Examining the Effects of Confirmed COVID-19 Cases and State Government Policies on Passenger Air Traffic Recovery by Proposing an OD Spatial Temporal Model

Abstract

As the world is reopening from the unprecedented global pandemic, investigating how the intensity of transmission and responsive policies affect passenger air traffic demand is valuable for the aviation industry recovery and post-pandemic economic development. This paper investigates the effects of confirmed COVID-19 cases and state government policies at 28 hub airports in the United States from March 2020 to September 2021 by proposing an origin-destination (OD) spatial temporal econometric model. The investigation finds that (1) confirmed COVID-19 cases and state government policies had the highest effects on air traffic in the same month as these events occurred and the effects were diminishing in the following months; (2) The policy of internal movement restrictions in a given state generated a higher impact for trips arriving at this state, while confirmed COVID-19 cases and the testing policy generated a higher impact for trips departing from this state; (3) Reopening offices, lifting movement restrictions, maintaining flexibility in accessing COVID-19 tests, and using facial covering onboard are effective policies for aviation industry recovery. This paper aims to be a timely study on air travel demand when the domestic traffic has almost achieved the pre-pandemic level, offering insights into recovery of the aviation industry and preparation for future uncertainties. In addition, the proposed OD spatial temporal model which captures OD spatial dependences and temporal correlations simultaneously can equip spatial economists with an innovative and powerful tool.