Mapping India’s Startup Landscape: Regional Specialization and Sector Concentration Using DPIIT Recognition Data

India hosts one of the world’s largest startup populations, yet activity is highly uneven across states and industries. Using the Government of India’s Startup Recognized by DPIIT dataset (157,705 recognitions; 36 States/UTs × 56 industries), we map lifetime counts and compute Location Quotients (LQ) and Herfindahl–Hirschman Indices (HHI) to reveal specialization and diversification patterns. Six Tier 1 hubs consisting Maharashtra, Karnataka, Uttar Pradesh, Delhi, Gujarat and Tamil Nadu contribute nearly two thirds of recognitions, but LQs expose niche strengths in smaller jurisdictions that volume rankings miss. Sectoral leadership also shifts by metric: states topping raw counts are not always the most specialized once national composition is considered. The ten Key Sectors (e.g., IT Services, AI, Agriculture) show distinct regional footprints, underscoring that “breadth” (diversification) and “depth” (specialization) demand different policy tools. By providing the first sector resolved, nationwide baseline through early 2025, the study equips policymakers to tailor Startup India and State Ranking Framework interventions and guides scholars toward richer finance and talent linkages.

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Publication Details

Journal
European Economic Letters (EEL)
Published
2025-07-24
DOI
https://doi.org/10.52783/eel.v15i3.3479
Primary Topic
Economic and Technological Innovation
Type
article
Field-Weighted Citation Impact
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article

Mapping India’s Startup Landscape: Regional Specialization and Sector Concentration Using DPIIT Recognition Data

Syed Mohammad Asghar Tahir
European Economic Letters (EEL)
Economic and Technological Innovation
article

Mapping India’s Startup Landscape: Regional Specialization and Sector Concentration Using DPIIT Recognition Data

Syed Mohammad Asghar Tahir
article en

Abstract

India hosts one of the world’s largest startup populations, yet activity is highly uneven across states and industries. Using the Government of India’s Startup Recognized by DPIIT dataset (157,705 recognitions; 36 States/UTs × 56 industries), we map lifetime counts and compute Location Quotients (LQ) and Herfindahl–Hirschman Indices (HHI) to reveal specialization and diversification patterns. Six Tier 1 hubs consisting Maharashtra, Karnataka, Uttar Pradesh, Delhi, Gujarat and Tamil Nadu contribute nearly two thirds of recognitions, but LQs expose niche strengths in smaller jurisdictions that volume rankings miss. Sectoral leadership also shifts by metric: states topping raw counts are not always the most specialized once national composition is considered. The ten Key Sectors (e.g., IT Services, AI, Agriculture) show distinct regional footprints, underscoring that “breadth” (diversification) and “depth” (specialization) demand different policy tools. By providing the first sector resolved, nationwide baseline through early 2025, the study equips policymakers to tailor Startup India and State Ranking Framework interventions and guides scholars toward richer finance and talent linkages.

European Economic Letters (EEL)Vol. 15(3)
Openalex Percentile: Top 75%
Economic and Technological Innovation
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