An Econometric Dynamic Model to estimate passenger demand for air transport industry

Abstract

In this paper, we propose an Econometric Dynamic Model (EDM) to estimate pax demand. We apply the panel data Arellano-Bover method to calibrate the EDM, which is validated by the Sargan test and the Arellano-Bond Autocorrelation test. We propose a forecasting approach using the EDM to foresee pax demand. Finally, we show an application of the EDM by proposing an approach to solve the Airline Airport Hub (AAH) location problem. The case study is about the Mexican air transport industry, AAHs are identified for each predicted year.