Border Region Bridge and Air Transport Predictability

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.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Regional Transport Demand; Neural Networks; Econometric Forecasting
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R4 - Transportation Economics > R41 - Transportation: Demand, Supply, and Congestion ; Travel Time ; Safety and Accidents ; Transportation Noise

References

An G. and Puttitanun T. (2009). “Revisiting McCallum’s Border puzzle”, Economic Development Quarterly, Vol. 23, pp. 167-170.

Ashur S., Weismann J., Perez S. and Weismann A. J. (2001). “Traffic simulation at international ports of entry—El Paso-Mexico case study”, Transportation Research Record, Vol. 1763, pp. 48-56.

Bain R. (2009). “Error and optimism bias in toll road traffic forecasts”, Transportation, Vol. 36, pp. 469-482.

Bradbury S. L. (2002). “Planning transportation corridors in Post-NAFTA North America”, Journal of the American Planning Association, Vol. 68, pp. 137-150.

Celikoglu H. B. and Akad M. (2005). “Estimation of public transport trips by feed forward back propogation artificial neural networks: A case study for Istanbul”, in: Proceedings of the 8th Online World Conference on Soft Computing Methodologies & Applications, pp. 27-36.

Charney A. H. and Taylor C. A. (1984). “Decomposition of Ex–Ante state model forecasting errors”, Journal of Regional Science, Vol. 24, pp. 229-247.

Cooper J. P. and Nelson C. R. (1975). “The Ex-Ante prediction performance of the St. Louis and FRB-MIT-Penn econometric models and some results on composite predictors”, Journal of Money, Credit, and Banking, Vol. 7, pp. 1-32.

De Leon M., Fullerton T. M. Jr. and Kelley B. W. (2009). “Tolls, exchange rates, and borderplex international bridge traffic”, International Journal of Transport Economics, Vol. 36, pp. 223-259.

Dunne S. and Ghosh B. (2012). “Regime-based short-term multivariate traffic condition forecasting algorithm”, Journal of Transportation Engineering, Vol. 138, pp. 455-466.

Figliozzi M. A., Harrison R. and Mccray J. P. (2001). “Estimating Texas-Mexico North American free trade agreement truck volumes”, Transportation Research Record, Vol. 1763, pp. 42-47.

Fildes R., Wei Y. and Ismail S. (2011). “Evaluating the forecasting performance of econometric models of air passenger traffic flows using multiple error measures”, International Journal of Forecasting, Vol. 27, pp. 902-922.

Flyvbjerg B., Holm M. K. S. and Buhl S. L. (2005). “How (in)accurate are demand forecasts in public works projects? The case of transportation”, Journal of the American Planning Association, Vol. 71, pp. 131-146.

Flyvbjerg B., Holm M. K. S. and Buhl S. L. (2006). “Inaccuracy in traffic forecasts”, Transport Reviews, Vol. 26, pp. 1-24.

Fullerton T. M. Jr. (2000). “Currency movements and international border crossings”, International Journal of Public Administration, Vol. 23, pp. 1113-1123.

Fullerton T. M. Jr. (2001). “Specification of a borderplex econometric forecasting model”, International Regional Science Review, Vol. 24, pp. 245-260.

Fullerton T. M. Jr. (2004). “Borderplex Bridge and air econometric forecast accuracy”, Journal of Transportation and Statistics, Vol. 7, pp. 7-21.

Fullerton T. M. Jr. (2007). “Empirical evidence regarding 9/11 impacts on the borderplex economy”, Regional & Sectoral Economic Studies, Vol. 7, July-December, pp. 51-64.

Fullerton T. M. Jr. and R. Tinajero (2002). “Cross border cargo vehicle flows”, International Journal of Transport Economics, Vol. 29, pp. 201-213.

Granger C. W. J. and Ramanathan R. (1984). “Improved methods of combining forecasts”, Journal of Forecasting, Vol. 3, pp. 197-204.

Harrison R., Sanchez-Ruiz L. A. and Lee C. E. (1998). “Truck traffic crossing Texas-Mexico border”, Transportation Research Record, Vol. 1643, pp. 136-142.

Heravi S., Osborn D. R. and Birchenhall C. R. (2004). “Linear versus neural network forecasts for European industrial production series”, International Journal of Forecasting, Vol. 20, pp. 435-446.

Jagric T. and Strasek S. (2005). “A nonlinear extension of the NBER model for short-run forecasting of business cycles”, South African Journal of Economics, Vol. 73, pp. 435-448.

Lam W. H. K., Ng P. L. P., Seabrooke W. and Hui E .C. M. (2004). “Forecasts and reliability analysis of Port Cargo throughput in Hong Kong”, Journal of Urban Planning and Development, Vol. 130, pp. 133-144.

Levinson D. (2005). “Paying for the fixed costs of roads”, Journal of Transport Economics and Policy, Vol. 39, pp. 279-294.

McCallum J. (1995). “National borders matter—Canada-US regional trade patterns”, American Economic Review, Vol. 85, pp. 615-623.

McCray J. P. (1998). “North American free trade truck highway corridors—US-Mexican truck rivers of trade”, Transportation Research Record, Vol. 1613, pp. 71-78.

Mukhopadhyay S. (2006). “Predicting global diffusion of the internet: An alternative to diffusion models”, Communications of the Association for Information Systems (January).

Nozick L. K. (1996). “Trade between the United States and Mexico”, Transportation Quarterly, Vol. 50, pp. 111-133.

Pagan A. R. (1974). “A generalised approach to the treatment of autocorrelation”, Australian Economic Papers, Vol. 13, pp. 267-280.

Pindyck R. S. and Rubinfeld D. L. (1998). Econometric Models and Economic Forecasts (4th ed.), Irwin McGraw-Hill: New York, NY.

Rumelhart D. E., Hinton G. E. and Williams R. J. (1988). “Learning internal representations by error propagation”, in: Parallel Distributed Processing Explorations in the Microstructure of Cognition, Volume 1, MIT Press: Cambridge, MA.

Saintgermain M. A. (1995). “Problems and opportunities for cooperation among public managers on the U.S.-Mexico border”, American Review of Public Administration, Vol. 25, pp. 93-117.

Smith B. L. and Demetsky M. J. (1997). “Traffic flow forecasting: Comparison of modeling approaches”, Journal of Transportation Engineering, Vol. 123, pp. 261-266.

Stank T. P. and Crum. M. R. (1997). “Just-in-time management and transportation service performance in a cross-border setting”, Transportation Journal, Vol. 36, pp. 31-42.

Taylor J. W. (2010). “Exponentially weighted methods for forecasting intraday time series with multiple seasonal cycles”, International Journal of Forecasting, Vol. 26, pp. 627-646.

Taylor J. C., Robideaux J. R. and Jackson G. C. (2004). “US-Canada transportation and logistics: Border impacts and costs, causes, and possible solutions”, Transportation Journal, Vol. 43, pp. 5-21.

Theil H. (1961). Economic Forecasts and Policy (2nd ed.), North Holland Publishing Company: Amsterdam, NE.

Tsekeris T. and C. Tsekeris (2011). “Demand forecasting in transport: Overview and modeling advances”, Ekonomska Istrazivanja – Economic Research, Vol. 24, pp. 82-94.

Villa J. C. (2006). “Status of the US-Mexico commercial border crossing process—Analysis of recent studies and research”, Transportation Research Record, Vol. 1966, pp. 10-15.

Vlahogianni E. I., Golias J. C. and Karlaftis M. G. (2004). “Short-term traffic forecasting: Overview of objectives and methods”, Transport Reviews, Vol. 24, pp. 533-557. Wei Y. and Chen M. C. (2012). “Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks”, Transportation Research Part C – Emerging Technologies, Vol. 21, pp. 148-162.

West C. T. (2003). “Structural Regional Factors that Determine Absolute and Relative Accuracy of U.S. Regional Labor Market Forecasts”, Journal of Agricultural & Applied Economics, Vol. 35, Supplement, pp. 121-135.

Xiang C., Ding S. Q. and Lee T. H. (2005). “Geometrical interpretation and architecture selection of MLP”, IEEE Transactions on Neural Networks, Vol. 16, pp. 84-96.