Multidimensional poverty in India: decoding the Niti Aayog report | In Focus podcast

Summary

This discussion critiques India's Multi-Dimensional Poverty Index (MPI), highlighting its failure to accurately reflect the country’s economic realities, especially regarding unemployment and the unorganized sector. Professor Kumar argues that the decline of the unorganized sector, which employs millions, is not captured in official data, leading to inflated claims of poverty reduction. He emphasizes that focusing on outcomes—such as employment and income—rather than theoretical inputs is crucial for understanding poverty. Despite claims of India’s progress toward SDG targets, Kumar remains skeptical about the true economic growth and poverty reduction, particularly given the challenges faced by youth and women in the labor market.

Takeaways

• 😀 The Multi-Dimensional Poverty Index (MPI) does not fully capture the reality of poverty in India, as it mainly focuses on inputs, not outcomes.
• 😀 Unemployment is a critical factor in poverty but is not adequately reflected in the MPI, leading to an incomplete understanding of poverty levels.
• 😀 There are four types of unemployment in India: regular unemployment, disguised unemployment (especially in agriculture), underemployment, and discouraged workers.
• 😀 The decline of the unorganized sector is a significant issue, as it employs a large portion of India's workforce. Sectors like agriculture and trade are facing job losses due to mechanization and modernization.
• 😀 The official growth rate of 7% is misleading, as it reflects growth in the organized sector, while the unorganized sector is shrinking, which suggests a much lower real growth rate of 1-2%.
• 😀 Distress migration, where people move due to lack of employment opportunities, is an important indicator of the ongoing poverty and employment crisis.
• 😀 The rise of e-commerce and large retail chains is hurting small, neighborhood stores, which are a key employer in the unorganized sector.
• 😀 Mechanization in agriculture is increasing, which reduces employment opportunities for agricultural laborers and contributes to disguised unemployment.
• 😀 India is facing a high degree of youth unemployment, particularly among educated individuals in the age group of 15-29, exacerbating poverty and social inequality.
• 😀 Women’s labor force participation is low in India, and although it has recently increased, it remains much lower than the global average, which affects the overall poverty situation.
• 😀 To truly assess poverty, it is necessary to focus on outcomes (such as employment and income levels) rather than inputs (such as access to basic services). The MPI does not effectively address this.

Q & A

What is the main issue with the Multi-Dimensional Poverty Index (MPI) as discussed in the transcript?

The main issue with the MPI, as discussed in the transcript, is that it does not accurately capture key factors contributing to poverty, such as unemployment, underemployment, and the decline of the unorganized sector. This leads to misleading conclusions about the actual state of poverty in India.

Why is unemployment not considered a significant factor in the MPI for measuring poverty in India?

Unemployment is not considered a significant factor in the MPI because the index primarily focuses on inputs, such as education and basic living standards, rather than outcomes like actual employment status. Various forms of unemployment, like disguised unemployment and underemployment, are not captured, which are important indicators of poverty.

How does the decline of the unorganized sector affect poverty levels in India?

The decline of the unorganized sector, which includes sectors like small-scale businesses and agriculture, leads to higher unemployment and lower incomes, especially in rural areas. As this sector shrinks, more people face economic instability, exacerbating poverty, but this decline is not adequately reflected in national poverty measures.

What is disguised unemployment, and how does it impact poverty in India?

Disguised unemployment refers to a situation where individuals are technically employed, but their work is not productive or sufficient in terms of income. This is particularly common in agriculture, where mechanization reduces the need for human labor, contributing to low incomes and poverty in rural areas.

What does Professor Kumar argue about India's reported economic growth rate?

Professor Kumar argues that the reported 7% economic growth rate does not reflect the actual growth of the economy. He claims that the growth is mainly in the organized sector, while the unorganized sector is shrinking. As a result, the actual growth rate may be closer to 1-2%, which undermines claims of poverty reduction.

What role does e-commerce and mechanization play in the decline of the unorganized sector?

E-commerce and mechanization play a significant role in the decline of the unorganized sector. E-commerce has led to the closure of neighborhood stores, while mechanization in agriculture has reduced the need for human labor, both of which decrease employment opportunities in these sectors.

How does unemployment among youth and women contribute to poverty in India?

Unemployment among youth and women is a significant driver of poverty in India. Youth unemployment is high, especially among educated individuals aged 15 to 29. Additionally, women's labor force participation remains low, although it has slightly increased in recent years. These issues create economic instability and hinder poverty reduction.

Why does Professor Kumar question the government's claim of meeting SDG goals related to poverty reduction?

Professor Kumar questions the government's claim of meeting SDG goals related to poverty reduction because the data used to assess poverty is flawed. If unemployment and the shrinking unorganized sector are not captured in national statistics, any claims about reducing poverty or meeting SDG goals are based on inaccurate data.

What does Professor Kumar suggest should be the focus when measuring poverty?

Professor Kumar suggests that poverty measurement should focus on outcomes, such as actual unemployment rates, income levels, and the employment conditions of various sectors, rather than inputs like education and basic needs indicators. This approach would provide a more accurate reflection of poverty in India.

How does the lack of accurate data affect poverty measurement and policy making in India?

The lack of accurate data, particularly regarding unemployment and the unorganized sector, leads to misleading conclusions about the state of poverty. This can result in ineffective policies that do not address the root causes of poverty, such as the decline of rural employment and underemployment.