The ranked markets are in order of how strongly air travel moves with income. For each one, at least one repeat of the test on pre-COVID years alone disagrees about that long-run link.
What this shows: The vertical axis shows Long-run GDP elasticity of passenger demand.
Conditions and method
Status: descriptive (evidence strength varies by row; each row carries its own published status label).
Singapore: confirmed for existence only, because its second test gives a warning and not a pass, and that test also fails on the pre-COVID quarters alone. The United States and Brazil: confirmed, although their second test fails on the pre-COVID quarters alone. Australia: provisional, because its long-run test passes only with the pandemic quarters in the sample. China: inconclusive on its shorter window, 2011 Q1 to 2019 Q4. A status rests on the first test of a long-run link; the second only corroborates it.
Rows run from the lowest elasticity to the highest. Two neighbours are told apart only when their intervals do not overlap, the difference between them is statistically clear and no robustness check reverses them; otherwise they are tied, as Singapore and the United States are. China is shown last and not ranked. On one common window, 2005 Q1 to 2019 Q4, the same models give Singapore 1.043, the United States 1.908, Australia 1.264 and Brazil 3.169; this checks comparability and is not a second ranking (the order differs, and only Brazil passes its test there).
Singapore is a transit hub, so its elasticity blends resident demand with connecting traffic. For the United States, other specifications the data cannot reject give 0.900 to 1.315, and adjusting for a change in which carriers report gives 0.806 to 0.940. For Brazil, the carriers flying in 2000 alone give 1.12 against 2.842 for the whole market, so about 61% of that may reflect market liberalisation and not income; this rough comparison makes no causal claim. China’s relation is unstable over its window, so its figure averages over a change; with a trend in the model it is not identified.
United Kingdom: its source data has no figures for 2000 to 2002, and the quarters after the gap fail the long-run test. Canada: its two traffic series disagree (passenger-kilometres give 0.984, passengers 0.192). India: a one-time drop in its passenger series leaves the long-run link unresolved. Japan: GDP barely moves over its sample, so no elasticity can be identified. Mexico: its long-run test passes, but three checks of whether the elasticity is identified go the other way. South Korea: a break in 2020 Q2 sits inside its sample, so its passing test cannot be read as a stable link.
The rows do not count the same thing: Singapore counts airport passenger movements, international only, with a transfer passenger counted twice; the United States counts enplanements (flight legs, not trips); Australia counts passengers; Brazil counts paid passengers; China counts passengers carried on Chinese airlines only. No row’s model has a fare term, and real fares fell over these samples, so each elasticity is the response to income together with the fare declines that came with it. A ladder with a fare term has not been estimated.
Every whisker is a 95% interval built the same way, though the markets are estimated on samples of different lengths. Each interval holds the model’s form fixed, with no time trend; where a trend is added, the estimates move and are less certain. The samples end in 2024 Q4, except that of China (2019 Q4). The ⚠ on a label marks a short sample: China (36 quarters).