Narrow-bodies leave service at a median of 25 years of age
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Here, regional aircraft leave US service youngest, wide-bodies oldest and narrow-bodies in between. Every median is later if only aircraft reported as withdrawn count, so the result depends on how an exit is counted.
descriptive The medians depend on how an exit is defined; counting only aircraft last filed as withdrawn puts every median later.
Details
Vertical axis: Survival probability (%)
Series: Narrow-body; Wide-body; Regional
One curve point per age: the share of aircraft still filed at the year-end census at that age. An aircraft is one airframe under every tail number it was filed with, and a passenger aircraft converted to a freighter has not left. The median is the first age at which half are no longer filed. Under the six other rules tried for identifying an aircraft and dating its entry and exit, the medians move by no more than a year: narrow-bodies 24 to 25, wide-bodies 26 to 27 and regional aircraft 18 to 19 years.
Counting only aircraft last filed as withdrawn, the median age at leaving is 31 years for narrow-bodies (25 as plotted), 31 for wide-bodies (27) and 28 for regional aircraft (19).
Maintenance cost per flight hour is about 4 times as high for a fleet averaging 35 years old as for one averaging 1 year
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Older fleets cost more to maintain per flight hour, on one age slope for every aircraft class. At any age the wide-body curve sits well above the narrow-body one and the regional curve a little below it.
descriptive The age slopes are pooled across aircraft categories because the per-category differences are jointly insignificant, so the categories differ only in level.
Details
Vertical axis: Maintenance cost ($/hour)
Series: Narrow-body; Wide-body; Regional
Maintenance expense divided by airborne (flight) hours, for one carrier's aircraft of one type in one year; the age is the average age of those aircraft. The fit uses 2,565 such observations and explains 28% of the variation in the log of their cost per hour.
The three curves share one age slope and differ only in level, because the differences between the categories' age slopes are jointly insignificant.
Top 15 aircraft types (2024)
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One Boeing single-aisle model is the most numerous active type by a wide margin. Boeing's and Airbus's single-aisle families fill most of the ranking; regional jets and two older Boeing types make up the rest.
Details
Vertical axis: Active aircraft count
Within a family, each new generation burns less fuel than its predecessor
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Within each family, every newer generation burns less fuel per flying hour than the one before it. The figures are not adjusted for aircraft size, so they do not compare one family with another.
Details
Vertical axis: Fuel consumption (gallons per hour)
Series: Fuel (gal/hr)
The bars are in the order of the aircraft families, narrow-body first and then wide-body, and run from the older to the newer generation within each family.
Fleet utilisation by category
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Daily flying hours per aircraft have held steady for big jets but fallen by roughly a third for regional aircraft over the past decade and a half.
Details
Window: 2010 to 2024
Data through: 2024
Vertical axis: Daily utilisation (hours)
Series: Narrow-body; Wide-body; Regional
Latest: Narrow-body 7.96; Wide-body 8.57; Regional 4.48
At assumed GDP growth, US airlines would need about 59% more seat-miles in 2044 than they flew in 2024
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In this what-if, each line grows today's seat-miles at an assumed rate of economic growth times the income elasticity. Seat-miles measure the capacity airlines fly, not the number of aircraft they need.
projection Capacity paths translated from macro scenarios at a fixed elasticity, not an independent demand forecast.
Details
Window: 2005 to 2044
Observed data through: 2024 (the chart extends to 2044 with projected values)
Vertical axis: Available seat-miles (billions)
Series: Observed (T-100, US carriers); GDP growth 2.5% a year (central); GDP growth 1.5% a year; GDP growth 3.5% a year; GDP growth 0.5% a year; GDP growth -0.5% a year
Latest: Observed (T-100, US carriers) 1,353
Projected to 2044: GDP growth 2.5% a year (central) 2,152; GDP growth 1.5% a year 1,790; GDP growth 3.5% a year 2,583; GDP growth 0.5% a year 1,486; GDP growth -0.5% a year 1,231
Each line is a scenario, one per assumed GDP growth rate. The spread between them is not a confidence band.
This chart is a constant-elasticity translation of assumed GDP growth into seat-miles: 2.5% a year times an elasticity of 0.94, about 2.35% a year over 2024-2044. The site's income-model projection counts passengers and grows them about 0.93% a year over 2025-2044. Of the 1.4 points between the two rates, 0.5 is the GDP assumption (the projection's own path grows 1.99% a year, giving 1.87% at 0.94) and 0.9 the projection's saturating curve, which responds less to income.
Each path compounds observed 2024 US-carrier seat-miles (1,353 billion, T-100) at an assumed GDP growth rate multiplied by the US income elasticity of passenger demand (0.939). No productivity or load-factor term enters: seat-miles are assumed to move in step with passengers.
The GDP growth rates are assumptions, and no source for them is cited in this project. Each path holds one rate for all 20 years (3.5%, 2.5%, 1.5%, 0.5%, -0.5% a year). The lines are named for their rate because a low rate held for 20 years is not a recession followed by a recovery. The central path is this chart's own choice of rate.
By fleet age 16 the odds tip from growing the fleet to shrinking it
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The older a fleet of one aircraft type, the less often it grows and the more often it shrinks, though at most ages it is likeliest to stay as it is. This describes whole fleets, not one aircraft's chance of retiring.
exploratory This models how a carrier grows, keeps or shrinks its fleet of an aircraft type, not an aircraft's chance of retirement, and the age at which the odds tip is read off a coarse age grid with no interval around it.
Details
Vertical axis: Probability
Series: P(Keep); P(Grow); P(Shrink)
The age at which the odds tip is where the fitted probability of shrinking the fleet first reaches that of growing it. The model's age grid first shows the shrink probability at or above the grow probability at age 20; interpolating between the grid points at 15 and 20 puts the crossing at 16. It is a single point read off the fitted curves and has no interval.
The model describes a carrier's choice to grow, keep or shrink its fleet of one aircraft type from one year to the next (2,138 carrier-type-years, 451 growing and 392 shrinking), with the average age of that fleet among its drivers. It is not the chance that an individual aircraft of a given age is retired. Its pseudo R-squared is 0.07.