Who Is Overlooked in Poverty Studies and Why It Matters

What is it about?

This study critically examines the prevailing methodologies and paradigms within poverty analysis across high-income countries, highlighting significant methodological issues that can lead to the underrepresentation of poverty. It argues that current poverty measurement approaches obscure the prevalence of poverty and exclude some of the most marginalized groups from income surveys, resulting in inaccurate poverty estimates and limited public understanding of poverty dynamics. The piece underscores the diminished validity of income surveys due to data quality and coverage issues, which exacerbate inaccurate representation of the lowest-income groups in official poverty statistics and policy evaluation. The research also explores how these data practices contribute to epistemic erasure: obscuring how state institutions and policies affect women, ethnic minorities, migrants and people with limiting health conditions. It critiques the normative judgments inherent in current data practices, which prioritize certain populations over others in welfare policy and politics. Ultimately, the research calls for a reassessment of data practices to better address and understand the causes and effects of deep poverty in high-income contexts.

Featured Image

Photo by De an Sun on Unsplash

Photo by De an Sun on Unsplash

Why is it important?

This study demonstrates how mainstream poverty analysis impacts on social scientific understanding of disadvantage across high-income countries. It addresses the limitations and biases in current data practices that obscure the realities and dynamics of deep poverty for certain social groups more than others. The work underscores the importance of revisiting these methods to enhance the accuracy of poverty measurement, and the responsiveness of social and public policy-making. Key Takeaways: 1. The research discusses how conventional poverty analysis methods obscure the prevalence and impact of deep poverty, particularly affecting visibility of the structural violence experienced by the most marginalized groups. 2. It argues that the exclusion of hyper-marginalized groups from income surveys undermines the accuracy of poverty estimates and public comprehension of its dynamics and causes. 3. The study presents a viewpoint on how data quality efforts paradoxically worsen the representation of the lowest-income groups, leading to policy blindness towards deep poverty and its effects.