Time Series Analysis of China’s Air Passenger Traffic Amid the COVID-19 Pandemic

Muge Deng

doi:10.54691/bcpbm.v34i.3155

Authors

Muge Deng

DOI:

https://doi.org/10.54691/bcpbm.v34i.3155

Keywords:

ADL model; Granger Causality; COVID-19; Air transportation.

Abstract

China’s air transportation industry has a great development in recent decades along with economic growth and liberalization. However, the impact of COVID-19 pandemic on China’s civil aviation industry is severe and persistent. The paper discusses the development of China’s air transportation and examines the impact of the pandemic on airline industry. The Autoregressive Distributed Lag (ADL) Model and Granger Causality test will be used to investigate the relationships between China’s air passenger traffic and its potential factors including the new COVID-19 cases in China, the Consumer Price Index and unemployment rate in China. The investigation concludes that China’s air passenger traffic is closely related to its own past observations, and the past observations of new infected cases in China is significant in forecasting air passenger traffic. The ADL model forecasts China’s air passenger traffic will have an increasing trend in the following years, but it will still require longer time to recover from the COVID-19 impact.

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