Modeling the impacts of COVID-19 on Arabian Gulf air transportation industry using multiple regression and Vector AutoRegression models

Abstract

COVID-19 pandemic appeared unexpectedly and spread globally, which influenced several sectors worldwide including air traffic that reached Kuwait at later stages. The main objective of this study was to analyze the consequences of the pandemic on such characteristics of air travel such as arriving and departing aircraft, passengers as well as freight. Identifying the impact of COVID-19 on these sectors was necessary to provide solutions to mitigate its effect. In this study, data about Kuwait’s air travel were obtained from the Civil Aviation department. Likewise, data on coronavirus status was collected from the official statistics. Two models were used to analyze the data: multiple regression and Vector AutoRegression. Results proved that the pandemic had significantly impacted on the airline industry except for arriving passengers and departing freight, for which no significant impact was found. To provide the appropriate solutions, a questionnaire was conducted requiring the responses of Kuwait International Airport employees. Based on questionnaire results, social distancing on aircraft, temperature testing of all passengers at departure and arrival gates and PCR (Polymerase Chain Reaction) testing for all passengers were the most popular solutions suggested.