THE CONTEXT: The NITI Aayog and UNDP’s report on the Multidimensional Poverty Index raises critical discussions on poverty measurement in India. Government claims of poverty reduction contradict scholarly critiques on the validity of data considering the COVID-19 pandemic impact. This debate underscores an urgent need for transparent, accurate socioeconomic statistics to inform equitable policymaking.

ISSUES:

• The Reliability of Multidimensional Poverty Index (MPI) Data: There is a concern about the accuracy of the statistical methods and the credibility of the MPI data, especially given the contrast with the economic slowdown and the impact of the COVID-19 pandemic. Existence of unresolved theoretical and methodological questions concerning the measurement of multidimensional poverty.
• Projection Beyond Survey Data: Use of NFHS data for a limited period to project trends beyond the actual survey years raise questions about the validity of such forward projections.
• Disproportionate Economic Impact of the COVID-19 Pandemic on Poverty: Evidence suggests that lower-income groups experienced greater income losses during the pandemic, thus potentially increasing multidimensional poverty. Differential impact on income levels across various percentiles, with the poorest experiencing significant income drops.
• Non-monetary Deprivations: The pandemic exacerbated difficulties accessing essential services like education and healthcare, likely increasing multidimensional poverty. Increasing non-monetary educational, healthcare, and nutrition deprivations points to a rise in absolute and relative poverty measures.
• Challenges in Poverty Statistics: The suspension of consumption expenditure surveys since 2014 has led to a lack of updated and reliable data for accurate poverty measurement. There is a need for critical scrutiny of poverty and welfare statistics to avoid misleading conclusions.
• Political and Ideological Overtones in Poverty Measurement: There are accusations that the MPI data is being used to support a government narrative of successful poverty reduction rather than presenting an objective reality.
• Development Indices’ Limitations: Limitations are inherent in the chosen indicators and metrics used to construct development indices.
• Utility versus Deprivation Perspectives: The inadequacy of growth as a sole indicator of quality of life and the imperative for considering utility and deprivation in evaluating poverty. Poverty is a broader concept reflecting powerlessness and lack of opportunity rather than mere income levels.

THE WAY FORWARD:

• Revival and Improvement of Statistical Mechanisms: The government should prioritize reviving the consumption expenditure survey and regularly updating the census data to provide a reliable foundation for poverty assessment.
• Transparent Data Sharing and Accessibility: An institutional framework ensuring transparency and public accessibility of raw data can be effective. This would facilitate cross-verification and independent analysis, enhancing the conclusions’ credibility.
• Inclusion of Pandemic Impact in Data Modelling: Given the adverse economic impacts of the COVID-19 pandemic, new models should be developed to capture the multidimensional aspects of poverty that account for this shock.
• Multi-disciplinary Approach to Poverty: Addressing poverty requires understanding its multifaceted nature, involving economists, sociologists, public health experts, and other relevant professionals to encompass all dimensions of poverty.
• Policy Responsiveness: Design policies responsive to the ground realities captured through robust data and ensure that welfare programs are readjusted based on empirical evidence of their impact.
• Multipronged Poverty Assessment: There should be an incorporation of diverse methods for poverty assessment beyond income/expenditure, including indices that reflect real access to services and opportunities and acknowledge non-monetary deprivations.
• Expanding Social Protection Measures: The government should re-examine and expand social protection measures to shield the most vulnerable from economic shocks, such as those experienced during the pandemic.

THE CONCLUSION

The robust debate around the Multidimensional Poverty Index highlights the vital need for transparent, empirical data to shape effective policy. Addressing poverty in India with accurate metrics is crucial for directing welfare measures where they are most needed. Through this lens of critical evaluation and non-partisan methodology, future policies must be crafted to address the multifaceted nature of poverty truly.

UPSC PREVIOUS YEAR QUESTION

Q. Though there have been several different estimates of poverty in India, all indicate reduction in poverty levels over time. Do you agree? Critically examine with reference to urban and rural poverty indicators. (2015)

MAINS PRACTICE QUESTION

Q. Discuss the challenges and implications of using the Multidimensional Poverty Index (MPI) to measure poverty in India, considering the conflicting narratives and political influence on poverty statistics. What steps should be taken to ensure a depoliticized and analytically coherent discourse on poverty and social policy in the country? Explain.

SOURCE: https://thewire.in/economy/niti-aayog-poverty-covid

THE CONTEXT: The NITI Aayog released the ‘National Multidimensional Poverty Index: A Progress Review 2023’. However, the Union government’s claim that there is a significant decline in poverty in recent years based on Multidimensional Poverty Index (MPI) is being questioned.

MULTIDIMENSIONAL POVERTY INDEX (MPI)

• NITI Aayog is the nodal agency for the National MPI which ranks States and UTs based on their performance. It has been responsible for constructing an indigenised index for monitoring the performance of States and Union Territories (UTs) in addressing multidimensional poverty.
• It captures overlapping deprivations in health, education and living standards to ascertain multidimensional poverty.
• Each of the specific parameters under 3 broad categories is assigned a value to calculate what is called a ‘deprivation score’. The deprivation score is the sum of the weighted status of all the indicators for an individual  if it is more than 0.33, only then an individual is considered multidimensionally poor.

FINDING OF MPI, 2023:

• India has achieved a remarkable reduction in its MPI value and Headcount Ratio between 2015-16 and 2019-21. Uttar Pradesh (UP), Bihar, Madhya Pradesh (MP), Odisha and Rajasthan recorded steepest decline in number of MPI
• Improvement in nutrition, years of schooling, sanitation, and cooking fuel played a significant role in reducing the MPI
• The MPI estimates highlight a near-halving of India’s national MPI value and decline in the proportion of population in multidimensional poverty from 24.85% to 14.96% between 2015-16 and 2019-21.
• This reduction of 9.89 % in multidimensional poverty indicates that, at the level of projected population in 2021, about 135.5 million persons have escaped poverty between 2015-16 and 2019-21.
• Besides, the intensity of poverty, which measures the average deprivation among the people living in multidimensional poverty, reduced from 47.14% to 44.39%.

ISSUES IN MPI:

• Similar issues as UNDP’ HDI: United Nations Development Programme (UNDP) constructed an overall measure of human development with uniform weights of the three components. Following this methodology, NITI Aayog and the UNDP released recently a National Multidimensional Poverty Index/MPI: A Progress Review 2023. Hence, these reports suffer from the same flaws as the UNDP human development index aggregation with uniform weighting.
• Reliability on authenticity of data: The government had failed to provide access to authentic and unimpeachable data on many indicators. Rise in income alone cannot measure other dimensions of poverty such as access to healthcare, sanitation and transport. While the MPI should be seen in addition to data on income-level, the government was silent on income data. MPI relies upon National Family Health Survey (NFHS) 4 and NFHS 5, which are not detailed enough for its estimation. The government had not released a consumption expenditure survey conducted by the National Survey Organisation (NSO) in 2017-18. The NSO has announced consumption expenditure surveys for 2022-23 and 2023-24.
• Did not take into account pandemic situation: As a consequence of this pandemic, there was a huge economic shock from which the Indian economy has been struggling to recover. To illustrate, GDP growth has declined from 8% in 2015-16 to 3.78 % in 2019-20 and slumped -6.60 in 2020-21, as also per capita income. Country’s economy had not even gone back to the pre-pandemic level, this raises question of how such a large number of people had escaped poverty.

THE WAY FORWARD:

• Quality of data: There is a need to enhance the quality and availability of data on multidimensional poverty at more frequent intervals. It can be done by integrating the MPI into planning, budgeting, implementation and evaluation processes at all levels of government.
• Rigorous Analysis: There is a need of in-depth analysis of the parameters of multidimensional poverty at the national, State/UT, and district levels. It will help in development of the National MPI to act as public policy tool which monitors multidimensional poverty, informs evidence-based and focused interventions.
• Collaboration and coordination: There is a need to strengthen the coordination and convergence among different ministries, departments, agencies and stakeholders involved in addressing multidimensional poverty.
• Increase in investment: Government should focus on investments in critical areas as education, nutrition among others to eradicate poverty. It can be done through targeted policies, schemes, and developmental programmes rolled out at both the national and sub-national levels.
• Awareness: There is a need to increase the awareness and participation of civil society, media, academia and other actors in advocating for and monitoring multidimensional poverty reduction.

THE CONCLUSION:

Recently released MPI index have several lacunae which need reinterpretation to eradicate poverty with proper policy interventions. Consistent policy implementation across a diverse set of programmes and initiatives that have strong interlinkages will lead to a further reduction in deprivations across multiple indicators.

PREVIOUS YEAR QUESTION

Q.1 Though there have been several different estimates of poverty in India, all indicate a reduction in poverty levels over time. Do you agree? Critically examine with reference to urban and rural poverty indicators. (2015)

MAINS PRACTICE QUESTIONS

Q.1 Poverty impacts the social, economic and environmental aspects of the nation differently. Suggest the possible ways to eradicate poverty and achieve sustainable development goals in India.

Q.2 Recent assessment of poverty by Multidimensional Poverty Index (MPI) has been termed as flawed as the government estimates fail to paint an accurate picture of the realities. Critically analyse this statement.

SOURCE: https://www.thehindu.com/opinion/op-ed/multidimensional-poverty-index-reduction-under-the-nda-is-flawed/article67611818.ece#:~:text=Astonishingly%2C%20the%20MPI%202023%20estimates,%2D16%20and%202019%2D21.