise, specify and determine the objectives of technologies. Appropriation should be considered relative to specific functions, realities and interests: depending on the pursued goals (such as eradicating poverty, ending violence in a particular educational institution, or steering young people away from criminality through public libraries), technology appropriation takes on different meanings. It is then necessary to move away from indeterminate ICTs and generalist training programmes focused solely on tool usage, and instead specify their uses based on individual functions. Consequently, policies should not be formulated from a top-down, ‘technocratic or instrumental perspective’ (70, p. 95) nor should they adopt a purely instructive or means-based approach to technology (Castellar, 2021 ). Rather, they should be designed to empower individuals in their particular activities, based on the needs of specific social actors and their distinctive objectives.

Conclusions

Although largely neglected in the digitalisation process until recent years, Latin American populations living in vulnerable conditions have become the object of growing academic interest, especially since the 2019 pandemic. Public educational policies aimed at digital inclusion have also gained attention over time, recognising digitalisation as a complex multidimensional phenomenon, rather than a purely technological one.

The reviewed studies show that digitalisation is no longer considered solely in terms of access, as access alone does not suffice for development. Instead, the capacity for digital appropriation—based on the context (a key mediator, as Quinones et al. ( 2021 ) point out), and relative to the function or goods pursued—comes into play. This is especially important for those living in vulnerable conditions, given the potentially transformative power of ICTs. Therefore, access and access points are now aimed at fostering meaningful appropriation, tailored to the different purposes or goods pursued by different individuals and communities. As Pick et al. ( 2021 ) conclude in their research, the key point lies in investigating ‘the purposeful uses of ICTs’ (p. 259) in Latin America. This paper has addressed this by examining the theoretical perspectives on digitalisation in the selected studies: the aims toward which digitalisation is directed, the functions it is understood to perform in everyday life, the factors affecting it and the political views influencing it.

The analysis carried out suggests that the symbolic, social, contextual and communitarian approach to digitalisation identified in many of the articles serves as a strong theoretical foundation for advancing development, understood in human and not just economic terms. However, there are some ambivalences in the studies that have been discussed above. For instance, alongside the positive affirmation of individual and local purposes through ICTs, there is also a (negative) liberation process aimed at removing the barriers that continue to seriously affect the digitalisation of the most vulnerable populations in Latin America. In the same vein, the generally accepted focus on social justice and social inclusion characteristic of the humanistic perspective is sometimes overshadowed by a competitive, market-driven view of ICT typical of Western neoliberal societies. Both academics and practitioners should note these ambivalences and emphasise the need to further strengthen a humanistic understanding of technology. This is evident in the recommendations for digital policies which (1) move beyond a purely instrumental interpretation of technologies, (2) assign a social role to them, and (3) adapt to different sociocultural contexts, especially where vulnerable populations are concerned. The prominent role of these groups and (4) the objectives or goods they pursue, both in the design and implementation of the programmes, appear to be the only effective way to achieve their empowerment.

These approaches prove to be more suitable for promoting the social advancement of disadvantaged populations through ICT since they encompass a broader understanding of what is at stake (identity recognition, not just capital; internal self-determination, not just external factors; substantive goods, not just procedural rights). They serve as a better framework for promoting human development in a more holistic way. Consequently, the nexus observed by Pradhan et al. ( 2022 ) between ICT infrastructure and institutional quality should include the perspectives highlighted in these studies, especially when considering vulnerable contexts in the Latin American region.

This paper has offered an overall view of the Latin American region by examining the scientific articles published on digitalisation and poverty in the last 22 years in it. Theoretical reviews or metatheories contribute to scientific research and policy-making because they draw attention to how theoretical approaches are built, substantiated and justified and enable the identification of ambivalences and conceptual confusion, which could impact methods and decision-making.

However, a significant limitation of this study is that, although it offers a valuable general overview of Latin America, this broad perspective does not capture the unique contexts and specific challenges of individual countries. Additionally, a methodological constraint of this study is that only articles with a focus on education have been considered to limit the scope of the research, but there might be other fields of study that approach the digitalisation of populations in vulnerable conditions in the region, which are also relevant for the understanding of the topic and the theoretical assumptions underpinning digitalisation.

Finally, the cultural perspective of the researchers might influence the interpretation and discussion of the results, as well as the categories identified regarding the theoretical perspectives on digitalisation and the specific digital needs of the culturally diverse populations living in vulnerable conditions in Latin America, given the continent’s great cultural diversity.

Future studies should focus on detailed country-specific analyses within Latin America to uncover local nuances and provide tailored insights into the digitalisation of the most disadvantaged in the various kinds of contexts they inhabit. This approach will help to better understand the unique circumstances and challenges faced by individual countries. The overview presented of the theoretical perspectives from which digitalisation is conceived in Latin America in relation to the human development of the most vulnerable can serve as a framework for this purpose.

Data availability

The list of the 87 primary documents used for this theoretical review can be found in Annex 1 and has been uploaded as supplementary material. The database search strings used can be seen in Fig. 1 .

Adorno T, Horkheimer M (2007) Dialectic of enlightenment. Akal, Madrid

Google Scholar

Allana S, Clark A (2018) Applying meta-theory to qualitative and mixed-methods research. Int J Qual Methods 17:1–9. https://doi.org/10.1177/1609406918790042

Article Google Scholar

Aznar J (2019) Bienestar y Salud Social. In: Pérez AdánJ (ed.) Economía y salud social. Más allá del capitalismo. Eunsa, Pamplona, pp. 287–308

Bandura A, Walters RH (1977) Aprendizaje Social y Desarrollo de la Personalidad. Alianza, Madrid

Barón L, Gómez R (2012) Perceptions of connectedness: public access computing and social inclusion in Colombia. Anuario Electr ónico de Estudios en Comunicación Soc 5(1):6, http://erevistas.saber.ula.ve/index.php/Disertaciones/issue/view/136/showToc

Bauman Z, Bordoni C (2016) State of crisis. Paidós, Barcelona

Bingham AJ, Witkowsky P (2022) Deductive and inductive approaches to qualitative data analysis. In: Vanover C, et al., (eds.) Analyzing and interpreting qualitative data. SAGE, New York, pp. 133–146

Camilli C, Römer M (2017) Metasíntesis en alfabetización para el empoderamiento de grupos vulnerables. Comunicar 53:9–18. https://doi.org/10.3916/C53-2017-01

Campbell M, Egan M, Lorenc T et al. (2014) Considering methodological options for reviews of theory: illustrated by a review of theories linking income and health. Syst Rev 3:114. https://doi.org/10.1186/2046-4053-3-114

Article PubMed PubMed Central Google Scholar

Carter I (2010) Positive and negative liberty. Rev Internacional de Filos ía 10:15–35. https://plato.stanford.edu/entries/liberty-positive-negative/

Castellar E (2021) Challenge of educational policies: a historical look at the inclusion of ICT in some Latin American countries. EDUCA. Revista internacional para la calidad educativa 53-72. https://revistaeduca.org/index.php/educa/article/view/16/10

CEPAL (2022) Panorama Social de América Latina, 2021. Cepal, Santiago

Cortina A (2001) Ciudadanía económica cosmopolita. El País, Madrid

Díaz B, Barrientos M (2019) The appropriation of virtual education by social collectives: the new relations between technology, knowledge and social. Rev Brasileira de Educ çao do Campo 4:1–15. https://doi.org/10.20873/uft.rbec.e6908

Ellacuría I (1990b) Historización de los DD.HH. desde los pueblos oprimidos y las mayorías populares. In: Insausti X, Aguirre JM, Martínez JM eds Pensamiento crítico, ética y absoluto. Eset, Vitoria, pp. 147–158. (coords.)

Ellacuría I (1990a) Filosofía de la realidad histórica. UCA

Espinosa Z (2022) Problem-based service learning (PB-SL): constructing a pedagogy of poverty based on Ignacio Ellacuría. Educ Philos Theory 54(14):2446–2457. https://doi.org/10.1080/00131857.2021.1993823

Freire P (1994) Letters to Cristina. Paz e Terra, Säo Paulo

Fuentes MC (2015) Unconventional training in cybercafés: a conceptual scaffolding. Polis Investig Y Análisis Sociopolítico y Psicosoc 11(2):151–185. https://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1870-23332015000200151

Gascó-Hernández M, Equiza-López F, Acevedo-Ruiz M (2006) Digital opportunities, equity, and poverty in Latin America. In: Cecchini S (ed.) ICTs and human development. IGI Global, Hershey, p 1–22. (coord.)

González-Zabala M, Polo C, Galvis-Lista E (2018) Identification of information technology tools for the inclusion of people in condition of extreme poverty. EATIS’18 16:1–5. https://doi.org/10.1145/3293614.3298782

Gozálvez-Pérez V (2011) Education for democratic citizenship in a digital culture. Comunicar 36:131–138. https://doi.org/10.3916/C36-2011-03-04

Helsper EJ, Smahel D (2020) Excessive Internet use by young Europeans: Psychological vulnerability and digital literacy? Commun Soc 23(9):1255–1273. https://doi.org/10.1080/1369118X.2018.1563203

Henríquez JA (2021) Digital hospitality: a concept for the education of the 21st Century. EDU Rev 9(1):55–65. https://doi.org/10.37467/gka-revedu.v9.2839

Herrero-Diz P, Ramos-Serrano M, Nó J (2016) Minors as creators in the digital age: From prosumer to collaborative creator. Theoretical review 1972-2016. Rev Lat de Comunicacion Soc 71:1301–1322. https://doi.org/10.4185/RLCS-2016-1147en

Higgins JPT, Thomas J, Chandler J et al. (2022) Cochrane Handbook for Systematic Reviews of Interventions 6.3. Cochrane. www.training.cochrane.org/handbook

Keane T, Keane WF, Blicblau AS (2016) Beyond traditional literacy: learning and transformative practices using ICT. Educ Inf Technol 21(4):769–781. https://doi.org/10.1007/s10639-014-9353-5

Levi GE (2021) Los desafíos que deja la pandemia. Telos 117:80–84. https://telos.fundaciontelefonica.com/telos-117-cuaderno-fronteras-gabriel-e-levy-los-desafios-que-deja-la-pandemia/

Loh YA, Chib A (2022) Reconsidering the digital divide: an analytical framework from access to appropriation. Inf Technol People 5(2):647–676. https://doi.org/10.1108/ITP-09-2019-0505

López-García H (2020) Cuban society on the horizon of digital transformation: a view from mediations to the social appropriation of technology. Int J Cuba Stud 12(1):119–134. https://doi.org/10.13169/intejcubastud.12.1.0119

López-Núñez JA, Campos-Soto MN, Díaz IA et al. (2022) Digital competence of the teaching staff to attend to students with learning difficulties. A theoretical review. Rev Electr ónica Interuniversitaria de Form ón del Profr 23(2):143–154. https://doi.org/10.6018/reifop.419171

MacIntyre A (1987) After virtue: a study in moral theory. Crítica, Barcelona

Maritain J (1984) Para una filosofía de la persona humana. Club de lectores, Madrid

Martínez-Bravo MC, Sádaba-Chalezquer C, Serrano-Puche J (2020) Fifty years of digital literacy studies. Profesional de la Inf ón 29(4):1–15. https://doi.org/10.3145/epi.2020.jul.28

Martino F, Spoto A (2006) Social network analysis: a brief theoretical review and further perspectives in the study of information technology. PsychNology J 4(1):53–86. http://www.psychnology.org/index.php?page=psychnology-journal-volume-4-number-1

Mkhize TR, Davids MN (2021) Towards a digital resource mobilisation approach for digital inclusion during COVID-19 and beyond. Educ Res Soc Change 10(2):18–32. https://doi.org/10.17159/2221-4070/2021/v10i2a2

Ngwenyama O, Morawczynski O (2009) Factors affecting ICT expansion in emerging economies: an analysis of ICT infrastructure expansion in five Latin American countries. International. Technol Dev 15(4):237–258. https://doi.org/10.1002/itdj.20128

Nicholas D, Globerman J, Antle B et al. (2006) Processes of meta-study. lnt J Qual Methods 5:1–10. https://doi.org/10.1177/160940690600500105

Noor S, Isa FM, Mazhar FF (2020) Online teaching practices during the COVID-19 pandemic. Educ Process: Int J 9(3):169–184. https://doi.org/10.22521/edupij.2020.93.4

Nussbaum MC (2011) Creating capabilities: the human development approach. Belknap Press, Cambridge

Book Google Scholar

Nussbaum MC (2014) Cultivating humanity: a classical defense of reform in liberal education. Harvard University Press, Cambridge

Page MJ, McKenzie JE, Bossuyt PM et al. (2021) The PRISMA 2020 statement. BMJ 372(71):1–9. https://doi.org/10.1136/bmj.n71

Paterson BL, Thorne SE, Canam C et al. (2001) Meta-study of qualitative health research: a practical guide to meta-analysis and meta-synthesis. SAGE, London

Paulhiac JC, Ortega AJ (2019) Use and appropriation of ICTs: An exploration of access to cyber cafés and Kioskos Vive Digital in rural communities. Análisis: Rev Colombiana de Humanidades 95:289–318. https://doi.org/10.15332/21459169.4456

Pick J, Sarkar A, Parrish E (2021) The Latin American and Caribbean digital divide: a geospatial and multivariate analysis. Inf Technol Dev 27(2):235–262. https://doi.org/10.1080/02681102.2020.1805398

Pick JB, García-Murillo M, Navarrete CJ (2007) Information technology research in Latin America. Inf Technol Dev 13(3):207–216

Pradhan RP, Arvin MB, Nair M et al. (2022) Institutional development in an information-driven economy: can ICTs enhance economic growth for low- and lower middle-income countries? Inf Technol Dev 28(3):468–487. https://doi.org/10.1080/02681102.2022.2051417

Prestwich A, Sniehotta FF, Whittington C et al. (2014) Does theory influence the effectiveness of health behavior interventions? Meta-analysis. Health Psychol 33:465–474. https://doi.org/10.1037/a0032853

Article PubMed Google Scholar

Quinones G, Heeks R, Nicholson B (2021) Embeddedness of digital start-ups in development contexts: field experience from Latin America. Inf Technol Dev 27(2):171–190. https://doi.org/10.1080/02681102.2020.1779638

Regmi KD (2015) Lifelong learning: foundational models, underlying assumptions and critiques. Int Rev Educ 61(2):133–151. https://doi.org/10.1007/s11159-015-9480-2

Reuge N, Jenkins R, Brossard M et al. (2021) Education response to COVID 19 pandemic. Int J Educ Dev 87:1–4. https://doi.org/10.1016/j.ijedudev.2021.102485

Rifkin J (2009) The empathic civilization: the race to global consciousness in a world in crisis. Paidós, Barcelona

Rivoir AL, Escuder S (2021) Digital inequality and Internet uses in public telecentres: dilemmas and challenges of Digital Inclusion Spaces in Uruguay. Informatio 26(1):246–279. https://doi.org/10.35643/Info.26.1.13

Sandia BE, Luzardo M, Aguilar-Jiménez AS (2019) Appropriation of ICT as Generators of Educational Innovations. Cienc Docencia y Tecnol ía 30(58):267–89. https://doi.org/10.33255/3058/413

Sen A (2000) Development as freedom. Anchor, Barcelona

Solorio I, Guzmán J, Guzmán I (2023) Participatory decision-making in the policy integration process: indigenous consultation and sustainable development in Mexico. Policy Sci 56:115–140. https://doi.org/10.1007/s11077-022-09487-x

Stratton C, Nemer D (2020) ICTD research in Latin America: literature review, scholar feedback, and recommendations. Inf Technol Dev 26(4):692–710. https://doi.org/10.1080/02681102.2019.1701970

Taylor CH (2016) The ethics of authenticity. Paidós, Barcelona

Thorne S, Jensen L, Kearney MH et al. (2004) Qualitative metasynthesis: reflections on methodological orientation and ideological agenda. Qual Health Res 14(10):1342–1365. https://doi.org/10.1177/1049732304269888

Umaña MJ (2021) Social development and digital policy. Contradictions present in the school. Aularia Rev Digital de Comunicación 1:29–34. http://hdl.handle.net/10272/19179

Valdivia P, Sepúlveda P, Chávez V (2021) Social capital as a foundation for community development: the experience of the telecentre network in the Peruvian jungle. Rev de Educación Soc 32:225–243. https://eduso.net/res/revista/32/el-tema-revisiones/el-capital-social-como-fundamento-para-el-desarrollo-comunitario-la-experiencia-de-la-red-de-telecentros-en-la-selva-peruana

Walton E (2012) Using Literature as a Strategy to Promote Inclusivity in High School Classrooms. Intervention Sch Clin 47(4):224–233. https://doi.org/10.1177/1053451211424604

World Bank (2021) Recovering growth rebuilding dynamic post-COVID-19 economies amid fiscal constraints. World Bank, Washington

Zubiri X (1995) Estructura dinámica de la realidad [The dynamic structure of reality]. Alianza, Madrid

Download references

Acknowledgements

This piece of research was supported by the Andalusian Agency of International Cooperation for Development (Spain) as part of the project “La digitalización en poblaciones desfavorecidas de República Dominicana para contribuir a su desarrollo digital en el contexto de los ODS y el COVID-19: líneas de acción para las agencias de desarrollo y metodología innovadora para investigar la digitalización en el Sur global. Convocatoria Universidades AACID 2020”.

Author information

Authors and affiliations.

Department of Education, Universidad Internacional de La Rioja (UNIR), Logroño, Spain

Jesús Plaza de la Hoz

Department of Humanities and Philosophy, Loyola University, Córdoba, Spain

Zaida Espinosa Zárate

Department of Education, Universidad Complutense de Madrid, Madrid, Spain

Celia Camilli Trujillo

You can also search for this author in PubMed Google Scholar

Contributions

Jesús Plaza de la Hoz: writing original draft, review; Zaida Espinosa Zárate: conceptualisation, writing original draft, review; Celia Camilli Trujillo: methodology, review.

Corresponding author

Correspondence to Jesús Plaza de la Hoz .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Ethical approval

Ethical approval was not required as the study did not involve human participants.

Informed consent

Informed consent was not required as the study did not involve human participants.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Annex 1 list of the 87 source documents, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Plaza de la Hoz, J., Espinosa Zárate, Z. & Camilli Trujillo, C. Digitalisation and poverty in Latin America: a theoretical review with a focus on education. Humanit Soc Sci Commun 11 , 1194 (2024). https://doi.org/10.1057/s41599-024-03692-0

Download citation

Received : 03 May 2024

Accepted : 30 August 2024

Published : 13 September 2024

DOI : https://doi.org/10.1057/s41599-024-03692-0

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

Explore articles by subject
Guide to authors
Editorial policies

Mental health effects of poverty, hunger, and homelessness on children and teens

Rising inflation and an uncertain economy are deeply affecting the lives of millions of Americans, particularly those living in low-income communities. It may seem impossible for a family of four to survive on just over $27,000 per year or a single person on just over $15,000, but that’s what millions of people do everyday in the United States. Approximately 37.9 million Americans, or just under 12%, now live in poverty, according to the U.S. Census Bureau .

Additional data from the Bureau show that children are more likely to experience poverty than people over the age of 18. Approximately one in six kids, 16% of all children, live in families with incomes below the official poverty line.

Those who are poor face challenges beyond a lack of resources. They also experience mental and physical issues at a much higher rate than those living above the poverty line. Read on for a summary of the myriad effects of poverty, homelessness, and hunger on children and youth. And for more information on APA’s work on issues surrounding socioeconomic status, please see the Office of Socioeconomic Status .

Who is most affected?

Poverty rates are disproportionately higher among most non-White populations. Compared to 8.2% of White Americans living in poverty, 26.8% of American Indian and Alaska Natives, 19.5% of Blacks, 17% of Hispanics and 8.1% of Asians are currently living in poverty.

Similarly, Black, Hispanic, and Indigenous children are overrepresented among children living below the poverty line. More specifically, 35.5% of Black people living in poverty in the U.S. are below the age of 18. In addition, 40.7% of Hispanic people living below the poverty line in the U.S. are younger than age 18, and 29.1% of American Indian and Native American children lived in poverty in 2018. In contrast, approximately 21% of White people living in poverty in the U.S. are less than 18 years old.

Furthermore, families with a female head of household are more than twice as likely to live in poverty compared to families with a male head of household. Twenty-three percent of female-headed households live in poverty compared to 11.4% of male-headed households, according to the U.S. Census Bureau .

What are the effects of poverty on children and teens?

The impact of poverty on young children is significant and long lasting. Poverty is associated with substandard housing, hunger, homelessness, inadequate childcare, unsafe neighborhoods, and under-resourced schools. In addition, low-income children are at greater risk than higher-income children for a range of cognitive, emotional, and health-related problems, including detrimental effects on executive functioning, below average academic achievement, poor social emotional functioning, developmental delays, behavioral problems, asthma, inadequate nutrition, low birth weight, and higher rates of pneumonia.

Psychological research also shows that living in poverty is associated with differences in structural and functional brain development in children and adolescents in areas related to cognitive processes that are critical for learning, communication, and academic achievement, including social emotional processing, memory, language, and executive functioning.

Children and families living in poverty often attend under-resourced, overcrowded schools that lack educational opportunities, books, supplies, and appropriate technology due to local funding policies. In addition, families living below the poverty line often live in school districts without adequate equal learning experiences for both gifted and special needs students with learning differences and where high school dropout rates are high .

What are the effects of hunger on children and teens?

One in eight U.S. households with children, approximately 12.5%, could not buy enough food for their families in 2021 , considerably higher than the rate for households without children (9.4%). Black (19.8%) and Latinx (16.25%) households are disproportionately impacted by food insecurity, with food insecurity rates in 2021 triple and double the rate of White households (7%), respectively.

Research has found that hunger and undernutrition can have a host of negative effects on child development. For example, maternal undernutrition during pregnancy increases the risk of negative birth outcomes, including premature birth, low birth weight, smaller head size, and lower brain weight. In addition, children experiencing hunger are at least twice as likely to report being in fair or poor health and at least 1.4 times more likely to have asthma, compared to food-secure children.

The first three years of a child’s life are a period of rapid brain development. Too little energy, protein and nutrients during this sensitive period can lead to lasting deficits in cognitive, social and emotional development . School-age children who experience severe hunger are at increased risk for poor mental health and lower academic performance , and often lag behind their peers in social and emotional skills .

What are the effects of homelessness on children and teens?

Approximately 1.2 million public school students experienced homelessness during the 2019-2020 school year, according to the National Center for Homeless Education (PDF, 1.4MB) . The report also found that students of color experienced homelessness at higher proportions than expected based on the overall number of students. Hispanic and Latino students accounted for 28% of the overall student body but 38% of students experiencing homelessness, while Black students accounted for 15% of the overall student body but 27% of students experiencing homelessness. While White students accounted for 46% of all students enrolled in public schools, they represented 26% of students experiencing homelessness.

Homelessness can have a tremendous impact on children, from their education, physical and mental health, sense of safety, and overall development. Children experiencing homelessness frequently need to worry about where they will live, their pets, their belongings, and other family members. In addition, homeless children are less likely to have adequate access to medical and dental care, and may be affected by a variety of health challenges due to inadequate nutrition and access to food, education interruptions, trauma, and disruption in family dynamics.

In terms of academic achievement, students experiencing homelessness are more than twice as likely to be chronically absent than non-homeless students , with greater rates among Black and Native American or Alaska Native students. They are also more likely to change schools multiple times and to be suspended—especially students of color.

Further, research shows that students reporting homelessness have higher rates of victimization, including increased odds of being sexually and physically victimized, and bullied. Student homelessness correlates with other problems, even when controlling for other risks. They experienced significantly greater odds of suicidality, substance abuse, alcohol abuse, risky sexual behavior, and poor grades in school.

What can you do to help children and families experiencing poverty, hunger, and homelessness?

There are many ways that you can help fight poverty in America. You can:

Volunteer your time with charities and organizations that provide assistance to low-income and homeless children and families.
Donate money, food, and clothing to homeless shelters and other charities in your community.
Donate school supplies and books to underresourced schools in your area.
Improve access to physical, mental, and behavioral health care for low-income Americans by eliminating barriers such as limitations in health care coverage.
Create a “safety net” for children and families that provides real protection against the harmful effects of economic insecurity.
Increase the minimum wage, affordable housing and job skills training for low-income and homeless Americans.
Intervene in early childhood to support the health and educational development of low-income children.
Provide support for low-income and food insecure children such as Head Start , the National School Lunch Program , and Temporary Assistance for Needy Families (TANF) .
Increase resources for public education and access to higher education.
Support research on poverty and its relationship to health, education, and well-being.
Resolution on Poverty and SES
Pathways for addressing deep poverty
APA Deep Poverty Initiative

Educational Poverty in Japan

Every citizen in Japan is guaranteed the right to an education. But interviews conducted by NHK have revealed that some young people lack access to this basic right. Some have missed elementary or junior high school, and are unable to do simple math or write hiragana -- the easiest form of Japanese writing. Such people face many problems in their everyday lives. They don't know how to take medicine, because they can't read kanji characters. They don't know how much a sale item costs as they can't calculate. NHK investigated the cause behind this educational poverty and the hardships it causes.

Some find even basic Japanese difficult

Kosuke is a 19 year old living in eastern Japan. He rarely attended school after the second grade. Although he can read, he is unable to properly write hiragana. All he can manage to write in kanji are his name and address. He can't do multiplication or division.

Last year, Kosuke took up a part-time job in the delivery business. He says he was scolded by his superior because he couldn't write delivery reports.

Some paper in his home shows how hard he practiced to write kanji characters needed to fill in memos for people who were not home to receive his deliveries.

But Kosuke quit his job in about a month, as it made him increasingly uncomfortable.

Kosuke and his brother were raised by their mother. She moved from one part-time job to another to look after them, and now lives on welfare, as she cannot work due to multiple illnesses.

Kosuke was regularly beaten by his brother, who is 6 years older. The stress caused by poverty and abuse made him lose his will to go to school.

At first, teachers and officials from his municipality visited his home and tried to encourage him to go to school. But they gradually stopped.

Kosuke says he can't think about his future. He grew up without a proper education, and he is now at a loss over how to go on living.

"Education opportunities are not equal"

Hitomi, a 21 year old living in Osaka, lacks self-esteem because she didn't receive a compulsory education.

When Hitomi was in elementary school, her mother, who was raising her alone, suffered a stroke. Hitomi started missing school to look after her and help her do the chores.

When she was in the 4th grade, they moved to another city due to debt. Her mother failed to take procedures to transfer Hitomi to another school, and she has never attended since then.

Hitomi says she has nothing to write on her resume. She says she feels like an outcast, and it makes her miserable.

Hitomi also faces problems in various areas of her life due to the lack of education. She is interested in fashion and beauty, like other women her age, but she has not visited a hair salon for a long time. She says she is afraid of conversing with the stylist as she doesn't want to open up about herself.

When she goes shopping, Hitomi always uses a calculator to check the money she needs before going to the cashier. She doesn't want others to see her in a flurry over not having enough money.

Hitomi avoids interacting with people as much as possible, and doesn't have any friends her age.

She studied kanji on her own, using a dictionary made for elementary school children. Using what she learned, she wrote, "Why is it so difficult to do anything without a compulsory education? I don't think educational opportunities are equal."

Educational poverty spreading

To get a clearer picture of young people suffering from a lack of education, NHK questioned officials in charge of helping the needy find jobs. Surveys were sent to such officials at about 800 municipal facilities nationwide, and 40 percent responded.

The results show that 597 young people who came to receive assistance had missed a compulsory education. 78 of them said they find it difficult to write and read, and 69 don't know how to do math. 208 said they have trouble interacting with others. Many also said they lack self-esteem, suggesting that a lack of education has an adverse psychological impact.

Asked why they failed to attend school, 101 said they were bullied. The same number of people gave a disability as their reason, and 71 said it was due to illness of one or both parents. 67 answered abuse or lack of understanding by their parents, and 51 responded that it was due to poverty. This shows that the family environment is a major contributing factor in a lack of education.

The government last conducted a survey on the Japanese literacy rate in 1955. Since then, officials have believed most Japanese have no trouble reading and writing.

But a census in 2010 found that more than 120 thousand people had failed to finish elementary school. About 20,000 were below the age of 40. No further details are available, but the figure likely includes people like Kosuke and Hitomi.

Most of the people I interviewed appeared to keep a distance from society. A lack of education doesn't result only in inconveniences in everyday life. Having no academic record makes it difficult for people to land jobs and function as members of society, depriving them of the power to lead productive lives.

Municipality Efforts

To prevent educational poverty, the city of Fukuyama in Hiroshima Prefecture is coordinating the efforts of the welfare division and the board of education.

The 2 sides now share information about families on welfare and single-parent families, and on children who are not attending school.

They created a list of families with children who require assistance, and welfare officials made visits to them. They provide support, such as waking children up in the morning and seeing them off to school, if parents are unable to do so due to illness and other reasons.

Fukuyama City currently provides such support to 71 children, but it plans to increase its staff to offer more assistance.

Night schools help take the first step

Night schools are offering help to those who could not receive a basic education.

In the past, students at night schools were mostly elderly people who could not attend school in the confusion after the war, and foreign residents. Recently, however, the number of young students is said to be increasing.

Hitomi, who could not finish elementary school, began attending night school in Osaka 3 years ago at the age of 19.

Since then, her academic ability has improved dramatically. At first, she could bearly recite the multiplication table, but now, she can solve complicated math problems.

She has also become able to express herself through writing. By engaging in conversation with classmates of various ages, the way she interacts with others has changed as well.

During an interview, she revealed that she wanted to visit the elementary school she attended until the fourth grade. As she approached it and saw children practicing for an athletic event, she appeared to be recalling the past. Hitomi said memories of those days used to torment and keep her awake at night. This was the first time she was able to visit her old school.

"Something has changed, although I don't know exactly what. Attending night school has given me courage, so that might be it," she says.

Measures to prevent educational poverty

To support those who haven't received an education and those at risk of not receiving one, it's important to create an educational safety net that can support everyone.

In 2017, the government enacted a law to guarantee all citizens a basic education.

Following this move, authorities have also instructed regional governments to set up at least one publicly-run night school, like the one Hitomi is attending, in each prefecture. At the moment, only 8 out of 47 prefectures in Japan have such schools.

According to the Educational Ministry's survey, 6 prefectures, including Kochi and Kumamoto, and 74 municipalities are considering building night schools. Support from the central government is crucial in having other regions take part in the initiative.

It's also necessary to provide adults with free study support if they can't attend evening classes due to work or because they have small children.

It is not easy for people who have trouble reading or writing to find the assistance they require. It will be helpful to provide information about learning opportunities when they come to job placement centers looking for work.

Sophia University Professor Akira Sakai says that the most important thing is for authorities to understand the severity of the situation.

He says, "The country's public education system must be reexamined to provide all children with educational opportunities guaranteed in the Constitution. Coordination between the government and the private sector is also indispensable. Until now, authorities have focused on providing education to children who come to school, but they must also consider offering other ways to learn."

To learn is to live your own life

Hitomi says she had been harboring a desire to study again since she saw a poster of a night school in a street. She agreed to be interviewed by NHK in the hopes that "people in a similar situation who are struggling will find a place to study again."

Hitomi has taken a step forward, as have others who were interviewed for this story. Hearing their stories made me realize that learning is crucial for us to live our lives with dignity.

A place for learning isn't just somewhere to study reading, writing, and math. It's also a place to meet friends and teachers who will provide lifelong support. And it's the starting point of a journey to fulfill dreams and ambitions. I will continue to investigate what is being done to ensure everyone can enjoy the right to an education.

Poverty and economic decision making: a review of scarcity theory

Open access
Published: 09 March 2021
Volume 92 , pages 5–37, ( 2022 )

Cite this article

You have full access to this open access article

Ernst-Jan de Bruijn ORCID: orcid.org/0000-0002-8414-679X 1 , 2 &
Gerrit Antonides ORCID: orcid.org/0000-0002-9983-1263 1

54k Accesses

78 Citations

104 Altmetric

Explore all metrics

Poverty is associated with a wide range of counterproductive economic behaviors. Scarcity theory proposes that poverty itself induces a scarcity mindset, which subsequently forces the poor into suboptimal decisions and behaviors. The purpose of our work is to provide an integrated, up-to-date, critical review of this theory. To this end, we reviewed the empirical evidence for three fundamental propositions: (1) Poverty leads to attentional focus and neglect causing overborrowing, (2) poverty induces trade-off thinking resulting in more consistent consumption decisions, and (3) poverty reduces mental bandwidth and subsequently increases time discounting and risk aversion. Our findings indicate that the current literature predominantly confirms the first and second proposition, although methodological issues prevent a firm conclusion. Evidence for the third proposition was not conclusive. Additionally, we evaluated the overall status of scarcity theory. Although the theory provides an original, coherent, and parsimonious explanation for the relationship between financial scarcity and economic decision making, the theory does not fully accord with the data and lacks some precision. We conclude that both theoretical and empirical work are needed to build a stronger theory.

Attentional Trade-Offs Under Resource Scarcity

The effect of financial scarcity on discretionary spending, borrowing, and investing

Limitarianism, Upper Limits, and Minimal Thresholds

Explore related subjects.

Artificial Intelligence

Avoid common mistakes on your manuscript.

1 Introduction

Poverty is associated with seemingly irrational and counterproductive behaviors in several areas of economic life, both in developed and developing countries. Low-income households tend to save too little (Shurtleff 2009 ), to borrow repeatedly at high-interest rates (Banerjee and Duflo 2007 ; Skiba and Tobacman 2008 ), and to spend relatively large parts of money on tobacco, alcohol, and lotteries (Banerjee and Duflo 2007 ; Blalock et al. 2007 ; Haisley et al. 2008 ; World Health Organization 2011 ). Additionally, low-income individuals are more likely to cut back their non-emergency healthcare services (Lusardi et al. 2010 ) and while they are eligible for welfare programs, take-up rates are low (Bertrand et al. 2006 ; Hernanz et al. 2004 ). The debate about these behaviors of the poor reflects several views. One view suggests that these behaviors mirror the poor’s preferences and should be seen as rational adaptations to their economic circumstances. The culture-of-poverty view proposes that the poor’s norms, values, and attitudes deviate from others and shape their preferences and behaviors (Lewis 1998 ). The human capital view suggests that these behaviors reflect a lack of human capital due to a lack of education, work experience, and financial literacy (see e.g., Lusardi and Mitchell 2014 ).

A few years ago, Mullainathan and Shafir ( 2013 ) published their influential book, Scarcity , presenting a new theory about these behaviors. Footnote 1 Footnote 2 Scarcity theory integrates insights from cognitive psychology and economics and attempts to explain a wide range of behaviors of the poor. The poor have to make their decisions under severe financial conditions that change the way they feel and think. Mullainathan and Shafir ( 2013 ) propose that poverty itself induces a scarcity mindset, which subsequently affects the poor's decisions and behaviors. The poor face tight budgets and income volatility, which requires them to juggle with current and upcoming expenditures. These urgent demands consume elementary cognitive resources, such as attention, executive control, and working memory, leaving fewer resources for non-pressing demands. As a consequence, financial scarcity forces the poor into counterproductive behaviors that may perpetuate the condition of poverty.

Scarcity theory is widely seen as a unified, attractive, and promising view on poverty and economic decision making. Footnote 3 This theory played a prominent role in the World Development Report 2015 ( 2015 ). Furthermore, this theory has opened a new direction for scientific research. Scientists from different disciplines have begun to test specific elements of scarcity theory in lab studies and real-world settings (e.g., Carvalho et al. 2016 ; Fehr et al. 2019 ; Huijsmans et al. 2019 ; Lichand and Mani 2020 ; Ong et al. 2019 ; Plantinga et al. 2018 ; Shah et al. 2015 ). Other studies integrated elements of the theory into broader frameworks explaining consumption behavior and economic decision making under financial constraints (Adamkovič and Martončik 2017 ; Cannon et al. 2019 ; Hamilton et al. 2019a , b ; Hamilton, Thompson, et al. 2019a , b ).

The purpose of our work is to provide an integrated review of scarcity theory applied to the context of poverty. To this end, we focus on reviewing the evidence for three fundamental propositions of this theory. First, poverty leads to an attentional focus on scarcity-related demands and neglect of other issues, causing overborrowing. Second, poverty induces trade-off thinking, i.e. weighing a particular expense against other possible expenses, resulting in more consistent consumption decisions. Third, poverty reduces mental bandwidth (cognitive capacity and cognitive control), increasing time discounting and risk aversion. For each of these propositions, we discuss its foundation and review initial and new studies, including replications, non-findings, and criticisms. Additionally, we discuss the implications for the validity and generalizability of the proposition, identify gaps in knowledge, and propose pathways for future research. Finally, we integrate our findings into an overall evaluation of the status of scarcity theory.

Our study results in four main findings. First, lab studies provide consistent evidence of scarcity drawing one's attentional focus to scarcity-related demands and causing overborrowing. However, the literature lacks field studies investigating whether these mechanisms hold in real-world contexts. Second, most studies confirm that poverty induces trade-off thinking and subsequently results in more consistent consumption decisions, but important methodological issues prevent a firm conclusion. Third, the literature provides mixed evidence of poverty impairing cognitive capacity and cognitive control, and only weak evidence of poverty increasing time discounting and risk aversion via this mechanism. Fourth, although scarcity theory does provide an original, coherent, and parsimonious explanation that financial scarcity affects economic decision making, the theory does not fully accord with the data. We conclude that both theoretical and empirical work is needed to address this issue.

Our work contributes to the current literature by providing an up-to-date and integrative overview of the literature and by critically reviewing the evidence of scarcity theory applied to poverty and economic decision making. Previous literature studies have concentrated on providing an overview of the key ideas of scarcity theory and evidence supporting this theory (Shah et al. 2015 ; Zhao and Tomm 2018 ). Others discussed evidence for specific relationships of the theory as part of a broader literature review (Adamkovič and Martončik 2017 ; Cannon et al. 2019 ; Dean et al. 2019 ; Hamilton et al. 2019a , b ; Kremer et al. 2019 ; Sheehy-Skeffington and Rea 2017 ). While the field is fast-growing, the literature lacks an up-to-date, integrative, and critical review of (the evidence for) all key aspects of scarcity theory. Footnote 4 Our work aims at filling this gap.

Our paper proceeds as follows. In Sect. 2 , we discuss the main concepts of scarcity theory and methods used in empirical studies. Sections 3 – 5 review the literature concerning the three key propositions of scarcity theory mentioned above. In Sect. 6 , we discuss our integrated findings and general directions for future research.

2 Scarcity theory: an overview

Scarcity theory explains several behaviors and decisions of people who face scarcity in a particular area of life. Mullainathan and Shafir ( 2013 ) define scarcity as "having less than you feel you need" (p. 4). Footnote 5 Scarcity can be experienced in several contexts, e.g., when people are dieting, when being thirsty, by facing deadlines, in the case of loneliness, and when facing poverty (Cannon et al. 2019 ). The theory builds on cognitive psychological research regarding several features of human cognition that affect (economic) decision making. The key idea of scarcity theory is that scarcity itself induces a specific mindset by affecting how people think and decide, and subsequently affect human behaviors. Poverty is the key domain to which scarcity theory has been applied (Zhao and Tomm 2018 ).

Figure 1 reflects the theoretical framework of scarcity theory applied to poverty and economic decision making. Footnote 6 In this framework, poverty affects economic decisions and behaviors via three routes stemming from two core psychological mechanisms (tunneling and cognitive load). Footnote 7 First, poverty causes an attentional focus that enhances resource efficiency and facilitates memory-encoding, and an attentional neglect that leads to forgetful, neglectful, and overborrowing behaviors (arrows 1 and 2). This process of attentional focus and neglect is also referred to as tunneling. Second, poverty-induced focus causes trade-off thinking (3) which creates a more stable frame of value and consistent consumption decisions (4). Third, poverty reduces mental bandwidth (cognitive capacity and executive control) (5) and subsequently increases temporal discounting and risk aversion (6). Scarcity theory assumes that cognitive load underlies the negative effect of poverty on cognitive capacity and executive control.

Theoretical framework reflecting scarcity theory applied to poverty and economic decision making

As reflected in Fig. 1 , scarcity theory contains a poverty cycle in which poverty itself causes poverty-reinforcing behaviors via specific psychological mechanisms (routes 1–2–7 and 5–6–7). Increased temporal discounting and overborrowing may ultimately reduce the overall payoff of the poor. Similarly, increased risk aversion can discourage long-term investments (e.g., in education or health) that would result in larger future payoffs. Subsequently, these behaviors reinforce the condition of poverty. As a consequence, it becomes more difficult to escape the situation of poverty. Otherwise, the trade-off thinking route may positively affect the economic condition of the poor (route 1–3–4–7). We will discuss each of these three routes in more detail in Sects. 3 – 5 .

Studies testing the hypotheses of scarcity theory reflect three types of study designs. First, laboratory experiments often exogenously induce scarcity by varying levels of resources (e.g., time, attempts, budgets) to be used in a task or game (see e.g., Shah et al. 2012 , 2019 ; Spiller 2011 ; Zhao and Tomm 2017 ). Because the researcher has full control over the environment, this method helps to detect the causality of relationships and to gain insights into its underlying mechanisms. Second, cross-sectional and quasi-experimental studies investigate the consequences of poverty outside the lab. Cross-sectional difference studies typically investigate whether low- and high-income participants do react differently to a particular cue or a specific scenario (see e.g., Shah et al. 2015 , 2018 ). Quasi-experimental studies typically investigate how variation in income interacts with other factors to reshape cognition and behaviors (see e.g., Mani et al. 2013a , b ; Plantinga et al. 2018 ; Shah et al. 2015 , 2018 ). Although these studies build on an ecologically valid approach, they face difficulties in establishing causality. Third, scientists use natural and field experiments to establish causality in a real-world environment. These studies typically test how fluctuations in income, wealth, or perceived financial situation affect outcomes (see e.g., Carvalho et al. 2016 ; Mani et al. 2013a , b ; Ong et al. 2019 ). Each of these methods has its pros and cons, reason why it is important to provide a review of the integrative evidence of empirical studies.

We observe a mismatch between the poverty definition of scarcity theory and the instruments used in empirical studies to measure this concept. Building on the general scarcity definition ("having less than you feel you need"), scarcity theory defines poverty as "the gap between one's needs and the resources available to fulfill them" (Mani et al. 2013a , p. 976). Hagenaars and De Vos ( 1988 ) distinguish three types of poverty definitions. First, objective absolute poverty defines poverty as having less than a defined minimum income. Second, the objective relative poverty definition classifies people to be poor when having a relatively low income or when lacking certain commodities that are common in society. Third, subjective poverty refers to feelings or perceptions of having not enough to get along (see also Van Praag and Frijters 1999 ). Following this categorization of poverty definitions, scarcity theory builds on the subjective poverty definition, which concentrates on having not enough financial means to fulfill one’s felt needs. Remarkably, almost all cross-sectional and quasi-experimental studies use income as a measurement instrument of poverty consistent with the objective relative poverty definition. Footnote 8 This mismatch is remarkable because Mullainathan and Shafir ( 2013 ) already concluded that income is "at best a crude proxy for scarcity" (p. 72). Not all low-income individuals experience feelings of having less than they need. Furthermore, "some of those whom we classified as well off might well have been experiencing scarcity, for example, some were surely burdened by mortgage payments, credit card debt, college loans, or large families" (Mullainathan and Shafir 2013 , p. 72). According to scarcity theory, the extent to which one feels that one has enough to fulfill one's needs defines subjective poverty, not the level of income. Footnote 9

This mismatch between the poverty definition and chosen measurement instruments can be problematic. Using a measurement instrument that only roughly measures financial scarcity may prevent detecting the effects of financial scarcity on hypothesized outcomes. We recommend future empirical studies to use measurement instruments aligning the subjective poverty definition. To facilitate this alignment, an inventory of both existing measures and the development of new instruments is needed. Footnote 10 The next three sections discuss the evidence for the propositions of our framework.

3 Poverty, attention, and borrowing behavior

Attention refers to "the flexible allocation of cognitive resources toward stimuli, internal representations, and outputs that are currently most important for the accomplishment of a behavioral goal" (Dosenbach and Petersen 2009 , p. 655). Attention allocation is a central and unifying theme in behavioral economics (Gabaix 2019 ). Inattention may explain a broad range of behavioral phenomena ranging from inattention to prices to hyperbolic discounting. Mullainathan and Shafir ( 2013 ) hypothesize that feelings of scarcity influence the way attentional resources are allocated and subsequently affect economic decisions and behavior. This mechanism consists of two parts when applied to poverty: Poverty causes (1) an attentional focus on poverty-related issues that enhances resource efficiency and facilitates memory encouding, and (2) an attentional neglect that results in neglectful, forgetful, and overborrowing behaviors. The process of attentional focus and neglect is also referred to as tunneling (Mullainathan and Shafir 2013 ). Table 1 (see Appendix) provides an overview of studies testing these propositions. We will discuss these findings in more detail below.

3.1 Poverty leads to a greater focus

Several studies have shown that feelings of scarcity induce a focus on scarcity-related demands (see Zhao and Tomm 2018 for an overview). Two lab experiments showed this mechanism using manipulations of physiological scarcity. One experiment used manipulations of drink scarcity. Participants who were made feeling thirsty scored better on a recall task concerning drinking-related items compared to non-thirsty participants, while this was not the case for non-drinking-related items (Aarts et al. 2001 ). The same held in an experiment where participants were assigned to either longer or shorter periods of food deprivation. Fasting participants showed higher recall of food-related words, but not non-food-related words, compared to non-fasting participants (Radel and Clement-Guillotin 2012 ). Similarly, students with higher levels of financial anxiety paid relatively high attention to money-related cues (Shapiro and Burchell 2012 ). These results suggest that feelings of scarcity allocate attentional resources toward scarcity-related needs.

Shah et al. ( 2012 ) examined whether attention focusing also holds for poverty-related scarcity. Their study consisted of several lab experiments where participants played budget-based games. To manipulate scarcity, participants were randomly allocated to small budgets (poor) or large budgets (rich). In one experiment, participants played the Angry Blueberries game. Participants had to fire blueberries with a slingshot to hit waffles. They earned points for each waffle that they hit. To manipulate levels of scarcity, participants were allocated to either small (3 per round) or large (15 per round) numbers of available shots. The poor (small number of shots) invested on average more time for aiming the first shot in each level of the game, suggesting that they focused and expended greater effort into the task at hand compared to more affluent participants (larger number of shots). Footnote 11 Shah et al. ( 2019 ) replicated this finding using a larger sample underpinning the robustness of this result. A study by Zhao and Tomm ( 2017 ) provides additional evidence for the hypothesis by tracking visual attention. In one experiment, participants were randomly assigned to either a small ($20) or a larger ($100) price budget and were asked to place an order from a hypothetical restaurant menu. Using an eye-tracking technique to measure visual attention, they found that participants under scarcity spent significantly more time focusing on scarcity-related information (e.g., prices) than participants under abundance. Overall, these findings show that feelings of scarcity serve to allocate one's attention to scarcity-related issues, irrespective of the scarcity domain. Footnote 12

This mechanism can be translated into the real-world environment of poverty (Shah 2015 ; Shah et al. 2012 ). When having access to enough financial resources, basic expenditures such as groceries, rent payments, and utility bills do not require much attention and effort to manage. However, under financial scarcity these expenses might become urgent, pressing, and difficult to handle because one's financial resources are not enough to fulfill all needs. As a consequence, these activities capture one's attention, resulting in a greater focus to solve these issues. A recent study suggests that the poor mentally associate everyday experiences and activities with money. Shah et al. ( 2018 ) showed that lower-income people are more likely to think about the costs of everyday activities than higher-income people. Furthermore, these thoughts arise spontaneously (e.g., when thinking about visiting a doctor) and are hard to suppress. Overall, these results suggest that the poor are more focused on the economic dimension of activities, thus providing a fuller picture of the subjective experience of being poor.

Scarcity-induced focus seems to come with some benefits. First, it might enhance resource or performance efficiency, also referred to as "focus dividend" (Mullainathan and Shafir 2013 ). In the Angry Blueberries study, participants with smaller budgets earned on average more points per shot and were thus more efficient than participants with larger budgets. Second, scarcity-induced focus might facilitate memory-encoding of task-relevant information. In the restaurant menu study, Zhao and Tomm ( 2017 ) found that participants with a smaller budget were significantly better at recalling scarcity-related information (e.g., prices) afterward than participants with larger budgets. Footnote 13 This finding might explain why low-income people are more likely to know the starting price of a taxi than high-income individuals, despite the fact that they take taxis less frequently (Mullainathan and Shafir 2013 ).

Lichand and Mani ( 2020 ) investigated the effect of scarcity on attention allocation outside the lab. In a field study among Brazilian farmers who regularly face periods of droughts, the authors investigated the differential effects of income uncertainty and income level on tunneling. To examine the impact of income uncertainty, they exploited exogenous variation in daily rainfall. They found that participants exposed to less rainfall were more likely to tunnel (i.e., scarcity-related demands captured their attentional resources) than participants facing more rainfall. Additionally, they incorporated a lab-in-the-field experiment in which randomly half of the participants were induced with drought-related worries. Similar to the field study, they found that induced scarcity-related worries led to tunneling. Furthermore, in the same experimental setting, they investigated the impact of income level on tunneling using variation in a payday of a conditional cash transfer program. Footnote 14 They found that participants were more likely to tunnel in the period before payday than after payday. More specifically, the effect sizes were larger closer to payday. Overall, the authors conclude that both a low level of income and greater uncertainty in income induces tunneling.

We provide two methodological notes to these findings. First, variation in payday seems not to reflect variation in income levels (as proposed by the authors), because the amount of the cash transfer did not differ between experimental groups. We suggest that variation in payday rather reflects variation in liquidity constraints as households are more likely to face liquidity problems before than after payday. Second, the tunneling measure showed some inconsistencies. Tunneling was not directly observed, but derived from performance on a number of tasks. Although the overall effect of variation in rainfall on the tunneling index was significant, the effects on individual measures differed and for some measures even pointed in the opposite direction. This questions the validity of the tunneling measures. Furthermore, the effects of variation in rainfall on the individual tunneling measures were quite different from that of induced drought-related thoughts, suggesting that different mechanisms are at play.

3.2 Poverty leads to neglect of other useful information

Scarcity theory hypothesizes that a greater focus on pressing needs comes at a cost: Scarcity-induced focus leads to neglect of other useful information. Studies so far have not provided clear evidence for this proposition. Shah et al. ( 2012 ) examined this hypothesis using an experiment called “Family Feud.” In this game, participants earned points for guessing popular answers to survey questions. Participants were allocated either small or large time budgets. Furthermore, some participants got a preview of questions of future rounds, others not. While the rich performed better with than without previews, no differences were found for poorer participants. This finding suggests that poorer participants did not pay enough attention to future issues, possibly because they focused more on the current question. However, in their high-powered replication study, Shah et al. ( 2019 ) found that richer participants performed only slightly better with than without previews. Furthermore, they did not find significant differences between poor and rich participants. Overall, these studies provide only very weak evidence for the hypothesis that scarcity-induced focus leads to attentional neglect of future events. We note that these studies have only tested this hypothesis indirectly because (visual) attention of the participants was not directly observed.

To solve this issue, Zhao and Tomm ( 2017 ) used eye-tracking to measure visual attention in their restaurant menu experiment, as discussed above. Participants under scarcity not only spent more time on scarcity-related information (e.g., prices) but also less time on other useful information (e.g., calorie information) than participants under abundance. Importantly, they were also more likely to neglect beneficial information (e.g., a discount placed at the bottom of the menu card) that would have alleviated the condition of scarcity. These findings suggest that scarcity not only leads to a greater focus on scarcity-related information but also results in attentional neglect of other useful information. Additional experiments of Zhao and Tomm ( 2017 ) provide a richer picture of how scarcity induces neglect of useful information apart from the narrow focus on scarce resources. They showed that people under time scarcity were less likely to detect time-saving cues and more likely to forget previous instructions than people under abundance. These results suggest that scarcity impairs both information detection and prospective memory.

3.3 Poverty leads to overborrowing

Scarcity theory predicts that poverty leads to overborrowing via attentional focus and neglect. Shah et al. ( 2012 ) examined this hypothesis using two lab experiments. In the first experiment, participants played a follow-up of the Angry Blueberries game. Participants were not only randomly assigned to small or large budgets of shots but also to some borrowing options (no borrowing, borrowing shots with or without paying interest). Importantly, borrowing was a choice, so participants could neglect this opportunity. Results showed that the poor borrowed a higher proportion of their budget than the rich and gradually increased borrowing when their time budget shrunk. Furthermore, participants performed best when not having the opportunity to borrow, worse when they could borrow without interest, and worst when they could borrow against interest. Thus, borrowing under scarcity was counterproductive, especially when it was expensive. Meanwhile, the rich performed similarly under these conditions. In the second experiment, they examined the same mechanism using a follow-up of the Family Feud game. In this version, some of both the time-rich and time-poor participants could borrow time from future rounds while others could not. Again, they found that scarcity itself led people to overborrow and enter into cycles of debt, while this behavior did not happen under abundance. Importantly, these results were replicated in their high-powered study (Shah et al. 2019 ), although the effect sizes were smaller than in the initial study. Overall, these studies provide consistent evidence from the lab that scarcity leads to overborrowing.

These decision-making patterns seem to reflect the choices of people living in the context of financial scarcity. Attention is allocated to the most pressing financial problems and needs. Future needs loom far away. From this point of view, borrowing, even at high-interest rates, appears to be a proper solution to meet the pressing needs. However, the Angry Blueberries experiments show that borrowing might be counterproductive in the long run. It suggests that people may pay too little attention to the future implications of borrowing as a result of facing financial scarcity. This may explain why the poor rely on payday loans even when annualized costs of these loans exceed 7000% (Skiba and Tobacman 2008 ).

However, the mechanism underlying the effect of scarcity on borrowing behavior remains unclear. Scarcity theory proposes that this effect is the result of attentional focus and neglect. The initial Angry Blueberries study of Shah et al. ( 2012 ) provides some correlational evidence that attentional focus predicts borrowing behavior. They found that for budget-poor participants, spending more time on aiming a shot was associated with subsequently borrowing more shots. However, this result was not replicated in their larger-sample study (Shah et al. 2019 ). Although the Angry Blueberries studies showed that scarcity leads to a greater focus on scarcity-related issues, it remains unclear whether this mechanism also explains the borrowing behavior of the poor participants. Future lab studies should examine the exact mechanism underlying the effect of scarcity on overborrowing. Furthermore, the literature contains only lab studies providing evidence for the effect of scarcity on overborrowing. Field studies are needed that investigate the impact of scarcity on borrowing behavior in real-world settings.

In summary, lab studies provide consistent evidence that scarcity leads to a greater focus and causes overborrowing. Evidence that scarcity leads to attentional neglect is weaker. We recommend future lab studies to test this proposition further and to find out under what circumstances this proposition holds. Importantly, a large gap exists between scarcity inductions in lab experiments (e.g., manipulating budgets in the Angry Blueberries game) and facing financial scarcity in real life. The gap might limit the extrapolation of findings of lab experiments to real-world poverty. Specifically, these lab experiments differ from real life in duration (short vs. longer), frequency (once vs frequently), and severity (facing scarcity in a game vs. real life) of experiencing scarcity. To solve this problem, we recommend designing lab settings that better reflect facing scarcity in the daily lives of the poor. Furthermore, lab studies are needed to identify the exact mechanism underlying the effect of scarcity on overborrowing. So far, studies investigating the attentional mechanism outside the lab are scarce. Studies in real-world contexts are needed to examine the ecological validity of this mechanism. As discussed above, the field study of Lichand and Mani ( 2020 ) provides some evidence for differential effects of income level and income uncertainty on attention allocation, although the study comes with some methodological issues. More studies are needed to clarify whether the attentional mechanism holds in the real world and underlies the impact of poverty on borrowing decisions.

4 Poverty, trade-off thinking, and consumption decisions

Standard microeconomic theories build on the rationale that all people face scarcity and consequently have to make trade-offs between consumption options as no individual has access to unlimited financial resources. Thus, buying a particular product comes with opportunity costs, meaning that, by spending on one good, one forgoes another consumption good. However, behavioral research has shown that people often neglect these opportunity costs when making consumption decisions in real life (Frederick et al. 2009 ). Scarcity theory hypothesizes that poverty induces trade-off thinking, which creates a more stable frame of value and makes the poor less prone to some inconsistencies in making consumption decisions. As a consequence, the poor's decision-making processes align better with microeconomic assumptions resulting in more consistent choices and higher utility within a given budget. Next, we discuss the evidence for each of these predictions (see Table 2 for an overview).

Some empirical investigations support the hypothesis that poverty induces trade-off thinking. Compared to higher-income people, lower-income individuals report more trade-off thinking in case of hypothetical purchases (Mullainathan and Shafir 2013 ) and deciding about their willingness to pay for a product (Shah et al. 2015 ). The proposed underlying mechanism is that the poor naturally think about trade-offs because they face tight budgets (Mullainathan and Shafir 2013 ; Shah et al. 2015 ). In deciding about buying a product, alternative consumption options come quickly to the top of their mind. Individuals who experience abundance tend to pay less attention to opportunity costs because their budgets do not feel as limited. Findings of Spiller ( 2011 ) suggest that this is not the result of pre-existing differences between the rich and the poor. In a lab experiment, participants were more likely to pay attention to opportunity costs in performing a shopping task when randomly assigned to weekly (tighter) compared to monthly (more extensive) budget frames. Similarly, participants with a smaller budget ($10) were more likely to consider opportunity costs when deciding about ordering items from a hypothetical breakfast menu than participants with a larger budget ($40). These results suggest that scarcity alters people's valuation by directing attention to opportunity costs, implying that it is indeed scarcity that drives trade-off thinking and not pre-existing (wealth) differences between people.

Scarcity theory hypothesizes that if the poor are more likely to use trade-offs, it will make them less susceptible to irrelevant context features in consumption decisions. Two studies support this idea. In a series of experiments, Shah et al. ( 2015 ) showed that low-income people were less susceptible to irrelevant features in valuing offers, items, and situations. Footnote 15 Some of these experiments revealed that the poor are less susceptible to relativity bias. Participants were asked about their willingness to travel a certain amount of time to another shop for a fixed amount of discount ($50) on a particular purchase price ($300, $500, or $1,000). Participants were randomly assigned to one of these price conditions. According to standard economic theory, the hypothetical question implies a trade-off between the costs (travel a certain amount of time) versus the benefits (for a certain amount of discount). The original purchase price should be seen as a "supposedly irrelevant factor" (Thaler 2015 ). In line with previous findings of Tversky and Kahneman ( 1981 ), higher-income participants were more likely to travel to obtain the discount on lower purchase prices, suggesting that they valued the offer in relative terms. However, lower-income participants were less sensitive to the proportional size of the discount. The poor seem to value the real trade-off of this question better, making them less susceptible to the relativity bias. Another study found similar response patterns for citizens of low- and middle-income countries as for low-income U.S. residents, although differences in wealth within countries seem not to play a role (World Bank 2015 ). Similarly, Lichand and Mani ( 2020 ) found that Brazilian farmers were less susceptible to the relativity bias before than after payday. Footnote 16 Overall, trade-off thinking seems to create a more consistent internal valuation standard while neglecting irrelevant external effects.

To what extent are these patterns incentive-compatible and confirmed in the field? To our best knowledge, only one field study examined whether people under scarcity are less susceptible to inconsistencies in consumption decisions. Fehr et al. ( 2019 ) found that facing financial scarcity reduces exchange asymmetries (also known as the endowment effect). In a large-scale study among Zambian farmers, interviewers gave participants halfway through the survey randomly one of two similarly-valued items as compensation for their participation. At the end of the survey, the interviewers offered them the opportunity to exchange the given item for an alternative good. Standard microeconomic theory predicts that half of the people will trade the endowed for the offered product because they received the less preferred item (Kahneman et al. 1991 ). Footnote 17 However, the authors found strong evidence for the existence of exchange asymmetries: A significantly larger share of participants than predicted did not exchange their product. Importantly, exploiting ecological variation in financial scarcity around harvest, they found that participants were less susceptible to the endowment effect pre-harvest (when farmers face relative financial scarcity) than post-harvest (when farmers face relative abundance). This finding was robust under other sources of variation in financial scarcity (cross-sectional differences in wealth and experimental variation in liquidity constraints). These findings suggest that under financial scarcity people tend to pay more attention to the trade-off between the endowed and offered good, which subsequently reduces the endowment effect. As a consequence, the quality of decision making improves under scarcity.

However, not all studies support the hypothesis that the poor are less sensitive to inconsistencies in decision making. Some experiments conducted by Shah et al. ( 2015 ) did not reveal differences between higher- and lower-income participants. In one of these experiments, they tested whether lower-income individuals are less susceptible to the anchoring effect than higher-income individuals. Treatment group participants valued items after being exposed to an arbitrary anchor (a random number), while the control group did the same without this anchor. Contrary to their expectations, they did not find that lower-income participants were less sensitive to the anchoring effect. Footnote 18 Similarly, they did not find significant differences between both income groups for the mental budgeting effect in the lost ticket scenario (Tversky and Kahneman 1981 ).

Furthermore, the results of Plantinga et al. ( 2018 ) do not support the proposition of scarcity theory that poverty induces trade-off thinking. They found equal rates of opportunity cost neglect among low-income and high-income people. In a series of high-powered experiments, they asked participants whether they would buy a particular product (e.g., a DVD or tablet) at a particular price. As a manipulation, some participants were reminded of the opportunity costs of this hypothetical purchase while others were not. Footnote 19 They hypothesized that this reminder would have a smaller effect on the willingness to buy the product for lower-income than for higher-income individuals. If the poor use trade-off thinking in their decision-making process about the offer, they would naturally think about the opportunity costs. However, they did not find evidence that the poor show less opportunity cost neglect than the rich. High-income and low-income participants showed an equally strong decrease in willingness to buy in response to the reminder. This result was robust under both objective and subjective poverty measures and to different types and prices of the offered products. Importantly, this result contradicts the finding of Spiller ( 2011 ) that people are more likely to consider opportunity costs when facing financial constraints.

We provide two methodological notes to the findings of Plantinga et al. ( 2018 ). First, the results might have suffered from hypothetical bias. People may apply different decision processes in hypothetical purchasing scenarios compared to real-world decision contexts. Specifically, we question whether the hypothetical decision context did activate the needs threat, which is pivotal in detecting the effects of financial scarcity on outcomes. Otherwise, Frederick et al. ( 2009 ) found that people behave similarly when purchasing decisions are incentivized compared to hypothetical choices. Second, the quasi-experimental design used income as the predicting variable, which serves only as a rough proxy of financial scarcity (as discussed in Sect. 2 ). Third, the quasi-experimental design of their study does not allow drawing final conclusions about causality as their scarcity measure was based on existing rather than manipulated income levels. Importantly, these methodological notes also apply to the studies of Shah et al. ( 2015 ) and Mullainathan and Shafir ( 2013 ), discussed before. Their study designs also involved hypothetical decision scenarios and they used existing income levels as scarcity measure.

Overall, the literature does not provide an unambiguous conclusion regarding the proposition of scarcity theory that poverty induces trade-off thinking. Results of most studies underpin this proposition showing that low-income people report more trade-off thinking (Mullainathan and Shafir 2013 ; Shah et al. 2015 ) and value offers and products more consistently (Shah et al. 2015 ) than higher-income individuals. Similarly, Fehr et al. ( 2019 ) showed that people facing financial scarcity are less susceptible to the endowment effect than when they face financial abundance. However, other studies found that high- and low-income groups are equally sensitive to opportunity cost neglect (Plantinga et al. 2018 ) and the anchoring and mental budgeting effect (Shah et al. 2015 ). Methodological issues prevent drawing a firm conclusion. We recommend future studies to use measures aligning the poverty definition of scarcity theory and to design experiments incorporating incentivized consumption choices close to real-world contexts. Footnote 20 Finally, future research should clarify when and to what extent trade-off thinking guides the decisions of the poor.

5 Poverty, mental bandwidth, and economic decision making

Mental bandwidth is an umbrella term and could be described as the cognitive ability to perform higher-level decisions and behaviors (Schilbach et al. 2016 ). Mental bandwidth also referred to as cognitive function, includes two components: cognitive capacity and executive control. Cognitive capacity, closely related to fluid intelligence, embraces the ability to solve problems and to reason logically. Executive control (also called cognitive control or executive function) refers to a set of mental processes that enable people to manage their cognitive activities (Carter et al. 1997 ; Schilbach et al. 2016 ). Executive control comprises three basic functions: (1) working memory operations to keep information retrievable, (2) inhibitory control to override impulses and automatic responses, and (3) cognitive flexibility to switch between tasks and perspectives (Diamond 2013 ). Executive control enables people to control their impulses, to multitask, to self-monitor, and to focus. So both cognitive capacity and executive control are at the core of decision making (Benjamin et al. 2013 ; Dohmen et al. 2010 , 2018 ). Scarcity theory applied to poverty hypothesizes that poverty reduces mental bandwidth (i.e., cognitive capacity and executive control), which subsequently increases time discouting and risk aversion. Below we will discuss the evidence for these hypotheses (see Table 3 for a literature overview).

5.1 Poverty reduces mental bandwidth: initial findings

Scarcity theory hypothesizes that poverty causally impairs cognitive capacity and executive function. Initial findings of Mani et al. ( 2013a ) confirm this hypothesis. Their research consists of two complementary studies: A lab study among shoppers of a mall in New Jersey (USA) and a field study involving Indian farmers. Their lab experiment aimed at examining the impact of facing financial challenges. Participants were allocated either large (e.g., an immediate $1500 car repair) or small financial challenges (same but $150) and were asked to think about solutions to finance it. While thinking about these scenarios, participants had to perform two psychological tests measuring fluid intelligence (IQ) and inhibitory control. Footnote 21 While facing the hard financial challenge, low-income participants scored significantly worse on both tasks compared to higher-income people, while no differences were found while facing the small financial challenge. The magnitude of the effect on fluid intelligence (cognitive capacity) was remarkably high, comparable to a difference of 13–14 IQ points. The decrease in correct presses in the inhibitory control task was 20% points on average in the case of the “hard” financial challenge as compared with the easy financial challenge.

The proposed mechanism is that the hard financial challenge triggers thoughts of scarcity by low-income participants, bringing monetary issues to the top of mind, and temporarily leaving less mental bandwidth for other tasks. Richer people, who have more space in their budgets to solve the immediate car bill problem directly, are not required to put much cognitive effort to the challenge. Some additional experiments ruled out the possibility of anxiety for large numbers, (no) payment for correct test responses, and the impact of the cognitive tests themselves as alternative explanations. The effects were equally large in the replication studies. Overall, these results suggest that poverty-related monetary concerns directly and temporarily impair cognitive function.

The field study tried to deal with external validity by examining the relationship between poverty and cognitive function in a natural setting. The income of Indian sugarcane farmers largely depends on the revenues of the harvest. Consequently, they face more monetary concerns before than after harvest, as evidenced by substantially higher loan rates and higher rates of reported trouble with paying ordinary bills. The farmers were interviewed twice: before and after harvest. Both interviews incorporated a fluid intelligence test and an inhibitory control task. Footnote 22 Before harvest, the same farmers performed significantly worse on the cognitive control task than after harvest. More specifically, they made 15% more errors and were 11% slower in responding. Furthermore, participants scored significantly lower on the fluid intelligence test, corresponding with a decline of 9–10 IQ points. Although their research design could not inherently rule out potential confounds, the authors argue that the results cannot be fully explained by factors like learning effects, stress, or physical exertion. They conclude that poverty itself impedes cognitive function. So scarcity of financial resources results in monetary challenges that require mental bandwidth to address, leaving less available bandwidth for other activities.

How does financial scarcity impair cognitive function? Scarcity theory proposes that cognitive load underlies the impact of poverty on cognitive capacity and executive control (Gennetian and Shafir 2015 ; Mani et al. 2013a ; Mullainathan and Shafir 2013 ; Schilbach et al. 2016 ). Mental bandwidth can be taxed when the mind of people has to deal with too many demands and disruptions. Cognitive load tends to affect both aspects of mental bandwidth in a negative way [see Gennetian and Shafir ( 2015 ) for an overview in light of scarcity theory]. Poverty can produce cognitive load via both internal and external sources. Scarcity theory follows the internal cognitive load mechanism. Footnote 23 Living in poverty means that one has to deal with many monetary and non-monetary concerns attracting attention, like managing income volatility and payment deadlines, juggling expenses, and making difficult trade-offs in consumption. Additionally, low-income individuals dwell more upon their financial problems (Johar et al. 2015 ) and worry more about their financial future (de Bruijn and Antonides 2020 ). These preoccupations consume cognitive resources leaving less bandwidth for other activities.

While the results were striking, the studies of Mani et al. ( 2013a ) have some important methodological limitations. First, the harvest study uses a simple pre-post research design as an identification strategy, thus lacking a control group. As a consequence, this study cannot fully rule out time trends or potential learning effects (Kremer et al. 2019 ; Wicherts and Zand Scholten 2013 ). Additionally, the used cognitive control task in the shopping mall study seems to be inappropriate due to ceiling effects caused by the simplicity of the task (Wicherts and Zand Scholten 2013 ). The used task did not discriminate well among individuals with higher cognitive control levels, specifically among higher-income individuals. As a consequence, Wicherts and Zand Scholten ( 2013 ) suggest that financial worries might also impair the cognitive control of higher-income individuals. Footnote 24

5.2 Poverty reduces mental bandwidth: findings from replication studies

Since the initial findings of Mani et al. ( 2013a ) were published, several studies have tried to replicate these results. These replication studies examining the impact of poverty on mental bandwidth show mixed results. Two studies examined the effect of poverty on cognitive capacity (fluid intelligence). First, as part of a study examining the impact of financial worries on risk-aversion, Dalton et al. ( 2019 ) also investigated the effect on fluid intelligence. To this end, they conducted a lab-in-the-field experiment among low-income small retailers in Vietnam. To induce financial worries, they used a similar method as Mani et al. ( 2013a ) in which participants were randomly assigned to scenarios either involving large ("hard") or small ("easy") negative financial shocks. Contrary to the findings of Mani et al. ( 2013a ), they did not find an effect of financial worries on fluid intelligence. Second, in their study among Zambian farmers, Fehr et al. ( 2019 ) also investigated the effects of financial scarcity on fluid intelligence. They found an inconsistent relationship between scarcity and fluid intelligence. Using cross-sectional differences in wealth, they found that lower wealth was associated with lower fluid intelligence. However, this finding did not replicate under seasonal (pre- vs. post-harvest) and experimental (disbursement of a consumption loan) variation in financial scarcity. Footnote 25 Fluid intelligence scores did not significantly differ between pre-harvest compared to post-harvest conditions and before vs. after paying back a consumption loan. As a methodological limitation, we note that both the cross-sectional and pre-post (harvest) elements of the study might have failed to control for all potential confounders, while the experimental manipulation might not have been strong enough to evoke different levels in feelings of financial scarcity.

Four studies have investigated the effect of poverty on cognitive control, showing mixed results. Two of these studies did not reveal this effect. In their study among Zambian farmers, Fehr et al. ( 2019 ) found a similar inconsistent effect on cognitive control as for fluid intelligence. Although lower wealth was associated with lower levels of cognitive control, this result did not carry over to seasonal and experimental variation in financial scarcity. In another study, Carvalho et al. ( 2016 ) exploited natural variations in financial resources of U.S. low-income households around payday to examine the causal effect of financial circumstances on cognitive function. Households were randomly assigned to a before-payday or an after-payday survey. Baseline data of both studies show that households face tougher financial circumstances before payday compared to after payday (e.g., lower expenditures, cash holdings, and checking and savings account balances). However, results did not support the hypothesis of greater scarcity before payday impeding executive function. Footnote 26 This holds both for the full sample as for more financially constrained subgroups. They conclude that short-term variations in financial circumstances did not diminish cognitive function.

However, the results of the latter study are subject to debate due to some methodological issues. First, variation in financial scarcity around payday might not be extreme enough for identifying the effects on cognitive function. As noted by Mani et al. ( 2013a ), participants received up to four payments within a study month, of which one payment was chosen as the payday shock. Thus, around payday, participants faced only a small temporary shock in financial resources, especially when compared with participants in the harvest study of Mani et al. ( 2013a ). Second, the payday research design might not have captured well the financial shocks around payday. Reanalyzing the data, Mani et al. ( 2020 ) show that insufficient control of the time of survey completion (before vs. after payday) seems to explain the non-results. Additionally, they found that executive control declined consistently as participants approached payday suggesting that facing financial scarcity causes cycles in executive control. We note that causal evidence is needed to fully rule out selection effects for this finding.

The results of two other studies confirmed the hypothesis that poverty impairs cognitive control. Ong et al. ( 2019 ) investigated the impact of a debt relief program (worth about three months of income) on cognitive functioning. They found that low-income Singaporean participants performed significantly better on a cognitive control task (Flanker task) after debt relief than before. Because this study used a pre-post design to identify treatment effects, similar to the harvest study of Mani et al. ( 2013a ), learning effects and potential confounders might have affected the results. In their field study among Brazilian farmers, Lichand and Mani ( 2020 ) also investigated the impact of variations in rainfall (uncertainty) and payday (liquidity) on executive function. Farmers exposed to less rainfall worried more about rainfall and performed worse on cognitive control than farmers exposed to more rainfall. Footnote 27 This drop in cognitive performance was equivalent to the gap between higher and lower educated farmers and was largest for low-income farmers. Furthermore, experimental induction of drought-related worries provided similar results. However, variation in payday did not affect executive function, except for farmers in the poorest regions. These results suggest that the minds of farmers facing less rainfall were loaded with thoughts about droughts and related financial uncertainty leaving less bandwidth for other activities. Additionally, the results suggest that income uncertainty (facing a lack of rainfall) dominates temporary liquidity constraints (around payday) as the main driver of the mental bandwidth tax caused by poverty.

Overall, the literature does not provide unambiguous evidence for the hypothesis that poverty reduces mental bandwidth. Footnote 28 The above studies show some general results. First, the effect of poverty on fluid intelligence (cognitive capacity), initially found by Mani et al. ( 2013a ), did not hold in replication studies (Dalton et al. 2019 ; Fehr et al. 2019 ). Second, studies that have investigated the impact of poverty on cognitive control show mixed results. Specifically, the effect was not found in studies exploiting (monthly) payday (Carvalho et al. 2016 ; Lichand and Mani 2020 ) or loan disbursement (Fehr et al. 2019 ), possibly because these financial shocks are too small to affect cognitive control meaningfully. Furthermore, these payday research designs did not capture financial uncertainty, which might primarily drive the adverse effect of poverty on cognitive control (Lichand and Mani 2020 ). As far as we know, no study attempted to fully replicate the findings of the shopping mall study of Mani et al. ( 2013a ). Footnote 29 We highly recommend a direct replication of this lab-in-the-field experiment in different economic environments (low-, middle-, and high-income countries) to gain insight into the robustness and external validity of these core findings.

Investigating the impact of poverty on mental bandwidth comes with methodological challenges, as we illustrated for each discussed study. We will shortly discuss these challenges and provide some directions to improve study designs. First, identification of treatment effects in real-world settings is challenging. Specifically, it is hard to isolate the effect of financial scarcity from that of other environmental and poverty-related causes. In designing field studies, researchers should consider the size and timing of the financial shock (Mani et al. 2020 ). The before-after differences in income or wealth due to the financial shock must be large enough and should be distinguishable from other shocks in income or expenditure. Additionally, researchers should consider whether the financial shock incorporates only shocks in levels of income, wealth, or liquidity, or also variation in financial uncertainty. Furthermore, alternative mechanisms (e.g., stress or motivational factors) might drive the (non-)results and must thus be accounted for. Finally, researchers should a-priori seek ways to control for confounding variables. As is the case for all natural and field experimental studies, the quality of the control group strongly determines the quality of the results. Cash-transfer and basic income experiments might provide good opportunities to further examine the effect of poverty on mental bandwidth.

Second, measuring (effects on) cognitive function in field settings using psychological tasks is challenging. Performance on these tasks can be affected by pre-existing differences between experimental groups, learning effects, interview-related load, and floor and ceiling effects. In field settings, it is hard to fully control for these potential artifacts possibly leading to spurious effects. To solve this issue, we recommend to specify the cognitive mechanism under investigation a-priori and design the experimental study accordingly. Just adding a particular task or test (somewhere in the experimental procedure) to control for cognitive function as a potential explanation is not enough. Both lab and field studies should clarify that their study design captures the temporary effect of facing financial scarcity on mental bandwidth. Additionally, besides selecting a suitable control group, careful task selection and extensive piloting of the full test and interview procedure in the target population will help to minimize measurement problems (see Schilbach et al. 2016 , and Dean et al. 2019 , for overviews of suitable measures in field settings). Specifically, more attention is required for using the Raven test as a measurement instrument for fluid intelligence. All studies that measured the effect of poverty on fluid intelligence used a small subset of Raven matrices. However, it is unknown whether this abbreviated version did affect its reliability and validity. Footnote 30 As the use of abbreviated Raven tests becomes increasingly popular in economic studies, we recommend the development of a standardized protocol. This protocol should shed light on selecting an appropriate number of matrices, whether or not including the progressive component of the original Raven test, and how the number of matrices affects the reliability and validity of the measure.

5.3 Effects on economic decision making

Time discounting and risk aversion are central elements of a broad range of economic decisions and behaviors. Several studies have shown that poverty increases both time discounting and risk aversion (see for an overview: Haushofer and Fehr 2014 ), while stress and negative affect (Haushofer and Fehr 2014 ) and rational responses to liquidity constraints (Carvalho et al. 2016 ) act as main underlying mechanisms. Scarcity theory hypothesizes that financial scarcity increases temporal discounting and risk aversion via cognitive load (Schilbach et al. 2016 ). Footnote 31 We review the evidence for this hypothesis in two parts. First, we discuss evidence for the effect of cognitive load on both temporal discounting and risk aversion. We then review studies that have investigated the impact of financial scarcity on both outcomes and discuss whether cognitive load acts as an underlying mechanism.

Several studies have examined the impact of cognitive load on economic decision making. Some of these studies show how the decision-making process alters due to cognitive load. Cognitive load increases the reliance on shortcuts and heuristics in making choices (Kahneman 2011 ; Kahneman and Frederick 2002 ). According to the dual-processing model, cognitive load affects the controlling operations of the deliberative, reflective thinking system (System 2) resulting in increased reliance on the intuitive cognitive system (System 1). As a consequence, cognitive load potentially contributes to more errors in making decisions. Other studies address the question of how decisions change as a result of cognitive load. In their overview of empirical research, Deck and Jahedi ( 2015 ) show consistent evidence that cognitive load increases risk aversion. Evidence of a detrimental impact of cognitive load on temporal choices is mixed. While some studies suggest that cognitive load makes people more impatient, others do not support this hypothesis. Additional experiments conducted by Deck and Jahedi ( 2015 ) confirmed the above results and showed that cognitive load increased both risk aversion and money-related impatience.

Recently, researchers have begun to investigate the effect of poverty on economic decision making via the scarcity mechanism. Studies consistently show that facing financial scarcity increases temporal discounting (Bartos et al. 2018 ; Carvalho et al. 2016 ; Cassidy 2018 ; Ong et al. 2019 ). In a lab-in-the-field experiment among low-income Ugandan farmers, Bartos et al. ( 2018 ) investigated the effect of feelings of poverty on time discounting. Similar to the manipulation used by Mani et al. ( 2013a ), these farmers were asked to think about the consequences of a scenario involving either a minor or a severe negative financial shock. Thereafter, they had to make a consequential decision about the timing of consuming entertainment early and delaying work effort. The results show that poverty-induced thoughts increased the farmers' preference for consuming entertainment earlier and delaying work effort, reflecting increased time discounting. The authors suggest that poverty-related thoughts directly reduce the ability to exercise self-control, possibly via cognitive load. As the cognitive load was not directly measured, the exact mechanism still remains unclear. Footnote 32 In their study among Singaporean low-income households, Ong et al. ( 2019 ) showed that debt relief reduced present bias. However, they found only weak descriptive evidence of a mediating role of cognitive control underlying this effect. Other studies exploiting variation in payday (Carvalho et al. 2016 ) and windfalls (Cassidy 2018 ) found that poverty increased time discounting, but not due to cognitive load. Both studies propose that increased time discounting might reflect rational adaptations of the poor to changes in liquidity constraints rather than increased cognitive load.

The literature shows mixed evidence for the hypothesis that financial scarcity increases risk aversion, while evidence of cognitive load as an underlying mechanism is almost absent. In their study among Vietnamese retailers, Dalton et al. ( 2019 ) found that induced financial worries resulted in less risk-averse behavior. Furthermore, induced financial worries increased perceived stress, but not fluid intelligence (as discussed in Sect. 5.2 ). These results contradict both the hypothesis that financial scarcity increases risk aversion and findings that cognitive load increases risk aversion (Deck and Jahedi 2015 ). The authors propose that acute stress rather than cognitive load function as underlying mechanism. In their payday study, Carvalho et al. ( 2016 ) did not find an effect of financial scarcity on risk behavior. Only a study of Ong et al. ( 2019 ) found that debt relief reduced risk aversion. Similar to the effect on time discounting, suggestive evidence for a mediating role of cognitive control was weak.

Overall, the literature provides consistent evidence that financial scarcity increases temporal discounting, although evidence for cognitive load as underlying mechanism is weak. The literature does not provide consistent evidence that financial scarcity increases risk aversion, while evidence for the cognitive load as the underlying pattern is almost absent. These findings raise two issues. First, it is unclear how financial scarcity affects risk aversion as studies have shown positive (Ong et al. 2019 ), negative (Dalton et al. 2019 ), or no effects (Carvalho et al. 2016 ). A potential explanation is that risk behavior under financial scarcity might depend on whether the prospect involves a potential loss or gain (Adamkovič and Martončik 2017 ). Under poverty, people may have the tendency to take less risk for a potential financial gain (see e.g., Guiso and Paiella 2008 ) and to risk more to avoid a potential loss (Dalton et al. 2019 ). Thus, financial scarcity might strengthen loss aversion, which refers to people's tendency to prefer avoiding losses over acquiring equivalent gains (Kahneman and Tversky 1979 ). Indeed, lower income is associated with increased loss aversion (Vieider et al. 2019 ). Second, we question whether the effect of poverty on economic decision making operates via cognitive load. While our literature review shows consistent evidence that poverty increases time discounting, evidence for an effect of cognitive load on this outcome is mixed (Deck and Jahedi 2015 ). Similarly, the cognitive load literature confirms that cognitive load increases risk aversion (Deck and Jahedi 2015 ), but evidence for the hypothesis that financial scarcity increases risk aversion is mixed at best.

We note that financial scarcity can affect other economic outcomes via cognitive load. In a recent study among Indian workers, Kaur et al. ( 2019 ) randomized the timing of income payment while equalizing overall earnings. Workers receiving an earlier payment increased their productivity by 5.3% in comparison with workers who received their payments later. This increase in productivity almost doubled for poorer workers. Additionally, early payment reduced attentional errors suggesting that facing lower financial strain improves cognition and subsequently productivity. Future studies should examine what exactly happens when people face financial scarcity and how that affects cognition and subsequent economic decisions and behaviors.

6 Discussion

Our work aimed to review scarcity theory applied to the context of poverty. To this end, we reviewed the evidence for three fundamental hypotheses of this theory. Below, we will shortly summarize the status of the evidence for each hypothesis, discuss the overall status of scarcity theory applied to poverty, and provide some general directions for future research.

Scarcity theory applied to poverty hypothesizes that poverty affects economic decisions and behaviors via three mechanisms (see Fig. 1 ). We briefly state the status of the evidence for each relationship. As we showed in Sect. 3 , lab studies provide consistent evidence that scarcity leads to a greater focus on scarcity-related demands, enhances resource efficiency, facilitates memory-encoding, and causes overborrowing. Evidence that scarcity leads to attentional neglect is weaker. It is still unclear whether overborrowing results from attentional focus and neglect. Additionally, evidence for the ecological validity of the attentional focus mechanism is weak as field studies examining this mechanism in real-world contexts are scarce. As discussed in Sect. 4 , most studies confirmed that poverty induces trade-off thinking and subsequently results in more consistent consumption decisions. However, methodological issues and some inconsistent findings prevent a firm conclusion. As reported in Sect. 5 , the literature provides mixed evidence for the hypothesis that poverty impairs cognitive capacity and executive control. Additionally, the literature consistently shows that financial scarcity increases time discounting, while evidence for a positive effect on risk aversion is mixed. However, the current literature does not support the view that cognitive load underlies the effect of financial scarcity on temporal discounting and risk aversion.

This overview brings us to a remaining question: How should we evaluate the overall status of scarcity theory? Following the definition of Kerlinger and Lee ( 2000 ), "a theory is a set of interrelated constructs, definitions, and propositions that present a systematic view of phenomena by specifying relations among variables, with the purpose of explaining and predicting the phenomena" (p. 11). We apply the properties of a useful theory proposed by Dennis and Kintsch ( 2007 ) to evaluate the status of scarcity theory applied to poverty. Building upon reasonable claims that cognitive resources are limited, scarcity theory applied to poverty provides an original, coherent, and parsimonious explanation that a single phenomenon (financial scarcity) explains a variety of behavioral phenomena (economic decisions and behaviors) operating via two core psychological mechanisms (tunneling and cognitive load). Furthermore, these mechanisms do not only operate under poverty but also under several other forms of scarcity (e.g., drink, food, and time scarcity). Importantly, the theory provides testable and falsifiable hypotheses. However, the theory lacks precision in defining key mechanisms (as researchers use different names, definitions, and operationalizations for the attentional and cognitive load mechanism) and predicting economic outcomes (which are rather empirically driven than theory-based). Furthermore, we showed that the theory does not fully accord with the available data. More specifically, while the literature provides (mainly) consistent evidence for the attentional focus and neglect mechanism and related borrowing and consumption behaviors, evidence for the cognitive load mechanism and associated behaviors is mixed at best. As the strength of a theory relies on the evidence, the current evidence limits the strength of scarcity theory.

We recommend two general lines for future research in additional to the specific recommendations in Sect. 2 – 5 . First, more theoretical work is needed. Currently, scarcity theory is stated verbally. We recommend researchers to translate the theory into formal models (e.g., mathematical or computational models) to enforce precision in defining constructs and mechanisms and to predict economic outcomes. Second, future work should focus on improving our understanding of the mechanisms enforced by facing financial scarcity. Brain research might help to detect which brain activities underly the effect of facing scarcity on downstream behaviors. In an initial study, Huijsmans et al. ( 2019 ) found that a scarcity mindset is associated with increased activity in the orbitofrontal cortex (which encodes valuation processes) and decreased activity in the dorsolateral prefrontal cortex (which is known for its involvement in the executive functions). Additionally, we need to know whether other mechanisms are at play, besides tunneling and cognitive load, and how these mechanisms compete with each other. At least stress and negative affect seem to play a role (Haushofer and Fehr 2014 ) but it is unclear to what extent these mediators coincide with each other. Finally, future studies should deepen our understanding of when facing scarcity improves and when it impairs performance. Scarcity theory predicts that facing scarcity makes people both less (via trade-off thinking) and more (via attentional neglect and cognitive load) susceptible to biases in decision making. However, it is not fully clear how scarcity triggers either mechanism. For example, the shopping task (Spiller 2011 ) and the Angry Blueberries (Shah et al. 2012 ) experiment contained similar intertemporal choice contexts but predicted and found different results. We suggest that choice architecture might also play a role. Future studies should address this issue.

In conclusion, we have reviewed the evidence for the key propositions of scarcity theory applied to poverty and evaluated the overall status of this theory. Although scarcity theory coherently and parsimoniously explains how financial scarcity affects economic decisions and behaviors, the theory does not fully accord with the available data. In general, both building models and testing implications contribute to a virtuous cycle of theory development (Smaldino 2019 ). While building formal models will help to enforce precision, rigorous testing will help to unravel empirical patterns. We recommend increased efforts on both elements of the theory development cycle. Finally, these efforts will contribute to a stronger theory explaining how financial scarcity affects economic decision making.

See Tables 1 , 2 and 3 .

Scarcity theory is part of the behavioral economic view proposing that the behaviors of the poor reflect a psychology of poverty. Living in poverty creates specific psychological outcomes (e.g., stress, negative affect, mental bandwidth tax) that subsequently impair economic decision making (see e.g., Haushofer and Fehr 2014 ; Schilbach et al. 2016 ).

The book received positive reviews from Nobel Prize winners Daniel Kahneman and Richard Thaler, several other leading behavioral economic experts, and popular media. According to The Economist , "the book's unified theory of the scarcity mentality is novel in its scope and ambition" (The Economist 2013 ).

Mullainathan and Shafir did not provide a single umbrella term for the theory discussed in their book. Others refer to the theory as "psychological responses to scarcity" (Zhao and Tomm 2018 ) or "resource scarcity" (Hamilton et al. 2019a , b ). We will consistently use the term "scarcity theory," referring to the title of their book.

Almost half of the reviewed studies appeared in 2019 or 2020. Most of these studies were not included in previous reviews.

This definition highlights the subjective nature of scarcity. Others define (resource) scarcity as "the condition of having insufficient resources to cope with demands" (Zhao and Tomm 2018 , p. 2) or "a discrepancy between one’s current level of resources and a higher, more desirable reference point" (Cannon et al. 2019 , p. 105).

We derived this framework from Mullainathan and Shafir ( 2013 ) and the literature overview of Shah ( 2015 ).

In our review, we focus on the routes proposed by Mullainathan and Shafir ( 2013 ).

This claim is based on our literature review. As Tables 1 , 2 and 3 shows, nearly all cross-sectional and quasi-experimental studies use income as measure of poverty. This claim does not carry over to other study designs (lab and natural experiments).

Of course, factors such as having a relatively low income compared to others or lacking commodities that are common in society will at least partly explain subjective poverty.

See Hagenaars and De Vos ( 1988 ) for some existing subjective poverty measures that might be useful.

Additionally, Shah et al. ( 2012 ) conducted a lab experiment where participants were allocated either small or large accounts of guesses in a word puzzle game. The authors proposed that small-budget participants would engage more deeply in the game which might cause cognitive exhaustion. Indeed, this initial study shows that poor participants performed worse compared to richer participants on a cognitive control task. However, this result was not replicated in studies containing much larger samples (Camerer et al. 2018 ; Shah et al. 2019 ).

A study of Sharma and Alter ( 2012 ) suggests that financial scarcity elicits a greater focus on scarce cues more generally. Participants were asked to recall a situation in which they were financially worse (better) off than their peers. Next, financially deprived participants were more likely to attend to and consume scarce rather than abundant stimuli and goods. These results suggest that financial scarcity leads to paying more attention to what is scarce in the environment.

This finding also generalized to another scarcity domain (calorie scarcity).

More specifically, the authors exploited variation in the timing of monthly Bolsa Família payments.

This finding not only held under financial scarcity but also under scarcity of time and food. People facing scarcity (limited time or a diet) showed fewer inconsistencies in valuing loss of time or fattening in fast-food-frames.

Similarly, farmers were more likely to use proportional thinking after being exposed to little rainfall compared to more rainfall. We note that the authors used the relativity bias task as part of a tunneling measure (see Sect. 3 ).

This prediction assumes that half of those who are indifferent between both goods will also exchange.

In line with this finding, Lichand and Mani ( 2020 ) did not find differences in sensitivity to the anchoring effect before versus after payday. We note that they incorporated the anchoring measure into a cognitive load index measure (see Sect. 5.2 ).

This scenario was previously used by Frederick et al. ( 2009 ).

The study of Fehr et al. ( 2019 ) can serve as a good example of such a field study.

Fluid intelligence was measured using Raven’s Matrices test, in which participants had to choose which shape was missing from a sequence of shapes. Inhibitory control was measured using a spatial incompatibility task. Participants had to alternate between congruent and incongruent actions. For some stimuli, they had to press a button on the same side of the screen. For other stimuli, they had to press a button on the opposite side.

Cognitive capacity was measured using Raven’s Matrices test (same as in the shopping mall study). Inhibitory control was measured using a numerical Stroop task which is appropriate to test low-literacy participants. To perform well on the test, participants had to neglect their automatic response. When they see 4 4 4 on the screen, they had to respond with the number of digits (3) instead of the digit 4 (the intuitive response).

Scarcity theory focuses on the financial and material dimensions of poverty, more specifically on the effects of feelings of having less than one needs. This neglects the social context (social class, stigmatization), physiological issues (lack of nutrition) and physical obstacles (lack of sleep) that surround individuals living in poverty. These may create additional taxes on people’s mental bandwidth. Beyond the scope of scarcity theory, poverty may also induce cognitive load via these external stimuli. Recent studies have begun to unravel how poverty impairs cognitive function and economic performance via a lack of sleep (Bessone et al. 2020 ) and background noise (Dean 2020 ). See Dean et al. ( 2019 ) for a literature overview and a discussion of other mechanisms.

Furthermore, Wicherts and Zand Scholten ( 2013 ) argued that the median split income procedure, applied by Mani et al. ( 2013a ) to analyze the shopping mall experiment, was unnecessary and inappropriate. They reanalyzed the data without dichotomization of income for each of the three core experiments and found insignificant interaction effects (financial scenarios vs. income) on fluid intelligence. However, Mani et al. ( 2013b ) responded that using binary income variables is standard when income data is noisy. Furthermore, they found a significant interaction effect on fluid intelligence when analyzing the data of the three core experiments together. Overall, we consider the effect on fluid intelligence as robust.

Overall, results of this study did confirm the trade-off thinking but not the mental bandwidth tax hypothesis of scarcity theory.

The cognitive function tests included the Cognitive reflection test (System 1 vs. System 2 thinking), the Flanker task (inhibitory control task), the working memory task, and the Numerical Stroop Task (cognitive control).

More specifically, this study measured the effects on cognitive load using an index including scores on executive function (measured using an attention and inhibitory control task, and a working memory task) and an anchoring scenario. This latter measure deviates from others because it incorporates decisions that might be affected by cognitive load.

Some studies have found that particular cognitive functions even improve under scarcity. Dang et al. ( 2016 ) found that lower-income participants performed better than their more affluent counterparts on an information-integration categorization task after being induced with financial concerns. These findings suggest that poverty-induced thoughts improve procedural-based cognitive functions. Additionally, Zhao and Tomm ( 2017 ) showed that scarcity-induced focus facilitates memory-encoding of task-relevant information (see Sect. 3.1 ).

As far as we know, no study attempted to fully replicate the effects on both fluid intelligence and cognitive control in a similar experimental setting. As discussed, Dean et al. ( 2019 ) tried to replicate the effect of poverty on fluid intelligence using similar scenarios as Mani et al. ( 2013a ). Because the literature might suffer from a publication bias, we searched for unpublished direct replications among Google references to the original paper of Mani et al. ( 2013a ), last in December, 2020. Using the search term "replicate," we found 279 hits. Among these hits, we found three Master theses that attempted to directly replicate the effect of poverty on fluid intelligence. First, Graves ( 2015 ) did not find a significant effect of poverty on fluid intelligence. However, this replication was underpowered as noticed by the author. Second, Joy ( 2017 ) found a significant effect on fluid intelligence similarly to that of Mani et al. ( 2013a ). Third, Plantinga ( 2014 ) did not find a significant effect of scarcity on both cognitive control and fluid intelligence in an online experiment.

An abbreviated Raven test might perform almost equally well as the full version [see e.g., Bilker et al. ( 2012 )]. However, it is unknown whether this is also the case for the versions used by Mani et al. ( 2013a ), Dean et al. ( 2019 ), and Fehr et al. ( 2019 ).

This hypothesis was proposed by Schilbach et al. ( 2016 ) in their literature overview. We note that Mullainathan and Shafir ( 2013 ) did not provide specific predictions for these economic outcomes in their book.

The authors investigated whether attentional distraction underlies the effect on temporal discounting. However, they did not find differences between experimental conditions in decision-making time, distraction while making the decision, and patterns of information acquisition. In sum, these results do not support the view that poverty reduces attention. We note that this study does not provide a formal test of the attentional mechanism of scarcity theory as discussed in Sect. 3 . The study tested whether poverty-induced thoughts reduced attention during the decision-making process, rather than changed attentional allocation.

Aarts, H., Dijksterhuis, A., & Vries, P. (2001). On the psychology of drinking: Being thirsty and perceptually ready. British Journal of Psychology, 92 (4), 631–642. https://doi.org/10.1348/000712601162383 .

Article Google Scholar

Adamkovič, M., & Martončik, M. (2017). A review of consequences of poverty on economic decision-making: A hypothesized model of a cognitive mechanism. Frontiers in Psychology, 8, 1–13. https://doi.org/10.3389/fpsyg.2017.01784 .

Banerjee, A. V., & Duflo, E. (2007). The economic lives of the poor. Journal of Economic Perspectives, 21 (1), 141–167. https://doi.org/10.1257/jep.21.1.141 .

Bartos, V., Bauer, M., Chytilová, J., & Levely, I. (2018). Effects of poverty on impatience: Preferences or inattention? CERGE-EI working paper 623. https://doi.org/10.2139/ssrn.3247690

Benjamin, D. J., Brown, S. A., & Shapiro, J. M. (2013). Who is “behavioral”? Cognitive ability and anomalous preferences. Journal of the European Economic Association, 11 (6), 1231–1255. https://doi.org/10.1111/jeea.12055 .

Bertrand, M., Mullainathan, S., & Shafir, E. (2006). Behavioral economics and marketing in aid of decision making among the poor. Journal of Public Policy & Marketing, 25 (1), 8–23. https://doi.org/10.1509/jppm.25.1.8 .

Bessone, P., Rao, G., Schilbach, F., Schofield, H., & Toma, M. (2020). The economic consequences of increasing sleep among the urban poor . National Bureau of Economic Research working paper 26746. https://doi.org/10.3386/w26746

Bilker, W. B., Hansen, J. A., Brensinger, C. M., Richard, J., Gur, R. E., & Gur, R. C. (2012). Development of abbreviated nine-item forms of the Raven’s standard progressive matrices test. Assessment, 19 (3), 354–369. https://doi.org/10.1177/1073191112446655 .

Blalock, G., Just, D. R., & Simon, D. H. (2007). Hitting the jackpot or hitting the skids: Entertainment, poverty, and the demand for state lotteries. American Journal of Economics and Sociology, 66 (3), 545–570.

Camerer, C. F., Dreber, A., Holzmeister, F., Ho, T.-H., Huber, J., Johannesson, M., et al. (2018). Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015. Nature Human Behaviour . https://doi.org/10.1038/s41562-018-0399-z .

Cannon, C., Goldsmith, K., & Roux, C. (2019). A self-regulatory model of resource scarcity. Journal of Consumer Psychology, 29 (1), 104–127. https://doi.org/10.1002/jcpy.1035 .

Carter, A., Frye, D., Reznick, J. S., & Zelazo, P. D. (1997). Early development of executive function: A problem-solving framework. Review of General Psychology, 1 (2), 198–226. https://doi.org/10.1037/1089-2680.1.2.198 .

Carvalho, L. S., Wang, S. W., & Meier, S. (2016). Poverty and economic decision-making: Evidence from changes in financial resources at payday. American Economic Review, 106 (2), 260–284. https://doi.org/10.1257/aer.20140481 .

Cassidy, R. (2018). Are the poor so present-biased? Institute for Fiscal Studies working paper 18/24. https://www.ifs.org.uk/uploads/publications/wps/WP201824.pdf .

Dalton, P. S., Nhung, N., & Rüschenpöhler, J. (2019). Worries of the poor: The impact of financial burden on the risk attitudes of micro-entrepreneurs. Journal of Economic Psychology . https://doi.org/10.1016/j.joep.2019.102198 .

Dang, J., Xiao, S., Zhang, T., Liu, Y., Jiang, B., & Mao, L. (2016). When the poor excel: Poverty facilitates procedural learning. Scandinavian Journal of Psychology, 57 (4), 288–291. https://doi.org/10.1111/sjop.12292 .

de Bruijn, E. J., & Antonides, G. (2020). Determinants of financial worry and rumination. Journal of Economic Psychology, 76, 102233. https://doi.org/10.1016/j.joep.2019.102233 .

Dean, E. B., Schilbach, F., & Schofield, H. (2019). Poverty and cognitive function. In C. B. Barrett, M. R. Carter, & J.-P. Chavas (Eds.), The economics of poverty traps (pp. 57–118). Chicago: University of Chicago Press.

Google Scholar

Dean, J. T. (2020). Noise, cognitive function, and worker productivity . Working paper. https://joshuatdean.com/wp-content/uploads/2020/02/NoiseCognitiveFunctionandWorkerProductivity.pdf .

Deck, C., & Jahedi, S. (2015). The effect of cognitive load on economic decision making: A survey and new experiments. European Economic Review, 78, 97–119. https://doi.org/10.1016/j.euroecorev.2015.05.004 .

Dennis, S., & Kintsch, W. (2007). Evaluating theories. In R. J. Sternberg, H. L. Roediger III., & D. F. Halpern (Eds.), Critical thinking in psychology (pp. 143–159). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511804632.010 .

Chapter Google Scholar

Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64 (1), 135–168. https://doi.org/10.1146/annurev-psych-113011-143750 .

Dohmen, T., Falk, A., Huffman, D., & Sunde, U. (2010). Are risk aversion and impatience related to cognitive ability? American Economic Review, 100 (3), 1238–1260. https://doi.org/10.1257/aer.100.3.1238 .

Dohmen, T., Falk, A., Huffman, D., & Sunde, U. (2018). On the relationship between cognitive ability and risk preference. Journal of Economic Perspectives, 32 (2), 115–134. https://doi.org/10.1257/jep.32.2.115 .

Dosenbach, N. U. F., & Petersen, S. E. (2009). Attentional networks. In Encyclopedia of neuroscience (pp. 655–660). Elsevier. https://doi.org/10.1016/B978-008045046-9.00204-7

Fehr, D., Fink, G., & Kelsey, J. (2019). Poverty, seasonal scarcity and exchange asymmetries. National Bureau of Economic Research working paper 26357. www.nber.org/papers/w26357 .

Frederick, S., Novemsky, N., Wang, J., Dhar, R., & Nowlis, S. (2009). Opportunity cost neglect. Journal of Consumer Research, 36 (4), 553–561. https://doi.org/10.1086/599764 .

Gabaix, X. (2019). Behavioral inattention. In D. Bernheim, S. DellaVigna, & D. Liabson (Eds.), Handbook of behavioral economics (Vol. 2, pp. 261–343). Amsterdam: Elsevier B.V. https://doi.org/10.1016/bs.hesbe.2018.11.001 .

Gennetian, L. A., & Shafir, E. (2015). The persistence of poverty in the context of financial instability: A behavioral perspective. Journal of Policy Analysis and Management, 34 (4), 904–936. https://doi.org/10.1002/pam .

Graves, V. (2015). Does poverty really impede cognitive function? Experimental evidence from Tanzanian fishers (master's thesis). University of San Francisco. https://repository.usfca.edu/thes/129 .

Guiso, L., & Paiella, M. (2008). Risk aversion, wealth, and background risk. Journal of the European Economic Association, 6 (6), 1109–1150. https://doi.org/10.1162/JEEA.2008.6.6.1109 .

Hagenaars, A., & de Vos, K. (1988). The definition and measurement of poverty. The Journal of Human Resources, 23 (2), 211. https://doi.org/10.2307/145776 .

Haisley, E., Mostafa, R., & Loewenstein, G. (2008). Myopic risk-seeking: The impact of narrow decision bracketing on lottery play. Journal of Risk and Uncertainty, 37 (1), 57–75. https://doi.org/10.1007/s11166-008-9041-1 .

Hamilton, R. W., Mittal, C., Shah, A. K., Thompson, D. V., & Griskevicius, V. (2019a). How financial constraints influence consumer behavior: An integrative framework. Journal of Consumer Psychology, 29 (2), 285–305. https://doi.org/10.1002/jcpy.1074 .

Hamilton, R. W., Thompson, D., Bone, S., Chaplin, L. N., Griskevicius, V., Goldsmith, K., et al. (2019b). The effects of scarcity on consumer decision journeys. Journal of the Academy of Marketing Science, 47 (3), 532–550. https://doi.org/10.1007/s11747-018-0604-7 .

Haushofer, J., & Fehr, E. (2014). On the psychology of poverty. Science, 344 (6186), 862–867. https://doi.org/10.1126/science.1232491 .

Hernanz, V., Malherbet, F., & Pellizzari, M. (2004). Take-up of welfare benefits in OECD countries: A review of the evidence. OECD Social, Employment and Migration working Paper 17.

Huijsmans, I., Ma, I., Micheli, L., Civai, C., Stallen, M., Sanfey, G., & A. . (2019). A scarcity mindset alters neural processing underlying consumer decision making. Proceedings of the National Academy of Sciences . https://doi.org/10.1073/pnas.1818572116 .

Johar, G., Meng, R., & Wilcox, K. (2015). Thinking about financial deprivation: Rumination and decision making among the poor. Advances in Consumer Research , 43 , 208–211. http://acrwebsite.org/volumes/1020157/volumes/v43/NA-43 .

Joy, E. E. (2017). For the poor, does attentional bias or worry explain the relationship between financial stressors and poor cognitive performance? (master's thesis). Washburn University. https://wuir.washburn.edu/handle/10425/409 .

Kahneman, D. (2011). Thinking, fast and slow . New York: Penguin Books.

Kahneman, D., & Frederick, S. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. In T. Gilovich, D. Griffin, & D. Kahneman (Eds.), Heuristics and biases: The psychology of intuitive judgment . New York: Cambridge University Press.

Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1991). Anomalies: The endowment effect, loss aversion, and status quo bias. Journal of Economic Perspectives, 5 (1), 193–206. https://doi.org/10.1257/jep.5.1.193 .

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47 (2), 263–292. https://doi.org/10.1111/j.1536-7150.2011.00774.x .

Kaur, S., Mullainathan, S., Schilbach, F., & Oh, S. (2019). Does financial strain lower worker productivity? Working paper. https://economics.mit.edu/files/16997 .

Kerlinger, F. N., & Lee, H. B. (2000). Foundations of behavioral research (4th ed.). Fort Worth, TX: Harcourt College Publishers.

Kremer, M., Rao, G., & Schilbach, F. (2019). Behavioral development economics. In B. D. Bernheim, S. DellaVigna, & D. Laibson (Eds.), Handbook of behavioral economics: Foundations and applications 2 (pp. 345–458). Amsterdam: Elsevier. https://doi.org/10.1016/bs.hesbe.2018.12.002 .

Lewis, O. (1998). The culture of poverty. Society, 35 (2), 7–9. https://doi.org/10.1007/BF02838122 .

Lichand, G., & Mani, A. (2020). Cognitive droughts . Working paper 341. University of Zurich, Department of Economics. https://doi.org/10.5167/uzh-185364 .

Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52 (1), 5–44. https://doi.org/10.1257/jel.52.1.5 .

Lusardi, A., Schneider, D. J., & Tufano, P. (2010). The economic crisis and medical care usage . National Bureau of Economic Research working paper 15843. papers3://publication/uuid/788A2DE0–5C60–4B15–9A2B-4E1A24C67427.

Mani, A., Mullainathan, S., Shafir, E., & Zhao, J. (2013a). Poverty impedes cognitive function. Science, 341 (6149), 976–980. https://doi.org/10.1126/science.1238041 .

Mani, A., Mullainathan, S., Shafir, E., & Zhao, J. (2013b). Response to comment on “Poverty impedes cognitive function.” Science, 342 (6163), 1169–1169. https://doi.org/10.1126/science.1246799 .

Mani, A., Mullainathan, S., Shafir, E., & Zhao, J. (2020). Scarcity and cognitive function around payday: A conceptual and empirical analysis . CSAE Working Paper Series 2020–04.

Mullainathan, S., & Shafir, E. (2013). Scarcity: Why having too little means so much . New York: Henry Holt and Company.

Ong, Q., Theseira, W., & Ng, I. Y. H. (2019). Reducing debt improves psychological functioning and changes decision-making in the poor. Proceedings of the National Academy of Sciences . https://doi.org/10.1073/pnas.1810901116 .

Plantinga, A. (2014). Decisions under poverty: The effects of scarcity on cognitive mindset and financial decisions (Master’s thesis). Tilburg University. http://arno.uvt.nl/show.cgi?fid=135541 .

Plantinga, A., Krijnen, J. M. T., Zeelenberg, M., & Breugelmans, S. M. (2018). Evidence for opportunity cost neglect in the poor. Journal of Behavioral Decision Making, 31 (1), 65–73. https://doi.org/10.1002/bdm.2041 .

Radel, R., & Clement-Guillotin, C. (2012). Evidence of motivational influences in early visual perception: Hunger modulates conscious access. Psychological Science, 23 (3), 232–234. https://doi.org/10.1177/0956797611427920 .

Schilbach, F., Schofield, H., & Mullainathan, S. (2016). The psychological lives of the poor. American Economic Review, 106 (5), 435–440. https://doi.org/10.1257/aer.p20161101 .

Shah, A. K. (2015). Social class and scarcity: Understanding consumers who have less. In M. I. Norton, D. D. Rucker, & C. Lamberton (Eds.), The Cambridge handbook of consumer psychology (pp. 673–692). Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781107706552.025 .

Shah, A. K., Mullainathan, S., & Shafir, E. (2012). Some consequences of having too little. Science, 338 (6107), 682–685. https://doi.org/10.1126/science.1222426 .

Shah, A. K., Mullainathan, S., & Shafir, E. (2019). An exercise in self-replication: Replicating Shah, Mullainathan, and Shafir (2012). Journal of Economic Psychology, 75, 102127. https://doi.org/10.1016/j.joep.2018.12.001 .

Shah, A. K., Shafir, E., & Mullainathan, S. (2015). Scarcity frames value. Psychological Science, 26 (4), 402–412. https://doi.org/10.1177/0956797614563958 .

Shah, A. K., Zhao, J., Mullainathan, S., & Shafir, E. (2018). Money in the mental lives of the poor. Social Cognition, 36 (1), 4–19. https://doi.org/10.1521/soco.2018.36.1.4 .

Shapiro, G. K., & Burchell, B. J. (2012). Measuring financial anxiety. Journal of Neuroscience, Psychology, and Economics, 5 (2), 92–103. https://doi.org/10.1037/a0027647 .

Sharma, E., & Alter, A. L. (2012). Financial deprivation prompts consumers to seek scarce goods. Journal of Consumer Research, 39 (3), 545–560. https://doi.org/10.1086/664038 .

Sheehy-Skeffington, J., & Rea, J. (2017). How poverty affects people’s decision-making processes . York: Joseph Rowntree Foundation.

Shurtleff, S. (2009). Improving savings incentives for the poor . National Center for Policy Analysis . National Center for Policy Analysis. http://www.ncpa.org/pdfs/ba672.pdf

Skiba, P. M., & Tobacman, J. (2008). Payday loans, uncertainty, and discounting: Explaining patterns of borrowing, repayment, and default . Vanderbilt University Law School working paper 08–33. http://ssrn.com/abstract=1319751 .

Smaldino, P. (2019). Better methods can’t make up for mediocre theory. Nature, 575 (7781), 9–9. https://doi.org/10.1038/d41586-019-03350-5 .

Spiller, S. A. (2011). Opportunity cost consideration. Journal of Consumer Research, 38 (4), 595–610. https://doi.org/10.1086/660045 .

The Economist. (2013). The psychology of scarcity: Days late, dollars short. https://www.economist.com/books-and-arts/2013/08/31/days-late-dollars-short .

Thaler, R. H. (2015). Misbehaving: The making of behavioral economics . New York: WW Norton & Company.

Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211 (4481), 453–458.

Van Praag, B. M. S., & Frijters, P. (1999). The measurement of welfare and well-being: The Leyden approach. In E. Diener, D. Kahneman, & N. Schwarz (Eds.), Well-being: The foundations of hedonic psychology (pp. 413–433). New York: Russell Sage Foundation.

Vieider, F. M., Martinsson, P., Nam, P. K., & Truong, N. (2019). Risk preferences and development revisited. Theory and Decision, 86 (1), 1–21. https://doi.org/10.1007/s11238-018-9674-8 .

Wicherts, J. M., & Zand Scholten, A. (2013). Comment on “Poverty impedes cognitive function.” Science, 342 (6163), 1169–1169. https://doi.org/10.1126/science.1246680 .

World Bank. (2015). World Development Report 2015: Mind, society, and behavior . Washington DC: The World Bank. https://doi.org/10.1596/978-1-4648-0342-0 .

Book Google Scholar

World Health Organization. (2011). Systematic review of the link between tobacco and poverty . http://apps.who.int/iris/bitstream/10665/136001/1/9789241507820_eng.pdf .

Zhao, J., & Tomm, B. M. (2017). Attentional trade-offs under resource scarcity. In Lecture notes in computer science (Vol. 10285, pp. 78–97). / https://doi.org/10.1007/978-3-319-58625-0_6 .

Zhao, J., & Tomm, B. M. (2018). Psychological responses to scarcity. In Oxford research encyclopedia of psychology (pp. 1–21). Oxford University Press. https://doi.org/10.1093/acrefore/9780190236557.013.41 .

Download references

This work was supported by the Dutch Research Council [023.005.060 to E.B.].

Author information

Authors and affiliations.

Department of Social Sciences, Wageningen University, P.O. Box 8130, 6700 EW, Wageningen, The Netherlands

Ernst-Jan de Bruijn & Gerrit Antonides

Department of Economics, Leiden University, Leiden, The Netherlands

Ernst-Jan de Bruijn

You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ernst-Jan de Bruijn .

Ethics declarations

Conflicts of interest.

The authors declares that they have no competing interest.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

de Bruijn, EJ., Antonides, G. Poverty and economic decision making: a review of scarcity theory. Theory Decis 92 , 5–37 (2022). https://doi.org/10.1007/s11238-021-09802-7

Download citation

Accepted : 08 February 2021

Published : 09 March 2021

Issue Date : February 2022

DOI : https://doi.org/10.1007/s11238-021-09802-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Scarcity theory
Literature review
Economic decision making
Find a journal
Publish with us
Track your research

What is Learning Poverty?

All children should be able to read by age 10. Reading is a gateway for learning as the child progresses through school—and conversely, an inability to read slams that gate shut. Beyond this, when children cannot read, it’s usually a clear indication that school systems aren’t well organized to help children learn in other areas such as math, science, and the humanities. And although it is possible to learn later in life with enough effort, children who don’t read by age 10—or at the latest, by the end of primary school—usually fail to master reading later in their schooling career.

In recent years, it has become clear that many children around the world are not learning to read proficiently. Even though most children are in school, a large proportion are not acquiring fundamental skills. Moreover, 260 million children are not even in school. This is the leading edge of a learning crisis that threatens c ountries’ efforts to build human capital and achieve the Sustainable Development Goals (SDGs). Without foundational learning, students often fail to thrive later in school or when they join the workforce. They don’t acquire the human capital they need to power their careers and economies once they leave school, or the skills that will help them become engaged citizens and nurture healthy, prosperous families. As a major contributor to human capital deficits, the learning crisis undermines sustainable growth and poverty reduction.

To spotlight this crisis, we are introducing the concept of Learning Poverty, drawing on new data developed in coordination with the UNESCO Institute for Statistics. Learning poverty means being unable to read and understand a simple text by age 10. This indicator brings together schooling and learning indicators: it begins with the share of children who haven’t achieved minimum reading proficiency (as measured in schools) and is adjusted by the proportion of children who are out of school (and are assumed not able to read proficiently).

Using a measure developed jointly by the World Bank and UNESCO’s Institute of Statistics , we have determined that 53 percent of children in low- and middle-income countries cannot read and understand a simple story by the end of primary school. In poor countries, the level is as high as 80 percent. Such high levels of illiteracy are an early warning sign that all global educational goals and other related sustainable development goals are in jeopardy.

Progress in reducing learning poverty is far too slow to meet the SDG aspirations: at the current rate of improvement, in 2030 about 43% of children will still be learning-poor. Even if countries reduce their learning poverty at the fastest rates we have seen so far in this century, the goal of ending it will not be attained by 2030.

There is an urgent need for a society-wide commitment to invest more and better in people. If children cannot read, all education SDGs are at risk. Eliminating learning poverty is as important as eliminating extreme monetary poverty, stunting, or hunger. To achieve it in the foreseeable future requires far more rapid progress at scale than we have yet seen.

The learning poverty indicator focuses on reading for three reasons:

Reading proficiency is an easily understood learning measure
Reading is a student’s gateway to learning in other areas
Reading proficiency can serve as a proxy for foundational learning in other subjects

The learning poverty indicator allows us to illustrate progress toward SDG 4’s broader goal to ensure inclusive and equitable quality education for all. It particularly highlights progress towards SDG 4.1.1(b), which specifies that all children at the end of primary reach at least a minimum proficiency level in reading.

Methodology

The indicator combines the share of primary-aged children out-of-school who are schooling deprived (SD) , and the share of pupils below a minimum proficiency in reading, who are learning deprived (LD) . By combining schooling and learning, the indicator brings into focus both “more schooling”, which by itself serves a variety of critical functions, as well as “better learning” which is important to ensure that time spent in school translates into acquisition of skills and capabilities.

How Learning Poverty is defined

The learning poverty indicator is calculated as follows:

Lp = [ld x (1-sd)] + [1 x sd].

LP = Learning poverty

LD = Learning deprivation , defined as share of children at the end of primary who read at below the minimum proficiency level, as defined by the Global Alliance to Monitor Learning (GAML) in the context of the SDG 4.1.1 monitoring

SD = Schooling deprivation , defined as the share of primary aged children who are out-of-school. All out-of-school children are assumed to be below the minimum proficiency level in reading.

Learning poverty can be improved in two ways: (i) by reducing learning deprivation as countries raise proficiency levels for children below the minimum proficiency threshold, or (ii) by reducing schooling deprivation as countries expand coverage and bringing out-of-school population into the system.

While schooling deprivation can be directly observed depending on whether the child is enrolled or not enrolled in school, learning deprivation cannot be directly observed, and is measured through standardized assessments using SDG’s definition of minimum proficiency level, where reading proficiency is defined as:

Three complementary concepts: Learning poverty level, gap, and severity

The learning poverty level (or headcount ratio) shown above, that is the share of 10-year-olds who are not in school (schooling deprived) or are below the minimum proficiency level (learning deprived), has limitations. It does not capture the average learning shortfall among children under the minimum proficiency level. Hence, we include the learning poverty gap , that measures the average distance of a learning deprived child to the minimum proficiency level and indicates the average increase in learning required to eliminate learning poverty.

However, the gap measure cannot distinguish between an increase in the learning gap driven by students near the threshold and one driven by those at the very bottom of the learning distribution. Learning poverty severity captures the inequality of learning among the learning poor population and is the gap squared in relation to the minimum proficiency squared.

The concepts of learning poverty gap and learning poverty severity are important to fully understand children’s access to learning. It is possible that countries with the same learning poverty level have different learning poverty gaps, or countries with the same learning poverty gaps have different learning poverty severity, with implications for policies used to address learning poverty.

For example, where two countries have the same level of learning poverty, but one has a higher learning poverty gap , the latter would need greater effort to bring children above the minimum proficiency level. At the same time, where two countries have the same learning poverty gap , but one has higher learning poverty severity , the latter would need to adopt strategies that address the unequal distribution of learning among those below the minimum proficiency threshold. Furthermore, as we anticipate learning losses due to the pandemic, or the growing share of children who are learning poor, we can examine widening inequalities with the gap and severity calculations.

Calculation details

The implementation of this indicator and the production of the global estimates rely on:

Reporting window of 9 years, a ±4 interval around a reference year. In the first release of the learning poverty, the reference year was set to 2015, implying data from 2011-2019 could be included. In practice, most recent data was from 2017.
Learning assessments with a minimum proficiency threshold benchmarked by Global Alliance to Monitor Learning (GAML), which occurred within the reporting window. If a country has multiple eligible learning assessments, the following hierarchy is applied: PIRLS reading > TIMSS science > Regional assessments > National assessments. Between two rounds of the same assessments, the one closest to the reference year is preferred.
School participation is derived from adjusted net enrollment rate (ANER) for primary schools and computed by the UIS using administrative records. Adjusted net enrollment is a measure of both “stock” and “flow” and accounts for both age- and grade-based distortions, as it is the percent of primary school age children enrolled either in primary or secondary education, as opposed to gross enrollment which is the share of children of any age that are enrolled in primary school, or net enrollment which is the share of primary school age children that are enrolled in primary school. We use the same year of school participation as the preferred learning assessment for each country.
Aggregations for each region comprise the average learning poverty of countries with available data, weighted by their population ages 10–14 years old. To obtain a global estimate, we weight the regional aggregations by the 10–14-year-old population regardless of data availability. This is equivalent to imputing missing country data using regional values.

Note: While the reference age for Learning Poverty is age 10, learning assessments are sampled based on specific grades and not age. To incorporate assessments administered at different grades, we chose for each country the grade between 4 and 6 where relevant and reliable data were available.

You can download the Learning Poverty data directly from Development Data Hub . The database contains pooled and gender-disaggregated indicators for percent of children in learning poverty, percent of primary school-aged children who are out of school, and percent of children below minimum proficiency in reading at the end primary.

You may also access the learning poverty data directly through EdStats .

To load the Learning Poverty data directly in Stata you can use this code:

// Install the user-written command if you don't have itcapture which wbopendataif _rc == 111 ssc install wbopendata // Query Learning Poverty indicator from World Bank APIwbopendata, indicator(SE.LPV.PRIM) latest long clear

To load the Learning Poverty data directly in Python you can use this code:

# Load the packageimport wbgapi as wb # Query the most recent non-empty value (mrnev parameter)df = wb.data.DataFrame('SE.LPV.PRIM', db=12, mrnev=1, columns='time', numericTimeKeys=True)

Current findings

Learning poverty map.

The map below is a snapshot of Learning Poverty across the world. You can also view the indicator for females and males. You may edit this map directly in DataBank .

Learning Poverty Map

Figure 1 Learning Poverty around the World (hover to see country numbers)

How does learning poverty vary by gender?

Using all available cross-country assessments (as well as gender-disaggregated enrollment data from UIS), we have computed gender-specific learning poverty rates. Given data availability, we have only been able to compute this disaggregation for 92 countries. Access to microdata in some countries, particularly in South Asia, has been a significant challenge to compute gender-disaggregated outcomes.

Learning Poverty gender gap, by country

Despite the barriers confronting girls in some areas of education, in virtually all countries for which we have data, girls have lower rates of learning poverty than boys do.

Replicate our results in GitHub

Our processes are documented on the LearningPoverty Github repository, which also includes instructions on how to replicate our numbers. You can find information about data source selection, calculations, aggregations here .

Forthcoming update

The recent release of new learning assessment results – TIMSS 2019, SEA-PLM 2019, and PASEC 2019 – calls for an update of the learning poverty indicator. A public update of the regional and global estimates is planned for September 2021 , to include the forthcoming LLECE 2019 results.

Significant changes are anticipated in some country estimates due to the replacement of national learning assessments by international ones. The initial learning poverty estimate was 52.7 percent in low- and middle-income countries, anchored in 2015. It used data from 62 countries, covering 80 percent of the target population. In September 2021, we plan to publish a corporate update of these global numbers. Using 2017 as the reference year implies accepting assessments from 2013 onwards, including the recently released TIMSS, SEA-PLM, PASEC from 2019 and the forthcoming LLECE 2019. With the new data, the coverage of the indicator will increase to 66 countries and 81 percent of the target population. The new update will also allow temporal comparisons in instances where countries have results from the same assessment in the last round.

Learning Poverty serves as an early-warning indicator for the Human Capital Project. For more information, visit website .

"Literacy Makes Sense" campaign
Ending Learning Poverty
Country Learning Poverty Briefs
Human Capital Project
Education Homepage
World Bank Human Capital Index
Accelerator Program
Learning Data Compact
SDG Atlas - Quality Education: Learning Poverty
Education Service Delivery Indicators

Brochure: What is Learning Poverty Overview

Reports using Learning Poverty Measures

The State of Global Learning Poverty: 2022 Update

Press Release: 70% of 10-Year-Olds now in Learning Poverty, Unable to Read and Understand a Simple Text

Ending Learning Poverty: What Will It Take?

Simulating the Potential Impacts of COVID-19 School Closures on Schooling and Learning Outcomes: A Set of Global Estimates

Learning Poverty: Measures and Simulations

Learning Poverty in the Time of COVID-19: A Crisis Within a Crisis

INFOGRAPHIC: A Policy Package to Promote Literacy for All Children

How could COVID-19 hinder progress with Learning Poverty? Some initial simulations

Learning for All: Within-country learning inequality

Learning for All: Beyond an Average Score

We should avoid flattening the curve in education – Possible scenarios for learning loss during the school lockdowns

Multiple exposures to learning assessments: A photo mosaic from Brazil

How to tackle Learning Poverty? Delivering education’s promise to children across the world Why focus on learning?

Communities working together to end learning poverty

Reducing learning poverty through a country-led approach

UIS Resources

Global Alliance to Monitor Learning (GAML)

Technical Cooperation Group on the Indicators for SDG 4 (TCG)

How the SDG 4.1.1 Framework and Learning Poverty Can Help Countries Focus Their Education Policy Response to COVID-19

Projections for Learning Proficiency Can Inform Post-COVID-19 Educational Strategies

This site uses cookies to optimize functionality and give you the best possible experience. If you continue to navigate this website beyond this page, cookies will be placed on your browser. To learn more about cookies, click here .

Share on twitter
Share on facebook

Impact Rankings 2024: no poverty (SDG 1) methodology

Share on linkedin
Share on mail

Browse the full results of the Impact Rankings 2024

This ranking focuses on universities’ research on poverty and their support for poor students and citizens in the local community.

View the methodology for the Impact Rankings 2024 to find out how this data is used in the overall ranking.

Research on poverty (27%)

Field-weighted citation index of papers related to poverty (10%)
Number of publications related to poverty (10%)
Proportion of all research papers co-authored with low- or lower-middle-income countries (7%)

This focuses on research that is relevant to poverty. The field-weighted citation index is a subject-normalised score of the citation performance of publications.

The data are provided by Elsevier’s Scopus dataset, based on a query of keywords associated with SDG 1 (no poverty). The dataset includes all indexed publications between 2018 and 2022 and is supplemented by additional publications identified by artificial intelligence. The data are normalised across the range using Z-scoring.

The third indicator measures the proportion of publications where one or more co-author is associated with a university that is based in a low- or lower-middle-income country. All indicators are normalised across the range using Z-scoring.

Proportion of students receiving financial aid (27%)

This indicator measures the proportion of a university’s students who receive significant financial aid in order to attend the institution because of poverty.

It is based on data for full-time equivalent students across both undergraduate and postgraduate courses in the 2022 academic year.

The data were provided directly by universities and normalised across the range using Z-scoring.

University anti-poverty programmes (23%)

Targets to admit students who fall into the bottom 20% of household income in the country (4.6%)
Graduation/completion targets for students who fall into the bottom 20% of household income in the country (4.6%)
Support for students from poorest families to enable them to complete university – for example, in relation to food, housing, transport, legal services (4.6%)
Programmes to assist students who fall into the bottom 20% of household income in the country to successfully complete their studies (4.6%)
Schemes to support poor students from low- or lower-middle-income countries – for example, offering free education or grants (4.6%)

The evidence was provided directly by universities, evaluated and scored by THE and not normalised.

Community anti-poverty programmes (23%)

Education or resources to assist the start-up of sustainable businesses in the local community – for example, mentorship programmes, training workshops, access to university facilities (5.75%)
Financial assistance to aid the start-up of sustainable businesses in the local community (5.75%)
Training or programmes to improve access to basic services for all (5.75%)
Participate in policymaking at a local, regional, national and/or global level to implement programmes and policies to end poverty (5.75%)

The programmes can be community-led but they must be supported by the university.

When we ask about policies and initiatives – for example, the existence of mentoring programmes – our metrics require universities to provide the evidence to support their claims. In these cases, we give credit for the evidence, and for the evidence being public. These metrics are not usually size-normalised.

Evidence is evaluated against a set of criteria, and decisions are cross-validated where there is uncertainty. Evidence need not be exhaustive – we are looking for examples that demonstrate best practice at the institutions concerned.

In general, the data used refer to the closest academic year to January to December 2022. The date range for each metric is specified in the full methodology document.

The ranking is open to any university that teaches at undergraduate or postgraduate level. Although research activities form part of the methodology, there is no minimum research requirement for participation.

THE reserves the right to exclude universities that it believes have falsified data, or are no longer in good standing.

Data collection

Institutions provide and sign off their institutional data for use in the rankings. On the rare occasions when a particular data point is not provided, we enter a value of zero.

Register to continue

Why register?

Registration is free and only takes a moment
Once registered, you can read 3 articles a month
Sign up for our newsletter

Or subscribe for unlimited access to:

Unlimited access to news, views, insights & reviews
Digital editions
Digital access to THE’s university and college rankings analysis

Already registered or a current subscriber? Login

Featured jobs

LIVE DISCOURSE
BLOG / OPINION
SUBMIT PRESS RELEASE
Advertisement
Knowledge Partnership
Media Partnership
Energy & Extractives

Suriname at a Crossroads: Navigating Poverty, Inequality, and the Promise of Oil Wealth

Suriname, emerging from a crippling economic crisis, is at a pivotal moment as it anticipates significant oil revenues. however, challenges persist in poverty and inequality, with human capital deficiencies and labor market disparities holding back growth. the government must prioritize education, social assistance, and fiscal stability to ensure that the potential oil boom benefits all citizens. this article explores insights from the suriname poverty and equity assessment..

Suriname, a small Caribbean nation, finds itself at a turning point. After years of sluggish growth, compounded by the COVID-19 pandemic and a global commodity slump, the country’s economy contracted severely in 2020. However, recent economic reforms have brought signs of recovery, and the much-anticipated offshore oil revenues offer new hope for prosperity. Yet, the road ahead is uncertain, and without targeted reforms, the benefits of this potential oil boom may not reach all citizens.

According to the Suriname Poverty and Equity Assessment, published by the World Bank in July 2024, Suriname's socioeconomic landscape is marred by high poverty rates, deep-rooted inequalities, and significant human capital deficiencies. While the oil sector offers a path to recovery, the report urges the government to address critical challenges such as education, social assistance, and labor market disparities to ensure that economic growth is inclusive.

From Crisis to Recovery: Economic Stability or Fragile Hope?

Suriname's economy suffered a major setback in 2020, with a sharp 17.5% decline in GDP per capita. The collapse was primarily driven by a drop in global commodity prices and poor economic management. The COVID-19 pandemic only worsened the situation, pushing many Surinamese into poverty. By 2022, the poverty rate stood at 17.5%, with about 1.1% of the population living in extreme poverty. Despite these alarming figures, the nation has begun to show signs of recovery, largely due to stringent economic reforms.

However, this fragile recovery faces new challenges, with much hope pinned on anticipated oil revenues. If managed well, the oil boom could provide the fiscal space needed for long-term poverty reduction. Yet, Suriname’s over-reliance on natural resources, coupled with the risk of Dutch disease—where other sectors of the economy suffer due to a sudden influx of wealth—poses risks. The oil and gas sector is capital-intensive, meaning job creation may be limited, and without skilled workers, much of the benefit may bypass local populations.

Poverty, Inequality, and the Education Gap

While economic recovery is underway, poverty and inequality remain deeply entrenched in Suriname. Ethnic and geographic disparities continue to divide the country, with poverty rates significantly higher in the rural interior. More than one in four Surinamese living in these regions falls below the World Bank’s upper-middle-income poverty line of US$6.85 per day. Indigenous and Maroon communities are particularly vulnerable.

A key driver of this inequality is a severe deficiency in human capital, particularly in education. The report reveals that Suriname's education system is underperforming, with lower secondary school completion rates comparable to much poorer nations such as Mozambique and Senegal. Despite education spending being on par with other countries in the region, the outcomes are dismal, especially among boys. Women, on the other hand, outperform men in education, yet face considerable barriers in the workforce. High rates of early marriage and adolescent fertility significantly hinder women's ability to transition from school to employment, exacerbating labor market inequalities.

Suriname’s education system needs urgent reform. Improving school completion rates, particularly for marginalized communities, is critical to breaking the cycle of intergenerational poverty. The report also calls for better vocational training programs to equip the workforce with the skills needed to capitalize on future economic opportunities, particularly in the oil sector.

Strengthening Social Assistance for a Resilient Future

In addition to education, the report highlights the need for stronger social assistance programs. While Suriname has several key programs, including the General Old Age Pension and a Child Allowance, these efforts fall short in covering the full spectrum of poverty. About 55% of poor households benefit from some form of assistance, but a significant portion remains excluded. Social protection for historically marginalized groups, such as the Maroons and Indigenous populations, is particularly lacking.

The World Bank’s assessment stresses that Suriname’s social safety nets must be expanded and reformed to better target the most vulnerable. This is especially important as economic shocks, such as fluctuations in oil prices, can quickly reverse gains in poverty reduction. The introduction of a more robust social registry and the modernization of payment systems could enhance the efficiency and reach of these programs.

Can Suriname’s Oil Boom Bring Inclusive Growth?

While the potential for an oil boom offers a lifeline for Suriname, the report urges caution. The influx of oil revenues could provide the government with much-needed fiscal space, but without a focus on equitable growth, the benefits could remain concentrated among the wealthy. The report suggests that investments in education, social assistance, and targeted economic policies are essential to ensure that the oil windfall translates into lasting poverty reduction.

Suriname stands at a crossroads. The promise of oil wealth is tantalizing, but the path to inclusive, sustainable development will require more than natural resources. It demands a commitment to addressing the systemic issues of poverty and inequality that have long held the country back. Only through sound fiscal management and investment in human capital can Suriname hope to turn this moment of opportunity into a lasting era of prosperity for all.

READ MORE ON:
economic crisis
social assistance
labor market
fiscal discipline
human capital
FIRST PUBLISHED IN:
Devdiscourse

President Murmu Advocates for Enhanced Research in Education

Iydf and red gym brighten orphanage with educational, sports, and daily essentials, president murmu's call for women's socio-economic and educational development, gaza schoolgirl's hope for education amidst war, delhi's educational transformation: new academic blocks inaugurated in old seemapuri.

Lupin to Launch Vonoprazan Tablets in India under Patent Agreement with Take...

France's Radical New Law Targets Tech Titans Over Platform Misuse

Investors Await Fed's Interest Rate Decision Amid Market Uncertainty

Deakin University Kicks Off Interactive Week 2024 in India

Opinion / blog / interview, the growing burden of ncds: challenges for human capital and economic stability, empowering rwanda's economy: high-potential technologies for sustainable growth, powering liberia’s future: economic growth, energy access, and structural reforms, criminalization vs. inclusion: the global divide on rights for sexual and gender minorities, latest news, "cheap stunt" by "anti-democratic bjp" says trinamool's derek o'brien after pm modi's cabinet clears 'one nation, one election', fed's first rate cut in four years: signaling a new economic phase, godrej capital ventures into affordable housing loans: aiming high for future growth, union cabinet unveils bio-ride scheme to boost biotechnology.

Connect us on

ADVERTISEMENT
KNOWLEDGE PARTNERSHIP
MEDIA PARTNERSHIP
Agro-Forestry
Art & Culture
Economy & Business
Law & Governance
Science & Environment
Social & Gender
Urban Development
East and South East Asia
Europe and Central Asia
Central Africa
East Africa
Southern Africa
West Africa
Middle East and North Africa
North America
Latin America and Caribbean

OTHER PRODUCTS

Email: [email protected] Phone: +91-720-6444012, +91-7027739813, 14, 15

Environment
Science & Technology
Business & Industry
Health & Public Welfare
Topics (CFR Indexing Terms)
Public Inspection
Presidential Documents
Document Search
Advanced Document Search
Public Inspection Search
Reader Aids Home
Office of the Federal Register Announcements
Using FederalRegister.Gov
Understanding the Federal Register
Recent Site Updates
Federal Register & CFR Statistics
Videos & Tutorials
Developer Resources
Government Policy and OFR Procedures
Congressional Review
My Clipboard
My Comments
My Subscriptions
Sign In / Sign Up
Site Feedback
Search the Federal Register

This site displays a prototype of a “Web 2.0” version of the daily Federal Register. It is not an official legal edition of the Federal Register, and does not replace the official print version or the official electronic version on GPO’s govinfo.gov.

The documents posted on this site are XML renditions of published Federal Register documents. Each document posted on the site includes a link to the corresponding official PDF file on govinfo.gov. This prototype edition of the daily Federal Register on FederalRegister.gov will remain an unofficial informational resource until the Administrative Committee of the Federal Register (ACFR) issues a regulation granting it official legal status. For complete information about, and access to, our official publications and services, go to About the Federal Register on NARA's archives.gov.

The OFR/GPO partnership is committed to presenting accurate and reliable regulatory information on FederalRegister.gov with the objective of establishing the XML-based Federal Register as an ACFR-sanctioned publication in the future. While every effort has been made to ensure that the material on FederalRegister.gov is accurately displayed, consistent with the official SGML-based PDF version on govinfo.gov, those relying on it for legal research should verify their results against an official edition of the Federal Register. Until the ACFR grants it official status, the XML rendition of the daily Federal Register on FederalRegister.gov does not provide legal notice to the public or judicial notice to the courts.

Design Updates: As part of our ongoing effort to make FederalRegister.gov more accessible and easier to use we've enlarged the space available to the document content and moved all document related data into the utility bar on the left of the document. Read more in our feature announcement .

Submission for Office of Management and Budget (OMB) Review; 2024 National Survey of Early Care and Education Longitudinal Follow-ups (OMB #: 0970-0391)

A Notice by the Children and Families Administration on 09/18/2024

This document has been published in the Federal Register . Use the PDF linked in the document sidebar for the official electronic format.

Document Details Published Content - Document Details Agencies Department of Health and Human Services Administration for Children and Families Document Citation 89 FR 76477 Document Number 2024-21210 Document Type Notice Pages 76477-76478 (2 pages) Publication Date 09/18/2024 Published Content - Document Details
View printed version (PDF)
Document Dates Published Content - Document Dates Dates Text Comments due within 30 days of publication. OMB must make a decision about the collection of information between 30 and 60 days after publication of this document in the Federal Register. Therefore, a comment is best assured of having its full effect if OMB receives it within 30 days of publication. Published Content - Document Dates

This table of contents is a navigational tool, processed from the headings within the legal text of Federal Register documents. This repetition of headings to form internal navigation links has no substantive legal effect.

SUPPLEMENTARY INFORMATION:

Annual burden estimates ( print page 76478).

This feature is not available for this document.

Additional information is not currently available for this document.

Sharing Enhanced Content - Sharing Shorter Document URL https://www.federalregister.gov/d/2024-21210 Email Email this document to a friend Enhanced Content - Sharing
Print this document

This document is also available in the following formats:

More information and documentation can be found in our developer tools pages .

This PDF is the current document as it appeared on Public Inspection on 09/17/2024 at 8:45 am.

It was viewed 3 times while on Public Inspection.

If you are using public inspection listings for legal research, you should verify the contents of the documents against a final, official edition of the Federal Register. Only official editions of the Federal Register provide legal notice of publication to the public and judicial notice to the courts under 44 U.S.C. 1503 & 1507 . Learn more here .

Document headings vary by document type but may contain the following:

the agency or agencies that issued and signed a document
the number of the CFR title and the number of each part the document amends, proposes to amend, or is directly related to
the agency docket number / agency internal file number
the RIN which identifies each regulatory action listed in the Unified Agenda of Federal Regulatory and Deregulatory Actions

See the Document Drafting Handbook for more details.

Department of Health and Human Services

Administration for children and families.

Office of Planning, Research, and Evaluation, Administration for Children and Families, Department of Health and Human Services.

Request for public comments.

The Administration for Children and Families (ACF), U.S. Department of Health and Human Services (HHS), is proposing a data collection activity to be conducted January 2025 through December 2025 as a follow-up of the 2024 National Survey of Early Care and Education (NSECE). The objectives of the 2024 NSECE Longitudinal Follow-ups are to build on the design and implementation of the 2024 NSECE to collect urgently needed information on the following two topics relevant to early care and education (ECE) policy: (1) how households learn about and make use of financial assistance in seeking and selecting ECE, with additional focus on paid individual care arrangements; and (2) patterns of retention and attrition among individuals in the center-based ECE workforce.

Comments due within 30 days of publication. OMB must make a decision about the collection of information between 30 and 60 days after publication of this document in the Federal Register . Therefore, a comment is best assured of having its full effect if OMB receives it within 30 days of publication.

Written comments and recommendations for the proposed information collection should be sent within 30 days of publication of this notice to www.reginfo.gov/public/do/PRAMain . Find this particular information collection by selecting “Currently under 30-day Review—Open for Public Comments” or by using the search function. You can also obtain copies of the proposed collection of information by emailing [email protected] . Identify all requests by the title of the information collection.

Description: The 2024 NSECE Longitudinal Follow-ups will consist of two nationally representative surveys drawing from 2024 NSECE respondents:

1. a survey of households (1) with incomes under 300 percent of the federal poverty level (FPL) and/or (2) who had used paid care by an individual in 2024 (2024 NSECE Household Follow-up)

2. a survey of individuals who were employed in 2024 in center-based ECE programs working directly with children in classrooms serving children age 5 years and under, not yet in kindergarten (2024 NSECE Workforce Follow-up).

Participants will be drawn from respondents to the 2024 NSECE Household and Workforce surveys.

The 2024 NSECE Longitudinal Follow-up data collection efforts will provide urgently needed information that will expand the potential of the 2024 NSECE data to describe: (1) households' search for and use of financial assistance for ECE (including assistance for paid individual care arrangements); and (2) employment experiences of individuals who have recently worked in center-based ECE classrooms.

The household follow-up in early 2025 will re-interview households participating in the 2024 NSECE who (1) report using paid individual ECE or (2) report incomes below 300 percent of the FPL. The workforce follow-up in late 2025 will re-interview individuals who participated in the 2024 NSECE workforce survey ( i.e., served as center-based classroom-assigned instructional staff between January and November 2024). Both follow-up surveys are designed to collect in-depth information that was not feasible to collect in the 2024 NSECE and which can be uniquely collected through re-interviews of selected 2024 NSECE participants. The household follow-up will include information about households' awareness of and experience with publicly funded ECE programs, how households selected ECE arrangements for Fall 2024, and who provided paid individual care to the households' children in 2024. The workforce follow-up will include information about the experiences of ECE instructional staff over time, where workers who leave ECE employers or the ECE sector go and why they leave, and workers' experiences in various ECE settings throughout their ECE careers. Accurate data on families with young children and the experiences of ECE workers are essential to assess the current landscape of ECE, and to provide insights to advance ECE policy and initiatives. The household follow-up will be fielded using multi-mode survey methodologies in early 2025, and the workforce follow-up will be fielded using multi-mode survey methodologies in the last half of 2025. Both follow-ups will enhance the value of the 2024 NSECE by expanding the potential utility of those data to describe household and worker experiences over time and to address additional information needs.

Respondents: 1. Households participating in the 2024 NSECE and reported either a. a paid individual ECE arrangement in 2024, or b. income under the 300 percent Federal poverty level in 2024. 2. Individuals who participated in the 2024 NSECE survey of center-based classroom-assigned instructional staff (workforce).

2024 NSECE Longitudinal Follow-ups (New Request Under This OMB Number)
Instrument	Number of respondents (total over request period)	Number of responses per respondent (total over request period)	Average burden per response (in hours)	Total/annual burden (in hours)
2024 NSECE Household Follow-up Questionnaire	3,750	1	.36	1,350
2024 NSECE Workforce Follow-up Questionnaire (Classroom Staff)	5,550	1	.33	1,832
2024 NSECE Household Longitudinal Follow-up Quality Assurance Questionnaire	38	1	.05	1.9
2024 NSECE Workforce Longitudinal Follow-up Quality Assurance Questionnaire	56	1	.05	2.8

Estimated Total Annual Burden Hours: 3,187.

Currently Approved and Ongoing Under This OMB Number
Instrument	Number of respondents (total over request period)	Number of responses per respondent (total over request period)	Average burden per response (in hours)	Total/annual burden (in hours)
2024 NSECE Household Screener	17,187	1	.1	1,719
2024 NSECE Household Questionnaire	4,231	1	1	4,231
2024 NSECE Home-based Provider Screener (listed home-based providers)	264	1	.03	8
2024 NSECE Home-based Provider Screener and Questionnaire (listed home-based providers)	946	1	.67	634
2024 NSECE Home-based Provider Screener and Questionnaire (unlisted home-based providers)	175	1	.33	58
2024 NSECE Center-based Provider Screener	4,401	1	.1	440
2024 NSECE Center-based Provider Screener and Questionnaire	3,602	1	.75	2,702
2024 NSECE Workforce (Classroom Staff) Questionnaire	3,794	1	.33	1,252

Estimated Total Annual Burden Hours: 11,044.

Authority: Child Care and Development Block Grant Act of 1990, as amended by the CCDBG Act of 2014 ( Pub. L. 113-186 ). Social Security Act, section 418 as extended by the Continuing Appropriations Act of 2017 and the TANF Extension Act of 2019. Section 3507 of the Paperwork Reduction Act of 1995, 44 U.S.C. chapter 35 .

Mary C. Jones,

ACF/OPRE Certifying Officer.

[ FR Doc. 2024-21210 Filed 9-17-24; 8:45 am]

BILLING CODE 4184-23-P

Executive Orders

Reader Aids

Information.

About This Site
Legal Status
Accessibility
No Fear Act
Continuity Information

IMAGES

The Relationship Between Education and Poverty
How Proper Education Will Help End Poverty
At what cost? Exposing the impact of poverty on school life
Rise in India’s Learning Poverty
The Link Between Poverty and Education: Can Education Be Used to
The impact of poverty on education

VIDEO

Is Passive Income The Answer?
Education (Fighting poverty)
CISE: Funding education for students in poverty
what is meant by poverty and what are the causes of poverty telugu || economics shatavahana
Lecture 2: Poverty Traps: Theory
Economics Chapter 4

COMMENTS

Understanding How Poverty is the Main Barrier to Education
Poverty is the most important factor that determines whether or not a girl can access education, according to the World Bank. If families cannot afford the costs of school, they are more likely to send boys than girls. Around 15 million girls will never get the chance to attend school, compared to 10 million boys.
How does education affect poverty? It can help end it.
Learn how a high-quality primary education can break the cycle of poverty and improve lives in developing countries. Concern USA offers education programs and other solutions to end poverty.
A World of Hardship: Deep Poverty and the Struggle for Educational
Learn how deep poverty affects children's learning, health, and well-being, and why accurate measures of poverty are essential for providing adequate services and resources. Explore the impact of COVID-19 on families and schools living in deep poverty, and the strategies to overcome the hardships and inequities.
Harvard study shows exactly how poverty impacts children's success
The study finds that exposure to lead, violence, and incarceration in poor neighborhoods predicts lower adult income and higher teen pregnancy for both black and white children. It suggests that environmental policy and criminal justice reform can be social mobility policy.
The transformative power of education in the fight against poverty
ZNotes is an online platform where students share notes and access educational resources for exams and career opportunities. Founded by Zubair Junjunia, a Generation17 young leader, ZNotes aims to break poverty cycles and empower youth with future skills and global citizenship.
The where, who, and what of poverty in schools: Re-framing the concept
Do all students have access to the "language of learning"? It is widely agreed that the relationship between poverty and education is bi-directional: poor people lack access to a decent education, and without the latter people are often constrained to a life of poverty (Van der Berg, 2008).Poverty as a "lifetime, and life-wide status" thus develops into a self-fulfilling prophecy that ...
The State of Global Learning Poverty: 2022 Update
The report reveals that COVID-19 has sharply increased learning poverty, a measure of children unable to read and understand a simple passage by age 10. It also provides a framework for countries to recover and accelerate learning after the pandemic.
70% of 10-Year-Olds now in Learning Poverty, Unable to Read and
The report reveals that 70% of 10-year-olds in low- and middle-income countries are unable to read and understand a simple text, due to school closures and income shocks. It also shows that learning poverty was higher than previously thought before the pandemic and calls for a national coalition for learning recovery and acceleration.
Reducing global poverty through universal primary and secondary education
The report shows how education is linked to the eradication of poverty and the achievement of the SDGs. It also provides the latest estimates on out-of-school children, adolescents and youth and the consequences of low education attainment.
The impact of poverty on educational outcomes for children
Educational outcomes are one of the key areas influenced by family incomes. Children from low-income families often start school already behind their peers who come from more affluent families, as shown in measures of school readiness. The incidence, depth, duration and timing of poverty all influence a child's educational attainment, along ...
Poverty and education
Absolute poverty - the absence of adequate resources - hampers learning in developing countries through poor nutrition, health, home circumstances (lack of books, lighting or places to do homework) and parental education. It discourages enrolment and survival to higher grades, and also reduces learning in schools.
Education Overview: Development news, research, data
Education is a human right, a powerful driver of development, and one of the strongest instruments for reducing poverty and improving health, gender equality, peace, and stability. It delivers large, consistent returns in terms of income, and is the most important factor to ensure equity and inclusion. For individuals, education promotes ...
Poverty's impact on educational opportunity
In other words, racial segregation remains a major source of educational inequality, but this is because racial segregation almost always concentrates black and Hispanic students in high-poverty schools, according to new research led by Sean Reardon, a professor at the Stanford Graduate School of Education (GSE) and a senior fellow at the ...
Poverty Impedes Children's Education Long Before They Enter The
Poverty is a cement barrier standing between low-income families and their ability to stimulate healthy early childhood development so their children can reap the full benefits of education.
Global poverty and education
facts & stats About World Poverty and Education. The research is conclusive: When we reduce barriers to education, we set children up to thrive. It's not only about knowledge and numbers, access to education reduces a child's involvement in gangs and drugs, and lowers the amount of teen pregnancies. Education leads to healthier childhoods ...
PDF Poverty and Education: Finding the Way Forward
While the primary focus of the report is on education, the broad array of non-education federal poverty programs is briefly described. U.S. anti-poverty policies frequently have been criticized in comparative research on their effectiveness in alleviating poverty, moderating income inequality, and promoting social mobility.
Where Has Poverty Gone?
Political polarization, the climate emergency, organized crime, migration, and low economic growth currently dominate the public debate in Latin America and the Caribbean (LAC), and rightly so. However, there is a significant structural challenge to human development and democracy itself that, along with inequalities, lies at the root of these crises: poverty. Today, 181 million …
Digitalisation and poverty in Latin America: a theoretical review with
The Economic Commission for Latin America and the Caribbean (CEPAL, 2022) reports that the number of people living in extreme poverty in this region increased to 86 million in 2021 as a ...
Effects of poverty, hunger and homelessness on children and youth
More specifically, 35.5% of Black people living in poverty in the U.S. are below the age of 18. In addition, 40.7% of Hispanic people living below the poverty line in the U.S. are younger than age 18, and 29.1% of American Indian and Native American children lived in poverty in 2018.
Educational Poverty in Japan
Educational Poverty in Japan. Friday Aug. 31, 2018. Every citizen in Japan is guaranteed the right to an education. But interviews conducted by NHK have revealed that some young people lack access ...
Poverty and economic decision making: a review of scarcity theory
As reflected in Fig. 1, scarcity theory contains a poverty cycle in which poverty itself causes poverty-reinforcing behaviors via specific psychological mechanisms (routes 1-2-7 and 5-6-7).Increased temporal discounting and overborrowing may ultimately reduce the overall payoff of the poor. Similarly, increased risk aversion can discourage long-term investments (e.g., in education or ...
What is Learning Poverty?
Learning poverty is the share of children who cannot read and understand a simple text by age 10, combining schooling and learning indicators. The World Bank and UNESCO estimate that 53 percent of children in low- and middle-income countries are learning-poor, and explain the concept, methodology, and implications of this crisis.
Impact of the COVID-19 pandemic on education
Tertiary education is normally taken to include undergraduate and postgraduate education, as well as vocational education and training. Individuals who complete tertiary education generally receive certificates, diplomas, or academic degrees. [290] For higher education, the preparation of the future workforce is a key priority.
Impact Rankings 2024: no poverty (SDG 1) methodology
This ranking focuses on universities' research on poverty and their support for poor students and citizens in the local community. View the methodology for the Impact Rankings 2024 to find out how this data is used in the overall ranking. Metrics. Research on poverty (27%) Field-weighted citation index of papers related to poverty (10%)
PDF Health, Wellbeing and Education: Building a sustainable future
promotion and education for sustainable development or climate change have common goals and fields of action. We therefore: • urge all stakeholders in health and climate/sustainability education to work together systematically to support young people to grow up and live healthily and sustainably;
Suriname at a Crossroads: Navigating Poverty, Inequality, and the
Poverty, Inequality, and the Education Gap. While economic recovery is underway, poverty and inequality remain deeply entrenched in Suriname. Ethnic and geographic disparities continue to divide the country, with poverty rates significantly higher in the rural interior. More than one in four Surinamese living in these regions falls below the ...
6 concerns Arizona schools have with Tom Horne, federal poverty funds
The U.S. Department of Education disburses set amounts to each state based in large part on census poverty data, then states distribute those dollars to districts and charter schools.
Submission for Office of Management and Budget (OMB) Review; 2024
SUPPLEMENTARY INFORMATION: Description: The 2024 NSECE Longitudinal Follow-ups will consist of two nationally representative surveys drawing from 2024 NSECE respondents: 1. a survey of households (1) with incomes under 300 percent of the federal poverty level (FPL) and/or (2) who had used paid care by an individual in 2024 (2024 NSECE Household Follow-up)

How does poverty affect education?

Why does poverty stop girls from going to school?

Can education help break the cycle of poverty?

How can we end extreme poverty through education?

Understanding How Poverty is the Main Barrier to Education

About . Click to expand section.

What We Do . Click to expand section.

Take Action . Click to expand section.

Donate . Click to expand section.

How does education affect poverty?

Go to the head of the class

1. Education is linked to economic growth

2. Universal education can fight inequality

Four ways that girls’ education can change the world

3. Education is linked to lower maternal and infant mortality rates

4. Education also lowers stunting rates

What is stunting?

5. Education reduces vulnerability to HIV and AIDS…

6. …and vulnerability to natural disasters and climate change

Climate change is one of the biggest threats to education — and growing

7. Education reduces violence at home and in communities

Fighting FGM in Kenya: A daughter's bravery and a mother's love

Education for all: Concern’s approach

More on how education affects poverty

6 Benefits of literacy in the fight against poverty

Child marriage and education: The blackboard wins over the bridal altar

Right to Learn

A World of Hardship: Deep Poverty and the Struggle for Educational Equity

Why Deep Poverty Matters for Educators

The Importance of Accurately Determining Eligibility for Increased Services

Blog Series: Learning in the Time of COVID-19

More From the Blog Series

Toward Educational Equity

Sign up for our mailing list

Featured Topics

Explore the Gazette

‘Could I really cut it?’

For this ring, I thee sue

Speech is never totally free

Unpacking the power of poverty

Study picks out key indicators like lead exposure, violence, and incarceration that impact children’s later success

More like this

Cities’ wealth gap is growing, too

Racial and economic disparities intertwined, study finds

Share this article

Harvard releases race data for Class of 2028

Parkinson’s may take a ‘gut-first’ path

High doses of Adderall may increase psychosis risk

The transformative power of education in the fight against poverty

Zubair Junjunia

Reducing global poverty through universal primary and secondary education

Related content

The impact of poverty on educational outcomes for children

POVERTY AND READINESS FOR SCHOOL

POVERTY AND EDUCATIONAL ATTAINMENT

REVERSING THE EFFECTS OF POVERTY

Early intervention

Highly regarded early interventions

Later intervention

Schools make a difference

WHAT CAN WE DO?

Poverty's impact on educational opportunity

More News Topics

Can global supply chains be fixed?

Presidential debate fact check: Analyzing Trump, Harris on abortion, immigration, more

Poverty Impedes Children’s Education Long Before They Enter The Classroom — Here’s How We Can Change That

Global poverty and education

Access to education

My order summary

INTER PRESS SERVICE

Where Has Poverty Gone?

Related Tags

Most popular

Digitalisation and poverty in Latin America: a theoretical review with a focus on education

Similar content being viewed by others

Scientometric analyses of digital inequity in education: problems and solutions

Inclusive education of refugee students with disabilities in higher education: a comparative case study

Digital transformation and digital literacy in the context of complexity within higher education institutions: a systematic literature review

Study context

Study design