Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain |
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| Institution: | 1. Poisonous Plant Research Laboratory, Agricultural Research Service, United States Department of Agriculture, 1150 E. 1400 N., Logan, UT 84341, USA;2. Central de Diagnóstico Veterinário, Escola de Veterinária, Federal University of Pará (UFPA), Castanhal, Pará 68743-080, Brazil;3. Veterinary Hospital, Federal University of Campina Grande (UFCG), Patos, Paraíba 58700-000, Brazil;1. CTS, UNINOVA, Dep. de Eng.ª Eletrotécnica, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal;2. University of Surrey, Guildford, Surrey GU2 7XH, UK;3. Sustainable Transport Research Group, Department of Civil Engineering, Faculty of Science and Engineering, University of Wolverhampton, Wolverhampton, UK;1. Department of Civil Engineering and Applied Mechanics, McGill University, 817 Sherbrooke Street West, Montreal, Quebec H3A 0C3, Canada;2. Department of Policy Analysis and Management, Cornell University, 251 Martha Van Rensselaer Hall, Ithaca, NY 14853, United States;3. Cornell Program in Infrastructure Policy, Cornell University, 251 Martha Van Rensselaer Hall, Ithaca, NY 14853, United States;1. Norwegian University of Science and Technology, 7491 Trondheim, Norway;2. Molde University College, PO Box 6405, Molde, Norway;3. Norwegian Public Roads Administration, PO Box 8142 Dep, 0033 Oslo, Norway;1. Volvo Research and Educational Foundation (VREF), Center of Excellence for Sustainable Urban Freight Systems (CoE-SUFS), Department of Civil and Environmental Engineering, Rensselaer Polytechnic Institute,, 110 8th St., Troy, NY 12180, USA;2. Center for Infrastructure, Transportation, and the Environment, Rensselaer Polytechnic Institute, 110 Eighth St., Troy, NY 12180, USA;3. Department of Planning and Transport, University of Westminster, 35 Marylebone Road, London NW1 5LS, UK;1. Energy Centre, Faculty of Business and Economics, The University of Auckland, Owen G Glen Building, 12 Grafton Road, Auckland 1010, New Zealand;2. Dept. of Economics and Energy Centre, Faculty of Business and Economics, The University of Auckland, Owen G Glen Building, 12 Grafton Road, Auckland 1010, New Zealand |
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| Abstract: | Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patterns of this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990–2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008. |
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| Keywords: | Heavy vehicle traffic Road freight Toll road Demand elasticities Dynamic panel data Spain |
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