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Poverty Estimation and Methodology in India UPSC NOTE

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  Poverty Definition and Estimation in India Poverty has been traditionally measured by minimum expenditure needed for a basic calorie intak...

 Poverty Definition and Estimation in India

  • Poverty has been traditionally measured by minimum expenditure needed for a basic calorie intake, with updates every 5 years using national surveys.

  • Over time, there has been a divergence in data between consumption estimates from the National Sample Survey Office (NSSO) and National Accounts, leading to questions about data accuracy.

  • Multiple methods have been used to assess poverty, including the Tendulkar and Rangarajan committees, each proposing different poverty lines.

  • After 2011-12, India lacked official poverty estimates due to data gaps, leading to the use of alternative poverty measures like the Multidimensional Poverty Index (MPI).

  • There have been claims of a significant reduction in poverty based on different poverty lines, but the results depend heavily on data sources and the poverty line used.

Concerns with the 2023-24 Household Consumption Expenditure Survey (HCES) Data

  • The 2023-24 HCES shows significant changes in poverty levels, but concerns about data accuracy persist.

  • Over time, different recall periods for consumption data (such as 7 days for some items and 30 or 365 days for others) have made comparisons difficult.

  • These variations in recall periods (Uniform Reference Period, Mixed Reference Period, etc.) lead to different expenditure estimates and, in turn, different poverty line calculations.

  • The introduction of new methodologies in recent years (e.g., better data collection through multiple visits to households) may produce higher estimates of expenditure, reducing poverty numbers when applied to older poverty lines.

Rural vs Urban Poverty Trends and Consumption Patterns

  • Data indicates that the rural-urban consumption gap is shrinking, with rural areas showing improvement in consumption patterns.

  • While food expenditure historically dominated rural consumption, recent data suggests that rural areas now have a more diverse consumption basket, similar to urban areas.

  • Rural areas are benefiting from improved access to services, but a clear distinction between rural and urban areas is needed for more accurate poverty analysis.

  • If peri-urban areas were classified as urban, poverty estimates in urban areas might show a sharper decline.

Need for a Clear Methodology for Poverty Measurement

  • There is a call for a consistent methodology for estimating poverty, as discrepancies in poverty estimates can result from different data collection methods.

  • The need for a clear and agreed-upon poverty line remains a major point of discussion, with some suggesting an update based on the latest data.

  • International comparisons, such as the UNDP’s poverty line estimate of $2.15/day, suggest poverty levels in India are lower than some local estimates, but this doesn’t settle the debate on how to measure poverty accurately.

Criticism of Multidimensional Poverty Index (MPI)

  • The Indian MPI includes 12 indicators, while the UNDP MPI has 10, sparking debate about whether the inclusion of more factors in India’s MPI is valid.

  • Critics argue that adding more indicators may not necessarily improve poverty measurement, as some indicators are already achieved once and don’t indicate future deprivation.

  • There’s concern that the current MPI doesn’t measure income vulnerability or how income disparities might lead to future deprivation, limiting its effectiveness in capturing poverty over time.

  • The existing index may understate poverty by not accounting for vulnerabilities and by failing to reflect the dynamic nature of poverty, particularly in terms of fluctuating income levels.

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Learnerz IAS | Concept oriented UPSC Classes in Malayalam: Poverty Estimation and Methodology in India UPSC NOTE
Poverty Estimation and Methodology in India UPSC NOTE
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Learnerz IAS | Concept oriented UPSC Classes in Malayalam
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