Intranational Home Bias in the Presence of Wholesalers, Hub-spoke Structures and Multimodal Transport Deliveries

Abstract

When modelling interregional flows it is standard to identify the origin and destination of a flow with the point of production and consumption. However, the presence of hub-spoke structures or multimodal flows may introduce bias, such as being an additional source for cross-sectional correlation between dyadic flows. The aim of this paper is to model inter-provincial flows within a country (Spain) considering this potential bias using a novel dataset with 50 inter-provincial flows and four transport modes. We then feed this dataset into various specifications of a gravity model that incorporates crosssectional dependence attributable to hub-spoke structures. express their gratitude to the UAM and the Ministry of Education and Science respectively for their generous FPI and FPU scholarships. Much-appreciated comments from various colleagues have served to improve the quality and scope of previous versions of this manuscript. However, any errors herein are entirely the responsibility of the authors. We all want to express our sincere gratitude to J.P. Lesage for gratefully sharing his Matlab routines in www.spatial-econometrics.com , which served as a base for our personal developments. Both investigations were developed in the context of three research projects: the C-intereg Project (www.c-intereg.es), founded by seven Tendance intra-nationale à privilégier le marché intérieur, au niveau des grossistes, de structures en étoile, et des livraisons par des moddes de transport multimodaux RÉSUMÉ lors de la modélisation de flux interrégionaux, la méthode standard consiste à identifier l'origine et la destination d'un flux avec le point de production et la consommation. Toutefois, la présence de structures en étoile ou de flux multimodaux est susceptible de fausser les données, en constituant, par exemple, une source additionnelle de corrélation transversale entre des flux dyadiques. Le but de la présente communication est de modéliser des flux interprovinciaux au sein d'un certain pays (l'Espagne), en tenant compte de ce parti pris potentiel, et en tenant compte d'un nouvel ensemble de données avec cinquante flux interprovinciaux et quatre modes de transport. Nous intégrons ensuite cet ensemble de données dans différentes spécifications d'un modèle à gravité incorporant une dépendance transversale attribuable à une structure en étoile.Favoritismo local intranacional en la presencia de mayoristas, estructuras de interconexión radial y repartos con transporte multimodal RESUMEN al modelar flujos interregionales, es normal determinar el origen y el destino de un flujo con el punto de producción y consumo. Sin embargo, la presencia de estructuras de interconexión radial o flujos multimodales puede dar origen a favoritismos, por ejemplo ser una fuente adicional para la correlación transversal entre flujos diádicos. El objetivo de este estudio es modelar los flujos interprovinciales en un país (España) considerando este posible favoritismo usando un conjunto de datos nuevo con cincuenta flujos interprovinciales y cuatro mo...

Greenhouse Gas Emissions from Intra-National Freight Transport: Measurement and Scenarios for Greater Sustainability in Spain

“…The variable lnDist m ij is the logarithm of the distance between province i and province j for each mode m. Note that, in line with Gallego et al [24], we have used alternative distance measures per transport mode. Each of these alternative distances is obtained as follows:…”

“…This dummy variable takes the value 1 if the flow's origin and destination are the same province and 0 otherwise. The anti-log of this dummy is the own-province effect or home bias extensively discussed in the literature of international trade [15,24,32,36,37].…”

“…This rich dataset was collected and filtered in accordance with the methodology described in Llano et al [18] and published as part of the C-intereg project (www.c-intereg.es). It includes refinements and extensions with respect to the dataset published in previous papers [15,24]. It is analyzed at the province level (Nuts 3), using the largest possible sectoral detail (29 products) compatible with the four transport modes.…”

“…This can be a drawback for accurate estimation of final emissions levels, but it is also a virtue in that it is more directly connected with the real economic activity capture in the National Accounts-usually an obligatory reference for any environmental analysis. In addition, the dataset has been subject to a debugging process with the aim of removing potential inter-national hub-spoke and re-exportation structures hidden within the intra-national freight flows [24]. This prevents the double counting of transit flows, mainly by road and railway, from hinterlands to ports before/after their loading/unloading for exporting to/importing from foreign markets.…”

“…For this, we use the gravity equation, the most standard methodology to model international and interregional trade flows [34,35]. This approach is rooted in previous articles modeling equivalent flows in Spain [15,18,24,34]. The baseline model is described by Equation (7):…”