Measuring the structural cost of aviation connectivity relative to GDP per capita, for every country with an international airport.
The Runway Index measures how much of a country's monthly income is spent reaching its nearest neighbours and the world's major global gateway cities. For each country it prices flights to seven regional neighbours and seventeen global gateway cities, then divides the average fare by monthly income.
The name comes from the airport runway. It is the strip of ground a country needs to connect to the world, and the index measures what that connection costs.
Singapore scores 3. Peru scores 75. Tanzania scores 466. 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 where that constraint is severe enough to act as a hidden tax on every business operating within them.
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.
A grouping of countries based on connectivity cost rather than the usual developed, emerging, and frontier labels. Some markets that look developed by income score worse than markets that look frontier, which is a different lens on how connected a country actually is.
| # | Country | Hub | Local | Global | Runway Index | Classification |
|---|
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 data shown is the inaugural edition. The second collection quarter, Q3 2026, is complete and will be reflected here shortly. 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 gateway cities. All seventeen cities are priced for every country. Gateway cities are selected as the primary international gateway to the most significant economic 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.
Data notes. Ireland and Luxembourg rank highest partly because their reported GDP per capita is inflated by multinational profit booking. Their real domestic income is lower, so their true scores sit modestly higher than shown. Sudan's figure reflects wartime conditions. Khartoum airport has been closed since 2023, so prices are measured from Port Sudan, the functioning gateway, against a collapsed economy. Namibia and Haiti are scored on their regional score only, as global hub fares were unavailable at collection. They are flagged local only in the table.
Full methodology paper and complete dataset publish alongside the 2026 data.
The Runway Index answers one question: how much of a country's monthly income is consumed simply by connecting to its nearest neighbours and the world's major global gateway cities?
The name comes from the airport runway. It is the strip of ground a country needs to connect to the world, and the index measures what that connection costs.
The index normalises airfare by monthly income rather than using absolute prices. A flight costing the same in absolute terms can represent three percent of monthly income in one country and two thousand percent in another. That difference is the structural inequality the index is designed to measure.
The 2026 edition covers 183 scored countries. Scores range from 2.92 for Ireland, the most affordable, to 2,453 for Sudan, the least.
The Runway Index is the equally weighted composite of two sub-scores:
| Component | Formula | Measures |
|---|---|---|
| Local Score | Avg(fares to 7 neighbours) / monthly GDP per capita × 100 | Regional connectivity cost |
| Global Score | Avg(fares to 17 hub cities) / monthly GDP per capita × 100 | Global capital access cost |
| Runway Index | (Local × 0.5) + (Global × 0.5) | Composite connectivity cost |
A higher score means a greater share of monthly income is consumed by connectivity. A score of 50 means connectivity costs the equivalent of half a monthly income. No logarithmic transformation is applied. The raw ratio preserves direct interpretability.
The Local Score measures the cost of reaching the seven most economically relevant regional neighbours from each country's primary international gateway.
Pure geographical proximity is insufficient. The gravity model corrects for this, drawing on one of the most established frameworks in international trade economics.
| Step | Action |
|---|---|
| 1 | Identify the 10 nearest sovereign countries by great-circle distance |
| 2 | Compute gravity score for each: sqrt(GDP) / distance |
| 3 | Select the 7 neighbours with the highest gravity score |
| 4 | Average route prices equally across the 7 selected neighbours |
Total nominal GDP is used as the economic variable, not GDP per capita, because the index selects for market size and regional economic gravity, not population wealth. The square root moderates the dominance of very large economies without eliminating their pull entirely.
The Global Score measures the cost of reaching a fixed basket of seventeen global gateway cities, expressed as a percentage of monthly GDP per capita. All seventeen cities are priced for every country to ensure a consistent global reference frame. Cities are selected as the primary international gateway to the most significant economic centre in each region, not the busiest airport by passenger volume. The basket is held constant over time.
| City | IATA | Region |
|---|---|---|
| New York | JFK | North America |
| Mexico City | MEX | Central America |
| Sao Paulo | GRU | South America |
| Lagos | LOS | West Africa |
| Johannesburg | JNB | Southern Africa |
| Cairo | CAI | North Africa |
| London | LHR | Northern Europe |
| Paris | CDG | Western Europe |
| Frankfurt | FRA | Western Europe |
| Istanbul | IST | Western Asia |
| Dubai | DXB | Middle East |
| Mumbai | BOM | South Asia |
| Singapore | SIN | South-East Asia |
| Hong Kong | HKG | East Asia |
| Shanghai | PVG | East Asia |
| Tokyo | NRT | East Asia |
| Sydney | SYD | Oceania |
Cheapest available one-way economy fare, collected via Google Flights calendar search for every day of the departure week, booked approximately 30 days in advance. For each route, fares are collected from both a US market context and, where supported, the local point-of-sale context of the origin country. The lower of the two fares is used per departure date. Where the calendar search returns no result, an individual date search is used as a fallback. Up to seven prices are collected per route and averaged. Routes with fewer than three days returning a price are flagged as thin.
| Parameter | Value | Rationale |
|---|---|---|
| Fare type | One-way economy | Measures single unit of connectivity |
| Departure days | All 7 of departure week | Full weekly demand cycle |
| Price sources | US + local point-of-sale | Lower of the two per date |
| Fallback | Individual date search | Recovers thin routes calendar misses |
| Booking horizon | 30 days in advance | Consistent across all routes |
| Currency | USD | Consistent cross-country comparison |
A full Runway Index score requires both a Local Score and a Global Score. Of the 183 scored countries, 181 have full coverage. Two countries, Namibia and Haiti, are scored on their Local Score alone because global hub fares were unavailable at collection. These are flagged as local only in the dataset and should be read as partial.
Six countries with an international airport are not scored because reliable GDP per capita data is unavailable: Afghanistan, Cook Islands, Cuba, Eritrea, North Korea, and Syria.
| Score | Classification | Interpretation |
|---|---|---|
| Below 50 | Well Connected | Aviation structurally affordable relative to income |
| 50 to 99 | Moderate | A notable but manageable cost |
| 100 to 199 | High Connectivity Tax | Significant structural constraint on integration |
| 200 and above | Very High | Aviation structurally inaccessible relative to income |
The index uses each country's primary international gateway and national GDP per capita as standardised inputs. These simplifications do not capture within-country variation in connectivity costs or income distribution. They are applied consistently across all countries. The purpose is cross-country comparison, not the full complexity of connectivity within any single country. No measurement is perfect. Transparent imperfection is more credible than false precision.
Certain high-income financial centres, including Ireland and Luxembourg, report GDP per capita significantly above actual resident living standards due to multinational profit booking. Their true scores sit modestly higher than shown.
Sudan's score reflects wartime conditions. Khartoum airport has been closed since 2023, so prices are measured from Port Sudan, the functioning gateway, against a collapsed economy. The figure is a real reflection of current connectivity, not a data artefact.
Prices are drawn from a single source, Google Flights, for consistency. Some genuinely bookable routes on thin markets are not priced by this source and are recorded as unpriced rather than estimated. All underlying data and assumptions are published alongside the index results.
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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