Growing up in poverty triples young people s likelihood of becoming NEET

Billy Odell Tucker-Robinson Founder & Host — Banking With Billy Network • Intelligence Network • Data Science • AI Research • World News
Published: 2026-09-16T14:05:23.506Z • Permanent link

Persistent poverty has long been recognized as a significant obstacle to social mobility and economic stability, particularly for young people. A recent study by the Bank of England's data analysis unit revealed that growing up in poverty triples young people's likelihood of becoming not in education, employment or training (NEET) at 17 or 23. Specifically, the research found that individuals who experience persistent poverty from childhood are 3.3 times more likely to be NEET at 17, and 3.4 times more likely at 23. These alarming statistics are rooted in the harsh realities faced by millions of young people worldwide, who are struggling to break the cycle of poverty and achieve economic stability.

The consequences of persistent poverty on young people's lives are far-reaching and devastating. For instance, research by the UK's Office for National Statistics found that individuals who experience poverty in childhood are more likely to experience mental health issues, such as depression and anxiety, later in life. Furthermore, poverty can also limit access to quality education and job opportunities, perpetuating a cycle of disadvantage that can be difficult to escape. The British government's own data shows that young people from disadvantaged backgrounds are more likely to be enrolled in low-skilled or low-wage jobs, which can further exacerbate poverty.

To address the root causes of poverty and its impact on young people, policymakers and researchers are turning to innovative data-driven approaches. For example, the Bank of England's research uses machine learning algorithms to analyze large datasets and identify patterns that may indicate poverty. By leveraging these insights, policymakers can develop targeted interventions to support vulnerable young people and break the cycle of poverty. Moreover, the study's findings have significant implications for the development of education and job training programs, which must be tailored to meet the needs of young people from disadvantaged backgrounds.

The findings of this study have significant implications for the Data Sources domain, particularly in terms of research communities and policy environments. Companies such as LinkedIn and Indeed are already using data analytics to identify and support vulnerable young people, providing them with access to job training and education programs. Research institutions, such as the University of Oxford, are also using data-driven approaches to better understand the root causes of poverty and develop evidence-based solutions. However, more needs to be done to address the scale and complexity of the problem.

To effectively address the issue of poverty and its impact on young people, policymakers must prioritize data-driven decision-making and invest in targeted interventions that support vulnerable populations. This may involve working with companies, research institutions, and community organizations to develop and implement evidence-based solutions. For instance, the UK's government has already launched initiatives to support young people from disadvantaged backgrounds, such as the Apprenticeship Levy and the National Careers Service. However, more needs to be done to ensure that these programs are effective and targeted to meet the needs of vulnerable young people.

The issue of poverty and its impact on young people is part of a broader pattern of social and economic inequality that has been growing in recent years. Research by the World Bank has shown that poverty rates have increased in many countries, including the UK, in recent years, with the poorest 10% of the population experiencing the largest declines in income. Furthermore, the rise of automation and artificial intelligence has raised concerns about the impact of technological change on employment and social stability. In this context, the study's findings highlight the need for policymakers to prioritize data-driven decision-making and invest in targeted interventions that support vulnerable populations.