Abstract
This paper models and estimates congestion prices and capacity for large hub airports. The model includes stochastic queues, time-varying traffic rates, and endogenous, intertemporal adjustment of traffic in response to queuing delay and fees. Relative costs of queuing and schedule delays are estimated using data from Minneapolis-St. Paul. Simulations calculate equilibrium traffic patterns, queuing delays, schedule delays, congestion fees, airport revenues, airport capacity, and efficiency gains. The paper also investigates whether a dominant airline internalizes delays its aircraft impose. It tests game-theoretic specifications with atomistic, Nash-dominant, Stackelberg-dominant, and collusive-airline traffic
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