Authors:
Hana Naghawi; Ala’ Alobeidyeen; Mu’tasim Abdel-Jaber;
Abstract:
The main objective of this paper is to develop an econometric passenger air travel demand model in Jordan. Two steps were employed in the model development process. In step one, the demand determinants that have high correlation with passenger air travel demand were identified using stepwise regression technique. In step two, multiple linear regression analysis was used for the econometric model development. Annual data from 2006 to 2017 and 6 explanatory variables/demand determinants were used. The output indicated that the best model which is capable of explaining the behavior of passenger air travel demand in Jordan is the one which only includes the Gross Domestic Product in USD as demand determinant. The performance of the regression model was evaluated based on the coefficient of determination (R2), significance of each parameter and the overall significance of the regression model. Finally, the model was checked for autocollinearity and multicollinearity problems. Durbin-Watson statistics was used to check the model for autocollinearity problem.
The tolerance of variables and the Variance Inflation Factor (VIF) were used to check the model for multicollinearity problem. The model was found to be statistically significant with a coefficient of
determination (R2) of 0.981, indicating that the two selected demand determinants explain 98.1% of the variability in passenger air travel demand in Jordan.
Keywords:
Econometric modeling, Multiple linear regression, Air travel demand, Statistical models.