The development of the TIGRIS XL model: A bottom-up approach to transport, land-use and the economy

The project appraisal method in the Netherlands distinguishes direct effects, indirect distribution effects and indirect generative effects. Transport models are generally available for calculating the benefits of transport projects to travellers as part of the direct effects. The TIGRIS XL model, a Land-Use and Transport Interaction model, adds indirect distribution effects for the housing and labour market, by modelling changes in the spatial distribution of jobs and residents. This paper describes the current TIGRIS XL model and how it can be applied in the evaluation of transport projects. It refers to work done with the TIGRIS XL model to improve the calculation of the direct benefits by applying the so-called ‘logsum’ method. Finally it discusses ideas on how to extend the TIGRIS XL model to address indirect generative effects as well.The current TIGRIS XL model, its integration with the National Model System (the standard tool for the Dutch government to analyse the effects on passenger transport) and basic design principles are the starting point of such an exploration. These design principles include:

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an emphasis on detail, both spatial as well as in socio-economic segments, to account for differences in the availability of choice alternatives and in choice behaviour, and to provide impacts by region and socio-economic group;

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the requirement that the relationships used rest on an empirical foundation.

The post-processing methods proposed on this paper for the calculation of the direct benefits and indirect generative effects are consistent with these design principles. To calculate the indirect generative effects, a post-processing module is proposed which transforms changes in travel times and land-use into agglomeration effects. These agglomeration effects combine several of the generative effects, like scale economies, an increasing variety of products, labour market matches and knowledge spill-over. The effects of changes in the agglomeration indicator on productivity can be estimated with existing data sources, as was demonstrated in the UK (Graham, 2005).