work represents the first complete theoretical investigation into the economics of airport noise
regulation using a model where the interests of the key relevant stakeholders are captured.
The main conclusions of the analysis are as follows: (i) noise regulation harms airline passengers
by raising fares and potentially reducing service quality; (ii) cumulative and per-aircraft
noise regulation have quite different effects on airline decisions; (iii) cumulative regulation appears
to be superior from a social-welfare perspective; (iv) under realistic sequential airline
choice behavior, the best a planner can do under cumulative regulation is to use an inefficiently
tight noise limit that yields lower-than-optimal flight frequency; (iv) noise taxation is
equivalent to cumulative noise regulation, generating exactly the same airline decisions when
the tax rate is suitably chosen.
The analysis has treated noise taxes and the two noise-regulation regimes, cumulative and
per-aircraft, as alternatives, when in fact these approaches often coexist in actual practice. In
other words, the FAA certification standard puts an upper bound on noise per aircraft, while
individual airports impose cumulative noise limits and other operating constraints, including
noise taxes. Given this real-world complexity, what practical lessons can be drawn from the
analysis? To reach an answer, the first observation is that most aircraft currently in production
already have lower noise signatures than the latest Stage 4 noise limits.29 This fact, along with
the presence of additional airport-level regulations, apparently means that airports do not
find the existing per-aircraft noise limits to be sufficiently stringent. Therefore, they impose
additional regulations, which generate a demand for aircraft quieter than the current FAA
standard.
Instead of allowing aircraft quietness to be effectively determined by airport-level policies,
the FAA could instead impose a per-aircraft limit that is even more stringent than the Stage
4 limit. But since a cumulative noise limit (or the equivalent tax) appears to be a superior
instrument, the analysis suggests that airport-level regulation may actually be a preferable
policy.
Although the highly stylized framework presented in this paper captures the essential
elements of the airport noise problem, additional refinements and extensions of the model
could be beneficial. For example, more-realistic specifications of the airline’s noise-abatement
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cost function and the functions giving cumulative noise and noise damage would improve the
model’s accuracy. Moreover, adding the airport itself to the list of stakeholders in the model
could provide further insights. The airport, responding to political pressure to reduce noise,
could be portrayed as choosing the noise regulatory regime that maximizes its profit for a
given target noise level. In other extensions, concurrent implementation of noise-abatement
measures, such as a nighttime curfew and a noise tax, could be modeled, and airline asymmetry
(with one large and one small carrier) could be introduced. Analysis of these extended models
might, in some cases, require numerical methods. But the insights gained from numerical
models, especially those that can be calibrated with empirical data, might prove valuable in
guiding airport noise policies.