Exploring the economic impacts of agglomeration economies in urban rail projects

In recent years, the potential to produce economic benefits has become increasingly important to the decision-making process for urban passenger rail investments. Such benefits are seen as a motivation for rail investment either by encouraging jobs to locate in a particular location or by opening up new journey-to-work opportunities for residential areas. However, while a significant portion of the benefits (e.g. travel time savings) are already well captured under the present Cost-Benefit Analysis (CBA) methodology, the current conventional frameworks do not take into consideration other potentially significant impacts such as agglomeration benefits in production. Agglomeration benefits in production are positive impacts on productivity amongst firms due to an increasing concentration of firms or increasing concentration of employment or widening of labour markets. A synthesis of evidence from previous studies suggests that agglomeration effects associated with urban rail projects might be significant. However, the wide range of estimated elasticity values clearly indicates that there is a knowledge gap pertaining to the plausible range of its economic value and the methodology to estimate such effects associated with urban rail. The focus of this research is to explore the economic impacts of agglomeration economies for urban rail projects. The research uses a framework of survey and secondary research as well as an experimental modelling approach involving transport modelling and economic Computable General Equilibrium (CGE) modelling. The Central Business District (CBD) of Melbourne City is adopted as the case study in this thesis to explore and estimate such agglomeration effects associated with urban rail. The fundamental assumption underlying the research methodology is that the urban passenger rail system serving Melbourne CBD is an enabler of the CBD’s economic growth. Therefore, if urban rail capacity is constrained (i.e. rail demand exceeds rail capacity provision), agglomeration diseconomies due to the corresponding increase in traffic congestion would set in. The poorer accessibility of the CBD may impact upon the CBD’s employment size and hence its productivity. The economic value of this urban dis-agglomeration will provide a mirror indication of the agglomeration benefits associated with the expansion of urban passenger rail provision. A major motivation for this approach is the overcrowding of Melbourne CBD rail services which has occurred over the last 5 years. Two measures of agglomeration economies in urban rail were explored in this research - the potential CBD employment suppression impact and the reduction in the proximity between CBD firms and workers due to an urban rail capacity constraint. This research estimated the potential CBD employment suppression impacts using three different approaches - outputs from the transport modelling with trip elasticities, findings from a CBD employer survey and outputs from secondary data analysis. Productivity elasticities (from secondary research) were applied on the employment suppression impacts to estimate the agglomeration dis-benefits associated with an urban rail constraint. The deterioration in the CBD’s accessibility (i.e. the 2nd measure of agglomeration economies used in this research) has also been employed to estimate the agglomeration dis-benefits and to derive a range of productivity shocks, using the method adopted by the UK and New Zealand to estimate agglomeration benefits. The productivity shocks were then inputted into a CGE model to estimate its impact on Melbourne CBD’s economy. A comparative assessment of the agglomeration estimates from the various approaches was carried out and the results presented in this thesis. This research provides an important contribution to knowledge by exploring a range of alternative methods to estimate agglomeration economies in urban rail and compares the results of these with the conventional method to understand the robustness and variability of outcomes. To the best knowledge of the author, no other published research has undertaken a comparative assessment of this kind. In particular, no previous published study has explored agglomeration economies associated with urban rail using CGE models in this manner. The main contribution of the CGE modelling work includes the development of the modelling approach for agglomeration economies in urban rail and the demonstration of how such agglomeration economies may impact Melbourne CBD and other regions in the short and long term. This finding contributes to the understanding of the overall effect of agglomeration economies in urban rail which is beneficial in the appraisal of future rail proposals. In addition, this understanding is also valuable as it can help eradicate the double-counting ambiguity regarding agglomeration benefits.