Abstract Gravity models have long served as a framework for analyzing bilateral flows, trade and many other activities. To estimate a gravity model, (parametric) linear regression techniques have been commonly employed to develop the relationship between passenger flows and factors that can significantly influence these flows. This study explores the application of an alternative method, the non-parametric multivariate adaptive regression spline (MARS) technique, to identify the determinants for air passenger flows between pairs of countries. The data of 2006 and 2007 air passenger flows between pairs of countries in the APEC region were collected to develop the MARS models. Results indicate that distance between the countries, annual import value, national per capita income, unemployment rate and consumer price index of the origin country, as well as GDP, annual import value, and consumer price index of the destination country are significant determinants for bilateral air passenger flows.

    Highlights This study applies the non-parametric MARS modeling technique to explore the determinants for air passenger flows. The data of 2006 and 2007 air passenger flows between pairs of APEC countries were collected to develop the MARS models. Results indicate that distance, GDP, import value, income, unemployment rate and CPI are the significant determinants.


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    Title :

    Analysis of bilateral air passenger flows: A non-parametric multivariate adaptive regression spline approach


    Contributors:

    Published in:

    Publication date :

    2013-01-01


    Size :

    8 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English