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Are secondary airports subject to the same fixed or random effects as large hub airports? A case study of the Chicago metropolitan area airports using dynamic panel data analysis
Journal of Airport Management,
5
(3),
269-281
(2011)
Abstract
In this study, dynamic panel data analysis focuses on whether the operational conditions that underlie congestion and delays have changed over five summers (when traffic and delays are at their peak) and within the same group of airports, that is, Chicago O'Hare International (ORD), Chicago Midway (MDW), Gary/Chicago International (GYY) and Milwaukee Mitchell International (MKE). Panel data analysis can help to determine whether any change in delays is the result of random or fixed effects. The panel compared the total minutes of gate arrival delay by each summer (time period) and by airport (cross-section variable) as a function of lagged gate arrival delay minutes, arrival demand, arrival volume, taxi-in times and percentage of airport capacity utilised. These variables are usually key factors in congestion and delays. The study reveals that the four airports were mostly subject to fixed effects. This implies that delay reduction initiatives should consider secondary airports in the overall strategy to address congestion and delays at the main hub airports.
Keywords: panel data models; airport delay; secondary airports
The full article is available to subscribers to the journal.
Author's Biography
Tony Diana is the Acting Division Manager, Outreach at the US Federal Aviation Administration (FAA). He received his doctorate in policy analysis and quantitative management from the University of Maryland, Baltimore County. He is involved in the communication of progress in modernisation programmes at US airports, metroplexes and airspaces. Prior to that position, he was Division Manager, NextGen Performance in the Office of NextGen Performance and Outreach and Deputy Division Manager, Forecasting and Performance Analysis, in the Office of Aviation Policy and Plans of the FAA, where he managed the aviation system performance metrics data warehouse. At the Maryland Aviation Administration, he was involved in performance measurement and route development. Tony’s main interests are performance evaluation and benchmarking as well as the study of delay. He is a certified Lean Sigma Master Black Belt and a certified Project Management Professional.
