Dynamic spatial equilibrium models for social cost benefit analysis of transport projects and policies: implementations for the Netherlands and Hungary

During the late 80’s the so-called SCGE (Spatial Computable General Equilibrium) models were introduced within the research community. These models were cross-sectional in nature and were most interesting from the perspective of showing the consequences of changes in interregional interactions; in other words, typically macro economic aspects were lacking. Since then, new models have been developed since that include dynamic properties of spatial economic systems and have an improved connection to macro-economic models. This paper reports on 2 new such projects in Japan/the Netherlands and Hungary. The Japanese and Dutch model are both similar in structure and are presented as one: the RAEM-Light model. They are dynamic, spatial computable general equilibrium models on a multiregional and multisectoral basis. Typical cases for which this model was applied, where dynamic effects matter, are the impacts of earthquakes in Japan, and the effect of gradual increase of congestion in the Netherlands. The Hungarian model is a a macro-regional economic model built for the government for development policy analysis. The model consists of a macroeconometric (the “macro block”), a spatial computable general equilibrium (the “regional block”) and a Total Factor Productivity (the “technology block”) sub-models. The regional block was derived from the Japanese/Dutch Spatial CGE model. The unique feature of the integrated macro-regional model is thus that it endogenizes technological change in a spatial context building on the findings of the sizeable literature of the geography of innovation and regional innovation systems. As such this model can be used for policy analyses on the effectiveness of various economic development tools targeting productivity increase such as infrastructure development (e.g., highway building), human capital or R&D investments. Not only the macro and regional effects of the actual amounts spent are investigated but also the effects of different geographical distributions of the funds can be analyzed by the model. We introduce the main features of the RAEM-Light model and the Hungarian and provide examples of applications of both. The application for the Netherlands shows well how interregional dynamics work in situations where resistances for transportation between regions change. The second application, for Hungary, concerns the impacts of regionally differentiated scenarios for investments using European structural funds. We conclude that the combination of dynamic, spatial and sectoral elements is a critical feature for analysis of regional development policies.