District level data reveals India’s unequal economic growth

Source: The post District level data reveals India’s unequal economic growth has been created, based on the article “Growth: A district-led approach” published in “Businessline” on 24 May 2025. District level data reveals India’s unequal economic growth.

UPSC Syllabus Topic: GS Paper3-Growth and Development

Context: India’s headline GDP growth hides regional disparities. District Domestic Product (DDP) data shows that a few districts drive most of the economy, while many areas remain underdeveloped. This undermines inclusive growth and highlights the need for granular policy planning.

Regional Concentration of Economic Output

1. Skewed Contribution Across States: A few districts dominate their State’s economic activity. In Uttarakhand, Haridwar, Udham Singh Nagar, and Dehradun generate 71% of the GSDP, while the other 10 districts contribute less than 30%. In Karnataka, Bengaluru alone produces 38%, with the next highest district at just 5.5%. In Maharashtra, Mumbai, Thane, Pune, and Nagpur account for over 60% of total output.
2. National Pattern of Imbalance: This is common across India. The top 10% of districts generate 50–60% of State output, while hundreds of others contribute only marginally. Even in Madhya Pradesh, Indore contributes 6.7%, double or triple the average of other districts.

Consequences of Economic Concentration

1. Migration and Urban Strain: Uneven growth drives large-scale migration to urban centres, leading to housing shortages, poor infrastructure, and growth in informal jobs.
2. Low Investment in Lagging Districts: Left-behind districts receive less investment in infrastructure and human capital, keeping them trapped in low-productivity and low-income cycles.
3. Misleading Aggregated Data: State or national GDP figures mask internal disparities. Without district-level visibility, policies can be misaligned and ineffective.

Challenges in Measuring District Economies

1. Outdated Distribution Methods: Many States do not directly measure DDP. Instead, State GDP is allocated using outdated formulas, missing the real economic picture.
2. Uncounted Informal Economy: In underdeveloped areas, informal work like small-scale manufacturing and services is not surveyed, leading to underestimation of actual activity.
3. Misreading Inequalities: The issue is not overstating inequalities but failing to grasp their real depth and distribution due to poor data systems.

The Need for District-Led Development

1. Reforming Data Infrastructure: DDP must be estimated annually using real data, with sectoral Gross Value Added (GVA) for agriculture, manufacturing, services, and informal sectors.
2. Regular Local Surveys: Frequent surveys of labour and unincorporated enterprises can accurately capture district economies, especially in backward regions.
3. District-Centric Planning: Development planning should focus on districts. Each district needs tailored strategies based on local resources, trends, and capacities.

Toward Inclusive and Balanced Growth

1. Granular Data for Smart Policy: Real-time district dashboards will enable better tracking of jobs, productivity, and investments. This leads to more precise planning.
2. Link Data with Incentives: States should be incentivised to build better district-level data systems, possibly linked to central funding.
3. Inclusive Growth Across 806 Districts: India’s future depends not just on fast growth but on shared prosperity across all 806 districts forming its economic base.

Question for practice:

Discuss how regional economic disparities in India affect inclusive growth and why district-level data is essential for effective policy planning.