The Wider Economic Benefits of Greater Connectivity

The picture shows the Oresund bridge between Copenhagen in Denmark and Malmo in Sweden, a truly transformational (€4 billion) transport project that led to economic benefits much greater than would be estimated using standard cost-benefit analysis.

Although something on that scale is unlikely in New Zealand, it does raise the question of whether investing in large transport infrastructure projects could deliver benefits additional to those estimated using the NZ Transport Agency’s Economic Evaluation Manual.

With funding from the Agency, a research consortium involving Infometrics [1] developed two models that can be used alongside the more established methods of transport appraisal, to assess the possible wider economic benefits from transport investment and where those benefits might occur. The two models are a gross value added (GVA) model and a spatial general equilibrium (SCGE) model. 

The GVA model largely deals with productivity improvements that stem from greater effective population density, generated by improved access between urban areas. It also identifies the industries in which the productivity improvements – but not necessarily the employment gains – would likely occur.

The SCGE model simulates where people choose to live and work as a function of the wages on offer at different locations, the cost of housing (land) at different locations and the cost of commuting. 

Both models were applied to a case study region that encompassed the combined areas around and between Auckland, Hamilton and Tauranga. The case study involved hypothetical changes to the road network (such as the Waikato Expressway) connecting these areas, with associated reductions in travel times. 

 

 

 

 

 

 

 

 

 

The research demonstrated that productivity effects vary by industry. In the case study they were concentrated amongst the manufacturing, consumer services, business services and community services industries. Approximately half of the total productivity gain was estimated to be the result of better access to airports, although it is possible that this effect was due to the proximity of those industries to large cities (which tend to have airports) in general rather than international airports per se. 

The SCGE model enabled estimation of the benefits attributable to a spatial reallocation of employment, GDP and household economic welfare, capturing both the direct time savings achieved through the road improvement and the subsequent productivity improvements derived from the GVA model. 

Although the results depended on the specification of the scenarios, broadly speaking the inclusion of productivity gains led to most of the benefit from improved travel times occurring in Auckland, but allowing for spatial reallocation led to most of the benefit occurring outside Auckland. In aggregate the gains from a spatial reallocation of economic activity outweighed those from greater productivity.

The analysis confirmed that transport changes can interact with land use changes to provide benefits that exceed the user benefits represented in standard transport appraisal approaches. Potentially therefore, the welfare benefits of transport projects that improve connectivity within the regions are being ignored, especially when they occur in the context of growing populations and economies.

The research concluded that the two models can be usefully applied to major transport projects. While they are unlikely to shift the current emphasis in transport appraisal away from transport user benefits, they can complement the standard analysis in five ways:

  1. The models provide relatively accessible ways to test the likely high level effects of major projects without the need for extensive traffic modelling. This will be useful in the early stages of business case preparation.
  2. The models provide a means of validating the current benefit estimates used in transport appraisals and may lead to an iterative process of improving traffic demand assumptions.
  3. The models provide a means of quantifying the benefits associated with land use change.
  4. The models estimate the spatial economic effects from major transport improvement projects. These estimates are unlikely to provide a definitive measure of what will occur, as they are sensitive to the assumptions in the models, but sensitivity testing will improve the understanding of dynamic and spatial effects.
  5. The models provide measures of effects that are more likely to be readily understood by stakeholders, such as effects in terms of GDP and jobs. 

 

Footnotes

[1] The research team comprised Adolf Stroombergen of Infometrics, Anthony Byett of ECPC,  James Laird from the Institute for Transport Studies at the University of Leeds) and transport consultant Richard Paling. 

Enjoyed this article?

You might like to subscribe to our newsletter and receive the latest news from Infometrics in your inbox. It’s free and we won’t ever spam you.