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Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain

机译:收费公路上重型车辆数量随时间的变化:动态面板数据可识别西班牙的主要解释变量

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摘要

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. (C) 2015 Elsevier Ltd. All rights reserved.
机译:在评估运输政策和预测未来投资需求时,关键是要不断提高对需求演变的认识。对于收费公路而言,这变得尤为重要,在最近几十年,收费公路已成为为公路项目提供资金的越来越普遍的手段。但是,关于收费公路需求弹性估算的文献很少,并且有一些重要方面需要更详细地分析。特别是,先前对交通分析的研究通常不会将重型车辆的需求与总需求进行分类,因此并未考虑该交通路段的特定行为模式。此外,GDP是主要的社会经济变量,最常被用来解释公路货运量随时间的增长。本文试图确定能够更好地解释收费公路随时间推移重型车辆需求变化的变量。为此,我们提出了一种动态面板数据方法,旨在确定可解释多年来道路货运行为的关键社会经济变量。结果表明,尽管采用了通常的做法,GDP可能无法构成重型车辆需求的合适解释变量。相反,仅考虑对运输需求(如建筑或工业)有重大影响的那些部门的GDP,会得出更一致的结果。该方法适用于1990-2011年期间的西班牙收费公路。在国际背景下,这是一个有趣的案例,因为自2008年经济危机开始以来,西班牙的公路货运需求比其他地方的下降幅度更大。(C)2015 Elsevier Ltd.保留所有权利。

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