Multidimensional Poverty Index — Explained

Detailed Explanation

The Multidimensional Poverty Index (MPI) represents a significant paradigm shift in how poverty is conceptualized and measured, moving beyond the unidimensional focus on income or consumption. This comprehensive framework offers a more nuanced understanding of deprivation, crucial for effective policy formulation and targeted interventions.

1. Origin and Historical Evolution

The genesis of the MPI can be traced back to the broader discourse on human development, which gained prominence with the introduction of the Human Development Index (HDI) in 1990 by the United Nations Development Programme (UNDP).

While HDI provided a composite measure of life expectancy, education, and standard of living, it was an aggregate national-level index and did not identify individual poverty or the specific deprivations faced by households.

The limitations of income-based poverty lines, such as the Tendulkar Committee or Rangarajan Committee recommendations in India, became increasingly apparent. These lines, while useful for identifying the monetary poor, failed to capture the non-monetary deprivations that often coexist with or even define poverty.

For a deeper understanding of traditional poverty line measurement, refer to .

In response to these limitations, the Oxford Poverty and Human Development Initiative (OPHI) and the UNDP jointly launched the Global Multidimensional Poverty Index (MPI) in 2010. This marked a critical evolution, providing an internationally comparable measure that identifies acute poverty at the individual level across more than 100 developing countries.

The Global MPI initially used data from Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), and other national surveys. Building on this global framework, India, through NITI Aayog, adopted and adapted the MPI methodology to create its National Multidimensional Poverty Index (National MPI) in 2021.

This adaptation was crucial to ensure the indicators and thresholds were relevant to the Indian context and utilized robust national data sources like the National Family Health Survey (NFHS). The National MPI serves as a crucial tool for monitoring India's progress towards Sustainable Development Goal (SDG) 1.

2, which aims to reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definitions by 2030. For a comprehensive Human Development Index comparison, refer to .

2. Constitutional and Policy Basis

While there isn't a specific constitutional article mandating the MPI, its underlying philosophy is deeply rooted in the Directive Principles of State Policy (DPSP) enshrined in Part IV of the Indian Constitution.

Articles like 38, 39, 41, 42, 43, and 47 emphasize the state's responsibility to secure a social order for the promotion of welfare, ensure adequate means of livelihood, provide public assistance in cases of unemployment, old age, sickness, and disablement, and raise the level of nutrition and standard of living.

The judiciary, through its interpretation of Article 21 (Right to Life), has also expanded its scope to include the right to live with dignity, encompassing access to basic necessities like food, water, shelter, health, and education.

The MPI, by measuring deprivations in these very dimensions, provides a quantifiable framework to assess the state's performance in fulfilling these constitutional mandates and upholding socio-economic justice.

The adoption of the National MPI by NITI Aayog underscores its importance as a key policy tool for development planning and resource allocation. For NITI Aayog's broader role in development policies, refer to .

3. Key Provisions and Calculation Methodology (Alkire-Foster Method)

The MPI is calculated using the Alkire-Foster (AF) method, which involves three key steps:

Step 1: Deprivation Identification: For each household and each of the 10 indicators, it is determined whether the household is deprived. Specific thresholds define deprivation for each indicator.

Step 2: Deprivation Score Calculation: Each indicator is assigned a weight. In the National MPI, the three dimensions (Health, Education, Living Standards) are equally weighted at 1/3 each. Within each dimension, indicators are equally weighted.

For instance, Health has three indicators, so each gets a weight of (1/3) * (1/3) = 1/9. Education has two indicators, so each gets (1/3) * (1/2) = 1/6. Living Standards has six indicators, so each gets (1/3) * (1/6) = 1/18.

A household's deprivation score is the sum of the weights of the indicators in which it is deprived.

Step 3: Poverty Identification (Dual Cutoff): A household is identified as multidimensionally poor if its deprivation score is equal to or greater than a specified poverty cutoff (k). For the Global and National MPI, k is typically 1/3. This means a household is poor if it is deprived in at least one-third of the weighted indicators.

Once poor households are identified, the MPI is calculated as the product of two components:

Headcount Ratio (H): — The proportion of people who are multidimensionally poor in the population. H = q/n, where q is the number of multidimensionally poor people and n is the total population.
Intensity of Deprivation (A): — The average deprivation score among the multidimensionally poor. A = (sum of deprivation scores of the poor) / q.
MPI = H * A

India's National MPI: Dimensions, Indicators, and Thresholds (NITI Aayog, based on NFHS-5 data):

A. Health (Weight: 1/3)

1
Nutrition (Weight: 1/9): — A household is deprived if any person under 59 months of age for whom nutritional information is available, or women between 15 and 49 years of age, or men between 15 and 49 years of age, has a BMI below 18.5 kg/m2 or if any child under 5 years of age is stunted, wasted, or underweight. [NFHS-5]
2
Child & Adolescent Mortality (Weight: 1/9): — A household is deprived if any child under the age of 18 years has died in the household in the five-year period preceding the survey. [NFHS-5]
3
Antenatal Care (Weight: 1/9): — A household is deprived if any woman who has given birth in the five-year period preceding the survey did not receive at least four antenatal care visits for her most recent birth. [NFHS-5]

B. Education (Weight: 1/3)

1
Years of Schooling (Weight: 1/6): — A household is deprived if no household member aged 10 years or older has completed at least six years of schooling. [NFHS-5]
2
School Attendance (Weight: 1/6): — A household is deprived if any school-aged child (up to the age of 18 years) is not attending school. [NFHS-5]

C. Living Standards (Weight: 1/3)

1
Cooking Fuel (Weight: 1/18): — A household is deprived if it cooks with dung, wood, or charcoal. [NFHS-5]
2
Sanitation (Weight: 1/18): — A household is deprived if it does not have an improved toilet facility or it is shared with other households. [NFHS-5]
3
Drinking Water (Weight: 1/18): — A household is deprived if it does not have access to improved drinking water or safe drinking water is at least a 30-minute walk from home (roundtrip). [NFHS-5]
4
Electricity (Weight: 1/18): — A household is deprived if it does not have electricity. [NFHS-5]
5
Housing (Weight: 1/18): — A household is deprived if it has inadequate housing materials in at least one of the three components: floor, roof, or walls. [NFHS-5]
6
Assets (Weight: 1/18): — A household is deprived if it does not own more than one of these assets: radio, TV, telephone, computer, animal cart, bicycle, motorbike, refrigerator, and does not own a car or truck. [NFHS-5]

Worked Numerical Example (Hypothetical Household):

Consider a household (HH1) with the following deprivations:

Nutrition: Deprived (Weight 1/9)
Child Mortality: Not Deprived
Antenatal Care: Deprived (Weight 1/9)
Years of Schooling: Deprived (Weight 1/6)
School Attendance: Not Deprived
Cooking Fuel: Deprived (Weight 1/18)
Sanitation: Deprived (Weight 1/18)
Drinking Water: Not Deprived
Electricity: Deprived (Weight 1/18)
Housing: Not Deprived
Assets: Deprived (Weight 1/18)

Deprivation Score for HH1: (1/9) + (1/9) + (1/6) + (1/18) + (1/18) + (1/18) + (1/18) = 2/9 + 1/6 + 4/18 = 4/18 + 3/18 + 4/18 = 11/18.

Since 11/18 (approx. 0.61) > 1/3 (approx. 0.33), HH1 is identified as multidimensionally poor.

Now, consider a sample district with 100 households. Suppose 20 households are identified as multidimensionally poor (q=20). The total population is 500 (n=500).

Headcount Ratio (H): — H = q/n = 20/500 = 0.04 (or 4%).
Suppose the sum of deprivation scores for these 20 poor households is 10.5.
Intensity of Deprivation (A): — A = (Sum of deprivation scores of poor) / q = 10.5 / 20 = 0.525.
MPI = H * A = 0.04 * 0.525 = 0.021.

4. Practical Functioning and Data Sources

In India, the National MPI is constructed using data from the National Family Health Survey (NFHS), specifically NFHS-4 (2015-16) for the baseline report (MPI 2021) and NFHS-5 (2019-21) for the progress report (MPI 2023).

NITI Aayog, as the nodal agency, is responsible for developing the methodology, calculating the index, and publishing reports. This robust data collection mechanism ensures that the MPI reflects ground realities and allows for disaggregation at state, district, and even sub-district levels, making it an invaluable tool for localized policy planning.

The MPI framework is also aligned with the global SDG 1 targets, enabling India to track its progress on international commitments. For a deeper understanding of SDG poverty targets and MPI alignment, refer to .

5. Criticism and Limitations

Despite its strengths, the MPI faces certain criticisms:

Data Lag: — The NFHS data, while comprehensive, is collected periodically (every 3-5 years), leading to a time lag in reporting. This means the MPI reflects past conditions, not real-time changes.
Indicator Selection and Thresholds: — The choice of indicators and their deprivation thresholds can be subjective and may not fully capture all aspects of poverty relevant to every community. For example, some argue that indicators like access to digital services or environmental quality could be included.
Intra-household Disparities: — The MPI identifies poor households, but it may not fully capture disparities within a household (e.g., gender-based deprivation).
Weighting Scheme: — The equal weighting of dimensions and indicators, while simplifying calculation, might not reflect the actual severity or priority of different deprivations in all contexts.
Exclusion of Income: — While a strength in moving beyond income, the MPI does not directly measure income poverty, which remains a critical aspect of deprivation.

6. Recent Developments and India's Performance

NITI Aayog published the 'National Multidimensional Poverty Index: A Progress Review 2023' based on NFHS-5 (2019-21) data, comparing it with the baseline report (MPI 2021) based on NFHS-4 (2015-16). Key findings include:

Significant Reduction: — India successfully reduced its MPI value from 0.117 in 2015-16 to 0.066 in 2019-21, marking a substantial decline. [NITI Aayog 2023]
Headcount Ratio: — The proportion of multidimensionally poor in India fell from 24.85% in 2015-16 to 14.96% in 2019-21, lifting approximately 135 million people out of multidimensional poverty during this period. [NITI Aayog 2023]
Intensity of Deprivation: — The intensity of deprivation among the poor improved from 47.14% to 43.92% during the same period, indicating that those who remain poor are experiencing fewer deprivations on average. [NITI Aayog 2023]
State-wise Performance (NITI Aayog 2023):

* Top 5 States (Lowest MPI): Kerala (0.000), Goa (0.001), Sikkim (0.003), Tamil Nadu (0.007), Punjab (0.008). * Bottom 5 States (Highest MPI): Bihar (0.347), Jharkhand (0.198), Uttar Pradesh (0.177), Meghalaya (0.109), Madhya Pradesh (0.108).

Fastest Reduction: — Uttar Pradesh, Bihar, Madhya Pradesh, Odisha, and Rajasthan recorded the fastest reduction in the proportion of MPI poor. [NITI Aayog 2023]
International Comparison: — India's MPI value of 0.066 (2019-21) places it favorably compared to some South Asian neighbors and developing economies. For instance, while India has made significant strides, countries like Sri Lanka (0.009 in 2016) and Bhutan (0.012 in 2017) had lower MPI values earlier. However, India's rate of reduction has been commendable, showcasing robust progress in poverty alleviation efforts. [UNDP/OPHI Global MPI Reports, various years]

7. Vyyuha Analysis: A Paradigm Shift and Policy Imperative

The Multidimensional Poverty Index is not merely another statistical tool; it represents a profound paradigm shift in India's approach to poverty alleviation. By moving beyond the traditional income-centric view, the MPI forces policymakers to confront the complex, interconnected nature of deprivations.

From a UPSC perspective, the critical examination angle here is how this shift influences the political economy of development. The adoption of MPI by NITI Aayog, a key policy think tank, signals a strong governmental commitment to a holistic welfare agenda.

It provides a robust framework for evidence-based policymaking, allowing for precise identification of deprived regions and specific deprivations, thereby enabling targeted resource allocation and scheme implementation.

This has significant budgetary implications, as funds can be directed more efficiently to address specific gaps in health, education, or living standards, rather than broad, untargeted programs. However, tensions can arise between MPI gains and persistent income inequality.

While MPI might show a reduction in headcount, income disparities could still widen, posing a challenge to inclusive growth. The MPI's strength lies in its ability to highlight the 'how' of poverty, pushing for a rights-based approach to development where access to basic services is seen as fundamental.

It also fosters inter-ministerial coordination, as improving MPI requires concerted efforts across health, education, sanitation, and energy ministries. This analytical lens is crucial for aspirants to understand the strategic importance of MPI in India's developmental trajectory and its role in shaping future policy directions.

8. Inter-Topic Connections

The MPI is intrinsically linked to several other critical topics in the UPSC syllabus:

Sustainable Development Goals (SDGs): — MPI directly monitors SDG 1 (No Poverty), particularly target 1.2. It also has strong linkages with SDG 2 (Zero Hunger), SDG 3 (Good Health and Well-being), SDG 4 (Quality Education), SDG 6 (Clean Water and Sanitation), SDG 7 (Affordable and Clean Energy), and SDG 11 (Sustainable Cities and Communities). For a deeper dive into SDG 1 targets, refer to .
Government Welfare Schemes: — The success in reducing MPI is largely attributable to the effective implementation of various central and state government schemes. These include PM-KISAN, Ayushman Bharat, Swachh Bharat Mission, Pradhan Mantri Ujjwala Yojana, Pradhan Mantri Awas Yojana, Jal Jeevan Mission, and Saubhagya. These schemes directly target the indicators of deprivation measured by the MPI. For an analysis of rural development schemes integration, refer to .
Economic Growth and Inequality: — While economic growth is essential for poverty reduction, the MPI highlights that growth alone is insufficient. Equitable distribution and access to basic services are equally vital. The MPI can reveal disparities even in growing economies, prompting policies to address inequality. For social sector spending analysis, refer to .
Data and Governance: — The reliance on NFHS data for MPI calculation underscores the importance of robust data collection and statistical agencies in effective governance and policy evaluation. NITI Aayog's role in this process is central. For NITI Aayog's role in MPI methodology, refer to .