Transport-mode competition in intra-national trade: An empirical investigation for the Spanish case

Llano, Carlos; Mata, Teresa Bullón; Lanchas, Jorge Díaz; Gallego, Nuria

doi:10.1016/j.tra.2016.10.023

Cited by 19 publications

(18 citation statements)

References 33 publications

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“…This may limit our ability to extrapolate a given share from any other product. In addition, the limit of 600 km is supported by previous analyses conducted in Spain [15,42,43], which suggest that railway is competitive with road beyond this threshold. Although, according to Figure 4, railway flows in tons agglomerate in short distances (<200 km), a detailed view of the distribution by product suggests that the agglomeration is driven by certain heavy products, whose performance is not comparable to that of products usually delivered by road.…”

Section: Scenario 2: Moderate Modal Shift From Road To Railwaysupporting

confidence: 60%

“…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.…”

Section: Estimating Ghg Emissions By Mode For 1995-2015mentioning

confidence: 99%

“…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):…”

Section: Forecasting Inter-provincial Flows In 2016-2030mentioning

confidence: 99%

“…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].…”

Section: Forecasting Inter-provincial Flows In 2016-2030mentioning

confidence: 99%

“…Based on findings from previous analyses [11,15,42], and the descriptive analysis reported in Figure 5, this scenario uses the following criteria:…”

Section: Scenario 2: Moderate Modal Shift From Road To Railwaymentioning

confidence: 99%

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

2018

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Greenhouse Gas (GHG) emissions is a topic of major concern worldwide. Following previous articles which provide a methodology for estimating GHG emissions associated with international trade by transport mode at the world level, in this paper, we estimate an equivalent database of GHG emissions for inter-regional trade flows within a country (Spain). To this end, we built a new database of GHG emissions for origin-destination flows between Spanish provinces during 1995-2015. For each year, we combine industry-specific flows by four transport modes (road, train, ship and aircraft) with the corresponding GHG emissions factor for each mode in tons*km, drawn from the specialized literature. With this dataset of GHG emissions, we generate and analyze the temporal, sectoral and spatial pattern of Spanish inter-regional GHG flows. We then forecast emissions for 2016-2030 and consider how transport mode shifts might produce a more sustainable freight system within the country through the substitution of environmentally friendly alternatives (railway) for specific origin-destination-product flows in high-polluting modes (road).

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Section: Scenario 2: Moderate Modal Shift From Road To Railwaysupporting

confidence: 60%

Section: Estimating Ghg Emissions By Mode For 1995-2015mentioning

confidence: 99%

Section: Forecasting Inter-provincial Flows In 2016-2030mentioning

confidence: 99%

Section: Forecasting Inter-provincial Flows In 2016-2030mentioning

confidence: 99%

“…Based on findings from previous analyses [11,15,42], and the descriptive analysis reported in Figure 5, this scenario uses the following criteria:…”

Section: Scenario 2: Moderate Modal Shift From Road To Railwaymentioning

confidence: 99%

See 3 more Smart Citations