The Hindu Editorial Summary

Editorial Topic 1: Poverty and Inequality Trends in India

GS-2, GS-3 Mains Exam : Poverty & Economy

Revision Notes

Basic Concept : Part-1

1.Uniform Reference Period (URP): Imagine asking people about their spending over the past 30 days only. This is URP, a simple method but potentially inaccurate for less frequent purchases.

  • In other Words : Uniform Reference Period (URP): This is a data collection method where people are asked to recall their consumption expenditure for a single, fixed timeframe. Typically, this period is 30 days. URP is simple to implement but might be inaccurate for purchases made less frequently.

2.Mixed Reference Period (MRP): MRP acknowledges some things are bought less often. It might ask about frequent items (food) in the past 30 days, but less frequent items (clothes) over a longer period (like a year). This provides a more nuanced picture.

  • In other Words :   Mixed Reference Period (MRP): MRP recognizes that some items are bought more often than others. It uses different recall periods for different categories. For example, people might be asked about everyday items like food for the past 30 days, while less frequent purchases like clothes could be reported based on the past year. This provides a more comprehensive picture of consumption habits.

3.Modified Mixed Reference Period (MMRP): MMRP is the most detailed. It assigns different recall periods to different categories. Imagine asking about everyday items (food) in the past 30 days, some things (clothes) in the past year, and very infrequent purchases (furniture) over an even longer span (maybe multiple years). This aims for the most accurate consumption picture.

  • In other Words :   Modified Mixed Reference Period (MMRP): MMRP is the most refined approach. It assigns specific recall periods to various spending categories. Imagine recollecting daily necessities (food) for the past month, occasional purchases (clothing) for the past year, and very rare items (furniture) over an even longer span (multiple years). MMRP aims for the most accurate representation of consumption patterns.


Basic Concept : Part-2

Important Committees on Poverty Estimation (without Data)

1.Task Force on Projections of Minimum Needs and Consumption Standards (1979)

  • Focus: Updated the poverty line considering inflation and changes in consumption patterns.
  • Conclusion: Revised the minimum calorie intake and included other essential items in the poverty line calculation.


2.Expert Group on Estimation of Proportion of Population Below Poverty Line (Lakdawala Committee, 1993)

  • Focus: Developed a methodology to estimate the number of people below the poverty line based on consumption expenditure data.
  • Conclusion: Introduced the concept of separate poverty lines for rural and urban areas, considering regional variations in consumption patterns.

3.Expert Group on Poverty Estimation Methodology (Tendulkar Committee, 2005)

  • Focus: Reviewed the Lakdawala Committee methodology and proposed revisions.
  • Conclusion: Recommended revising the poverty line based on mixed reference period (MRP) data for consumption expenditure, leading to a higher estimated poverty level compared to URP (uniform reference period) data used earlier.

4.Rangarajan Committee on Poverty Estimation (2011)

  • Focus: Further refined poverty line estimation methodology.
  • Conclusion: Introduced a modified mixed reference period (MMRP) approach for a more nuanced understanding of consumption patterns. This resulted in a lower poverty estimate compared to the Tendulkar Committee’s approach.


Back to the Editorial Analysis 

  • Data Source: Household Consumption Expenditure Survey (HCES) 2022-23 by National Sample Survey Office (NSSO)
  • Poverty Ratio Decline:
    • Rangarajan Committee Poverty Line: 29.5% (2011-12) to 10% (2022-23) – 1.77% points/year decline
    • Tendulkar Committee Poverty Line: 21.9% (2011-12) to 3% (2022-23) – 1.72% points/year decline
  • Inequality (Gini Coefficient):
    • Rural: 0.278 (2011-12) to 0.269 (2022-23) – 0.009 point decline
    • Urban: 0.358 (2011-12) to 0.318 (2022-23) – 0.04 point decline (More significant decline in urban areas)
  • Important Notes:
    • Poverty decline is significant but slower than 2004-05 to 2011-12 period.
    • Estimates depend on chosen poverty line.
    • NSSO changed data collection method (reference period) to improve consumption reporting.
    • Three consumption estimates exist based on recall period: URP, MRP, MMRP.
    • MMRP considered most accurate but requires consistent use for comparison.
    • Tendulkar Committee (1993-94, 2004-05) and Rangarajan Committee (2009-10, 2011-12) used MMRP for comparable estimates with 2022-23.
    • Maintaining the “appropriate mix” of recall periods is crucial for ongoing comparison.

Measurement Issues in Poverty Estimation

  • Tendulkar Committee (2004-05):
    • Adopted official urban poverty line based on Lakdawala Committee methodology (URP-based).
    • Converted it to MRP for estimation (considered less accurate).
    • Indirectly used Lakdawala’s calorie norms.
  • Public Expenditure:
    • Not fully captured in poverty line based on private consumption.
    • HCES 2022-23 attempted imputation for some public goods (e.g., subsidies).
    • Imputation has minimal impact on average monthly per capita expenditure (MPCE).
    • Need for better capture of public expenditure’s impact on poverty.

Note: Poverty likely declined, but measurement limitations exist. Public spending’s role needs better consideration.




The Hindu Editorial Summary

Smart Cities Mission – An Overview

GS-2 Mains Exam : Goverance

Revision Notes

Question : Discuss the significance of the pan-city approach in the Smart Cities Mission and explain its relevance in urban development.

Launched: June 25, 2015

  • Objective: Promote cities with core infrastructure, clean environment, and good quality of life through “smart solutions”

Smart City Definition (Lacks Universal Standard):

  • Emerged after 2009 financial crisis
  • Initially envisioned as tech hubs with advanced infrastructure

Mission Strategy:

  • Pan-city approach with at least one city-wide smart solution
  • Step-by-step area development in three models:
    • Retrofitting
    • Redevelopment
    • Greenfield

Core Infrastructure Elements:

  • Water supply
  • Electricity
  • Sanitation & waste management
  • Urban mobility & public transport
  • Affordable housing
  • IT connectivity & digitalization
  • Good governance (e-Governance & citizen participation)
  • Sustainable environment
  • Citizen safety & security (women, children, elderly)
  • Health & education


  • Centrally Sponsored Scheme (CSS)
  • Central Government: Rs. 48,000 crore over 5 years (Rs. 100 crore/city/year)
  • Matching contribution by State/ULBs (additional Rs. 1 lakh crore)


Smart Cities Mission: Concerns and Challenges

  • Flawed Selection Process:
    • 100 cities chosen competitively without considering diverse urban realities.
    • Ignored dynamic nature of Indian urbanization compared to the West.
  • Exclusionary Scheme:
    • Focused development on less than 1% of a city’s area.
    • State/local governments lack data to understand evolving community needs.
  • SPV Model Misalignment:
    • Designed SPV structure conflicted with 74th Constitutional Amendment, leading to governance objections.
  • Displacement and Disruption:
    • Smart city projects displaced low-income residents (street vendors) and disrupted public spaces.
  • Increased Flooding:
    • Infrastructure projects compromised natural water channels, making historically flood-free areas vulnerable.

Way Forward:

  • Data-Driven Approach:
    • Need a rational understanding of urban issues through systematic data collection.
  • Land Acquisition and Resettlement:
    • Facilitate smoother land acquisition for affordable housing and modern transportation with proper rehabilitation & resettlement.
  • Citizen Participation:
    • Involve citizens in policy, implementation, and execution as they are the ultimate beneficiaries.
  • Smart Leadership:
    • Requires collaborative leadership across all three levels of government.

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