Forecasting the recovery period of air passenger transportation by using vector error correction model

Abstract

The COVID-19 pandemic has had a significantly negative impact on all transportation modules, especially air passengers. The authors aimed to forecast the air passenger load factor using time series modelling for the affecting variables. After providing general information about this pandemic, the forecasting results regarding getting back into the recovery period were presented by time series modelling. The last five years (2016–2020) and the first eight months of 2021 were examined with the following variables: available seat kilometre, revenue passenger kilometre, passenger load factor, gross domestic product, and domestic and international passenger numbers. The forecast results reveal that the recovery period started in June of 2021 and continues with a robust growth trend until September 2021 due to the vaccination process and the starting of the summer season. This trend changed between September to November 2021 slightly negative, from November 2021 to January 2022 slightly positive, and from January 2022 to March 2022 mildly negative. Correspondingly, passenger load factor (PLF) is affected by itself and domestic transportation in the short-term period. This effect seems short-term in domestic and international transport. This research reveals that minimising the economic damage by benefiting from the increasing trend of air passenger numbers increases the recovery period.