March 2011 | Frontier Economics, Atkins, ITS 1
Appendix 1 – High speed railway Madrid – Barcelona in Spain
This chapter presents the results of the ex post cost-benefit analysis of the high speed railway line between Madrid and Barcelona.
1.1 Introduction
1.1.1 Project overview
Location & Description The LAV (Línea de Alta Velocidad ) Madrid – Barcelona – French border is a high speed railway line connecting Madrid to the French border via Barcelona. The route is shown in Figure 1 below. The figure shows the section that is already operational (Madrid to Barcelona) as well as the remaining section along the coast to the French border. This section is currently under construction. We have therefore excluded it from this evaluation.
Figure 1. High speed railway Madrid – Barcelona – French border
Girona
Zaragoza Lleida Barcelona
Tarragona
Madrid
Source: Openstreetmap.org
Appendix 1 – High speed railway Madrid – Barcelona in Spain
2 Frontier Economics, Atkins, ITS | March 2011
The line connects the two most densely populated urban areas in Spain, Madrid and Barcelona, with intermediate connections in Guadalajara, Calatayud Zaragoza, Lleida, Tarragona (station in Camp de Tarragona, between Tarragona and Reus). The LAV is part of the TEN-T Priority Project 3 (high-speed railway axis of south-west Europe), whose main objective is to provide high-speed rail connections between the Iberian Peninsula (Portugal and Spain) and the rest of Europe. The LAV between Madrid and Barcelona covers 621 kilometres, and it was developed in three stages: Section Madrid – Lleida: opened in October 2003, and covering around 442 km of high speed rail. Section Lleida – Tarragona: in operation since December 2006, adding 78 km of railway line to the previous section. Section Tarragona – Barcelona (Sants station): operational since February 2008, with an additional length of 100 km. The LAV is still under construction in the section Barcelona to Figueres in Spain, with 132 km expected to be completed in 2012. The section between Figueres and Perpignan in France was completed in 2008. Currently, the new railway line allows speeds up to 300 km/h, with future improvements increasing the maximum commercial speed up to 350 km/h. This implies current journey times for the commercial AVE service (Alta Velocidad Española) between Madrid and Barcelona of between 2h 38min and 3h 19min, depending on the number intermediate stations. The AVE service, operated by RENFE is the fastest railway service offered on the LAV. RENFE is the unique railway operator offering railway services on the LAV. Current journey times for the AVE are shown in Table 1.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 3
Table 1. AVE journey times between Madrid and Barcelona
Stopovers Duration
Non stop 2h 38min
Zaragoza 2h 52min
Zaragoza, Lleida and Tarragona 3h 12min
All stations 3h 19min
Source: RENFE
The project, as defined in the TORs, comprises 12 subprojects that account for the construction of 72 km of rail bed and the installation of 610 km of railway tracks. The total cost of the 12 subprojects was around €1,719 million, of which €1,442 million was eligible for funding. The total Cohesion Fund contribution for these subprojects in the period 2000-2006 was around €1,042 million, equal to 72.25% of the eligible project costs.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
4 Frontier Economics, Atkins, ITS | March 2011
Table 2. 12 Subprojects making up the project CF Start Description of project and contribution Subprojects date length (% of eligible cost)
Supply and installation of track June 642,214,556 Madrid - Lleida 1999ES16CPT001 material (485km, 52km of 1999 viaducts, tunnels and bridges) (72.25%)
March Supply and installation of track 165,781,097 Lleida-Olérdola 2003ES16CPT004 2003 material (125.5 km) (72.25%)
Lleida-Martorell November 164,034,000 Rail bed construction (18.54 km) 2000ES16CPT005 2000 (72.25%)
Martorell-Barcelona. July 69,168,327 Rail bed construction (5.88 km) 2004ES16CPT003 2002 (72.25%)
Accesos ferroviarios de estación November 77,755,000 Rail bed construction (8.5 km) de Zaragoza 2000ES16CPT003 2000 (72.25%)
Subtramos XI-A and XI-B entre November 67,070,000 Lleida y Martorell Rail bed construction (6.3 km) 2001 2001ES16CPT009 (72.25%)
Gelida-Sant Llorenç d'Hortons- March 57,797,005 Sant Esteve Sesrovires Rail bed construction (6.0 km) 2003 2003ES16CPT010 (72.25%)
Subtramos IX-A Lleida y Martorell Sept. 49,088,000 Rail bed construction (5.8 km) 2001ES16CPT005 2001 (72.25%)
Subtramos XI-C Lleida y Martorell November 52,928,000 Rail bed construction (6.2 km) 2001ES16CPT010 2001 (72.25%)
Subtramos IX-B Lleida y Martorell November 41,772,000 Rail bed construction (8.1 km) 2001ES16CPT006 2001 (72.25%)
Sant Esteve Sesrovires-Martorell - March 29,380,257 Rail bed construction (2.3 km) Río Llobregat 2003ES16CPT026 2003 (72.25%)
Río Llobregat - Costa Blanca - March 25,152,553 Conexión Vallés Rail bed construction (2.6 km) 2003 2003ES16CPT027 (72.25%)
1,041,946,723 TOTAL (72.25%)
Source: DG REGIO
We understand that the investments corresponding to the LAV Madrid – Barcelona segment cover a much larger number of projects than those included in the ToRs. However, in order to carry out a meaningful ex post CBA we have considered the whole set of projects leading to the completion of the high-speed rail line between Madrid and Barcelona, and not only those included in the ToRs.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 5
Without all these projects, most of the services currently offered on the line would not be operational. Capital investments corresponding to the LAV between Madrid and Barcelona amount to €7,336 million, with total Cohesion Fund contributions around €3,389 million during the period 2000 – 2006.
Socio-economic context The LAV goes through the Spanish regions (Comunidades Autónomas) of Madrid, Castilla la Mancha, Aragón and Cataluña. In order to describe the socio- economic context of the project we focus on the regions of Madrid, Aragón and Cataluña and the cities of Madrid, Zaragoza, Lleida and Barcelona.1 Even though, anecdotally, it is believed that the LAV has had a significant socio- economic effect on these regions, we can not conclude that changes in population, employment and GDP per capita are a direct and only consequence of the LAV. Moreover, regional figures might also include the impact of other infrastructure projects being developed contemporaneously, for example the A23 motorway through in Aragón.2 Figure 2 shows the evolution of the GDP per capita between 2001 and 2008 for the three regions involved, as a percentage of GDP per capita in Spain. Unemployment rate between 2000 and 2010 for Spain, Madrid, Aragón and Cataluña are presented in Figure 3. Overall, the evolution of the four series is very similar but the levels of unemployment in Aragon, Madrid and Cataluña, are lower throughout the period than in the rest of Spain.
1 We believe that the impact of the LAV on the region of Castilla la Mancha (stop in Guadalajara-Yebes) is rather limited given the low number of high-speed rail services stopping there. This equally applies to the cities of Guadalajara and Calatayud. The case of Tarragona is different, but the location of the station (Camp de Tarragona), 12 km away from the city centre, suggests a more limited impact of the LAV in Tarragona than in other cities. 2 The sections of the Autovia A23 that received Cohesion Funds during the period 2000-2006 are considered in this report as a separate case study.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
6 Frontier Economics, Atkins, ITS | March 2011
Figure 2. GDP per capita in regions (as % of GDP per capita in Spain)
140%
130%
Aragon 120% Cataluña Madrid
110%
100% 2001 2002 2003 2004 2005 2006 2007 2008
Source: Instituto Nacional de Estadística (INE)
Figure 3. Unemployment - Evolution of unemployment rate.
25.0
20.0 Spain Aragon 15.0 Cataluña Madrid 10.0
5.0
0.0 2000 2002 2004 2006 2008 2010
Source: Instituto Nacional de Estadística (INE)
Figure 4 shows the average growth rate of population in Zaragoza and Lleida before and after the LAV was completed. Both cities have seen their population increase following the arrival of the high-speed train. This result might be due to the fact that the new infrastructure has brought these cities closer to Madrid and
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 7
Barcelona, making them more attractive areas to reside and work. We explore this aspect further in the wider socio-economic impacts section.
Figure 4. Average annual population growth in capital cities (1999-2009)
2.5%
2.0%
1.5% Before AVE (199-2003) After AVE (2004-2009) 1.0%
0.5%
0.0% Zaragoza Lleida Total Spanish capital cities
Source: Instituto Nacional de Estadística (INE)
Strategic policy context The application forms of the 12 subprojects included in the ToRs list the objectives to be achieved by the LAV Madrid – Barcelona – French border. These were: significant reduction in travel times between Madrid, Zaragoza and the four province capitals in Cataluña (Lleida, Tarragona, Barcelona and Girona); increase rail‟s market share on global transport demand for the Madrid – Barcelona corridor making it more competitive with respect to road and air transport; increase passenger demand for both long distance and regional rail services; increase safety standards with the adoption of the latest automated train driving technology, fencing of the whole railway and eliminating level- crossings along the new railway line; increase capacity and regularity thanks to the dual railway line; and, increase comfort with the adoption of improved rolling conditions.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
8 Frontier Economics, Atkins, ITS | March 2011
As mentioned above, the project is part of the TEN-T Priority Project 3 (high- speed railway axis of south-west Europe). This axis is expected to enable rail connections between the Iberian Peninsula (Portugal and Spain) and the rest of Europe without the need for reloading as a result of the gauge difference between the rail networks in Spain/Portugal and the rest of Europe. The Madrid – Barcelona – French borer high-speed railway line represents a decisive step for the interoperability of Spain‟s high-speed network, as well as the improvement of connectivity within different regions of the Spanish territory and between Spain and the rest of Europe. The railway connection between Madrid and Barcelona means that the two biggest cities in Spain are linked by train in two hours and a half.
1.1.2 Sources We have relied on a variety of different sources of information provided by DG REGIO and by stakeholders in Spain. This allowed us to review the ex ante analysis used in the applications for EU funding. We have obtained the funding applications and the funding decisions for each of the 12 subprojects listed above from DG REGIO. Each application provided a detailed description of the respective subproject, its objectives and the expected costs. DG REGIO also provided us with additional supporting documentation, such as the initial overall cost-benefit analysis and the final reports for each of the 12 subprojects. We also contacted the Transport Documentation Centre (Centro de Documenatación del Transporte) from Ministerio de Fomento which provided us with the methodology used in the economic analysis of railway projects. The complete list of documents obtained, mainly related with the review of the ex ante analysis, is provided in Table 3.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 9
Table 3. Summary of project-related documentation
Documents Obtained from
Funding Applications DG REGIO All subprojects Funding Decisions DG REGIO All subprojects Ex ante CBA INECO Report. “Rentabilidad de la Línea Madrid – Barcelona DG REGIO – Figueres”, May 2001 Methodology used in the economic analysis of the projects, “Manual de evaluación de inversiones en Ministerio de ferrocarriles de vía ancha", Dirección General de Fomento Infraestructuras del Transporte Ferroviario, 1987 To carry out an ex post analysis of the project, we had meetings in Madrid with representatives of ADIF (the railway network operators) and of RENFE (the train operating company) Both institutions made available significant amounts of data. From ADIF, we have received information on investment and operational costs. They have also provided us with an updated version of the cost-benefit analysis of the Madrid – Barcelona – French border high-speed train. RENFE‟s data request was made through the Ministerio de Fomento. They have provided information on passenger‟s demand, rolling stock investment and operating costs. Table 4 summarises the data we have received along with the respective source.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
10 Frontier Economics, Atkins, ITS | March 2011
Table 4. Summary of Primary & Secondary Data Availability
Data Source Issues
Infrastructure investment costs ADIF
Infrastructure operating costs ADIF
“Actualización del estudio de determinación de la capacidad de autofinanciación en la Cost benefit analysis ADIF construcción del trazado ferroviario de alta velocidad Madrid-Frontera francesa”, April 2009
Passenger number RENFE
Rolling stock investment costs RENFE
Operator’s operating costs RENFE
1.2 Ex post cost-benefit analysis We have carried an ex post cost benefit for the LAV between Madrid and Barcelona. While the LAV is part of a longer corridor between Madrid and the French border, our analysis only focus on the Madrid – Barcelona segment. The segment between Barcelona and the French border is still under construction. No outturn data is available to conduct an ex post CBA. The analysis considers costs and benefits between 1997, year in which the first investments took place, and 2033, 25 years after the opening of the fully high- speed rail line between Madrid and Barcelona. To carry out the ex post analysis, RENFE has provided us with data corresponding to all rail services using exclusively or partially the high-speed rail line. The ex post analysis compares the net benefits generated by the services offered on the new line with the counterfactual (no LAV and, therefore, no high- speed services).
1.2.1 Headline results from the analysis This section contains the headline results of the economic and financial analysis.
Economic analysis To capture the uncertainty about future benefits, we have considered a Low case and a High case. These two scenarios use different assumptions regarding the traffic growth on the services using the new rail line, from 2009 onwards. Table 5 shows the assumptions on passengers‟ growth used in each case.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 11
Table 5. Assumed growth rates of passengers on the LAV
Short run Medium run Long run (2010 – 2015) (2016 – 2025) (2026-2033)
LOW case 2.5% 1.25% 0.6%
HIGH case 5% 2.5% 1.3%
Source: Frontier Economics
We have calculated the economic indicators (NPV, IRR and BCR) covering the LAV between Madrid and Barcelona and using a 5.5% discount rate. We have used 2008 as the base year, following the choice of that as base year in the 2009 ADIF analysis. Table 6 summarises the results of the ex post analysis under both scenarios. In both cases, the NPV of the project is negative. Correspondingly the benefit-cost ratios are below 1, indicating that the project‟s costs have exceeded its benefits.
Table 6. Summary of ex post economic analysis (2008 prices)
Low case High case
Net Present Value (€m) -2,736 -1,948
Economic IRR (%) 2.63% 3.70%
Benefit-cost ratio 0.6 0.7
Source: Own calculation
Annexe 1 provides the detailed results of the cost benefit analysis for each option, following the structure used in the 2008 EC Guide. The values in these figures are non-discounted and are expressed in 2008 prices.
Financial analysis We have done an ex post financial analysis for the whole project, calculating the annual cash flows related to the new rail services using the infrastructure. Table 7 summarises the results of the ex post financial analysis. We have used a 5% discount rate.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
12 Frontier Economics, Atkins, ITS | March 2011
Table 7. Summary of ex post financial analysis (2008 prices)
Low case High case
Net Present Value – Investment (€m) -4,766 -4,288
Financial IRR – Investment (%) -0.45% 0.65%
Net Present Value – Capital (€m) -919 -351
Financial IRR – Capital (%) 3.7% 4.5%
Source: Own calculation
Annexe 1 provides the detailed results of the financial analysis.
Wider socio-economic impacts A study supporting this ex post evaluation of the Madrid-Barcelona high speed train (HST) investment, Bellet (2010),3 identifies that most studies carried out on wider socio-economic impacts conclude the HST is not a sufficient condition to cause major transformations in the cities and regions connected by it. The HST only facilitates socio-economic changes that may be already underway. However, the same study also points out that access to HST services may provide important competitive advantages to those cities that are on the HST network compared with those that are not in the network and have therefore less train services. According to the economic literature and experience in other European countries where HST services have been introduced before suggest the main wider economic impacts of HST infrastructure and services are impact on mobility and accessibility, socio-economic structures, urban image and spatial effects. The same applies to the cities connected by the Madrid-Barcelona HST line, particularly Zaragoza and Lleida. In sum, in terms of wider economic impacts, the advantages provided by the HST may accompany or support wider economic changes that are already underway rather than induce or generate new changes.
1.2.2 Costs We have grouped costs into two different categories.
One-off costs. These costs include the capital investment costs incurred by the network operator (ADIF) to build the infrastructures and the rolling stock costs incurred by the railway operator (RENFE).
3 Bellet, Carme, “Efectos socieconómicos de la LAV Madrid – Barcelona, mimeo, 2010.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 13
Ongoing costs. The costs including the operational and maintenance costs incurred by ADIF and RENFE on annual basis.
One-off costs ADIF provided us with the nominal value of the capital investments for the LAV Madrid – Barcelona. We have used IMF inflation and exchange rate data to convert these nominal figures into figures into 2008 Euros. Figure 5 shows the evolution of capital expenditure over time. Expenditures started in 1997 and peaked up in 2001, just before the Madrid – Lleida section was finished. Investment costs decreased substantially from 2009, once the whole Madrid – Barcelona section was opened.
Figure 5. Capital expenditure 1997 to 2010 (€, 2008 prices)
1,800
1,600
1,400
1,200
1,000
800
Million Euros Million 600
400
200
0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Source: ADIF
We assume that ADIF will not incur any further capital costs as the Madrid – Barcelona segment is completed. We also assume that without this project ADIF would have not incurred any additional capital cost in the railway line between Madrid and Barcelona. Rolling stock costs have been estimated using information available in the 2009 ADIF analysis. Specifically, that document provides information related to the number of initial trains bought by RENFE to operate a certain rail service on the LAV, and the additional trains expected to the bought in the following 30 years. In the absence of information on when these additional trains will be acquired, we have evenly spread the acquisition of these trains along a 30 years period. In order to calculate the residual value of the rolling stock, we have used the
Appendix 1 – High speed railway Madrid – Barcelona in Spain
14 Frontier Economics, Atkins, ITS | March 2011
approach followed in the ex ante CBA, where it is assumed that annual rolling stock depreciation is 11.29%. As it can be observed in Figure 6, investment costs peaked in 2008 when whole Madrid – Barcelona line became operational. The chart also shows the residual value of the rolling stock in 2033. As the chart shows costs, the residual value is shown as a negative value.
Figure 6. Rolling stock costs (€, 2008 prices)
600,000
500,000
400,000
300,000
200,000
100,000
0 ThousandEuros 2003 2006 2009 2012 2015 2018 2021 2024 2027 2030 2033 -100,000
-200,000
-300,000
Source: ADIF and Frontier Economics
Unit cost calculation Table 8 summarises the ex post unit costs of the project, using the methodology developed in the context of the WP10 study. The table shows the Level 1 unit cost as well as some Level 2 unit costs, calculated on the basis of the available data.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 15
Table 8. Summary of ex post unit costs (2008 prices)
Non-discounted
Level 1 „All-in‟ (€/km) 14,281,581
Track (€/km) 7,455,877
Stations (€/station) 79,940,000 Level 2 Bridges (€/bridge) 24,321,063
Tunnels (€/tunnel) 24,262,745
Source: ADIF
Ongoing costs Both ADIF and RENFE incur ongoing costs. ADIF‟s ongoing costs include infrastructure maintenance and other general costs. The 2009 ADIF analysis provides the level of cost differences between the scenario with the new infrastructure and the counterfactual for the period 2004 to 2012. We have assumed that after 2012, these cost differences remain constant in real terms. This is because ADIF‟s ongoing costs are based on the number of stations and the number of kilometres of high speed rail line, and these are remain constant in the LAV Madrid – Barcelona after 2012. RENFE‟s ongoing costs can be separated into two groups. The first include those that depend on the number of passengers on the line. We have assumed that these costs will grow over time in the same proportion as the number of passengers. The second group includes those costs that are unrelated to the number of passengers on the line, but are proportional to the infrastructure size. We have assumed that after 2012 later costs remain constant in real terms.
1.2.3 Direct benefits To calculate the project‟s benefits, we have used the same approach as in the analysis carried out by ADIF in 2009 as well as the ex ante analysis of the line carried out by ADIF in 2001. We understand that this approach follows the methodological approach recommended by Ministerio de Fomento for the appraisal of rail projects in Spain. The 2009 analysis by ADIF provides updated parameter values, in 2008 Euros, used to estimate the monetary value of time savings, environmental externalities, accidents and vehicle operating cost savings. We have used this updated value in our analysis.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
16 Frontier Economics, Atkins, ITS | March 2011
Traffic volumes RENFE provided us with passenger data related to all rail services using the LAV Madrid – Barcelona and corresponding to years 2008 and 2009. These services use the LAV Madrid – Barcelona either exclusively or partially. Rail services that use the LAV exclusively are those between two destinations located along the LAV. Services in this category include the AVE Madrid – Zaragoza/Barcelona and the regional service AVMD Lleida – Barcelona. Rail services that use the LAV partially are those that combine segments of the LAV and other rail segments. Services in this category include, among others, the AVE Barcelona – Málaga or the ALVIA Madrid – Pamplona. We obtained passenger data for 19 different rail services using the new high speed line, with the AVE Madrid – Zaragoza/Barcelona service accounting for around two thirds of the total number of passengers. For the rail services that use the LAV Madrid – Barcelona partially, we have obtained passenger data corresponding to the high speed segment of the service. For these rail services, we use distance and time parameters corresponding to the LAV segment. For example the rail service between Barcelona and Bilbao, we only consider the distance and travel times corresponding to the Zaragoza – Barcelona segment. We assume that travel times outside the LAV are unchanged. The 2009 ADIF analysis provides information regarding the origins and destinations of passengers using the new or improved services on the LAV. For example, it reports that just over 50% of the passengers going from Madrid to Barcelona, and vice versa, on the new AVE service used the plane before the AVE service became operational; 18% used the train, 18% used the car and 4% used the bus. The remaining 10% of current AVE passengers in this segment are new passengers that were not travelling before. ADIF provides this information for all geographical segments covering the services that use the new rail line. Taking this modal shift information for all services using the new rail line, we have calculated the average modal shift of each transport mode and the percentage of induced passengers on the line. Table 9 shows this average modal shift for all the services operating on the LAV Madrid - Barcelona
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 17
Table 9. Origin of passengers using the LAV Madrid - Barcelona
Modal shift Induced traffic Trad. rail Car Bus Air
23% 44% 8% 16% 10%
Source: Frontier Economics with data from ADIF
Combining historical passenger data from RENFE and modal shift information from ADIF, we have estimated, for the years 2008 and 2009, the number of passengers in each segment of the new line, the distance travelled by each group, the transport mode used before the opening of the new line and the duration of the journey before and after the opening of the line. We have considered the LAV as a new mode of transport. We have then treated all passengers as new, except those who were already using the old rail service. Accordingly, the „rule of half‟ (discussed in Annexe 2) has been applied to all passengers except those already using the old rail previous to the LAV. We have not received estimated future passenger numbers from either RENFE or ADIF. Therefore, we have used the estimated future passenger-related benefits and costs induced by the LAV Madrid – Barcelona for the years 2008 and 2009 and applied them to the 2009 ADIF analysis to estimate future passengers of rail services on the line. The annual growth rates of these benefits and costs are shown in Table 10, for the period 2016 to 2033. Information included in the 2009 ADIF analysis for the years until 2015 are less relevant for our analysis as growth rates in these years are strongly influenced by the opening of the line from Barcelona-Sants station to the French border, a section we do not analyse in this exercise.
Table 10. Annual growth rates in 2009 ADIF analysis.
Medium run Long run (2016 – 2025) (2026-2033)
Variable costs related to passengers / 1.25% 0.5% tickets sold
Benefits from time savings, vehicle operating costs, accidents and 1.5% 1% environmental externalities
Source: Frontier Economics with data from ADIF
Using these estimated growth rates we have build our High and Low case scenarios. Both scenarios assume three different growth rates of passengers for
Appendix 1 – High speed railway Madrid – Barcelona in Spain
18 Frontier Economics, Atkins, ITS | March 2011
the short, medium and long-run. Assumed growth rates of passengers for the HIGH and LOW case are shown in previous Table 5. We have not received data from RENFE corresponding to the years 2004 to 2007, when the LAV Madrid - Barcelona was only partially open, between Madrid and Lleida until the end of 2006 and further extension to Tarragona in 2007. The 2009 ADIF analysis reports the benefits, related to time savings, vehicle operating costs savings, accidents and externalities, corresponding to these earlier years. Using the previous approach to estimate future passenger on the line, we have used the growth rates of benefits and costs in these earlier years to approximate the number of passengers on the line between 2004 and 2007, and calculate the associated benefits. Should RENFE provide actual data on outturn passenger numbers for the years 2004-2009 within the timeframe of this study, we will update the analysis accordingly in later drafts of this report.
Time savings Time saving benefits are given by the total number of minutes saved with the new infrastructure. Door–to–door journey times, including travel time plus access and waiting time at stations/airports, for different modes of transport and different segments have been obtained from the 2009 analysis by ADIF and from RENFE‟s web page. Access and waiting time is nil for car, while for bus and train ranges from 30 to 50 minutes, and for plane from 130 to 140 minutes. Using information on modal shifters from the 2009 ADIF analysis, we have estimated total minutes saved. Table 11 provides examples of door-to-door journey times for different transport modes for different segments on the line.
Table 11. Door-to-door journey time (Minutes)
High-speed Route Car Bus Air Trad. rail rail
Madrid – Barcelona 354 514 210 470 230
Lleida – Barcelona 100 185 – 230 100
Madrid – Zaragoza 181 279 190 200 140
Zaragoza – Lleida 87 152 – 150 83
Source: ADIF and RENFE Note: Air transport service is only available for certain routes. According to the 2009 ADIF analysis, the monetary value of time depends on the purpose of the journey. In that sense, business journey time would have a value of 17.21 EUR/hour and leisure journey time a value of 7.41 EUR/hour. The ADIF analysis also provides information on the percentage of business vs. leisure
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 19
journey by transport mode and segment on the rail services using the LAV. With this information, we have calculated a weighted average monetary value of time of 13.19 EUR/hour for passengers travelling from Madrid to Barcelona, and vice versa, and a value of 12.92 EUR/hour for all other segments on the line.
Vehicle operating costs Total vehicle operating costs are lower in rail (traditional and high-speed) than in other modes of transport. Because of modal shift away from other modes of transport, there is a decrease in operating costs. Compared with other categories of benefits, vehicle operating cost savings are the largest. The 2009 ADIF analysis provided us with unit savings on vehicle operating costs for the different transport modes other than rail. These are summarised in Table 12.
Table 12. Vehicle operating cost savings of rail with respect to other transport modes (EUR/passenger-km, 2008 prices)
Car Bus Air
Vehicle operating costs savings 0.084 0.042 0.108
Source: ADIF We have calculated total vehicle operating cost savings using information on modal shifters provided by ADIF and total passengers provided by RENFE for 2008 and 2009. As mentioned before, for years between 2010 and 2033 and between 2004 and 2007, we have calculated VOC savings using an estimated number of passengers.
Revenues RENFE provided tariff revenues for the years 2008 and 2009. As before, we have calculated future revenues, and revenues corresponding to years 2004 to 207, using an estimated number of passengers and assuming that real tariffs remain constant. These figures are calculated as net revenues, as we have also taken into account the (transport and infrastructure) operators‟ lost revenue from passengers moving form car, bus and airplane to the rail services offered on the LAV.
1.2.4 Externalities
Safety The 2009 ADIF analysis calculated the benefits from the reduced number of accidents on rail transport if compared with either car or bus. The analysis provided us with the parameter values related to the cost of accidents. Unit costs
Appendix 1 – High speed railway Madrid – Barcelona in Spain
20 Frontier Economics, Atkins, ITS | March 2011
associated to the four modes of transport considered are shown in Table 13. As rail transportation is slightly less safe than air transport, there is a cost associated with modal shift away from air travel. We have calculated the social benefits generated by modal shift switching to safer modes of transport using the information on passengers in 2008 and 2009 provided by RENFE and modal shifting patterns provided by ADIF. As mentioned before, for years between 2010 and 2033 and between 2004 and 2007, we have calculated accident savings using an estimated number of passengers.
Table 13. Social costs of accidents associated to different transport modes (EUR/1000 passenger-km, 2008 prices)
Rail Car Bus (trad. and Air high-speed)
Value of accident costs 25.8 3.1 1.0 0.5
Source: ADIF
Environmental We consider the environmental impact of the new infrastructure by calculating the social benefits generated by people switching to high-speed rail services, considered to be a more environmentally friendly mode of transport than car, bus or air. In order to calculate the environmental benefits generated by the new infrastructure we have followed a similar approach to the 2009 ADIF analysis. Environmental social benefits induced by rail transportation can be subdivided in four different components, pollution, climate change effects, nature and visual effects, and urban effects. The 2009 ADIF analysis provides parameter values for unit benefits related to environmental externalities. Table 14 present these parameters.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 21
Table 14. Environmental cost savings of rail with respect to other transport modes (EUR/1000 passenger-km, 2008 prices)
Car Bus Air
Pollution 7.5 17.8 -5.8
Climate change 8.4 1.6 29.5
Nature and Visual 2.9 0.1 0.2
Urban effects 0.4 -1.1 -1.6
Total 19.2 18.4 22.3
Source: ADIF
We have calculated the social benefits generated by modal shifters switching to high-speed rail services using the information on passengers in 2008 and 2009 provided by RENFE and modal shifting patterns provided by ADIF. As mentioned before, for years between 2010 and 2033 and between 2004 and 2007, we have calculated the total environmental externality using an estimated number of passengers.
1.2.5 Wider socio-economic impacts The high speed train (HST) can have a set of wider socio-economic and land use qualitative impacts which go beyond the more immediate quantitative costs and benefits. The two main characteristics that need attention to understand the wider socio-economic effects of HST are (i) the channels through which HST can have wider impacts and (ii) the time it takes those impacts to take effect
Impact channels The build up of HST infrastructure and start of rail service operations can influence the local socio-economic structures through different channels. Table 15 summarises what is known in the literature about the main wider socio- economic effects of the HST. The HST can influence mobility and accessibility, socio-economic structures (especially tourism and market expansion), the image of urban centres and spatial changes, both urban transformation and urban planning.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
22 Frontier Economics, Atkins, ITS | March 2011
Table 15. Socioeconomic and land-use impacts influenced by the High Speed Train
Specific Impact area What we know impacts
HST tends to have a large impact on external accessibility and travel times generating an increased 1.1 Amount of amount of travel. The increase in the number of trips 1. Mobility travel appears to be more significant when the HST infrastructure implies substantial changes in external accessibility experienced by the cities with HST stations
HST services tend to be competitive vis-à-vis air travel for middle distance corridors of 500-700 km, and possibly 1.2 Modal shift longer distance corridors of 1,000-1,500 km with speeds of 350km/h. in Europe, the HST has been able to capture up to 70% market share in some corridors (e.g. Paris- Lyon, London-Brussels, Madrid-Sevilla)
Following the introduction of the HST, the user profile and trip motive tends to be those of middle age, educated individuals who travel for business reasons. Over time, 1.3 Population as the HST services consolidate their services, other mobility patterns traveller profiles develop. A common development has been the HST commuter who travels middle and long distances, thereby expanding the functional scope of some labour markets.
HST infrastructure interact with other ongoing economic factors such as the labour market, scale economies and 2. Socio- 2.1 Support market size, thereby influencing labour productivity and economic ongoing corporate productive efficiency in central, well-developed structures transformations cities and in peripheral, less developed cities to a varying degree depending on initial conditions and strength of ongoing economic transformation in these localities.
The availability of HST services tends to have a direct influence on the tourism industry. Evidence suggests that 2.2 Tourism cities connected via a HST network experience an
dynamics increased volume of tourists from precisely the cities connected via the HST network, which tends to be accompanied by changes in the supply of tourism services and products on offer.
The introduction of the HST facilitates market expansion 2.3 New in service-related activities. People and enterprises economic located in the area of influence of the HST stations gain activities access to an increased and diversified number of services.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 23
Specific Impact area What we know impacts
Cities that become part of the HST network, and do not 3. Urban 3.1 Urban belong to the more well-known set of important national image image cities (e.g., Madrid, Barcelona etc) immediately improve their external image and achieve increased awareness (e.g. tourists, business conference organisers).
3.2 Local Cities take the opportunity of becoming part of the HST marketing network to initiate or adapt urban image campaigns intended to improve their attractiveness and promote the campaigns local economy.
New metropolitan interactions are created between small 4. Spatial 4.1 Metropolitan and medium cities with other small and medium cities changes dynamics connected by the HST network and long distance interactions irrespective of city size.
The physical transformation brought about by the HST is 4.2 Urban illustrated by a network remodelling promoting an
transformation improved integration and access of rail into town and the urban remodelling around HST stations, new ones and old but enhanced ones
Local and regional authorities take advantage of the new 4.3 Planning HST infrastructure to review existing urban plans or policies and policies or issue new ones: better integration of stations measures with their urban surroundings, mitigate potential negative effects, and improve accessibility
Local and regional authorities take advantage of the new 4.4 Urban HST infrastructure to also reinforce or launch city image
promotion and and tourist campaigns to enhance the attractiveness of marketing the cities and their tourism appeal
Source: Bellet (2010) and own analysis
Timeframe Figure 7 summarises the dynamic sequence of the HST impacts. The immediate short-term impact relates to the construction of the HST infrastructure and the changes in the urban image in the cities linked by the new HST infrastructure. The rest of the socio-economic impacts via multiplier effects materialise in the medium and long terms. Increased mobility and accessibility to urban centres can change land use patterns and facilitate the expansion of labour markets, for example. These long term impacts are the result of multiple interrelationships with other socio-economic phenomena (e.g. urban growth, population dynamics, planning policies, etc.) which makes it difficult to attribute any of those impacts exclusively to the HST. The French experience with HST infrastructure suggests
Appendix 1 – High speed railway Madrid – Barcelona in Spain
24 Frontier Economics, Atkins, ITS | March 2011
that it takes up to 20 years to be able to appreciate the wider socio-economic impacts of HST infrastructure and services.
Figure 7. Socio-economic impact of High Speed Train over time
Source: Bellet (2010)
The LAV Madrid – Zaragoza – Barcelona has the potential to produce several wider effects related to passenger‟s mobility, general image of the cities, socio- economics and spatial changes. We summarise these wider economic effects below.
Mobility effects The number of passengers using the LAV Madrid – Zaragoza – Barcelona has experienced a significant increase since the start of operations. According to RENFE, in 2008 around 2.5 million passengers used the AVE service between Madrid – Barcelona exclusively. In 2009 this number increased to around 3 million. This substantial increase in the number of passengers is also a consequence of changes in the modal distribution of transports. For example, for the route between Madrid and Barcelona, before the AVE service was opened, the train had a market share of 11.8%. Figures for the first semester of 2009 suggest that this market share has increased to 48.6%. A survey carried out by RENFE in October 2009 shows the following average traveler profile: middle age (from 30 to 44 years), with high levels of education (57% have university degrees or postgraduate or doctoral studies), 48% are
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 25
private employees performing management or administration functions, entrepreneur or self-employed, and 48% travel for business or professional reasons. The survey results also suggest that leisure/tourism is the reason for travelling in 29.2% of the responses. Previous studies of the Spanish southern HST corridor Madrid-Sevilla show that leisure/tourism trips increases over time and that the passenger profile also becomes more diversified over the years. Finally, a new type of traveller has appeared as a consequence of the LAV Madrid – Barcelona: the commuters. The frequency of trips between cities separated by less than 60 minutes (Zaragoza – Madrid, Zaragoza – Barcelona, and especially Lleida – Barcelona and Lleida – Camp de Tarragona) is very high. According to RENFE‟s survey, 21% of passengers in the Zaragoza – Madrid service were commuters. This percentage is much higher for the Catalan services (53.4%) given that since the introduction in April 2008 of the AVANT services, high-speed train services for short distances at competitive prices between Barcelona – Camps de Tarragona – Lleida.
Socio-economic effects The HST is seen as an instrument to improve the accessibility of cities and regions connected to the network. Several studies suggest that accessibility gains would be higher for medium and small cities (Zaragoza and Lleida) than for bigger cities (Madrid and Barcelona) because some activities would be reallocated to these smaller cities. These activities would include activities related to urban tourism, conference tourism, scientific meetings, and business meeting; and the relocation of specialized businesses and technical consultancy firms to take advantage of lower labour costs and availability of skilled labour while keeping good accessibility to Madrid and/or Barcelona.
Change in tourism dynamics As discussed above, one of the sectors that is most influenced by the arrival of the LAV, is the tourism. Overall, the number of visitors grows, especially from large cities and towns near the corridor or high-speed network. These dynamics appear to have been particularly intense in the cities of Zaragoza and Lleida. The reasons are: The train incorporates or strengthens the position of these cities as tourist destinations; With the new train infrastructure, these cities become closer and reinforces the role of these cities and their territories in the national tourism market; It tends to increase the number of congressional and business meetings that take place in medium and large cities;
Appendix 1 – High speed railway Madrid – Barcelona in Spain
26 Frontier Economics, Atkins, ITS | March 2011
Increased tourism causes a significant economic impact on local services, with or without overnight stays, such as catering, commerce, urban transport, travel agencies, etc. The HST can also work as a channel to publicize campaigns and local events, for example the 2008 International Exhibition in Zaragoza.
New activities The TAV Madrid – Zaragoza - Barcelona has been running since February 2008. Thus, it is too early to assess any lasting economic impact caused by the HST on the two major cities. However, in the case of Zaragoza and Lleida, which have had HST services since 2003, it is possible to establish a relationship between some local economic revitalization projects and the HST. 1. Zaragoza: logistics, international events and business land. The arrival of the LAV was exploited as a tool to develop local socio-economic plans (Plan estratégico de la ciudad y su entorno –Ebropolis, 1998). The objective was to carry out a thorough urban and socio-economic transformation of the city of Zaragoza. The implementation of the infrastructure was accompanied by other important projects: the 2008 International Exhibition about Water and the consolidation of PLAZA, a logistics platform. 2. Lleida: the LAV and the technology park. The Agribusiness Science and Technology Park (Parque Científico y Tecnológico Agroalimentario de Lleida – PCiTAL) was created in 2005 as a consortium between the University of Lleida and the Lleida City Council. It was established with the intention of becoming a major scientific and technological platform in the agribusiness industry in Spain.
Image effects In terms of image transformation as a consequence of the LAV Madrid – Barcelona, Zaragoza and Lleida are probably the two Spanish cities that have benefited the most, even more than Madrid and Barcelona. In the case of Zaragoza, the arrival of the LAV was used as an instrument (together with the Expo in 2008 and the logistic platform, PLAZA) to promote an ambitious urban and socio-economic transformation of the city. According to a survey by the Employer‟s Confederation of Zaragoza, 91.2% of respondents believe that the image of the city has improved with the LAV. In the case of Lleida, a year before the arrival of the LAV, the local Chamber of Commerce and Lleida City Council released a strategic plan, Plan de Dinamización del tren de alta velocidad, intended to promote the city as a touristic gateway. Some of the measures considered in the plan are currently being developed. Also a marketing campaign was released to reinforce the image of the city of Lleida.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 27
Spatial effects In Madrid and Barcelona, the implementation of the LAV will have the effect of converting high-speed train stations into intermodal hubs. For example, the future Sagrera project will mean an intense process of renewal of the Sant Andreu district in the north of the city of Barcelona. The Barcelona-Sagrera or Sagrera- TAV will probably become the most important railway station of Catalonia, the largest in Spain to international destinations, and the second largets in terms of national routes. In Madrid, the project called Operación Chamartin, can easily become one of the largest urban renewal operations in Europe. It was approved in late 2009 and will impact over 3 million square meters to be completed in 2023. The LAV Madrid – Zaragoza – Barcelona has produced the following spatial effects: Reinforcement of the two national metropolises, Madrid and Barcelona. Strengthening Madrid – Barcelona metropolitan dynamics through a high-speed corridor:
Intensification of the metropolitan dynamics with nearby cities (30 minutes travel time) as Madrid – Guadalajara and Barcelona – Camps de Tarragona
Inclusion to the metropolitan dynamics of close cities (60 minutes travel time) as Barcelona – Lleida Repositioning of large and medium size cities: Zaragoza and Lleida.
Utilisation rates As requested by the TORs, we have considered the evolution of the utilisation rates of this project. We have calculated these rates for the last two years, using the passenger data related to the rail services using the LAV Madrid – Barcelona provided by RENFE. Table 16 shows for the years 2008 and 2009 the maximum capacity available in passenger-kilometre on the services being provided, the total amount of passenger-kilometre and the resulting capacity utilisation, equal to 61% in 2008 and 57% in 2009. The contribution to this indicator by the high-speed rail services using exclusively the LAV Madrid-Barcelona, for example the AVE Madrid – Barcelona, is equal to 79% in 2008 and 67% in 2009. As mentioned before, there are other rail services using the LAV Madrid-Barcelona. These correspond to (i) high-speed rail services using the LAV Madrid-Barcelona and other LAVs, for example the AVE services between Barcelona and Sevilla; and (ii) rail services using the LAV and other Iberian standard rail segments, for example the ALVIA service between Barcelona and Bilbao.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
28 Frontier Economics, Atkins, ITS | March 2011
Table 16. Utilisation rates on the LAV Madrid - Barcelona (2008 and 2009)
2008 2009
Maximum number of passengers- 4,494 6,942 kilometer (Million)
Total number of passengers- 2,723 3,962 kilometer (Million)
Utilisation rate 61% 57%
Source: RENFE data
1.3 Review ex ante cost-benefit analysis The first assessment for the LAV Madrid – Barcelona – French border was elaborated by the Ministerio de Fomento in 19974 and it was used to prepare the applications for funding for subprojects 1999ES16CPT001, 2000ES16CPT003 and 2000ES16CPT005. This cost-benefit report was later updated in May 2001 by INECO.5 This study covers the 1997 – 2025 period. As it is the most complete, we focus our ex ante review on this analysis. The 2001 ex ante CBA follows the approach set out by Ministerio de Fomento (Dirección General de Ferrocarriles) and considers costs and revenues for both the network operator (ADIF) and the train operating company (RENFE). As in the previous assessment, the 2001 report is a single cost-benefit analysis of the whole LAV (that is, including the Barcelona – French border section, which is not completed at the moment).
1.3.1 Headline results from the analysis
Economic analysis The ex ante CBA prepared by INECO in 2001, and used to prepare most of applications for funding, considers only the option implemented. It assesses it against a counterfactual where the existing rail line is maintained. INECO considers a 29-year period for the analysis and assumes that the Madrid – Lleida section would open in 2003 and the Lleida – Figueres section in 2006.
4 “Estudio de optimización functional de la Línea de alta velocidad Madrid – Zaragoza – Barcelona – Frontera Francesa” 5 INECO Report, “Rentabilidad de la Línea Madrid – Barcelona – Figueres”, May 2001
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 29
The CBA report presents the results of the calculations of benefits and costs for each year of the appraisal period. The CBA distinguishes between economic analysis (Evaluación económica) and social analysis (Evaluación social), the latter includes positive externalities environmental benefits and employment generation. For both analyses, the report shows the Net Present Value, the economic rate of return and the benefit-investment ratios. INECO calculates the NPV of the project using a 6% discount rate. Table 17 shows the results. Instead of producing the benefit-cost ratio of the project, the ex ante cost benefit analysis reports the benefit-investment ratio. This ratio is not directly comparable with the ex post BCR, used in the other projcts under analysis.
Table 17. Results of ex ante cost benefit analysis for the whole line
Net Present Value Economic IRR BIR (€ million, 2005 prices) (%)
Economic Analysis 313.57 6.29% 0.04
Social Analysis 2,758.55 8.92% 0.38
Source: INECO Report, “Rentabilidad de la Línea Madrid – Barcelona – Figueres”, May 2001
Financial analysis The ex ante CBA shows a separate financial analysis for the infrastructure operator (ADIF) and for the railway operators. For this matter, access charges to be paid to the infrastructure manager are calculated in such a way that the railway operators‟ profitability is 9%. Table 18 presents the results of the financial analysis for the whole line. INECO calculated the financial NPV using a 6% discount rate.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
30 Frontier Economics, Atkins, ITS | March 2011
Table 18. Results of ex ante cost benefit analysis for the whole line
Net Present Value IRR BIR (€ million, 2005 prices) (%)
Infrastructure -7,946.17 -3.82% 0.01 manager
Railway 309.41 9.00% 1.6 operators
Source: INECO Report, “Rentabilidad de la Línea Madrid – Barcelona – Figueres”, May 2001
1.3.2 Key aspects of ex ante CBA The ex ante economic analysis considers benefits originating from time savings, safety improvement, environment and the creation of new employment generation.
Demand analysis The ex ante CBA considers not only the number of “direct” passengers (i.e. passengers going from Madrid / Zaragoza / Lleida / Tarragona / Barcelona to Madrid / Zaragoza / Lleida / Tarragona / Barcelona) travelling in high–speed trains (max. speed 350 km/h) but also “indirect” passengers (i.e. passengers travelling in routes that use part of the LAV Madrid – Barcelona – French border rail) travelling in TALGO trains (max. speed 220 km/h). Both national and international demand is considered. For national demand three types of services are included: “long-haul internal relations”, “long-haul external relations” and “regional relations”. Table 19 shows the correspondent routes. For international demand routes taken into account are those with origin in Cataluña, Centre-North of Spain, and South of Spain and with destination France, England, Benelux, Germany, Switzerland, Italy, and others.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 31
Table 19. Ex ante national demand routes
Long-haul internal Long-haul external Regional relations relations (High–speed relations (TALGO trains) (TALGO trains) trains)
Madrid to Barcelona / Ext. Madrid to Barcelona / Lleida to Tarragona / Zaragoza / Lleida / Zaragoza / Lleida / Vallés / Barcelona / Tarragona / Girona Tarragona / Girona Girona
Zaragoza to Barcelona / Ext. Zaragoza to Barcelona Tarragona to Vallés / Lleida / Tarragona / / Lleida / Tarragona / Barcelona / Girona Girona Girona
Vallés to Girona / Figueres
Barcelona to Girona / Figueres
Girona to Figueres
Source: INECO Report, “Rentabilidad de la Línea Madrid – Barcelona – Figueres”, May 2001
The second analysis concentrates on the railway operators. The analysis considers different investment cost and demand scenarios. Because the operator‟s profitability is fixed at 9%, the effect of the sensitivity analysis is only observed on the ADIF‟s profitability. Table 20 presents the results. We note that in all cases the NPV for ADIF is negative.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
32 Frontier Economics, Atkins, ITS | March 2011
Table 20. Sensitivity analysis for the infrastructure manager (ADIF) and railway operators (RO)
ADIF NPV (€ ADIF ADIF Net RO NPV (€ RO IRR million, IRR Revenue / million, (%) 2005 prices) (%) Investment 2005 prices)
+10% -8,203.2 -4.28% 8.7% 340.51 9% Railway Operators 0% -7,946.17 -3.82% 11.5% 309.41 9% investment cost -10% -7,815.89 -3.59% 13.0% 278.35 9%
+10% -7,900.53 -3.74% 12.0% 340.35 9% Railway Operators 0% -7,946.17 -3.82% 11.5% 309.41 9% Demand -10% -8,118.50 -4.13% 9.6% 278.47 9%
Source: INECO Report, “Rentabilidad de la Línea Madrid – Barcelona – Figueres”, May 2001
1.3.3 Quality of ex ante CBA The ex ante documentation that we have reviewed is of good quality. Generally, the approach followed in the INECO report is in line with the official guidelines of the Ministerio de Fomento and the methodology used for the analysis is well specified. Strengths of the ex ante CBA include good reference to sources of parameters used in the analysis and the inclusion of sensitivity analysis related to investment cost and demand for the infrastructure manager and for the railway operator. The ex ante CBA prepared by INECO has some weaknesses. Among them, we can highlight the fact that it only considers the option implemented, details on the methodology used to forecast demand are insufficient and no monitoring mechanism is established in order to scrutinize the actual benefits following scheme approval.
1.4 Differences between ex post and ex ante analysis As stated above the 2001 INECO ex ante cost benefit analysis considers the whole LAV Madrid – Barcelona – French border. However, because the Barcelona – French border section is not yet operational, and no data are available for it, our ex post cost benefit analysis considers the new infrastructure as being only the LAV Madrid – Barcelona segment. For this reason the two analyses are not fully comparable. Another important issue is that the ex ante
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 33
results are obtained considering the 1997–2024 period for the analysis while we consider the 1997-2033 period. Table 21 compares the results of the ex ante economic analysis carried out by INECO for the whole infrastructure with our results of the ex post CBA for the LAV Madrid – Barcelona. Ex ante figures have recalculated these series using a common base year, 2008, and the discount factor suggested by the EC Guide to Cost-Benefits Analysis (5.5%). The original ex ante economic analysis used 2005 as the base year and a discount factor equal to 6%.
Table 21. Comparison of ex ante and ex post economic and social CBA (2008 prices)
Ex ante Ex ante Ex post Ex post Economic CBA Social CBA Low Case High Case
Net Present 1,091 4,125 -2,736 -1,948 Value (€m)
Economic IRR 6.29% 8.92% 2.63% 3.70% (%)
Benefit-cost 1.07 1.26 0.6 0.7 ratio
Source: Frontier Economics
As shown above, the ex ante analysis carried out by INECO in the 2001 report presents, for the whole LAV Madrid – Barcelona – French border, an IRR of 6.29% and 8.92% for the Economic analysis and Social analysis respectively. The analysis completed by ADIF in 2009 also considers the whole LAV Madrid – Barcelona – French border. ADIF reports an IRR of 2.23% and 6.06% respectively. Apart from the fact that the ex ante analysis and the ex post analysis do not consider exactly the same infrastructure, there exist other difference between INECO and our approach that we summarize below.
Traffic volumes RENFE provided aggregate data on traffic volume for years 2008 and 2009, and together with information modal shift information from ADIF we have estimated the number of 2008 and 2009 passengers in each segment of the new line. When comparing ex ante and ex post data it can be said that, overall, the 2001 ex ante analysis assumes higher traffic volume than the estimated for the ex post analysis in 2008 and 2009. As an example, Figure 8 shows the number of passengers in the ex ante and ex post analysis for 2008, for a non-exhaustive number of segments considered in
Appendix 1 – High speed railway Madrid – Barcelona in Spain
34 Frontier Economics, Atkins, ITS | March 2011
the analysis. The chart shows that, with the exception of the Madrid – Barcelona segment, the ex ante analysis assumed a higher number of passengers compared with actual numbers.
Figure 8. Traffic volume comparison 2009
3,200
2,800
2,400
2,000 Ex ante 1,600 Ex post 1,200
800 Passengers ('1000s) Passengers
400
0 Madrid - Madrid - Zaragoza - Tarragona - Lleida - Lleida - Zaragoza - Barcelona Zaragoza Barcelona Barcelona Barcelona Tarragona Tarragona
Source: Frontier Economics
Capital costs Investment cost profiles are different in the ex ante and in the ex post analysis. Even though they are not directly comparable because, as mentioned above, the ex ante analysis includes the whole LAV Madrid – Barcelona – French border, ex post figures provided by ADIF are overall higher, suggesting an overspend for the entire infrastructure. Figure 9 present capital costs profiles for the 2001 ex ante CBA and for our ex post CBA.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 35
Figure 9. Capital cost comparison (€, 2008 prices)
1,800
1,500
1,200
Ex ante 900 Ex post
600
300
0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Source: Frontier Economics
Consumer Surplus distribution We have calculated the share of consumer surplus that each of vehicle operating costs, time savings, safety and environmental benefits represent, both for the ex ante and the ex post CBA. We also report figures for the 2009 ADIF report. Results are shown in Figure 10. The chart shows that there are substantial differences between the ex ante figures and both the ex post CBA and the 2009 ADIF report. In particular, the ex ante analysis assumes that time savings are by far the largest source of benefits, while in the ex post analysis vehicle operating cost savings are the largest. This difference may be due the use of different parameters and different assumptions about travel volumes. Unfortunately the ex ante CBA does not provide sufficient details on how benefits were calculated so we are unable to pinpoint the main causes for these discrepancies.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
36 Frontier Economics, Atkins, ITS | March 2011
Figure 10. Average contribution to consumer surplus of various identified benefits
100% 5% 10% 6% 19% 6% 80% 9%
40% 18% 60%
72% Enviromental Accidents 40% Time VOC 54% 45% 20%
18%
0% EX ANTE EX POST ADIF 2009
Source: Frontier Economics
Note: For the ex post case, average contribution is calculated taking the mean of the contribution in the high case and in the low case scenario.
Inclusion of additional impacts The ex ante CBA includes employment generation in the social analysis. The document does not provide any further detail on how employment generation is monetised but refers to a study carried out by the Ministerio de Fomento. In accordance with the approach followed in all the ex post evaluations, we have not included employment generation benefits in our analysis.
1.5 Role of CBA in decision-making process Discussions held with ADIF (the Spanish railway infrastructure operator) and Ministerio de Hacienda (“Hacienda”, the Spanish Treasury and final signatory of the official application for Community funds) confirmed that the department responsible for the use of CBA in this project is the General Directorate for Railway Infrastructures in the Ministerio de Fomento (“Fomento”), which is the equivalent of the Ministry for Public Works in Spain. The same Directorate is responsible for feasibility studies related to large transport infrastructure investments. The scope of the project was approved by Fomento while ADIF was in charge of its implementation. While ADIF could not confirm whether the ex
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 37
ante CBA of the AVE Madrid-Barcelona investment was audited, Hacienda confirmed that the European Investment Bank (EIB) were a co-financing party of the AVE Madrid-Barcelona high speed infrastructure. EIB reviewed and audited the CBA of the project as part of their standard project appraisal due diligence. The preparation of the business case for the project, including the ex ante CBA, largely followed the CBA technical methodologies developed by Fomento, including an Investment Manual (2000, 2009). Hacienda played a special role in estimating the funding gap in the business case taking account of the availability of financing sources (Community funds and expected commercial revenues) and the budgetary limits imposed by the state of Spanish public finance management. Hacienda also acted as a quality filter in the project preparation ensuring compliance of the project proposal with the relevant Community funding criteria. ADIF confirmed that the 2009 version of the Investment Manual adopts the recommendations of the Commission, in particular those in DG Regio‟s 2008 CBA Guidelines. The Investment Manual also benefits from the experience gathered over recent years; for example, it includes benefit and cost parameters and unit cost estimates. Both ADIF and Hacienda mentioned that the only difference they noticed was the value of the discount rate, which has decreased to 5.5% for the economic analysis and to 5% for the financial analysis. ADIF works with the ex ante CBA model prepared by Fomento and is in charge of reviewing the demand and cost estimates as the project gets implemented. Hacienda confirmed the existence of a Project Monitoring Committee (including as members relevant Commission officials and Spanish civil servants) for all large transport and environmental projects co-financed with Community funding, which met twice a year at the beginning of the AVE project implementation and annually afterwards. This Committee oversaw project implementation and discussed critical issues (e.g., environmental impact in the case of the AVE Madrid-Barcelona project) ADIF claimed that the updating of the financial and economic model translates into reduced uncertainty regarding demand figures and total costs. Both ADIF and Hacienda did not provide details abut acknowledged that unforeseen events related to the technical complexities of the project (e.g. geological risks related to soil conditions or access to Barcelona Sants railway station) resulted in some differences between projected and out-turn costs and forecasts. Finally, while ADIF could not comment on the uses of ex ante CBA by Fomento, they confirmed that, in addition to ex ante CBA, Fomento also commissions studies which us a multi-criteria methodology. Hacienda, on the other hand, confirmed that CBA was used in the AVE Madrid-Barcelona project to assess alternative route alignments in relation to the mitigation of environmental impacts. Hacienda confirmed that project selection follows project size and
Appendix 1 – High speed railway Madrid – Barcelona in Spain
38 Frontier Economics, Atkins, ITS | March 2011
political criteria after which CBA is used to inform the economic feasibility studies and to identify critical issues such as environmental impacts.
Appendix 1 – High speed railway Madrid – Barcelona in Spain
March 2011 | Frontier Economics, Atkins, ITS 39
Annexe 1: Detailed results
High speed railway Madrid–Barcelona in Spain
Figure 11. High speed rail – Spain. Economic analysis (€m, 2008 prices) – Low case
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
BENEFITS Consumers Surplus Time Benefits 0 0 0 0 0 0 0 5 5 7 8 66 86 Accidents 0 0 0 0 0 0 0 1 1 1 2 10 12 Vehicle Operating Costs 0 0 0 0 0 0 0 3 3 5 6 83 101 Externalities 0 0 0 0 0 0 0 1 1 1 1 19 23
Producer Surplus Revenues 0 0 0 0 0 0 0 11.5 12.1 16.2 19.3 222.0 296.3
TOTAL BENEFITS 0 0 0 0 0 0 0 21 22 30 35 400 518
COSTS Investment Costs Track construction 166 256 688 940 1569 1471 877 744 697 644 442 326 49 Rolling stock 0 0 0 0 0 0 0 6 6 6 6 52 58
Operating and maintenance costs 0 0 0 0 0 0 18 65 61 58 78 74 74
TOTAL COSTS 166 256 688 940 1569 1471 895 814 764 708 526 452 181
NET BENEFITS -166 -256 -688 -940 -1569 -1471 -895 -793 -742 -678 -490 -52 337
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
BENEFITS Consumers Surplus Time Benefits 87 89 91 94 96 98 100 101 102 103 105 106 107 Accidents 13 13 13 14 14 14 15 15 15 15 15 16 16 Vehicle Operating Costs 106 108 111 114 117 120 121 123 124 126 127 129 131 Externalities 24 24 25 26 26 27 27 28 28 28 29 29 29
Producer Surplus Revenues 300 307 315 323 331 339 343 348 352 357 361 365 370
TOTAL BENEFITS 529 542 556 570 584 599 606 614 621 629 637 645 653
COSTS Investment Costs Track construction 0 0 0 0 0 0 0 0 0 0 0 0 0 Rolling stock 61 61 61 61 61 61 61 61 61 61 61 61 61 0 0 0 0 0 0 0 0 0 0 0 0 0 Operating and maintenance costs 71 68 73 74 75 75 76 76 77 77 78 78 79
TOTAL COSTS 132 130 134 135 136 137 137 137 138 138 139 139 140
NET BENEFITS 397 413 422 435 448 462 469 476 484 491 498 506 513
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033
BENEFITS Consumers Surplus Time Benefits 109 110 111 112 113 114 114 115 116 116 117 Accidents 16 16 16 16 17 17 17 17 17 17 17 Vehicle Operating Costs 132 134 136 136 137 138 139 140 141 142 142 Externalities 30 30 30 31 31 31 31 31 32 32 32
Producer Surplus Revenues 375 0 0 0 0 0 0 0 0 0 0
TOTAL BENEFITS 287 290 294 296 297 299 301 303 305 307 309
COSTS Investment Costs Track construction 0 0 0 0 0 0 0 0 0 0 -2581 Rolling stock 61 61 61 61 61 61 61 61 61 61 61
Operating and maintenance costs 79 80 80 80 81 81 81 81 82 82 82
TOTAL COSTS 140 141 141 141 142 142 142 142 143 143 -2438
NET BENEFITS 146 150 153 154 156 157 159 161 162 164 2746
Discount Rate 5.5% ENPV -2736 ERR 2.63% B/C Ratio 0.6
Source: Own calculation
Annexe 1: Detailed results
40 Frontier Economics, Atkins, ITS | March 2011
Figure 12. High speed rail – Spain. Financial return on investment (€m, 2008 prices) – Low case
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
TOTAL REVENUES 0 0 0 0 0 0 0 11 12 16 19 222 296
Track construction 166 256 688 940 1569 1471 877 744 697 644 442 326 49 Rolling stock 0 0 0 0 0 0 0 6 6 6 6 52 58 TOTAL INVESTMENT COSTS 166 256 688 940 1569 1471 877 749 703 649 448 379 107
Operating and maintenance costs 0 0 0 0 0 0 18 65 61 58 78 74 74 TOTAL OPERATING COSTS 0 0 0 0 0 0 18 65 61 58 78 74 74 TOTAL OUTFLOWS 166 256 688 940 1569 1471 895 814 764 708 526 452 181
CASH FLOW -166 -256 -688 -940 -1569 -1471 -895 -803 -752 -692 -506 -230 116
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
TOTAL REVENUES 300 307 315 323 331 339 343 348 352 357 361 365 370
Track construction 0 0 0 0 0 0 0 0 0 0 0 0 0 Rolling stock TOTAL INVESTMENT COSTS 61 61 61 61 61 61 61 61 61 61 61 61 61
Operating and maintenance costs 71 68 73 74 75 75 76 76 77 77 78 78 79 TOTAL OPERATING COSTS 71 68 73 74 75 75 76 76 77 77 78 78 79 TOTAL OUTFLOWS 132 130 134 135 136 137 137 137 138 138 139 139 140
CASH FLOW 167 178 181 188 195 203 206 210 214 218 222 226 230
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033
TOTAL REVENUES 375 379 384 386 389 391 394 396 399 401 404
Track construction 0 0 0 0 0 0 0 0 0 0 -2581 Rolling stock 61 61 61 61 61 61 61 61 61 61 61 TOTAL INVESTMENT COSTS 61 61 61 61 61 61 61 61 61 61 -2520
Operating and maintenance costs 79 80 80 80 81 81 81 81 82 82 82 TOTAL OPERATING COSTS 79 80 80 80 81 81 81 81 82 82 82 TOTAL OUTFLOWS 140 141 141 141 142 142 142 142 143 143 -2438
CASH FLOW 234 239 243 245 247 249 252 254 256 258 2841
Discount rate 5.0% FNPV (C) -4766 FRR (C) -0.45%
Source: Own calculation
Annexe 1: Detailed results
March 2011 | Frontier Economics, Atkins, ITS 41
Figure 13. High speed rail – Spain. Financial return on capital (€m, 2008 prices) – Low case
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Revenues 0 0 0 0 0 0 0 11 12 16 19 222 296 Residual values TOTAL FINANCIAL INFLOWS 0 0 0 0 0 0 0 11 12 16 19 222 296
Local contribution Regional contrintribution National contribution 100 154 415 568 948 888 530 449 421 389 267 197 29 Total national public contribution 100 154 415 568 948 888 530 449 421 389 267 197 29 Operating and maintenance costs 0 0 0 0 0 0 18 65 61 58 78 74 74 Total Operating Costs 0 0 0 0 0 0 18 65 61 58 78 74 74 TOTAL FINANCIAL OUTFLOWS 100 154 415 568 948 888 548 514 483 447 345 271 103
NET CASH FLOW -100 -154 -415 -568 -948 -888 -548 -503 -471 -431 -325 -49 193
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
Revenues 300 307 315 323 331 339 343 348 352 357 361 365 370 Residual values TOTAL FINANCIAL INFLOWS 300 307 315 323 331 339 343 348 352 357 361 365 370
Local contribution Regional contrintribution National contribution 0 0 0 0 0 0 0 0 0 0 0 0 0 Total national public contribution 0 0 0 0 0 0 0 0 0 0 0 0 0 Operating and maintenance costs 71 68 73 74 75 75 76 76 77 77 78 78 79 Total Operating Costs 71 68 73 74 75 75 76 76 77 77 78 78 79 TOTAL FINANCIAL OUTFLOWS 71 68 73 74 75 75 76 76 77 77 78 78 79
NET CASH FLOW 300 307 315 323 331 339 343 348 352 357 361 365 370
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033
Revenues 375 379 384 386 389 391 394 396 399 401 404 Residual values 2581 TOTAL FINANCIAL INFLOWS 375 379 384 386 389 391 394 396 399 401 2985
Local contribution Regional contrintribution National contribution 0 0 0 0 0 0 0 0 0 0 0 Total national public contribution 0 0 0 0 0 0 0 0 0 0 0 Maintenance 79 80 80 80 81 81 81 81 82 82 82 Total Operating Costs 79 80 80 80 81 81 81 81 82 82 82 TOTAL FINANCIAL OUTFLOWS 79 80 80 80 81 81 81 81 82 82 82
NET CASH FLOW 296 300 304 306 308 311 313 315 317 319 2903
Discount rate 5.0% FNPV (K) -919 FRR (K) 3.7%
Source: Own calculations
Annexe 1: Detailed results
42 Frontier Economics, Atkins, ITS | March 2011
Figure 14. High speed rail – Spain. Financial sustainability (€m, 2008 prices) – Low case
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
EU Grant 66 101 272 372 621 582 347 295 276 255 175 129 19 Local contribution Regional contrintribution National contribution 100 154 415 568 948 888 530 449 421 389 267 197 29 Total national public contribution 100 154 415 568 948 888 530 449 421 389 267 197 29 Operating subsidies FINANCIAL RESOURCES 166 256 688 940 1569 1471 877 744 697 644 442 326 49 Passenger vehicles 0 0 0 0 0 0 0 11 12 16 19 222 296 TOTAL REVENUES 0 0 0 0 0 0 0 11 12 16 19 222 296 TOTAL INFLOWS 166 256 688 940 1569 1471 877 755 710 660 462 548 345
Track construction 166 256 688 940 1569 1471 877 744 697 644 442 326 49 Rolling stock 0 0 0 0 0 0 0 6 6 6 6 52 58 TOTAL INVESTMENTS COSTS 166 256 688 940 1569 1471 877 749 703 649 448 379 107 Operating and maintenance costs 0 0 0 0 0 0 18 65 61 58 78 74 74 TOTAL OPERATING COSTS 0 0 0 0 0 0 18 65 61 58 78 74 74 TOTAL OUTFLOWS 166 256 688 940 1569 1471 895 814 764 708 526 452 181
NET CASH FLOW 0 0 0 0 0 0 -18 -59 -55 -48 -64 96 164 CUMULATED CASH FLOW 0 0 0 0 0 0 -18 -77 -132 -180 -243 -148 17
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
EU Grant 0 0 0 0 0 0 0 0 0 0 0 0 0 Local contribution Regional contrintribution National contribution 0 0 0 0 0 0 0 0 0 0 0 0 0 Total national public contribution 0 0 0 0 0 0 0 0 0 0 0 0 0 Operating subsidies FINANCIAL RESOURCES 0 0 0 0 0 0 0 0 0 0 0 0 0 Passenger vehicles 300 307 315 323 331 339 343 348 352 357 361 365 370 TOTAL REVENUES 300 307 315 323 331 339 343 348 352 357 361 365 370 TOTAL INFLOWS 300 307 315 323 331 339 343 348 352 357 361 365 370
Track construction 0 0 0 0 0 0 0 0 0 0 0 0 0 Rolling stock 61 61 61 61 61 61 61 61 61 61 61 61 61 TOTAL INVESTMENTS COSTS 61 61 61 61 61 61 61 61 61 61 61 61 61 Operating and maintenance costs 71 68 73 74 75 75 76 76 77 77 78 78 79 TOTAL OPERATING COSTS 71 68 73 74 75 75 76 76 77 77 78 78 79 TOTAL OUTFLOWS 132 130 134 135 136 137 137 137 138 138 139 139 140
NET CASH FLOW 168 178 181 188 195 203 206 210 214 218 222 226 230 CUMULATED CASH FLOW 184 362 543 731 926 1129 1335 1546 1760 1978 2200 2427 2657
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033
EU Grant 0 0 0 0 0 0 0 0 0 0 0 Local contribution Regional contrintribution National contribution 0 0 0 0 0 0 0 0 0 0 0 Total national public contribution 0 0 0 0 0 0 0 0 0 0 0 Operating subsidies FINANCIAL RESOURCES 0 0 0 0 0 0 0 0 0 0 0 Passenger vehicles 375 379 384 386 389 391 394 396 399 401 404 TOTAL REVENUES 375 379 384 386 389 391 394 396 399 401 404 TOTAL INFLOWS 375 379 384 386 389 391 394 396 399 401 404
Track construction 0 0 0 0 0 0 0 0 0 0 0 Rolling stock 61 61 61 61 61 61 61 61 61 61 61 TOTAL INVESTMENTS COSTS 61 61 61 61 61 61 61 61 61 61 61 Operating and maintenance costs 79 80 80 80 81 81 81 81 82 82 82 TOTAL OPERATING COSTS 79 80 80 80 81 81 81 81 82 82 82 TOTAL OUTFLOWS 140 141 141 141 142 142 142 142 143 143 143
NET CASH FLOW 234 239 243 245 247 249 252 254 256 258 261 CUMULATED CASH FLOW 2891 3130 3373 3618 3865 4115 4366 4620 4876 5135 5395
Source: Own calculations
Annexe 1: Detailed results
March 2011 | Frontier Economics, Atkins, ITS 43
Figure 15. High speed rail – Spain. Economic analysis (€m, 2008 prices) – High case
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
BENEFITS Consumers Surplus Time Benefits 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4.9 5.2 6.8 7.9 66.4 85.7 Accidents 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 0.9 1.3 1.5 9.9 12.4 Vehicle Operating Costs 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.3 3.4 4.6 5.6 83.3 101.0 Externalities 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.7 0.7 1.0 1.2 18.7 22.8
Producer Surplus Revenues 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11.5 12.1 16.2 19.3 222.0 292.5
TOTAL BENEFITS 0.0 0.0 0.0 0.0 0.0 0.0 0.0 21.2 22.4 29.8 35.5 400.3 514.3
COSTS Investment Costs Track construction 166.2 255.7 687.8 940.0 1568.7 1470.7 877.1 743.8 697.5 643.9 442.4 326.3 48.8 Rolling stock 0.0 0.0 0.0 0.0 0.0 0.0 0.0 57.8 0.0 20.8 0.0 491.7 38.9
Operating and maintenance costs 0.0 0.0 0.0 0.0 0.0 0.0 18.0 64.9 61.4 58.5 77.6 73.8 73.8
TOTAL COSTS 166.2 255.7 687.8 940.0 1568.7 1470.7 895.1 866.4 758.9 723.2 520.0 891.8 161.5
NET BENEFITS -166.2 -255.7 -687.8 -940.0 -1568.7 -1470.7 -895.1 -845.2 -736.5 -693.4 -484.5 -491.6 352.8
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
BENEFITS Consumers Surplus Time Benefits 89.1 93.6 98.3 103.2 108.4 113.8 116.6 119.5 122.5 125.6 128.7 131.9 135.2 Accidents 13.1 13.7 14.4 15.1 15.9 16.7 17.1 17.5 18.0 18.4 18.9 19.3 19.8 Vehicle Operating Costs 108.4 113.8 119.5 125.4 131.7 138.3 141.8 145.3 148.9 152.7 156.5 160.4 164.4 Externalities 24.4 25.6 26.9 28.2 29.6 31.1 31.9 32.7 33.5 34.3 35.2 36.1 37.0
Producer Surplus Revenues 307.1 322.5 338.6 355.5 373.3 392.0 401.8 411.8 422.1 432.7 443.5 454.6 466.0
TOTAL BENEFITS 542.1 569.2 597.6 627.5 658.9 691.8 709.1 726.9 745.0 763.7 782.8 802.3 822.4
COSTS Investment Costs Track construction 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Rolling stock -5.7 8.3 35.0 168.8 -8.7 231.7 30.7 40.2 -3.0 -2.7 15.5 6.8 -3.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Operating and maintenance costs 71.2 68.4 72.9 74.6 76.2 78.0 79.0 79.9 80.9 81.9 83.0 84.0 85.1
TOTAL COSTS 65.6 76.8 107.9 243.3 67.5 309.7 109.7 120.1 77.9 79.2 98.5 90.8 82.1
NET BENEFITS 476.5 492.4 489.7 384.2 591.4 382.1 599.4 606.7 667.1 684.5 684.3 711.6 740.3
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033
BENEFITS Consumers Surplus Time Benefits 138.6 142.1 145.6 147.5 149.3 151.2 153.1 155.0 156.9 158.9 160.9 Accidents 20.3 20.8 21.4 21.6 21.9 22.2 22.4 22.7 23.0 23.3 23.6 Vehicle Operating Costs 168.5 172.7 177.0 179.3 181.5 183.8 186.1 188.4 190.7 193.1 195.5 Externalities 37.9 38.8 39.8 40.3 40.8 41.3 41.8 42.3 42.9 43.4 44.0
Producer Surplus Revenues 477.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
TOTAL BENEFITS 365.3 374.5 383.8 388.6 393.5 398.4 403.4 408.4 413.5 418.7 423.9
COSTS Investment Costs Track construction 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -2580.8 Rolling stock 9.8 12.1 -3.0 -11.1 -5.7 14.9 18.2 57.2 0.0 -5.7 0.0
Operating and maintenance costs 86.2 87.4 88.5 89.1 89.7 90.3 91.0 91.6 92.2 92.9 93.5
TOTAL COSTS 96.0 99.4 85.5 78.0 84.0 105.3 109.1 148.8 92.2 87.1 -2487.3
NET BENEFITS 269.3 275.0 298.3 310.6 309.5 293.1 294.3 259.7 321.3 331.6 2911.2
Discount Rate 5.5% ENPV -1948.0 ERR 3.70% B/C Ratio 0.7
Source: Own calculation
Annexe 1: Detailed results
44 Frontier Economics, Atkins, ITS | March 2011
Figure 16. High speed rail – Spain. Financial return on investment (€m, 2008 prices) – High case
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
TOTAL REVENUES 0 0 0 0 0 0 0 11 12 16 19 222 293
Track construction 166 256 688 940 1569 1471 877 744 697 644 442 326 49 Rolling stock 0 0 0 0 0 0 0 58 0 21 0 492 39 TOTAL INVESTMENT COSTS 166 256 688 940 1569 1471 877 802 697 665 442 818 88
Operating and maintenance costs 0 0 0 0 0 0 18 65 61 58 78 74 74 TOTAL OPERATING COSTS 0 0 0 0 0 0 18 65 61 58 78 74 74 TOTAL OUTFLOWS 166 256 688 940 1569 1471 895 866 759 723 520 892 161
CASH FLOW -166 -256 -688 -940 -1569 -1471 -895 -855 -747 -707 -501 -670 131
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
TOTAL REVENUES 307 322 339 356 373 392 402 412 422 433 444 455 466
Track construction 0 0 0 0 0 0 0 0 0 0 0 0 0 Rolling stock TOTAL INVESTMENT COSTS -6 8 35 169 -9 232 31 40 -3 -3 16 7 -3
Operating and maintenance costs 71 68 73 75 76 78 79 80 81 82 83 84 85 TOTAL OPERATING COSTS 71 68 73 75 76 78 79 80 81 82 83 84 85 TOTAL OUTFLOWS 66 77 108 243 68 310 110 120 78 79 98 91 82
CASH FLOW 242 246 231 112 306 82 292 292 344 354 345 364 384
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033
TOTAL REVENUES 478 490 502 508 514 521 527 534 541 547 554
Track construction 0 0 0 0 0 0 0 0 0 0 -2581 Rolling stock 10 12 -3 -11 -6 15 18 57 0 -6 0 TOTAL INVESTMENT COSTS 10 12 -3 -11 -6 15 18 57 0 -6 -2581
Operating and maintenance costs 86 87 89 89 90 90 91 92 92 93 94 TOTAL OPERATING COSTS 86 87 89 89 90 90 91 92 92 93 94 TOTAL OUTFLOWS 96 99 86 78 84 105 109 149 92 87 -2487
CASH FLOW 382 390 416 430 430 416 418 385 448 460 3042
Discount rate 5.0% FNPV (C) -4288 FRR (C) 0.65%
Source: Own calculation
Annexe 1: Detailed results
March 2011 | Frontier Economics, Atkins, ITS 45
Figure 17. High speed rail – Spain. Financial return on capital (€m, 2008 prices) – High case
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Revenues 0 0 0 0 0 0 0 11 12 16 19 222 293 Residual values TOTAL FINANCIAL INFLOWS 0 0 0 0 0 0 0 11 12 16 19 222 293
Local contribution Regional contrintribution National contribution 100 154 415 568 948 888 530 449 421 389 267 197 29 Total national public contribution 100 154 415 568 948 888 530 449 421 389 267 197 29 Operating and maintenance costs 0 0 0 0 0 0 18 65 61 58 78 74 74 Total Operating Costs 0 0 0 0 0 0 18 65 61 58 78 74 74 TOTAL FINANCIAL OUTFLOWS 100 154 415 568 948 888 548 514 483 447 345 271 103
NET CASH FLOW -100 -154 -415 -568 -948 -888 -548 -503 -471 -431 -325 -49 189
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
Revenues 307 322 339 356 373 392 402 412 422 433 444 455 466 Residual values TOTAL FINANCIAL INFLOWS 307 322 339 356 373 392 402 412 422 433 444 455 466
Local contribution Regional contrintribution National contribution 0 0 0 0 0 0 0 0 0 0 0 0 0 Total national public contribution 0 0 0 0 0 0 0 0 0 0 0 0 0 Operating and maintenance costs 71 68 73 75 76 78 79 80 81 82 83 84 85 Total Operating Costs 71 68 73 75 76 78 79 80 81 82 83 84 85 TOTAL FINANCIAL OUTFLOWS 71 68 73 75 76 78 79 80 81 82 83 84 85
NET CASH FLOW 307 322 339 356 373 392 402 412 422 433 444 455 466
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033
Revenues 478 490 502 508 514 521 527 534 541 547 554 Residual values 2581 TOTAL FINANCIAL INFLOWS 478 490 502 508 514 521 527 534 541 547 3135
Local contribution Regional contrintribution National contribution 0 0 0 0 0 0 0 0 0 0 0 Total national public contribution 0 0 0 0 0 0 0 0 0 0 0 Maintenance 86 87 89 89 90 90 91 92 92 93 94 Total Operating Costs 86 87 89 89 90 90 91 92 92 93 94 TOTAL FINANCIAL OUTFLOWS 86 87 89 89 90 90 91 92 92 93 94
NET CASH FLOW 391 402 413 419 425 430 436 442 448 454 3042
Discount rate 5.0% FNPV (K) -351 FRR (K) 4.5%
Source: Own calculations
Annexe 1: Detailed results
46 Frontier Economics, Atkins, ITS | March 2011
Figure 18. High speed rail – Spain. Financial sustainability (€m, 2008 prices) – High case
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
EU Grant 66 101 272 372 621 582 347 295 276 255 175 129 19 Local contribution Regional contrintribution National contribution 100 154 415 568 948 888 530 449 421 389 267 197 29 Total national public contribution 100 154 415 568 948 888 530 449 421 389 267 197 29 Operating subsidies FINANCIAL RESOURCES 166 256 688 940 1569 1471 877 744 697 644 442 326 49 Passenger vehicles 0 0 0 0 0 0 0 11 12 16 19 222 293 TOTAL REVENUES 0 0 0 0 0 0 0 11 12 16 19 222 293 TOTAL INFLOWS 166 256 688 940 1569 1471 877 755 710 660 462 548 341
Track construction 166 256 688 940 1569 1471 877 744 697 644 442 326 49 Rolling stock 0 0 0 0 0 0 0 58 0 21 0 492 39 TOTAL INVESTMENTS COSTS 166 256 688 940 1569 1471 877 802 697 665 442 818 88 Operating and maintenance costs 0 0 0 0 0 0 18 65 61 58 78 74 74 TOTAL OPERATING COSTS 0 0 0 0 0 0 18 65 61 58 78 74 74 TOTAL OUTFLOWS 166 256 688 940 1569 1471 895 866 759 723 520 892 161
NET CASH FLOW 0 0 0 0 0 0 -18 -111 -49 -63 -58 -344 180 CUMULATED CASH FLOW 0 0 0 0 0 0 -18 -129 -179 -242 -300 -643 -464
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
EU Grant 0 0 0 0 0 0 0 0 0 0 0 0 0 Local contribution Regional contrintribution National contribution 0 0 0 0 0 0 0 0 0 0 0 0 0 Total national public contribution 0 0 0 0 0 0 0 0 0 0 0 0 0 Operating subsidies FINANCIAL RESOURCES 0 0 0 0 0 0 0 0 0 0 0 0 0 Passenger vehicles 307 322 339 356 373 392 402 412 422 433 444 455 466 TOTAL REVENUES 307 322 339 356 373 392 402 412 422 433 444 455 466 TOTAL INFLOWS 307 322 339 356 373 392 402 412 422 433 444 455 466
Track construction 0 0 0 0 0 0 0 0 0 0 0 0 0 Rolling stock -6 8 35 169 -9 232 31 40 -3 -3 16 7 -3 TOTAL INVESTMENTS COSTS -6 8 35 169 -9 232 31 40 -3 -3 16 7 -3 Operating and maintenance costs 71 68 73 75 76 78 79 80 81 82 83 84 85 TOTAL OPERATING COSTS 71 68 73 75 76 78 79 80 81 82 83 84 85 TOTAL OUTFLOWS 66 77 108 243 68 310 110 120 78 79 98 91 82
NET CASH FLOW 242 246 231 112 306 82 292 292 344 354 345 364 384 CUMULATED CASH FLOW -222 24 254 367 673 755 1047 1339 1683 2036 2381 2745 3129
2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033
EU Grant 0 0 0 0 0 0 0 0 0 0 0 Local contribution Regional contrintribution National contribution 0 0 0 0 0 0 0 0 0 0 0 Total national public contribution 0 0 0 0 0 0 0 0 0 0 0 Operating subsidies FINANCIAL RESOURCES 0 0 0 0 0 0 0 0 0 0 0 Passenger vehicles 478 490 502 508 514 521 527 534 541 547 554 TOTAL REVENUES 478 490 502 508 514 521 527 534 541 547 554 TOTAL INFLOWS 478 490 502 508 514 521 527 534 541 547 554
Track construction 0 0 0 0 0 0 0 0 0 0 0 Rolling stock 10 12 -3 -11 -6 15 18 57 0 -6 0 TOTAL INVESTMENTS COSTS 10 12 -3 -11 -6 15 18 57 0 -6 0 Operating and maintenance costs 86 87 89 89 90 90 91 92 92 93 94 TOTAL OPERATING COSTS 86 87 89 89 90 90 91 92 92 93 94 TOTAL OUTFLOWS 96 99 86 78 84 105 109 149 92 87 94
NET CASH FLOW 382 390 416 430 430 416 418 385 448 460 461 CUMULATED CASH FLOW 3511 3901 4317 4747 5177 5593 6011 6396 6845 7305 7766
Source: Own calculations
Annexe 1: Detailed results
Frontier Economics Limited in Europe is a member of the Frontier Economics network, which consists of separate companies based in Europe (Brussels, Cologne, London & Madrid) and Australia (Brisbane, Melbourne & Sydney). The companies are independently owned, and legal commitments entered into by any one company do not impose any obligations on other companies in the network. All views expressed in this document are the views of Frontier Economics Limited.
FRONTIER ECONOMICS Europe BRUSSELS | COLOGNE | LONDON | MADRID
Frontier Economics Ltd 71 High Holborn London WC1V 6DA
Tel. +44 (0)20 7031 7000 Fax. +44 (0)20 7031 7001 www.frontier-economics.com