"Economies of agglomeration describe the productivity benefits that some firms derive from being located close to other firms. This could be because proximity to other firms facilitates more sharing of knowledge or because locating close to other firms means access to more suppliers and larger labour markets."[1]
The methodology employed for measuring a firm’s access to markets is ‘effective density’ (Graham, 2005). Effective density is a measure of the accessibility of zone i to jobs in all zones. The formula for effective density, of zone i, in situation X (X is base, Do-minimum or Do-Something) is given by:
where EjX is the employment in zone j and (gijX)α is the generalised cost of travelling between zone i and j in situation X. The parameter α represents the importance of distance in determining access to markets.
As such, although termed agglomeration benefits, practitioners should not assume that these benefits are exclusive to dense agglomerations, as the theory underlying them, that improved transport provides benefits by giving firms better access to markets and factors of production, applies equally to both areas of high and low initial levels of agglomeration. The name is an indication that benefits area associated with increases in agglomeration, rather any particular base level. Indeed, research suggests that there are diminishing returns to agglomeration, which implies that the greatest potential for a given change in transport costs to result in agglomeration benefits is in areas with a low initial effective density.
As a result, practitioners should not assume that agglomeration benefits will be focussed in urban areas rather than rural ones. Indeed, within agglomerations, which tend to have a very mature transport infrastructure, evidence shows that it is difficult to generate significant changes in the overall cost of travel and as such it is unlikely that any single transport scheme will result in significant changes to effective density in an agglomeration.
In contrast, although more rural areas will tend to have a smaller population exposed to any change in effective density, it is possible to achieve greater changes in transport costs, and therefore more significant changes in effective density, in these areas.
Practitioners should note, however, that any estimated agglomeration benefits will be affected by the assumptions regarding the α parameter. Although current best estimates of the value of α are that it is equal to one, this is an area subject to ongoing research and it is possible that it will be revised in the near future. As such, estimates of agglomeration benefits have a relatively high degree of associated uncertainty, and are to be treated as a sensitivity to the standard TEE analysis. Further detail on the calculation of agglomeration benefits and the parameters to be used is given in Section 9.3.5.
[1] Transport, Wider Economic Benefits and Impacts on GDP, Department for Transport (2006)
