Abstract This study investigates the factors that influenced the allocation of motorways across municipalities in mainland Portugal. Our analysis, based on Poisson Pseudo-maximum Likelihood models, suggests that population size and market potential in 1981 are important determinants of motorway density in 2020. Physical and geographical variables also help explain the spatial distribution of motorway investment, as terrain ruggedness and distance to the coast are negatively associated with motorway density. In addition, we consider the influence of the proximity to historical and pre-existing transport networks on the allocation of motorways; we find that municipalities that are closer to 1800's itineraries, the main roads of the 1945's National Road Plan, and 1981's train stations appear to have higher motorway densities in 2020, but this effect is concentrated in the vast and sparsely populated area of the country that excludes what we term the high-density Portuguese “blue banana”. Interestingly, it is also only in this low-density region that partisan alignment between the municipal and the national levels of government appears to affect the allocation of transport investment, which suggests that motorways are more of a political asset in more remote or less urbanised areas.

    Highlights Identifies factors that have influenced the spatial allocation of motorways in Portugal. Population size and market potential in 1981 are important determinants of motorway density in 2020. Physical and geographical variables also help explain the spatial distribution of motorways. Proximity to pre-existing networks has an effect, but this is much stronger in low-density areas. Partisan alignment between municipality and national government is also more relevant for low-density areas.


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    Title :

    What drives the allocation of motorways? Evidence from Portugal's fast-expanding network


    Contributors:


    Publication date :

    2022-06-03




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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