Multidimensional Poverty Index reduction under the NDA is flawed (The Hindu)

  • 08 Dec 2023

Why is it in the News?

The Multidimensional Poverty Index exaggerates the National Democratic Alliance’s success in fighting deprivation.

Context:

  • Some critics argue that the initiatives undertaken by the NDA Government might not have comprehensively tackled the various dimensions of poverty.
  • Additionally, there are concerns that the reported successes may not be accurately reflected in the Multidimensional Poverty Index (MPI), raising questions about its alignment with the ground reality of deprivation.
  • It is crucial to delve deeper into the methodologies and criteria employed for measuring multidimensional poverty to ascertain their resonance with the nuanced challenges confronted by the population.
  • Nobel Laureate Amartya Sen introduced a comprehensive and innovative outlook on well-being, emphasizing capabilities and functionings, commonly referred to as the capability approach.

What is Amartya Sen's Capability Approach?

  • Amartya Sen's Capability Approach serves as a normative framework for assessing individual well-being and societal arrangements.
    • Rather than focusing on happiness, preferences, or resources, this approach directs attention to the genuine opportunities and freedoms available to individuals in realizing lives aligned with their values.
  • Sen's Capability Approach comprises two central elements: functionings and capabilities.
    • Functionings represent valuable states of being and doing that an individual can attain, such as good health, education, or social engagement.
    • On the other hand, capabilities encompass the array of alternative functionings that individuals can choose from within their personal and social contexts.
  • Illustratively, an individual's capability may extend to being either well-nourished or undernourished, contingent upon factors like access to food and dietary choices.
    • Sen argues that the capability approach offers a superior means of evaluating human welfare compared to other approaches like utilitarianism and resourcism, which he deems either excessively narrow or insufficiently attuned to the diversity and intricacy of human experiences.
  • Utilitarianism centres around choices leading to the greatest happiness or satisfaction of desires, while resourcism concerns the distribution of resources like income, wealth, or goods in society.
    • According to Sen, the ultimate aim of development should be the expansion of people's capabilities, surpassing mere considerations of income or utilities.
  • Amartya Sen's Capability Approach has notably influenced the development of the Human Development Index.

What is the Human Development Index (HDI)?

  • HDI serves as a statistical tool employed to assess a country's overall achievements across its social and economic dimensions.
  • It is published by the United Nations Development Programme (UNDP).
  • It stands as the second most widely utilized indicator for gauging economic progress, following national income statistics (GDP).
  • Components: HDI comprises three key components, namely:
    • Health, quantified by life expectancy at birth;
    • Education, determined by a combination of mean years of schooling and expected years of schooling; and
    • Income, evaluated by gross national income per capita (at purchasing power parity).
  • Calculation: The ultimate score is computed as a geometric mean of the aforementioned three categories.

What is the Multidimensional Poverty Index (MPI)?

  • The Multidimensional Poverty Index (MPI) is an indicator of poverty that takes into account diverse aspects of well-being, extending beyond monetary considerations or income alone.
    • Originating from collaborative efforts between the Oxford Poverty and Human Development Initiative (OPHI) and the United Nations Development Programme (UNDP), the MPI offers a holistic perspective on poverty by incorporating a range of factors contributing to deprivation.
  • In assessing poverty, the MPI identifies individuals or households as multidimensionally poor when they experience deprivation across various indicators within different dimensions of well-being.
    • These dimensions typically encompass health, education, and the standard of living. By considering a broad spectrum of factors, the MPI provides a nuanced and comprehensive understanding of poverty.

What is the Current Status of MPI?

  • Regrettably, the United Nations Development Programme (UNDP) has chosen to adopt a capabilities-based approach to formulate a comprehensive measure of human development, applying uniform weights to the three primary components—health, education, and standard of living, along with their sub-indices.
    • Under this methodology, both NITI Aayog and the UNDP recently released the National Multidimensional Poverty Index/MPI: A Progress Review 2023, mirrored in the UNDP Report titled "Making Our Future: New Directions for Human Development in Asia and the Pacific," unveiled on November 7, 2023.
  • However, these reports share the same shortcomings as the UNDP human development index, primarily stemming from aggregation with uniform weighting.
    • Notably, the narrative surrounding the MPI exacerbates these distortions.
  • Surprisingly, the MPI 2023 estimates indicate a nearly halved value for India's national MPI and a decline from 24.85% to 14.96% between 2015-16 and 2019-21.
    • This substantial reduction of 9.89 percentage points suggests that approximately 135.5 million people have transitioned out of poverty during this period.
    • Furthermore, the intensity of poverty, gauging the average deprivation among individuals in multidimensional poverty, decreased from 47.14% to 44.39%.

Why the Reduction in MPI Numbers Under the Current Government is Flawed?

  • Misleading and Inadequate Information: The MPI relies on data from the National Family Health Surveys (NFHS) 4 and 5, which are deemed insufficiently detailed for accurate estimation.
    • NFHS 5 data is particularly questionable due to its suppression, driven by discrepancies in open defecation estimates conflicting with official claims of complete elimination.
  • Ideally, combining NFHS 4 and 5 with the 75th Round of the National Sample Survey (NSS) on household consumption expenditure should have provided a more comprehensive perspective.
    • However, this was abandoned as leaked poverty estimates indicated an increase.
  • Compounding the skepticism is the profound impact of the COVID-19 pandemic in 2020-21.
    • The widespread loss of livelihoods, reverse migration fatalities, and inadequate access to vaccines and medical care have created a substantial economic shock, hindering India's recovery.
    • For instance, GDP growth has plummeted from 8% in 2015-16 to 3.78% in 2019-20, reaching -6.60% in 2020-21, along with a decline in per capita income.
  • Greater Emphasis on Covariates: Comparing the elasticities of MPI with respect to various covariates reveals that the most significant reduction in MPI is attributed to higher State per capita income.
    • However, due to a drastic income decrease, MPI has spiked.
    • Urban location follows in importance, with a 1% increase resulting in a 0.90% MPI increase, reflecting the challenges associated with rural-urban migration and the growth of substandard living conditions.
  • Both healthcare and education expenditure are associated with lower MPI, with education exhibiting a higher elasticity, implying that a 1% increase in education spending reduces MPI more than a comparable increase in healthcare spending.
  • Reduction Between 2015 and 2019-21 is Considerably Lower than the Official Estimate:
    • Some research suggests that the reduction between 2015 and 2019-21 is notably lower than the official estimate, standing at 4.7 percentage points compared to the reported 9.89 percentage points.
    • A selective review of MPI estimates indicates a rise in poverty in Uttar Pradesh, India's most populous state, by over seven percentage points.
    • Among states that went to elections in November (Chhattisgarh, Madhya Pradesh, Mizoram, Rajasthan, and Telangana), MPI fell in Chhattisgarh (by over six percentage points), in Rajasthan (by two percentage points), and significantly in Madhya Pradesh (by about eight percentage points).

What Steps Should Be Taken in order to Improve MPI?

  • Adjustment for Income Variability: Given the substantial decrease in State per capita income causing a surge in MPI, consider implementing mechanisms to account for income fluctuations.
    • This may involve incorporating smoothing techniques or introducing a lagged income variable to capture economic effects over time.
  • Dynamic Impact of Urban-Rural Migration: Recognize the dynamic impact of factors on urban locations, particularly in light of the reverse migration during the COVID-19 pandemic.
    • Develop models that reflect changing patterns of rural-urban migration and its influence on living conditions and MPI.
  • Focus on Education Expenditure: Emphasize expenditure on education, as both healthcare and education spending are linked to lower MPI.
    • Notably, the elasticity of education is higher, suggesting that a 1% increase in education reduces MPI more than a comparable increase in healthcare.
    • Given the reported decline in state-level educational expenditure, a rise in MPI is likely.
  • Mitigate the Impact of MPs with Criminal Cases: Recognize and address the correlation between the share of Members of Parliament with criminal cases and higher MPI.
    • Explore strategies such as policy initiatives to curb corruption, enhance transparency, and address challenges posed by criminal elements within legislative bodies.
    • Studies indicate that when the share of MPs with criminal cases exceeds 20%, the MPI tends to be higher.
  • Sensitivity Analysis: Conduct sensitivity analyses to test the robustness of the MPI model.
    • This involves varying key parameters to understand how changes in inputs impact results, providing insights into the stability and reliability of MPI calculations.
  • Policy Recommendations: Utilize findings to inform policy recommendations targeting identified drivers of poverty.
    • Advocate for policies promoting income stability, targeted investments in education and healthcare, and measures to combat corruption and criminality within legislative bodies.

Conclusion

Enhancing the Multidimensional Poverty Index (MPI) requires proactive measures. Addressing income variability, acknowledging dynamic urban-rural migration impacts, and prioritizing education expenditure is pivotal. Additionally, mitigating the influence of MPs with criminal cases and conducting sensitivity analyses for robustness are essential steps. Ultimately, informed policy recommendations should focus on promoting income stability, targeted investments in education and healthcare, and tackling corruption to advance holistic poverty reduction strategies.