| Leader | – | Key words | – | Presentation | – | Work plan | – | Involved teams |
Task 2.3: The rural-urban dynamics of land use within the EU
|| Leader ||
| INRA EcoPub |
To characterise and explain the rural-urban dynamics of land use within the EU, task 2.3 will develop a specific framework that bridges the gap between environmental economics and economic geography. It will encompass environmental externalities, land markets, and drivers of spatial agglomeration and/or dispersion. The first step will characterise the determinants of shifts from one type of land use to another, over the past years, for rural areas, urban areas, forests. Nonlinear dynamics, with agglomeration and congestion effects, could occur. Determinants, such as the relative locations of suppliers versus end consumers, the spatial organisation of the supply chains, and the forms of urban development (mono vs. polycentric forms of density), may also differ across EU Member states. Using data pooled in WP1, we will econometrically estimate how different determinants of land use change over time and we will control individual heterogeneity, and spatial autocorrelation, using spatial econometrics with multinomial models. The identification of competition for resource determinants (e.g., water stock dynamics interact with the location of agricultural and residential uses), and the characterisation of the response to these determinants, will provide basic data for assessing policy action approaches. This approach will track the amount of land, of each quality, in each use, and at each point in time; and it will ultimately lead to an elasticity estimate that is appropriate for a long time frame. Transition matrices over a baseline time path will be estimated and then used in simulations of land use transitions, with transition probabilities in each period reflecting either exogenous determinants or political variables.
Econometric estimates of the impacts of the various determinants of land rents may be useful for predicting the use of land as a function of policy (e.g., domestic prices, farm policies, taxes, and zoning) and of exogenous determinants (e.g., climate change, macro environment, and exogenous drivers of transportation costs). Apart from their direct interpretation, the estimates from task 2.3 will be used to improve the empirical base used to specify land use choices in CAPRI.