How do changes in economic activity affect air passenger traffic? The use of state-dependent income elasticities to improve aviation forecasts. (January 2022)

• Record Type: Journal Article
• Authors: Hanson, Daniel; Toru Delibasi, Tuba; Gatti, Matteo; Cohen, Shamai
• Is Part Of: Journal of air transport management. Volume 98(2022)
• Publication Date: 2022-01
• Subjects: Airline traffic forecast -- Airline demand -- Impact of recession -- COVID-19 -- Income elasticities -- Bi-directional causality; Airlines -- Management -- Periodicals; Aeronautics, Commercial -- Management -- Periodicals; 387.7068
• DOI: 10.1016/j.jairtraman.2021.102147
• Languages: English
• ISSNs: 0969-6997

Abstract

Abstract: This paper explores the causal relationship between income and air travel demand to provide insights for the future growth of the aviation industry, with particular focus on the recovery period after a crisis. Using US data, we estimate the long-run and short-run income elasticities of air passenger demand and we estimate how they vary over the business cycle. We find that long-run income elasticities are lower than short-run elasticities and that the short-run elasticities are lower during the recovery period following an economic downturn. A reduction in income elasticity of demand during the recovery period is consistent with an increase in precautionary savings. We then apply our results to IMF economic forecasts, and our analysis suggests that a return of the air traffic to its pre-crisis levels would be slower that the return of economic activities to their levels. Forecasts using our estimates are likely to be more accurate than one based on constant income elasticities of demand and suggest that air traffic in the US would return to its 2019 level in 2025, which is three years after the recovery of real GDP in this scenario. The use of state dependent income elasticities – in conjunction with other techniques that can control for other likely changes in demand and supply in a post-COVID world – could play an important role in helping to generate better forecasts for the aviation industry. Highlights: We consider how the use of long-run and short-run state-dependent income elasticities can improve upon existing air traffic forecasting models, and using state dependent short-run elasticities allows us to generate more accurate forecasts. We find that long-run income elasticities are lower than short-run elasticities and that the short-run elasticities are lower during the recovery period following an economic downturn. We find that the impact of COVID-19 on air travel could last longer than its impact on economic growth. Air travel is likely to take longer to recover from the pandemic than would be predicted using constant incomeelasticities. The use of state dependent income elasticities – in conjunction with other techniques that can control for other likely changes in demand and supply in a post-COVID world – could play an important role in helping to generate better forecasts for the aviation industry.