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Linking models for land use analysis: experiences from the SENSOR project

Author

Listed:
  • Jansson, Torbjorn
  • Bakker, Martha M.
  • Boitier, B.
  • Fougeyrollas, A.
  • Helming, John F.M.
  • van Meijl, Hans
  • Verkerk, P.J.

Abstract

In order to quantify the effects of a comprehensive set of policies on land use, interaction between sectors needs to be accounted for, while maintaining a high level of detail for each sector. This calls for a combination of sector specific and sector wide models. This paper describes such a modelling system, with emphasis on the linking of the models to a coherent system. Five sectors of significant importance for land use are modelled individually: Forestry, agriculture, urban land use, transport infrastructure, and tourism. All models are connected as sub-modules to an economy-wide partial econometric model. In addition, a land cover model is used to disaggregate land use down to 1km grid resolution. The linking of such a diverse set of models in a consistent way poses conceptual as well as practical issues. The conceptual issues concern questions such as which items of the models to link, how to obtain a stable joint baseline scenario, and how to obtain a joint equilibrium solution for all models simultaneously in simulation. Practical issues concern the actual implementation of the conceptually sound linkages and provision of a workable technical solution. The linked system allows us to introduce a shock in either of the models, and the set of results will provide a joint solution for all sectors modelled in SENSOR. In this manner, the models take a complex policy scenario as argument and compute a comprehensive set of variables involving all five land use sectors on regional level, which in turn forms a basis for distilling out the impact on sustainability in the form of indicators. Without the extensive automation and technical linkages, it would not have been possible to obtain a joint equilibrium, or it would have required exorbitant amounts of working time.

Suggested Citation

  • Jansson, Torbjorn & Bakker, Martha M. & Boitier, B. & Fougeyrollas, A. & Helming, John F.M. & van Meijl, Hans & Verkerk, P.J., 2008. "Linking models for land use analysis: experiences from the SENSOR project," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44169, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae08:44169
    DOI: 10.22004/ag.econ.44169
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    References listed on IDEAS

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    1. Sebastian Rausch & Thomas Rutherford, 2010. "Computation of Equilibria in OLG Models with Many Heterogeneous Households," Computational Economics, Springer;Society for Computational Economics, vol. 36(2), pages 171-189, August.
    2. Richard E. Howitt, 1995. "Positive Mathematical Programming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(2), pages 329-342.
    3. Heckelei, Thomas & Britz, Wolfgang, 2005. "Models Based on Positive Mathematical Programming: State of the Art and Further Extensions," 89th Seminar, February 2-5, 2005, Parma, Italy 234607, European Association of Agricultural Economists.
    4. Hertel, Thomas, 1997. "Global Trade Analysis: Modeling and applications," GTAP Books, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, number 7685, December.
    5. Brecard, Dorothee & Fougeyrollas, Arnaud & Le Mouel, Pierre & Lemiale, Lionel & Zagame, Paul, 2006. "Macro-economic consequences of European research policy: Prospects of the Nemesis model in the year 2030," Research Policy, Elsevier, vol. 35(7), pages 910-924, September.
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    2. Alexander Gocht & Pavel Ciaian & Maria Bielza & Jean-Michel Terres & Norbert Röder & Mihaly Himics & Guna Salputra, 2016. "Economic and environmental impacts of CAP greening: CAPRI simulation results," JRC Research Reports JRC102519, Joint Research Centre.

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