Where India punches above its weight
Revealed advantage by product group.
How this is built. India supplies — of everything the fourteen tracked markets import. This index is India’s share of a single product group divided by that overall share, so 1.0 means average and 3.0 means India is three times more present in that product than in its trade as a whole. It is a Balassa revealed-comparative-advantage index computed on the tracked markets rather than on total world trade — directionally the same, but do not quote it as a global RCA.
Where India’s imports are concentrated
The largest single supplier’s share of India’s total import bill for each product group. A tall bar is a supply-chain risk.
Read this as exposure, not as a verdict — concentration is efficient until it isn’t. The denominator is India’s own reported world imports of the chapter, so these shares are exact.
How narrow is India’s customer base?
Export destinations, by share of India’s goods exports.
The Herfindahl-Hirschman index is the sum of squared market shares. Competition authorities treat a market above 2,500 as highly concentrated; applied to export destinations, a low number means a country is not dependent on any one buyer. India’s spread is one of the quieter strengths in its trade position.
When the two sides disagree
What each partner says it imported from India, against what India says it exported to that partner — same year, same goods, two sets of books.
Why any gap at all is normal — and why big ones are interesting. Partners report imports CIF (including freight and insurance) while India reports exports FOB, so partner figures should exceed India’s by roughly 5–15% as a matter of arithmetic. Gaps far outside that band mean something else: goods re-routed through a third country and re-labelled with India as origin, differences in when a shipment is recorded, or under-declaration. A negative gap — India reporting more than the partner received — usually points to goods declared to a hub and landed elsewhere. This is a signal to investigate, not proof of anything.
Take the data
Every dataset behind this site, as JSON. Free to reuse under CC BY 4.0 — please cite it.
Each file is regenerated by the monthly refresh, so these URLs stay current. JSON is the canonical form; every chart on the site also has a CSV button for the slice it shows. The build scripts that produce these files are in the repository, so the whole pipeline is auditable.
How to cite this data. ValueChain. (2025). ValueChain: India in global value chains [Data set]. https://valuechain.international
About these measures
All four are computed by scripts/build_research.py from
the datasets published above — nothing is estimated or modelled. The
revealed-advantage and dependence measures use HS 2-digit chapters
across the markets this site tracks; the concentration measure uses
India’s own reported exports to every partner; the mirror table
uses partner-reported imports from India, fetched directly from UN
Comtrade.
Known limits: the tracked markets are large but not the whole world, so shares are of tracked trade rather than global trade; chapter-level grouping hides product detail; and merchandise only — services are not in UN Comtrade. See the full limitations.
How to cite this page. ValueChain. (2025). Research & data: revealed advantage, dependence and mirror gaps. https://valuechain.international/research.html
Using this in a paper or a story? Tell us what you need — we are happy to cut the data differently.