2009), administrative feasibility or inequality creation when for instance some inhabitants are asset-rich but cash-poor (Medda, 2012). Another main issue is revenue predictability, i.e. the fact that it is difficult to anticipate the rent creation. We focus this study on this last point.

Econometric studies have been extensively used to analyze past impact of transport developments on housing and land prices (see reviews in Smith and Gihring, 2006; Stefania Radopoulou et al., 2011; Salon and Shewmake, 2011). This enables to retrospectively quantify the benefits that land value capture could have brought, and serves as a basis for future estimations. However, it is not directly possible to fully rely on econometric-based coefficients to anticipate land value potential. Indeed, transport is not a “standard” public amenity: contrary to, say, the creation of an attractive park or the presence of a good school, accessibility is not an amenity per se (Mohring 1961). Accessibility is only valuable if it enables travel to interesting places. To adequately analyze benefits provided by increased accessibility, and therefore how much can be potentially capitalized in land prices, the whole city should be taken into account and whole-city models should be used.

Using first a theoretical urban economic model, and then an applied model, Nedum-2D, calibrated on Paris urban area, we propose here to show how urban models can capture important mechanisms that cannot be taken into account when using only constant elasticities (of land prices in response to transport investment) from the literature. To do that, we analyze and compare with the model rent creation and land value capture potential corresponding to different public transport investments in the Paris urban area. The results of the applied model that we use here are fully consistent with urban economic theory, but they provide numerical estimations, taking into account geographical specificity of a given city.

The same land price increase will have very different impacts on households when they are landowners or when they are renters. In one case, it is indeed an increase in wealth, whereas in the other case it is often translated into an increase in housing expenditures. The impact of transport improvement on household welfare therefore strongly depends on the hypothesis about who owns the land (Brueckner, 2005; Gusdorf and Hallegatte, 2007). In this study, we do not consider welfare impacts, and focus only on land price variations. We also consider that absentee landowners own the land, i.e. that land price variations do not directly impact household income, and that rents are not redistributed to the city population.

These simulations show that a significant fraction of infrastructure costs (almost all costs, under optimistic hypotheses) can be extracted from land value increase, and that one of the main factors influencing rent creation is population increase in the city due to the infrastructure construction. Simulations also show that land value capture potential is affected by other transport infrastructure developments in the city. Especially, in a sequence of several infrastructure developments, land value capture potential depends on the timing of each investment.

These results are derived on the case of the Paris agglomeration, but the qualitative findings are valid in any large city. Moreover, we are well aware that the data and models needed to replicate this analysis are not available in all locations, especially in developing countries. This is why we also propose a reduced form model that approximates the full model (within a 15% error margin in the case of Paris) and can be applied with limited resources and little data. This reduced form model can be used to assess the potential for rent capture and identify cases where more in-depth studies are necessary.

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