Forecasting transportation demand for the U.S. market

Vasilios Plakandaras, Theophilos Papadimitriou and Periklis Gogas

Transportation Research Part A: Policy and Practice, 2019, vol. 126, issue C, 195-214

Abstract: In this paper we forecast air, road and train transportation demand for the U.S. domestic market based on econometric and machine learning methodologies. More specifically, we forecast transportation demand for various horizons up to 18 months ahead, for the period 2000:1–2015:03, employing, from the domain of machine learning, a Support Vector Regression (SVR) and from econometrics, the Least Absolute Shrinkage and Selection Operator and the Ordinary Least Squares regression. In doing so, we follow the relevant literature and consider the contribution of selected variables as potential regressors in forecasting. Our empirical findings suggest that while all models outperform the Random Walk benchmark, the machine learning applications adhere more closely to the data generating process, producing more accurate out-of-sample forecasts than the classical econometric models. In most cases, we find that the transportation demand is driven by fuel costs, except for road transportation where macroeconomic conditions affect transportation volumes only for specific forecasting horizons. This finding deviates from the existing literature, given the support of previous studies to macroeconomic conditions are driving factors of transportation demand. Our work relates directly to decisions on transport infrastructure improvement, while it can also be used as a forecasting tool in shaping transportation-oriented policies.

Keywords: Transportation; Transportation demand; Forecasting; Machine learning; Support Vector Regression; LASSO (search for similar items in EconPapers)
JEL-codes: C32 C53 L41 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0965856417313551
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:transa:v:126:y:2019:i:c:p:195-214

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.tra.2019.06.008

Access Statistics for this article

Transportation Research Part A: Policy and Practice is currently edited by John (J.M.) Rose

More articles in Transportation Research Part A: Policy and Practice from Elsevier
Bibliographic data for series maintained by Catherine Liu ().