appendix 1 – high speed railway madrid

March 2011 | Frontier Economics, Atkins, ITS 1

Appendix 1 – High speed railway Madrid –

Barcelona in Spain


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

Source: Openstreetmap.org

Madrid

ZaragozaLleida

Tarragona

Barcelona

Girona

Madrid

ZaragozaLleida

Tarragona

Barcelona

Girona

Madrid

ZaragozaLleida

Tarragona

Barcelona

Girona

2 Frontier Economics, Atkins, ITS | March 2011


Barcelona in Spain

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.



Barcelona in Spain

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.



Barcelona in Spain

Table 2. 12 Subprojects making up the project

Subprojects Start

date

Description of project and

length

CF

contribution

(% of eligible

cost)

Madrid - Lleida 1999ES16CPT001 June

1999

Supply and installation of track

material (485km, 52km of

viaducts, tunnels and bridges)

642,214,556

(72.25%)

Lleida-Olérdola 2003ES16CPT004 March

2003

Supply and installation of track

material (125.5 km)

165,781,097

(72.25%)

Lleida-Martorell

2000ES16CPT005

November

2000 Rail bed construction (18.54 km)

164,034,000

(72.25%)

Martorell-Barcelona.

2004ES16CPT003

July


69,168,327

(72.25%)

Accesos ferroviarios de estación

de Zaragoza 2000ES16CPT003

November


77,755,000

(72.25%)

Subtramos XI-A and XI-B entre

Lleida y Martorell

2001ES16CPT009

November


67,070,000

(72.25%)

Gelida-Sant Llorenç d'Hortons-

Sant Esteve Sesrovires

2003ES16CPT010

March


57,797,005

(72.25%)

Subtramos IX-A Lleida y Martorell

2001ES16CPT005

Sept.


49,088,000

(72.25%)

Subtramos XI-C Lleida y Martorell

2001ES16CPT010

November


52,928,000

(72.25%)

Subtramos IX-B Lleida y Martorell

2001ES16CPT006

November


41,772,000

(72.25%)

Sant Esteve Sesrovires-Martorell -

Río Llobregat 2003ES16CPT026

March


29,380,257

(72.25%)

Río Llobregat - Costa Blanca -

Conexión Vallés

2003ES16CPT027

March


25,152,553

(72.25%)

TOTAL 1,041,946,723

(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.



Barcelona in Spain

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.



Barcelona in Spain

Figure 2. GDP per capita in regions (as % of GDP per capita in Spain)

Source: Instituto Nacional de Estadística (INE)

Figure 3. Unemployment - Evolution of unemployment rate.


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

100%

110%

120%

130%

140%

2001 2002 2003 2004 2005 2006 2007 2008

Aragon

Cataluña

Madrid

0.0

5.0

10.0

15.0

20.0

25.0

2000 2002 2004 2006 2008 2010

Spain

Aragon

Cataluña

Madrid



Barcelona in Spain

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)


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.

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

Zaragoza Lleida Total Spanish capital

cities

Before AVE (199-2003)

After AVE (2004-2009)



Barcelona in Spain

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.



Barcelona in Spain

Table 3. Summary of project-related documentation

Documents Obtained from

Funding Applications

All subprojects DG REGIO

Funding Decisions

All subprojects DG REGIO

Ex ante CBA

INECO Report. “Rentabilidad de la Línea Madrid – Barcelona – Figueres”, May 2001

DG REGIO

Methodology used in the economic analysis of the projects, “Manual de evaluación de inversiones en ferrocarriles de vía ancha", Dirección General de Infraestructuras del Transporte Ferroviario, 1987

Ministerio de Fomento

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.



Barcelona in Spain

Table 4. Summary of Primary & Secondary Data Availability

Data Source Issues

Infrastructure investment costs ADIF

Infrastructure operating costs ADIF

Cost benefit analysis ADIF

“Actualización del estudio de determinación de la capacidad de autofinanciación en la 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.



Barcelona in Spain

Table 5. Assumed growth rates of passengers on the LAV

Short run

(2010 – 2015)

Medium run

(2016 – 2025)

Long run

(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.



Barcelona in Spain

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%


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.



Barcelona in Spain

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)

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

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Millio

n E

uro

s



Barcelona in Spain

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)

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.

-300,000

-200,000

-100,000

0

100,000

200,000

300,000

400,000

500,000

600,000

2003 2006 2009 2012 2015 2018 2021 2024 2027 2030 2033

Th

ou

sa

nd

Eu

ros



Barcelona in Spain

Table 8. Summary of ex post unit costs (2008 prices)

Non-discounted

Level 1 „All-in‟ (€/km) 14,281,581

Level 2

Track (€/km) 7,455,877

Stations (€/station) 79,940,000

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.



Barcelona in Spain

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



Barcelona in Spain

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

(2016 – 2025)

Long run

(2026-2033)

Variable costs related to passengers /

tickets sold 1.25% 0.5%

Benefits from time savings, vehicle

operating costs, accidents and

environmental externalities

1.5% 1%

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



Barcelona in Spain

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)

Route Car Bus Air Trad. rail High-speed

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



Barcelona in Spain

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



Barcelona in Spain

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)

Car Bus

Rail

(trad. and

high-speed)

Air

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.



Barcelona in Spain

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.



Barcelona in Spain

Table 15. Socioeconomic and land-use impacts influenced by the High Speed Train

Impact area Specific

impacts What we know

1. Mobility 1.1 Amount of

travel

HST tends to have a large impact on external

accessibility and travel times generating an increased

amount of travel. The increase in the number of trips

appears to be more significant when the HST

infrastructure implies substantial changes in external

accessibility experienced by the cities with HST stations

1.2 Modal shift

HST services tend to be competitive vis-à-vis air travel for

middle distance corridors of 500-700 km, and possibly

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)

1.3 Population

mobility patterns

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,

as the HST services consolidate their services, other

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.

2. Socio-

economic

structures

2.1 Support

ongoing

transformations

HST infrastructure interact with other ongoing economic

factors such as the labour market, scale economies and

market size, thereby influencing labour productivity and

corporate productive efficiency in central, well-developed

cities and in peripheral, less developed cities to a varying

degree depending on initial conditions and strength of

ongoing economic transformation in these localities.

2.2 Tourism

dynamics

The availability of HST services tends to have a direct

influence on the tourism industry. Evidence suggests that

cities connected via a HST network experience an

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.

2.3 New

economic

activities

The introduction of the HST facilitates market expansion

in service-related activities. People and enterprises

located in the area of influence of the HST stations gain

access to an increased and diversified number of

services.



Barcelona in Spain

Impact area Specific

impacts What we know

3. Urban

image

3.1 Urban

image

Cities that become part of the HST network, and do not

belong to the more well-known set of important national

cities (e.g., Madrid, Barcelona etc) immediately improve

their external image and achieve increased awareness

(e.g. tourists, business conference organisers).

3.2 Local

marketing

campaigns

Cities take the opportunity of becoming part of the HST

network to initiate or adapt urban image campaigns

intended to improve their attractiveness and promote the

local economy.

4. Spatial

changes

4.1 Metropolitan

dynamics

New metropolitan interactions are created between small

and medium cities with other small and medium cities

connected by the HST network and long distance

interactions irrespective of city size.

4.2 Urban

transformation

The physical transformation brought about by the HST is

illustrated by a network remodelling promoting an

improved integration and access of rail into town and the

urban remodelling around HST stations, new ones and

old but enhanced ones

4.3 Planning

policies and

measures

Local and regional authorities take advantage of the new

HST infrastructure to review existing urban plans or

policies or issue new ones: better integration of stations

with their urban surroundings, mitigate potential negative

effects, and improve accessibility

4.4 Urban

promotion and

marketing

Local and regional authorities take advantage of the new

HST infrastructure to also reinforce or launch city image

and tourist campaigns to enhance the attractiveness of

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



Barcelona in Spain

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



Barcelona in Spain

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;



Barcelona in Spain

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.



Barcelona in Spain

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.



Barcelona in Spain

Table 16. Utilisation rates on the LAV Madrid - Barcelona (2008 and 2009)

2008 2009

Maximum number of passengers-

kilometer (Million) 4,494 6,942

Total number of passengers-

kilometer (Million) 2,723 3,962

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



Barcelona in Spain

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

(€ million, 2005 prices)

Economic IRR

(%)

BIR

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.



Barcelona in Spain

Table 18. Results of ex ante cost benefit analysis for the whole line

Net Present Value

(€ million, 2005 prices)

IRR

(%)

BIR

Infrastructure

manager -7,946.17 -3.82% 0.01

Railway

operators 309.41 9.00% 1.6


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.



Barcelona in Spain

Table 19. Ex ante national demand routes

Long-haul internal

relations (High–speed

trains)

Long-haul external

relations (TALGO trains)

Regional relations

(TALGO trains)

Madrid to Barcelona /

Zaragoza / Lleida /

Tarragona / Girona

Ext. Madrid to Barcelona /

Zaragoza / Lleida /

Tarragona / Girona

Lleida to Tarragona /

Vallés / Barcelona /

Girona

Zaragoza to Barcelona /

Lleida / Tarragona /

Girona

Ext. Zaragoza to Barcelona

/ Lleida / Tarragona /

Girona

Tarragona to Vallés /

Barcelona / Girona

Vallés to Girona /

Figueres

Barcelona to Girona /

Figueres

Girona to Figueres


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.



Barcelona in Spain

Table 20. Sensitivity analysis for the infrastructure manager (ADIF) and railway

operators (RO)

ADIF NPV (€

million,

2005 prices)

ADIF

IRR

(%)

ADIF Net

Revenue /

Investment

RO NPV (€

million,

2005 prices)

RO IRR

(%)

Railway

Operators

investment

cost

+10% -8,203.2 -4.28% 8.7% 340.51 9%

0% -7,946.17 -3.82% 11.5% 309.41 9%

-10% -7,815.89 -3.59% 13.0% 278.35 9%

Railway

Operators

Demand

+10% -7,900.53 -3.74% 12.0% 340.35 9%

0% -7,946.17 -3.82% 11.5% 309.41 9%

-10% -8,118.50 -4.13% 9.6% 278.47 9%


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



Barcelona in Spain

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

Economic CBA

Ex ante

Social CBA

Ex post

Low Case

Ex post

High Case

Net Present

Value (€m) 1,091 4,125 -2,736 -1,948

Economic IRR

(%) 6.29% 8.92% 2.63% 3.70%

Benefit-cost

ratio 1.07 1.26 0.6 0.7


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



Barcelona in Spain

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


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.

0

400

800

1,200

1,600

2,000

2,400

2,800

3,200

Madrid -

Barcelona

Madrid -

Zaragoza

Zaragoza -

Barcelona

Tarragona -

Barcelona

Lleida -

Barcelona

Lleida -

Tarragona

Zaragoza -

Tarragona

Pa

sse

ng

ers

('1

00

0s)

Ex ante

Ex post



Barcelona in Spain

Figure 9. Capital cost comparison (€, 2008 prices)


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.

0

300

600

900

1,200

1,500

1,800

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Ex ante

Ex post



Barcelona in Spain

Figure 10. Average contribution to consumer surplus of various identified benefits


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

18%

45%

54%

72%

40% 18%

6%

6%

9%

5%10%

19%

0%

20%

40%

60%

80%

100%

EX ANTE EX POST ADIF 2009

Enviromental

Accidents

Time

VOC



Barcelona in Spain

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



Barcelona in Spain

political criteria after which CBA is used to inform the economic feasibility

studies and to identify critical issues such as environmental impacts.


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


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


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



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


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


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


Rolling stock




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


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


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%



Figure 13. High speed rail – Spain. Financial return on capital (€m, 2008 prices) –

Low case

Source: Own calculations

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


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


Local contribution







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


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%



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




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


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



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




Operating subsidies



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


Rolling stock 61 61 61 61 61 61 61 61 61 61 61 61 61




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




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



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



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



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


Rolling stock 0 0 0 0 0 0 0 58 0 21 0 492 39




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


Rolling stock

TOTAL INVESTMENT COSTS -6 8 35 169 -9 232 31 40 -3 -3 16 7 -3



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


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



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%



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


Local contribution







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


Local contribution







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




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%



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




Operating subsidies



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


Rolling stock 0 0 0 0 0 0 0 58 0 21 0 492 39




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




Operating subsidies



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


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



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




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



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

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