UPSC MainsECONOMICS-PAPER-II202220 Marks
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Q9.

Do you think that Multi Dimensional Poverty Index (MPI) is a better measure of poverty? Give reasons in support of your answer. What is the position of India in respect of MPI?

How to Approach

This question requires a comparative analysis of poverty measurement methodologies, specifically focusing on the Multi-Dimensional Poverty Index (MPI). The answer should begin by defining traditional poverty measures and then explain MPI, highlighting its advantages. A discussion on India’s performance based on MPI data is crucial. The structure should be: Introduction defining poverty & MPI, Body comparing MPI with other measures, India’s MPI position with recent data, and Conclusion summarizing the benefits of MPI and suggesting improvements.

Model Answer

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Introduction

Poverty, at its core, represents a deprivation of essential needs and opportunities. Traditionally, poverty has been measured using a unidimensional approach, primarily focusing on income or consumption expenditure. However, this approach often fails to capture the multifaceted nature of poverty. The Multi-Dimensional Poverty Index (MPI), developed by the Oxford Poverty and Human Development Initiative (OPHI) and the United Nations Development Programme (UNDP) in 2010, offers a more comprehensive understanding of poverty by considering multiple deprivations at the individual level. It assesses poverty based on indicators related to health, education, and standard of living, providing a more nuanced picture than solely relying on monetary measures.

Understanding Poverty Measurement: A Comparative Analysis

Traditional poverty measures, like the Head Count Ratio (HCR) which calculates the percentage of the population below a defined poverty line, are simple to understand and implement. However, they suffer from limitations. They don’t account for the intensity of poverty – how far below the poverty line a household is – nor do they consider non-monetary aspects of deprivation. The Poverty Gap Index attempts to address intensity, but still remains income-focused.

The MPI, in contrast, adopts a multi-dimensional approach. It identifies individuals as ‘multi-dimensionally poor’ if they are deprived in a certain proportion of weighted indicators. These indicators are grouped into three dimensions:

  • Health: Nutrition, Child Mortality
  • Education: Years of Schooling, School Attendance
  • Standard of Living: Electricity, Sanitation, Drinking Water, Flooring, Cooking Fuel, Assets

Each indicator is given a weight, and a deprivation score is calculated for each household. A household is considered multi-dimensionally poor if its deprivation score exceeds a pre-defined threshold. This allows for a more granular understanding of poverty, identifying specific areas of deprivation within a population.

Why MPI is a Better Measure

Several reasons support the claim that MPI is a better measure of poverty:

  • Comprehensive Assessment: MPI captures the overlapping deprivations experienced by individuals, providing a more holistic picture of poverty.
  • Targeted Interventions: By identifying specific deprivations, MPI helps policymakers design targeted interventions to address the root causes of poverty. For example, if a region shows high deprivation in sanitation, resources can be directed towards improving sanitation facilities.
  • Monitoring Progress: MPI allows for tracking progress in reducing poverty across different dimensions, providing a more nuanced understanding of development outcomes.
  • Reflects Human Development: MPI aligns with the broader concept of human development, recognizing that poverty is not just about income but also about access to essential services and opportunities.

India’s Position in Respect of MPI

India has made significant strides in reducing multi-dimensional poverty. According to the latest Global MPI 2023 report (based on data up to 2019-21), released by the OPHI and UNDP:

  • 16.7% of the population (230.6 million people) are multi-dimensionally poor. This is a substantial decline from 27.7% in 2015-16.
  • India is home to nearly one-fourth of the 1.1 billion people globally who are multi-dimensionally poor. Sub-Saharan Africa remains the region with the highest MPI value.
  • Bihar has the highest proportion of multi-dimensionally poor people at 34.7%, followed by Meghalaya (32.6%) and Uttar Pradesh (30.7%).
  • Significant reductions in deprivation in all indicators were observed, particularly in access to electricity, improved cooking fuel, and sanitation.

However, challenges remain. Regional disparities are significant, and certain groups, such as Scheduled Tribes and Scheduled Castes, experience higher levels of multi-dimensional poverty. Furthermore, the MPI data is often lagged, meaning it doesn’t fully reflect the impact of recent shocks like the COVID-19 pandemic and subsequent economic disruptions. The National Multidimensional Poverty Index (NMPI) released by NITI Aayog in 2023 provides a more granular picture at the district level, aiding in targeted policy interventions.

Indicator 2015-16 (%) 2019-21 (%)
National MPI 27.7 16.7
Bihar 51.9 34.7
Uttar Pradesh 37.7 30.7

Conclusion

The Multi-Dimensional Poverty Index represents a significant advancement in poverty measurement, offering a more comprehensive and nuanced understanding of deprivation than traditional income-based measures. India’s progress in reducing MPI is encouraging, but sustained efforts are needed to address regional disparities and ensure that the benefits of development reach all segments of the population. Further refinement of the MPI, incorporating more relevant indicators and utilizing real-time data, will enhance its effectiveness as a tool for poverty reduction and inclusive growth.

Answer Length

This is a comprehensive model answer for learning purposes and may exceed the word limit. In the exam, always adhere to the prescribed word count.

Additional Resources

Key Definitions

Head Count Ratio (HCR)
The Head Count Ratio is a simple measure of poverty that calculates the percentage of the population living below a specified poverty line.
Multidimensional Poverty
Multidimensional poverty refers to the deprivation of multiple basic needs simultaneously, encompassing aspects like health, education, and living standards, rather than solely focusing on income.

Key Statistics

Globally, 1.1 billion people (18.4% of the world’s population) are living in multi-dimensional poverty as of 2023.

Source: Global MPI 2023 Report, OPHI & UNDP

Between 2015/16 and 2019/21, India lifted 415 million people out of multidimensional poverty.

Source: Global MPI 2023 Report, OPHI & UNDP (as of knowledge cutoff)

Examples

Kerala’s Success Story

Kerala, India, has achieved remarkable progress in reducing multi-dimensional poverty through investments in education, healthcare, and social welfare programs. This demonstrates the effectiveness of a multi-pronged approach to poverty reduction.

Frequently Asked Questions

Does MPI replace the traditional poverty measures?

No, MPI complements traditional poverty measures. While income-based measures remain important for understanding economic well-being, MPI provides a more holistic picture of deprivation and helps identify specific areas for intervention.

Topics Covered

EconomySocial IssuesPovertySocial IndicatorsEconomic Development