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Erschienen in: Transportation 3/2014

01.05.2014

Assessing the employment agglomeration and social accessibility impacts of high speed rail in Eastern Australia

verfasst von: David A. Hensher, Richard B. Ellison, Corinne Mulley

Erschienen in: Transportation | Ausgabe 3/2014

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Abstract

There is growing interest in establishing additional evidence, under the umbrella of the wider economy impacts of transport infrastructure projects, to support transport projects in general and public transport projects in particular that struggle to obtain benefit–cost ratios sufficient to gain the support of financial agencies. This paper focuses on one element of wider economy impacts, often referred to as effective economic (employment) density or employment agglomeration impacts, and another, less usually identified, social accessibility impact (SAI) which we refer to as effective social density, which in broad terms provide, correspondingly, evidence of the potential gains in work-related output (often referred to as productivity gains) and potential gains in non-work-related outputs. Both are associated with gains in individual and household benefit attributable to improved accessibility to services linked with populations and particular locations. The SAIs may capture some of the induced benefits in those jurisdictions where these are included routinely in benefit–cost analysis, and the methodology here is most appropriate to those settings where an existing calibrated demand curve may not be available. Using the proposed high speed rail (HSR) project between Sydney and Melbourne as the empirical setting, we identify economic agglomeration and social accessibility benefits for work and non-work related activity respectively. We find the former to be relatively small compared to the significant gains associated with non-work related travel activity, suggesting the greatest benefits associated with HSR, especially for those residents outside of the major metropolitan areas, will be non-work related travel activity.

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Fußnoten
1
Bartik (2011) discusses ways of including job creation benefits into a benefit–cost analysis but recognises the complexity of this, in part influenced by the nature of employment creation (e.g. involuntary vs. voluntary unemployed sources). Given that job creation benefits are not typically included in the benefit–cost appraisal of transport infrastructure projects, they are seen, when captured as ‘wider economy’ impacts. With very low unemployment in Australia (less than 5 %), we speculate that new jobs will be largely serviced by a mix of growing migrants and individuals already in employment changing jobs.
 
2
In a full benefit–cost analysis, the risk of double counting is real and hence we have referred to the social impacts as induced social benefits. In this paper double counting of benefits has not occurred as, in line with the objective of the study we have identified real benefits to the population resident in regional Australia in particular instead of a focus on a fully fledged benefit–cost analysis. We have also ensured that the wider social impacts are separated from the wider economy impacts, as emphasised in the title of this paper.
 
3
We should be clear of the meaning of induced demand. We see it as essentially additional trips associated with project investment for existing populations, as well as additional trips for growth in population attributable to increased accessibility.
 
4
We thank Brian Alstadt of EDR Group for this observation.
 
5
The Federal government awarded a Phase 2 contract to AECOM in December 2011 to undertake new patronage studies as well as the full costing, design and impact studies. The final report was released in April 2013 and is available on the Federal Department of Infrastructure and Transport website.
 
6
The influences on modal switching and induced trips by HSR include generalised cost, income, size of travelling party and car ownership.
 
7
The Sydney–Melbourne corridor is often compared to corridors in other countries to get a sense of market shares for given travel times. For example, the UK indicates a rail share of the total air plus rail market of approximately 50 % and in Europe it is 75 % at 3 h rail in vehicle travel time, with a sharp switch in the UK but a flatter transition in Europe. The Sydney–Melbourne corridor, for all markets, currently has a market share as follows: 74 % car, 15 % air, 10 % rail and 1 % coach. Estimates of HSR market share (given induced demand of 10 %) suggest a market share of approximately 22 %, although this varies significantly by OD pair. For example, for Sydney–Canberra we predict modal switching to HSR varying from 73 % for non-scheduled coach to 17 % for non-business train. The big market segments are air business and car non-business with respective HSR diverted shares of 70 and 20 %. The latter is primarily non-family situations associated with a driver travelling alone.
 
8
Hensher et al. (2012a, b) provide details of data sources including desirable and available data. To measure output productivity directly would involve the estimation of an aggregate production function with multi-factor inputs (labour, capital, land) as well as material and other intermediate commodities as inputs. Lack of data on these factors and material inputs at a zonal level for different industries in Australia implies that an aggregate production function cannot be estimated to allow changes in multi-factor productivity for each zone and for each industry to be identified. Our approach concentrates on a narrower concept of factor productivity, namely labour productivity, based on an assumed relationship between labour productivity and its ultimate outcome, the average wage rate for labour in different industries and in different zones. If we assume labour is paid its marginal productivity, then any increase in labour productivity will flow on to its wage rate. If the flow on is not 100 % and provided there as there is a steady relationship between improvement in labour productivity and change in wage rate (perhaps through strong union bargaining), then the percentage change in the wage rate will be correlated with the percentage change in labour productivity. In addition there is a high correlation between movements in labour costs and output.
 
9
We are assuming that there are two key determinants of location utility, namely accessibility as proxied by generalised cost associated with each mode between a given location i and each and every j locations (\(j = 1 ,\ldots J\)), allowing for intra-zonal travel, and location i-specific attributes that are unobserved and implicitly assumed to be highly correlated with generalised cost.
 
10
A referee pointed out that the conventional consumer surplus measure being used in benefit–cost analysis as an aggregate estimate of the original derived demand benefit which, being a saving, feeds back through the economy. Hence it is a measure of, and some might suggest a surrogate for, these more widely distributed benefits. One area of current research is comparisons of the differences between the net benefits shown by SDGE models and the sum of the aggregate net benefits of consumer surplus and other “wider benefits”.
 
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Metadaten
Titel
Assessing the employment agglomeration and social accessibility impacts of high speed rail in Eastern Australia
verfasst von
David A. Hensher
Richard B. Ellison
Corinne Mulley
Publikationsdatum
01.05.2014
Verlag
Springer US
Erschienen in
Transportation / Ausgabe 3/2014
Print ISSN: 0049-4488
Elektronische ISSN: 1572-9435
DOI
https://doi.org/10.1007/s11116-013-9480-7

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