State of Inequality in India
Kartavya Desk Staff
Syllabus: Poverty and Issue
Source: TH
Context: A recent World Bank report claims that India has one of the lowest inequality levels globally, citing a fall in the Gini coefficient of consumption inequality from 0.288 (2011-12) to 0.255 (2022-23).
• However, multiple studies, including the World Inequality Database, contradict this, pointing to rising income and wealth inequality in India.
About State of Inequality in India:
Understanding the Types of Inequality:
• Consumption Inequality: Measures differences in spending patterns across households. Reported low by World Bank, but generally understates actual inequality. India’s falling Gini here may reflect greater consumption smoothing, not real income redistribution.
• Measures differences in spending patterns across households.
• Reported low by World Bank, but generally understates actual inequality.
• India’s falling Gini here may reflect greater consumption smoothing, not real income redistribution.
• Income Inequality: Refers to disparities in earnings and wages across individuals or households. Gini coefficient for income in India (WID 2023): 0.61, among the highest globally (only 47 countries are more unequal). Significantly higher than official estimates due to underreporting in household surveys.
• Refers to disparities in earnings and wages across individuals or households.
• Gini coefficient for income in India (WID 2023): 0.61, among the highest globally (only 47 countries are more unequal).
• Significantly higher than official estimates due to underreporting in household surveys.
• Wealth Inequality: Captures concentration of asset ownership, like property, shares, or savings. India’s wealth Gini: 0.75 in 2023 (WID), showing extreme wealth concentration.
• Captures concentration of asset ownership, like property, shares, or savings.
• India’s wealth Gini: 0.75 in 2023 (WID), showing extreme wealth concentration.
Calculating Real Inequality Is Difficult in India:
• Survey Limitations: Household Consumption Expenditure Surveys (HCES) miss high-income earners and under-report savings and property. Methodological differences between 2011–12 and 2022–23 surveys hinder time-series comparison.
• Household Consumption Expenditure Surveys (HCES) miss high-income earners and under-report savings and property.
• Methodological differences between 2011–12 and 2022–23 surveys hinder time-series comparison.
• Tax Data Exclusion: Only 6 crore individuals file income tax (CBDT data), leaving out vast informal income sources.
• Lack of Wealth Census: India has no systematic wealth census—data is derived from proxies like Forbes lists, SEBI filings, and real estate prices.
• Underestimation Bias: Richest individuals tend to under-report, and top wealth segments are statistically invisible in sample surveys.
Limitations of the Gini Coefficient:
• Aggregate measure—hides the intensity of concentration.
• Does not show wealth held by top 0.1% or bottom 50%.
• Needs to be supplemented with Top 1% wealth share, P90/P10 ratios, or Theil index.
Implications of High Inequality for India:
• Reduced Economic Mobility: Limits upward movement for bottom 50% of population.
• Lower Aggregate Demand: Savings of the rich do not translate into proportional spending.
• Social Fragmentation: Fuels resentment, political polarisation, and unrest.
• Distorted Policy Outcomes: Excess influence of elite groups on taxation, subsidies, and land use.
• Skewed Growth Patterns: Benefits of GDP growth accrue disproportionately to top 10%.
Constitutional and Policy Context:
• Article 38(2): Mandates state to minimize inequalities in income and opportunities.
• DPSP Article 39(c): Prevents concentration of wealth and means of production.
• Schemes: MGNREGA, PM-SVANidhi, PM-KISAN, JAM Trinity—aim to reduce inequality but suffer from poor targeting and leakage.
Way Ahead:
• Progressive Taxation: Reintroduce wealth and inheritance taxes on ultra-rich to reduce concentration and expand fiscal space.
• Universal Public Services: Increase public investment in health, education, and nutrition to equalize life opportunities.
• Formal Financial Access: Expand low-cost credit access and borrower safeguards to reduce dependence on informal lenders.
• Skilling & Jobs: Align skilling with market demand and promote job-rich sectors to uplift lower-income groups.
• Better Data: Integrate tax, survey, and asset records to publish accurate inequality metrics beyond consumption data.
Conclusion:
Addressing inequality is essential not just for social justice but for sustaining long-term economic growth. India’s structural disparities demand bold reforms in taxation, public provisioning, and data transparency. Only inclusive development can ensure equitable prosperity in the decades ahead.