Proceedings of the 9th International Conference on Applied Research in Management, Economics and Accounting
Year: 2024
DOI:
[PDF]
Modeling Air Passenger Market Demand Volatility for Large Airport Hubs in The United States
Fassil Fanta, Selcuk Ertekin
ABSTRACT:
Using econometric time-series modeling, this paper examines passenger demand volatility at top, middle, and low-ranking large airport hubs in the United States. Volatility is modeled using a Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model. We standardized volatility measures for domestic and international revenue passenger miles to ensure valid comparisons across airports of different rankings. Our results show that top-ranking hubs, such as Atlanta Hartsfield–Jackson International Airport, exhibit more stable revenue passenger miles than middle and lower-ranking hubs, such as Tampa and Orlando International Airports. Over the past decade, airports across all rankings have experienced reduced volatility, likely due to technological advancements and improved airport management practices. However, middle and low-ranking airports display higher volatility in international revenue passenger miles, possibly attributed to capacity limitations and their proximity to international leisure destinations. In contrast, top-ranking airports exhibit higher volatility in domestic revenue passenger miles, primarily due to increased competition among airlines in these major hubs.
keywords: Airport, Demand Forecasting, Volatility of Passenger Air Demand, Large Airport Hubs