Measuring the structural cost of aviation connectivity relative to GDP per capita, for every country with an international airport.
In business, runway is the time and capital a company has to grow. In aviation, it is what makes flight possible at all. The Runway Index asks how much of a country's income is spent simply getting airborne, and what that costs the companies trying to reach the world.
Singapore scores 3. Peru scores 65. Tanzania scores 427. That gap is structural, not incidental, and almost entirely invisible in standard investment analysis.
Average cost to the seven most economically relevant regional neighbours, selected using a gravity model combining distance and GDP.
Average cost to all seventeen cities in the fixed global basket divided by monthly income. Every country is measured against the same reference frame.
All seventeen cities are priced for every country. Where no commercial service exists on a route, it is recorded as unpriced and excluded from the average.
Which markets are most structurally constrained by connectivity costs, and how much of their apparent risk premium reflects a connectivity discount that capital has simply never measured.
As the index builds across annual editions, which markets are improving fastest and which are stagnating, producing a concrete measure of whether a country's connectivity position is getting better or worse over time.
Which markets appear well-connected by route count or network depth but are prohibitively expensive relative to local income, and which underrated markets are far more accessible than their reputation suggests.
Whether standard market classification systems predict connectivity reliably, and precisely where they fail. The hypothesis is that some markets classified as emerging or frontier will outscore markets classified as developed, which would be the most direct quantitative challenge to how global capital is currently allocated.
| # | Country | Hub | Local | Global | Runway Index | Classification |
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Flight prices collected via API for every day of the departure week, booked approximately 30 days in advance. Up to seven prices per route per quarter, averaged. Routes with fewer than three days returning a price are flagged as thin in the dataset. The inaugural edition covers Q2 only. The full 2026 edition published at year end covers Q2, Q3, and Q4. From 2027 all four quarters are collected annually.
The Local Score uses a gravity model to identify the seven most economically relevant regional neighbours from the ten nearest countries by distance. Gravity score = sqrt(GDP) / distance. Total nominal GDP from IMF DataMapper 2026 is used as the economic variable.
The Global Score is measured against a fixed basket of seventeen global economic hub cities. All seventeen cities are priced for every country. Hub airports are selected as the primary international gateway to the most significant financial centre in each region, not the busiest airport by passenger volume. GDP per capita from IMF DataMapper 2026 estimates, divided by twelve for monthly figures.
Full methodology paper and complete dataset publish alongside the 2026 data.
The Runway Index is the quantitative data publication of Understory Markets, an independent global markets research publication. Where Understory produces deep qualitative intelligence through interviews and field reports, the Runway Index provides the structural data layer underneath. Two formats, one purpose: understanding global markets from the inside.
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