Title
Border Region Bridge and Air Transport Predictability
Publication Date
11-11-2013
Source Full Text URL
https://mpra.ub.uni-muenchen.de/59583/
Document Type
Article
Abstract
Border region transportation forecast analysis is fraught with difficulty. In the case of El Paso, Texas and Ciudad Juarez, Chihuahua, Mexico, dual national business cycles and currency market fluctuations further complicate modeling efforts. Incomplete data samples and asymmetric data reporting conventions further confound forecasting exercises. Under these conditions, a natural alternative to structural econometric models to consider is neural network analysis. Neural network forecasts of air transportation and international bridge activity are developed using a multi-layered perceptron approach. Those out-of sample simulations are then compared to previously published forecasts produced with a system of simultaneous econometric equations. Empirical results indicate that the econometric approach is generally more accurate. In several cases, the two sets of forecasts are found to contain complementary information.
Comments
Fullerton, Thomas M., Jr. and Mukhopadhyay, Somnath (2013): Border Region Bridge and Air Transport Predictability. Published in: Journal of Business & Economics , Vol. 4, No. 11 (11. November 2013): pp. 1089-1104.