Topic: GS3 – poverty reduction
Introduction: Samuel Johnson’s Perspective and Amartya Sen’s Contribution
- Samuel Johnson highlighted that poverty undermines human happiness, destroys liberty, and affects the practice of virtues.
- Amartya Sen introduced a broader perspective on well-being, focusing on capabilities and functionings, emphasizing the importance of each capability in itself.
Issues with Conventional Measures of Poverty: UNDP’s Approach
- Conventional measures of poverty, based on income, are criticized for being narrowly focused on the scarcity of resources.
- UNDP’s Human Development Index (HDI) and the Multidimensional Poverty Index (MPI) use uniform weights, which Sen finds problematic.
Flaws in the MPI Story: India’s Poverty Reduction Claims
- Recent MPI estimates claim a near-halving of India’s national MPI value, indicating a significant reduction in poverty between 2015-16 and 2019-21.
- The reduction is questioned due to reliance on data from National Family Health Surveys (NFHS) 4 and 5, which face credibility issues, and the impact of COVID-19 is not adequately considered.
Critique of MPI Estimates: Methodological Concerns
- The MPI estimates are considered misleading and ill-informed due to inadequate data sources and the omission of critical factors such as the economic impact of the COVID-19 pandemic.
Analysis of MPI Covariates: Factors Influencing Poverty
- Covariate analysis focuses on factors such as per capita state income, urbanization, health and education expenditure, and the presence of criminal MPs.
- The most significant factor influencing MPI is higher per capita state income, but the drastic income decrease during the pandemic led to a spike in MPI.
- Urbanization contributes to higher MPI, driven by rural-urban migration and sub-standard living conditions.
- Both health and education expenditure are associated with lower MPI, with education having a more significant impact.
Selective Review of MPI Estimates: Discrepancies and State-Level Variations
- State-level analysis indicates discrepancies between official MPI estimates and alternative calculations, with a lower reduction in poverty according to the latter.
- Poverty appears to have risen in populous states like Uttar Pradesh, and state elections in Chhattisgarh, Rajasthan, and Madhya Pradesh show varying MPI trends.
Conclusion: Exaggeration of Success and Obfuscation of Poverty Measures
- The MPI exaggerates the success in poverty reduction and may obscure conventional measures, potentially presenting a contradictory story of poverty in India.
Question: Examine the methodological concerns and discrepancies in the recent National Multidimensional Poverty Index (MPI) estimates for India, and discuss how these challenges impact the assessment of poverty reduction efforts.