Forecasting air passenger volume in Singapore: Determining the explanatory variables for econometric models
Zhong, Zhao Wei
Date of Issue2017
School of Mechanical and Aerospace Engineering
Nowadays aviation industry has become an important portion of Singapore economies progressively. It is essential to provide accurate prediction for aviation development. However, due to instability of economies, it is advisable to capture the impact of economy into forecasting. This paper explores several explanatory variables, such as Singapore GDP, China GDP, exchange rate and tourist numbers, to build econometric models to predict the air passenger movements and analyzes and compares the relative results from corresponding models. Before applying for model simulation, correlations among variables were checked. Various combinations of the variables were implemented to establish the models. Five econometric models were constructed for 18 years prediction from 1998 to 2015 in our study and the performance of these models were measured using MAPE, RMSE and degree of divergence. By comparing the 5 models, the variables effectiveness is investigated. Moreover, the impact of the variables was also scrutinized. Finally, appropriate models for Singapore situation are to be recommended. Afterwards, forecasting for the next 18 years till 2033 is conducted and analyzed to have a better idea of the future development.
Air passenger volume
MATTER: International Journal of Science and Technology
© 2017 The author and GRDS Publishing.