LUCA-model: wider benefits of transportation 3 to 30% | Netherlands

LUCA is a spatial general equilibrium model for the Netherlands. It was constructed to study the wider effects of transportation developments on where people live, work, how they commute and use the land. Applications of LUCA show that the wider effects can vary between 3% and 30% of the direct transportation benefits.

LUCA works on a micro level; it models the choices of individual people, see left panel of the Figure. When making these choices, individuals take into account: (i) home location amenities (parks, nice sites, restaurants, etc.) and land and housing prices; (ii) job location characteristics such as e.g. wage; (iii) commuting costs. LUCA is estimated on real data for the Netherlands.

As an example, take a new railway between the economic centre of a country and its periphery, that reduces the commuting time between the two. In LUCA, this leads to more people taking the train and to more people willing to commute between periphery and centre. Labour supply in the centre increases and so does the number of jobs. The periphery loses jobs, but becomes a more attractive location to live in, because the accessibility of well-paid jobs in the centre is better now. As the demand for living in the periphery rises, land prices and land intensity increase. This restricts further demand growth and leads to a new equilibrium on the land market. In the new equilibrium the periphery has a higher population than in the reference situation, but fewer jobs.

LUCA allows to explicitly distinguish direct effects due to changes in transportation choices (modal shift), from wider effects due to changes in home and job location of individuals. In a LUCA-study of a train connection between the centre and its periphery, the wider effects were estimated to be 30% of the direct effects. In an LUCA-study of the impact of self-driving cars, the wider effects varied between 3% and 10%.

July 2017


- Teulings, C.N., Ossokina, I.V. and H.L.G. de Groot, 2018, Land use, worker heterogeneity and welfare benefits of public goods, Journal of Urban Economics 103: 67-82. Here you find a technical description of LUCA.

- Gelauff G., Ossokina, I.V. and C.N.Teulings, 2017, Spatial effects of automated driving: dispersion, concentration or