Simultaneous Modeling of Passenger and Cargo Demand at an Airport

Abstract

Forecasts for passenger and cargo demands are important parameters for airport planners. Although there are a number of studies for passenger demand in an airport, the number of studies for air cargo is much smaller. Also, these two entities are often dealt with separately in the literature. However, there can be advantages in modeling them simultaneously, especially when time series data are used for estimating the demand models. A seemingly unrelated regression (SUR) framework is followed to jointly model passenger and cargo demand at the Shahjalal International Airport at Dhaka, Bangladesh. Allowing for contemporaneous correlation between the air passenger and air cargo demand models in the SUR approach allows a more efficient and reliable estimate than ordinary least squares and individual cointegration methods. Results of the simultaneous demand modeling are used to forecast passenger and cargo demand at the airport up to 2030.