Air fares are collected automatically from travel portals every ten minutes, across a fixed basket of the fifteen busiest domestic city pairs and five booking lead times. For each route and lead time the cheapest available fare is recorded — the price a traveller could actually have transacted at. Those prices are converted to a single index using the geometric (Jevons) method, weighted by each route’s share of scheduled seats. The resulting movement is airfare inflation, which is the input a consumer price index requires for air travel.
Index by city pair and booking lead time, against the reference period. Red is dearer than the reference period, blue is cheaper. Blank cells had too few observations to price reliably and are excluded rather than estimated.
City pairs whose index has moved beyond ±15% from the reference period. The threshold is fixed in advance so that flagging is not a judgement made after seeing the data.
Index movement over the collection period, and average fare by day of week. Day-of-week effects are a known driver of airfare seasonality; the pattern firms up as more weeks are collected.
Observed fares by carrier. Carrier mix is not controlled for in the index; this table is the diagnostic that makes any mix effect visible.
The index is machine-readable. Central statistical systems can ingest it directly rather than transcribing from this page.
X-API-Key header. Every response
carries the reference period and the method used, so an ingested figure can never
be separated from how it was produced.