The Untolled Problems with Airport Slot Constraints
Abstract
This paper examines the efficiency and practicality of airport slot constraints using a deterministic bottleneck model of landing and takeoff queues. It adapts this congestion pricing model to determine the optimal timing and quantity of slot permits for any number of slot windows. Aircraft choose their optimal operating times subject to the slot constraints, and airport queues adjust endogenously. The number and length of slot windows affects the congestion levels and efficiency gains. The atomistic bottleneck model is extended to include self-internalizing dominant traffic and atomistic fringe traffic. The model raises questions about the implementation of slot constraints that do not arise in standard congestion models. The theory explains Daniel's (2009a) empirical findings that slot-constraints at Toronto are ineffective and suggests that recent proposals for slot constraints at US airports would be similarly ineffective. Effective slot constraints require many narrow slot windows, making slot auctions or markets difficult to implement.Download Info
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Paper provided by University of Delaware, Department of Economics in its series Working Papers with number 09-09.Length: 34 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:dlw:wpaper:09-09.
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Postal: Purnell Hall, Newark, Delaware 19716
Phone: (302) 831-2551
Fax: (302) 831-6968
Web page: http://www.lerner.udel.edu/departments/economics/
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Related research
Keywords: airport congestion; slot constraints; pricing; bottleneck; queuing.;Find related papers by JEL classification:
- R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Systems
- H2 - Public Economics - - Taxation, Subsidies, and Revenue
- L5 - Industrial Organization - - Regulation and Industrial Policy
- L9 - Industrial Organization - - Industry Studies: Transportation and Utilities
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-10-03 (All new papers)
- NEP-URE-2009-10-03 (Urban & Real Estate Economics)
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