Analysing the rising gap in incomes

There are certain discrepancies in the recent report by the State Bank of India (SBI) which highlights that India has witnessed a significant fall in inequality over the last decade.

Key Concerns with the Report –

• Challenges in Data Analysis:
  • The analysis is based on taxpayer data, presenting challenges as a significant portion of income-earners falls below the tax threshold.
  • Preliminary nature of the study necessitates further research to account for potential errors, self-reporting issues, and seasonal adjustments.
• Gini Coefficient Trends (2017-18 to 2022-23)

• • The Gini coefficient, representing income inequality, decreased from 0.4297 to 0.4197 during the period.
  • Disaggregated by employment type, the Gini coefficient fell for regular wage and casual wage workers but rose slightly for the self-employed.

• Polarisation in Income Growth
  • An analysis of decile-wise income growth reveals a polarisation trend, especially among self-employed workers.
  • While the majority experienced healthy income growth (8%-9%), the top 10% saw a rate of around 7.23%, outpacing the bottom 20% with only 1.67% growth.

• 90/10 Ratio and Self-Employed Divergence
  • The 90/10 ratio, measuring income gap between the top and bottom 10%, increased from 6.7 to 6.9.
  • Notably, the 90/10 ratio significantly rose for self-employed individuals, with the income of the top 10% being 8.3 times that of the bottom 10%.

• Impact of Women's Labor Force Participation
  • The rise in women's labor force participation, primarily in low-paid, part-time self-employed work, contributes to increased income gaps among the self-employed.
  • While overall Gini coefficient reduction suggests lower inequality, the divergence in self-employed incomes contradicts this trend.

Consequences of Discrepancies in Income Inequality Studies

• Policy Misdirection:
  • Inaccuracies in studies can lead to misguided policy decisions, hindering effective strategies to address income inequality.
• Public Trust Erosion:
  • Conflicting findings may erode public trust, creating skepticism about the severity of income inequality and impeding support for necessary interventions.
• Inequality Denial:
  • Discrepancies provide room for denial, hindering efforts to tackle root causes and promote social and economic justice.
• Resource Allocation Challenges:
  • Challenges in resource allocation arise, with policymakers struggling to distribute resources effectively based on inconsistent data.
• Benchmarking Difficulty:
  • Establishing benchmarks for measuring progress becomes challenging, impeding the assessment of policy impact over time.
• Impact on Research:
  • Persistent discrepancies may slow progress in understanding income inequality dynamics within the academic community.
• Ineffective Advocacy:
  • Advocacy efforts are weakened as inconsistent data hampers the ability to strengthen arguments and mobilize support for change.
• Global Cooperation Hurdles:
  • Global comparisons and cooperation face obstacles due to inconsistent data, hindering coordinated strategies to address income disparities globally.