2014-37
Comparing the Costs of Vertical Separation,
Integration, and Intermediate Organisational
Structures in European and East Asian Railways
Fumitoshi Mizutani Andrew Smith
Chris Nash Shuji Uranishi

Comparing the Costs of Vertical Separation, Integration, and Intermediate
Organisational Structures in European and East Asian Railways

Fumitoshi Mizutani (Kobe University)
Andrew Smith (University of Leeds)
Chris Nash (University of Leeds)
Shuji Uranishi (Osaka City University)

Correspondent Author: Fumitoshi Mizutani
Kobe University, Graduate School of Business Administration
2-1 Rokkodai, Nada-ku, Kobe 657-8501(Tel): +81-78-803-6905(Fax):+81-78-803-6977(E-mail): toshi@kobe-u.ac.jp

Acknowledgements
This research was partly funded by JSPS KAKENHI Grant Numbers 24330132, 24530286,
26380298 and the Community of European Railways and Infrastructure Companies (CER),
whose members also carried out some checks on the dataset and made a small number of
amendments where necessary. An abridged version of the preferred model set out in this paper
was reported and used, alongside other evidence, to support the conclusions of a report1

produced for CER; see van de Velde et al. (2012) and presented at the Thredbo conference in2013 (Nash et. al., forthcoming). We wish to thank Didier van de Velde, Edward Christie andcolleagues at CER for their comments. All views in the paper are those of the authors and notnecessarily of CER, and any remaining errors and omissions are the responsibility of theauthors.

Abstract
There is a major policy debate within Europe and more widely on how to structure railway
systems to enhance competition, whilst minimising costs. This is the first study in theacademic literature to examine, using econometric methods, the cost impacts of threedifferent approaches to structuring railway systems: vertical separation, vertical integrationand the intermediate holding company model. Our analysis is based on a panel of European
and East Asian railways (1994-2010). We find that the optimal railway structure depends on
the intensity and type of traffic running on the network. Our research suggests that, at least
on cost grounds, countries should be free to choose between vertical integration, the holding
company model or vertical separation.
Date of final version: April 7th 2014. Revised version: September 10th, 2014
Key Words: Vertical Separation, Holding Company, Horizontal Separation, Competition,
Railway, Cost2

1.0 Introduction
Since 1991 (European Commission Directive 91/440), European Commission policy has been
to reform Europe’s railway systems by progressively opening up rail markets to competition.
Via successive legislation (see Nash, 2013 for a review), Europe’s rail systems have beenrequired to separate train operations and infrastructure (at least into separate divisions with
their own accounts). Based on this separated model, competition “in the market” has been
allowed to develop via third-party open-access to the infrastructure (mainly for freight traffic),
whilst competitive tendering has been the chosen means of introducing competition inpassenger services, though in the period covered by this study competition in passenger wasconcentrated mainly in Britain, Sweden and Germany. The proposals contained in theEuropean Commission’s Fourth Railway package (European Commission, 2013) for further
reforms of Europe’s railways, mean that, once enacted, it will be compulsory to introduce
competitive tendering for passenger services run under public service contracts and open
access for commercial services across the whole of Europe.
Importantly, the requirement to separate train operations and infrastructure – seen asa pre-requisite to obtaining a level playing field so that competition can develop – has beenachieved in different ways in different European countries. Some countries, such as Sweden
and the UK, have implemented full institutional separation; others have re-organised3infrastructure and operations into separate subsidiaries within a holding company structure(the German “holding” model); finally, a number of countries have chosen separation of the
key functions of train slot allocation and infrastructure charging together with other functions
such as investment planning into a separate body (the French “separation of key functions”
model, although France is now proposing to move to a holding company model).
Outside Europe, most railways are vertically integrated (for example the US andJapan), with operators accessing the infrastructure of other companies, if at all, mainly on thebasis of negotiation rather than as of right. Only the Australian inter-state system has followed
the European model.
In the aforementioned Fourth Railway Package the European Commission has
articulated its preference for the Swedish, full legal separation model as the only means ofguaranteeing fair access to the network for new entrants. However, under pressure from some
European countries, it has stopped short of requiring all railways to implement this model;
though if legal separation is not implemented, strict safeguards are proposed to ensure fair
access.
An important empirical and policy question then is whether full, legal separation willraise total industry costs relative to the alternatives. On this question the previous literature
with respect to European railways is unclear (see Nash, 2013, for a full review of theliterature). To summarise, some papers find that vertical separation raises costs (Growitsch4and Wetzel, 2009; Merkert et al., 2012; Jensen and Stelling, 2007), whilst others find either nosignificant change (Wetzel, 2008; Asmild et al., 2008; Cantos et. al., 2011), or a reduction, atleast when combined with other reforms (Friebel et al., 2010 and Cantos et al., 2010). The
literature covering US railroads suggests that vertical separation would raise costs (see, forexample, Bitzan, 2003). A key contribution to this literature is the paper by Mizutani andUranishi (2013) which argued, based on a dataset of OECD railways, that whether verticalseparation reduces or increases costs depends on the intensity with which the network is used.
However, one key limitation of the Mizutani and Uranishi (2013) model in thecontext of the European rail policy debate, as with the rest of the previous literature, is that it
only considers the comparison between vertical separation and vertical integration. As noted,
of much greater importance in the European policy debate is whether the form of separation and in particular, whether separation is implemented within a holding model or through fullinstitutional separation - matters in terms of its impact on whole industry costs. It is also thecase that the Mizutani and Uranishi dataset (in common with all other papers in the previous
literature) excludes Britain, which is seen within Europe as a key case study (Britain
implemented the most radical rail reforms anywhere in the world). Its exclusion thus weakens
the power of any findings on the impact of rail industry structure. Finally, as structuralchanges are happening all the time in Europe, with markets being progressively opened up tocompetition, it is important to have as up-to-date a picture as possible. In this regard most5

previous papers have not extended beyond 2005, with the exception of Mizutani and Uranishi(2013) and Cantos et al. (2011), which extend as far as 2007 and 2008 respectively; our paper
is thus the most up-to-date study of its kind in the literature.
The purpose of this paper is therefore to adapt and develop the Mizutani and Uranishi(2013) model in a number of important ways: most importantly to expand the set of
institutional possibilities to be compared, now including a comparison of the holding
company model as compared to full, vertical separation or vertical integration. Our focus is onwhich of these forms performs better from a cost perspective and how this comparison might
depend on the intensity (and also now types of) traffic running on the infrastructure. The
paper is thus concerned with providing empirical evidence on an important question which iscentral to European rail policy. At the same time we also make several methodological anddata advances as noted. A version of this model was reported in a study commissioned by theCommunity of European Railways and Infrastructure Companies (CER) – the EVES Rail
Study (see van de Velde et. al., 2012)1 and an overview of the policy implications given in2013 at the Thredbo conference (Nash et. al., forthcoming).
The structure of the paper is as follows. Following this introduction, in section 2 webriefly summarise the relevant literature and our contribution to that literature. Section 3 sets
1

The previous study was focused on policy findings and used slightly different data as we have been able toupdate some of the data since that report and the earlier study also did not include the full range of models as inthis paper.

6

out the data and the method, and the results are set out and discussed in Section 4. Section 5
concludes.
2.0 Literature review
The purpose of this section is to discuss the policy background and briefly review theliterature on the impact of organization structures in railways on cost, in particular to draw out
the important methodological and data issues relevant for the analysis contained in this paper.
2.1

Policy context

The policy context for this paper lies in the major structural reforms implemented andproposed to be implemented in Europe’s railway systems. The aims of the reforms are to
improve the competitiveness of rail relative to other modes and to meet the objectives
contained in the European Commission’s White Paper (European Commission, 2011).
Specifically as part of its policy to reduce greenhouse gases, the Commission wishes to see
rail as the main mode of transport for medium distance passenger and long distance freighttransport.
One of the key debates, which is common to infrastructure industries (e.g. energy
networks), is whether full, legal separation is necessary to achieve a level playing field forcompetition, and whether such separation raises costs relative to vertical integration. Our
paper is solely concerned with the second question. Further, and more precisely, in the railway
sector, some countries have chosen to re-organise their railways within a holding company
7

structure, with separate divisions within the holding for passenger and freight railways andinfrastructure provision (the German “holding” model). If, through implementing strong
Chinese walls between the different divisions, backed by a strong regulator, fair access to theinfrastructure can be ensured, it is argued that this structure could allow lower costs than avertically separated structure.
2.2

Previous literature

The reasons put forward for cost differences between alternative structures are that transaction
costs may be lower in the holding (and vertically integrated) model than a fully separated
structure, and also that costs more widely may be reduced due to the avoidance of misaligned
incentives (a problem with separated structures, in that each company will seek to optimize its
own operations rather than the system as a whole). Whilst appropriate track access charges
and performance regimes go some way to reduce these problems, there is evidence – e.g.
McNulty, 2011– that they do not completely remove them. In respect of the former, Merkert etal. (2012) show that whilst transaction costs are higher in separated systems, overall they are
rather small, in the region of 2-3% of total railway costs. In respect of the latter, Mizutani andUranishi (2013) further postulated that the extent to which costs may change between
integrated and separated structures will depend on the intensity of usage of the network. The
authors emphasized transaction cost theory as the explanation for this phenomenon. Further
discussion of this point is contained in van de Velde et al. (2012), where it is noted that more8

heavily used networks will tend to imply higher transaction costs and also higher costs
associated with misaligned incentives more widely.
As noted in the introduction there are no clear conclusions emerging from theprevious literature on the question of whether vertical separation raises or reduces costs
relative to vertical integration. Some studies found that vertical separation raised costs whilst
others found that it reduced costs or had no significant effect. In some studies the success of
separation depends on the interaction with other reforms and the sequencing of the reforms.
Mizutani and Uranishi found that vertical separation would reduce costs for lightly used
railways but increase costs for more intensively used railways. We refer the reader to Nash(2013) for a detailed review of the findings. Whilst the evidence on the cost impact of verticalseparation versus vertical integration is unclear, more importantly, for the purpose of thispaper, there has been no study of the cost impact of the holding model relative to verticalseparation (or integration).
The previous literature is dominated by studies that utilise physical measures that
may not adequately capture the inputs used by railways (in particular, the use of track or route
length to measure the capital input neglects any attempt to measure infrastructure quality).
Moreover, physical measures are subject to input substitution problems, particularly in termsof staff numbers, given the very different degrees of subcontracting found in different railway
companies. A cost based study, such as that carried out by Mizutani and Uranishi (2013),
9

whilst not immune from data challenges (see section 3 below), at least employs an overallmeasure of the inputs used by railways, therefore overcomes a number of the above
weaknesses.
2.3

Contribution of this study

As a starting point we take the approach set out in Mizutani and Uranishi (2013) and adopt a
cost function approach. However, we develop the Mizutani and Uranishi (2013) study in a
number of important ways. First, we enhance the modeling of industry structure on costs. The
previous literature, including Mizutani and Uranishi (2013), only considered two forms,
namely vertical separation or vertical integration. In our analysis we consider also anintermediate form, namely the holding company model.
Second, we add British data to the sample; the exclusion of Britain from previous
studies has been a major disadvantage of earlier work, particularly as Britain undertook themost radical reforms of any railway in the world and, whilst there have been successes, costs
have increased considerably. We were able to add Britain by combining published data withnew data obtained directly from railway companies in Britain. We also update the analysis
beyond 2007, up to 2010 where possible2. Most previous papers have not extended beyond
2005, with the exception of Mizutani and Uranishi (2013) and Cantos et al. (2011), which
extend as far as 2007 and 2008 respectively. Our paper thus allows us to include additional2

For some companies it was only possible to update the data to 2007. We also added data for three companies,

as compared to Mizutani and Uranishi (Britain, Bulgaria and Latvia). See section 3.

10

years of data post important reforms; for example, domestic freight markets were not required
to be fully opened up to competition until 2007.
Third, we enhance the modeling of market opening. Previously, Mizutani andUranishi (2013) only looked at the impact of vertical integration / separation, and did notconsider the separate impact of competition. Whilst Cantos et al. (2011) included competition
effects, these were based (for freight) on potential rather than actual entry, and for passenger
were based on actual entry (tendering only), but did not distinguish between degrees of entry(i.e. that in some countries the proportion of services tendered is small, whereas in others amuch higher proportion of services is subject to tendering such as in Germany; with allservices tendered in Britain). Our model therefore includes freight competition dummy
variables that reflect whether actual entry (rather than potential entry) has occurred. We also
develop a passenger competition index that reflects the extent of entry (tendering and open
access). We also used additional data, collected via questionnaire from Community ofEuropean Railways and Infrastructure Companies (CER) members on the timing of verticaland horizontal separation and on the dates for and extent of opening up of passenger andfreight competition (thus correcting inaccuracies in the data for these variables in the previous
literature).
Finally we develop the modeling of the relationship between industry structure andtrain density to distinguish between passenger and freight traffic (which have different
11characteristics). We consider that by focusing on data and methodological developments, ourpaper represents an important contribution to the literature, where there is currently much
uncertainty on the impact of rail reforms on costs.
3.0 Data and methodology
3.1

The data and estimation method

The majority of the data used in this study comes from the International Union of Railways(UIC). The reader is referred to Mizutani and Uranishi (2013) for further details. In terms ofcountry coverage, we add Britain, Bulgaria and Latvia to the sample. As noted, via aquestionnaire, we also obtained new data from CER members, which was updated as far as
possible from 2007 to 2010. The dataset was also checked and improved by CER members,
though it was not possible for members to verify whether all definitions were totallyconsistent. Nevertheless, the process of having the UIC checked, improved and updated by
CER members is a major step forward compared to the previous literature which has largely
relied on the raw, published UIC data. The railway networks included in this study are shownin Table 1.
[Table 1 here]
In terms of the cost measure, ideally we aim to have a measure of total costs (TC) for
the railway system in each country. Specifically in this paper, total costs means the total

12infrastructure costs of the main infrastructure manager3 plus the costs of all passenger andfreight operators running on that main system. For separated systems, infrastructure charges
included in the operating company accounts are netted out to avoid double counting. One
issue then is that, as in the Mizutani and Uranishi (2013) study, our dataset is based on asample of companies, not countries, and does not typically include small, new train operators.
To address this point, and ensure a like for like comparison, we have scaled up thecost data for train operating company costs of the incumbent based on their market share to
give an estimate of total train operating company costs for the country as a whole (this is notnecessary for the infrastructure, since we are concerned only with the traffic running on themain infrastructure as noted). This adjustment is only carried out for those countries which
had experienced the highest degree of entry. Of course, where entry is limited or non-existent(particularly in passenger), the lack of data for smaller operators is of little concern. The
problem is further mitigated by the fact that both the costs and train-km of the new entrants
are excluded. One problem with our approach is that it assumes that new operators have thesame cost structure as the incumbent (new entrants may be more cost efficient, implying
lower costs; on the other hand they may not be able to fully exploit economies of scale ordensity, implying higher costs). Overall, however, for the reasons outlined above, we consider
that our approach should not appreciably bias the results.

3

In the case of Switzerland, there are two.

13

In this study, following Mizutani and Uranishi (2013) we employ a translog total costfunction. Whilst some studies have estimated variable cost functions4, since our focus here ison the impact of institutional and other policy variables on system cost it is important to lookat total system costs, including the cost of the infrastructure. We do, however, control for thesize of the network, via the network size variable (N). Our approach is in line with several
others in the literature, in addition to Mizutani and Uranishi (2013); see, for example, theapproach adopted in Smith (2006) and the associated literature review contained in that paper.
In the model, we study the impact of three types of policy variables. First, a set ofvariables representing the degree of vertical separation, which now includes the holding
company model (DHC) as a third form lying between full vertical separation (DVS) and vertical
integration (the omitted dummy variable). Secondly, we study the impact of horizontal
separation (DHS), by which we mean that passenger services and freight services are provided
by institutionally separate companies. Finally, and an addition to the Mizutani and Uranishi(2013) analysis, we study the impact of passenger (CMP) and freight competition (DCF) on
costs. These structural types and competition from 1994 to 2011 are summarized in Table 1.
The cost model is specified such that the effect of the degree of vertical separation on
cost varies according to the degree of train density (as represented in the model byinteractions between DVS and V (train density), and likewise for DHC). In line with the4See, for example, Savage (1997), Mizutani (2004) and Mizutani and Uranishi (2007).
14

literature, and recognizing the different marginal costs of passenger and freight traffic, ourmodel has two outputs (passenger and freight output) 5 . The preferred translog model
specification is set out below.
lnTC = 0 + mmlnQm + jjlnwj + NlnN + TT + (1/2) nmamn (lnQm) (lnQn) +jmamj (lnQm) (lnwj) + mamN (lnQm) (lnN) + mamT (lnQm) (T) +(1/2) kjjk (lnwj) (lnwk) + jbjN (lnwj) (lnN) + jbjT (lnwj) (T) +2(1/2) NN (lnN)2 + gNT (lnN) (T) + (1/2) TT (T) +f(Di, V) + g(Di, R) + h(Dj, CMP)

(1)

where
f(Di, V) = ( dVS1 +dVS2lnV) DVS + (dHC1 + dHC2lnV) DHC + dHSDHS(2)g(Di, R) = dVS3lnR DVS + dHC3lnR DHC(3)h(CMP, Dj) = dCP CMP + dCFDCF(4)

and where TC = total cost, QP = quantity of passenger output, QF = quantity of freight output,
wL = labour input price, wE = energy input price, wM = materials input price, wK = capital input
price, N = total route length, T = technology (T: percentage of electrified length), V = train
density6, R = proportion of revenue made up by freight, DVS = vertical separation dummy

5

In Mizutani (2013) an alternative specification, with a single output, combined with output characteristics, wastested alongside the multiple-output model, though the latter was preferred; see Mizutani and Uranishi (2013).
6

Measured as train-km per route-km. Alternative measures, such as train-km per track-km were also tried but

we had concerns over the quality of the UIC track-km data which was volatile for a number of countries.

15

(vertical separation =1, otherwise = 0), DHC = holding company dummy (holding company=1,
otherwise =0), DHS = horizontal (passenger-freight) separation dummy (horizontal separation= 1, otherwise = 0), CMP = measure of passenger competition (0 = no competition, 1 – 4
based on extent of competition; see below), and DCF = freight entry dummy (takes the value
unity if actual freight entry has occurred, zero otherwise).
As noted in the introduction, our measure of competition in passenger services takes
account of the degree of competition (so competition is not modelled as a “yes/no”
variable as in previous studies). This development matters because in some countries the
proportion of services tendered is very small, whilst in others, namely Sweden, Germany
and Britain it is much higher. The CMP measure is developed via the following approach:
Level 1: competition is possible, equivalent to the competition announcement effect(dummy 0-1); Level 2: competition has happened but is minor compared to the wholenetwork, it can be through minor open access or a small proportion of the network that was
submitted to competitive tendering, around 10% (dummy 0-1); Level 3: competition has
happened and is major compared to the whole network (around or more than about 25%, a(dummy 0-1); Level 4: all services are submitted to competition (e.g. the British case)(dummy 0-1).
In order to make the analysis tractable in our preferred model we sum the dummies to
produce an overall measure. Whilst this is to some extent arbitrary, we consider that it is16

preferable to a simpler approach whereby countries with very different levels of competitive
threat are given the same value (0 or 1) for the competitive dummy.
As is standard we impose the restriction on input factor prices such that jj = 1, kjk =0, jbjN = 0, jbjT = 0, jYj = 0, jgmj = 0, jk = kj, bjN = bNj, bjT = bTj, amn = anm, amj = ajm, amN= aNm, amT = aTm, gNT = gTN.

Furthermore, we apply Shephard’s Lemma to the total costfunction. Then we can obtain the input share equations as follows:
Sj = j + mamj (lnQm) + kjk (lnwk) + bjN (lnN) + bjT (T)
where

(5)

Sj: input j’s share of total cost.

We apply the seemingly unrelated regression (SUR) method by the total cost function and the
input share equations. For the estimation, to aide with the interpretation of the coefficients, we
divide all observations of each variable by the sample mean.
3.2

Economic rationale for modelling the impact of institutional arrangements

Before proceeding to the empirical analysis it is worth setting out our a priori expectations
regarding the impact of different institutional forms on railway system cost. Starting with thedistinction between vertical separation and vertical integration, vertical separation might be
expected to bring about cost savings via two primary mechanisms. First of all, verticalseparation may lead to greater transparency on cost (and public subsidy), or simply cost
reductions resulting from restructuring, which is often associated with careful examination ofstaffing and costs. Secondly, it might bring about cost reductions through enabling greater
17

competition on the network; with vertical integration, at least in the absence of a strong
regulator, making it difficult for new entrants to access the network on the same terms as theincumbent (vertically-integrated) operator.
On the other hand, it might be argued that misaligned incentives (between operatorsand the infrastructure manager) in a vertically separated rail system might raise costs – or put
the other way round, there could be coordination benefits from a single, vertically-integrated
company planning investment and operations of infrastructure and operations together.
Mizutani and Uranishi (2013) make a further step by noting that the difference between
vertical separation and integration in respect of co-ordination costs will depend on how
intensely the infrastructure is utilized (drawing on Williamson’s transaction cost economics).
It is argued that co-ordination costs (co-ordinating the activities of infrastructure andoperations) in a separated environment increase more sharply as train density increases. Thisis because, for example, maintenance operations become more frequent and challenging as a
network becomes closer to capacity and it might therefore be expected that the interactions
between a separate infrastructure manager and legally separate train operators also becomes
more frequent and complex at the day to day operational level. The associated contractual
framework also becomes more complex as does investment planning, and there is much scopefor incentives to be misaligned, even with detailed contracts in place. Whilst transaction costs,
in the narrowest sense, have not been found to be very significant in railways (see Merkert et.
18

al., 2012), there are wider costs relating to the knock-on effects of sub-optimal decisions due
to various types of incentive misalignment between different companies in a
vertically-separated environment (see van de Velde et. al., 2012) which could be substantial.
Taken together, we might (perhaps weakly) conclude that, a priori, vertical separation
might be expected to reduce costs for lightly used railways, whilst potentially increasing costfor more intensely-used railways. For the purpose of this paper we want to know where thecut-off point is as this gives us important information regarding appropriate policy with regard
to vertical separation of railways in the sample (see Figure 1).
[Figure 1 here]
In this paper we go further, building on the above theoretical framework, first byconsidering also the holding company model. The supposed advantage of this model is that byenacting an internal separation of infrastructure from operations, but within the same holding
company new entrants can get fair access to the network, whilst at the same time, the potential
coordination cost advantage of having the infrastructure and the dominant operator within thesame group is retained. Particular benefits include the ability to better coordinate investment(internalising infrastructure and rolling stock considerations) as well as production planning(e.g. wear and tear at the wheel / rail interface) and timetable planning coordination (thoughnoting the possible conflict with fair access). Discussions within the industry suggest that insome cases, including Germany, the holding company does fulfil these functions, although it
19

appears there are Europe-wide differences in practice even within the holding company model
which we have not been able to take into account. The argument for this structure is further
strengthened if there is a strong economic regulator with powers to ensure that all operators
have fair access to the network, so that the possible disadvantage of encouraging
discrimination is avoided. Further, the separation within the parent should enable thetransparency and focus on cost that full, legal vertical separation itself might achieve. As
noted earlier, the holding company is one means by which railway systems in Europe havesought to meet the European Commission’s requirements for greater transparency and fair
access to the rail network. However, its effectiveness (particularly in respect of fair access)has been questioned both by potential entrants and also by the European Commission.
The second innovation of our paper is that we permit the cost difference between
vertical separation and the other institutional forms (vertical integration and the holding
company) to depend not only on the intensity of use of the network, but also on the proportionof freight running on the network. A priori, it might be expected that freight services, which
are not subject to a timetable in the same way as passenger services, could raise transaction
and other costs in a separated environment.
4.0 Results
4.1

Definition of variables

As we explained in section 3, we collected data for 33 railway networks, covering 26
20

European and 7 East Asian countries over the 17 year period from 1994 to 2010. In total wehave 481 observations (it is an unbalanced panel).
Our measure of total system costs (TC) is defined as the sum of labor, energy,material costs and capital costs.

However, as noted in section 3, to avoid double counting,infrastructure charges in rail operating companies are excluded in the vertically separated total
system cost measure (because the total costs of infrastructure companies are included).
In line with the previous literature (e.g. Cantos and Maudos (2001), Mancuso andReverberi (2003), Farsi et al. (2005) and Mizutani and Uranishi (2013), for our output
measures we include both revenue passenger km (Qp) and revenue tonne km (Qf). Mizutani
and Uranishi (2013) also considered an alternative specification with total train-km as themain output variable, plus hedonic characteristics variables, though the former (two output
model) was preferred. In our model, output characteristics, train density (V) and the
proportion of freight revenues (R) are included as interaction terms with the institutionaldummy variables, so that we can see how the effects of these industry structures depend on
the intensity of usage (V) and type of traffic running on the network (R).
We use four input prices: labour, energy (fuel), materials and capital prices. These aredefined in detail in Mizutani and Uranishi (2013). As for the other control variables, following
Mizutani and Uranishi, we include a network variable, route length (N), and a technology
variable, the percentage of electrified lines (T). We include two competition variables. First,
21

passenger competition (CMP) is the overall passenger competitive threat variable. As we
explained in section 3, this variable captures not just whether competition has occurred, but
the differing degrees of competition in different countries. Second, freight competition (DCF)
is captured via a dummy variable taking the value unity when actual freight entry has
occurred (not potential entry, as in previous studies), but which is otherwise zero.
As set out in section 3, there are three kinds of structural dummy variables in thisstudy. The first two dummy variables capture the effects of vertical separation (DVS) and theholding company model (DHC) respectively. Vertical integration is the omitted dummy. We
also include a horizontal (passenger-freight) separation dummy (DHS) taking the value unity
when horizontal separation has taken place; zero otherwise.
We note that the vertical structure for some companies in the sample did not change
during the period covered by our analysis (including Britain, Sweden and the Japanesecompanies). Therefore we do not include company dummies (fixed effects) as we would thenbe relying entirely on the “within” variation in the data to study the impact of reforms which,as noted, is zero for part of the sample. In this respect our approach is in line with theprevious literature on the impact of industry structure on costs, to which our paper adds7. The
previous literature has instead dealt with the issue of heterogeneity between countries by

7

Cantos et. al. (2010) do estimate a panel model but that is part of a second stage analysis with DEA as a firststage; and their model does not cover all inputs (it omits other costs which can be substantial). The later work,
Cantos et. al. (2011) does not appear to include firm dummies.
22

including a range of characteristic variables within the cost function. In the discussion of theresults below we therefore consider the robustness of the findings to an alternative model
specification, also used in Mizutani and Uranishi (2013), which includes train-km as the
single output measure, together with a set of hedonic variables capturing different railway
characteristics. We also consider the robustness of our findings with respect to the choice ofsample.

4.2

Empirical Results

The SUR estimation results are summarized in Table 2. Table 2 shows five cases with Case 1
being the model estimated in Mizutani and Uranishi (2013): (i) Case 1 (base case: verticalseparation and horizontal separation); (ii) Case 2 (Case 1 + holding company); (iii) Case 3(Case 1 + holding company + proportion of freight revenues); (iv) Case 4 (Case 1 + holding
company + competition); (v) Case 5 (Case 1 + holding company + proportion of freight
revenues + competition). We are thus able to test the impact of the innovations proposed inthis paper.
The goodness-of-fit in all cases of regressions is acceptably high because pseudo R2of the cost functions is very high at over 0.98. The required properties in the cost function are
in general satisfactorily met. First, the required symmetry and homogeneity conditions in
input factor prices are satisfied via the restrictions imposed on the model. Second, we
23

evaluated the required monotonicity conditions by checking that the partial derivative of thecost function with respect to output and input factor prices is not negative (i.e. lnC/lnQi > 0,
lnC/lnwj > 0); these being satisfied at the sample mean. Global concavity in input prices
was tested based on whether the Hessian matrix is negative semi-definite for the wholesample. The condition holds for around one fifth of the observations; however, we note that
there is no convenient way of imposing global concavity, and it is recognised in the literaturethat imposing this condition may seriously undermine the flexibility properties of the translog(see for example Coelli et. al., 2005, page 229). We tested a range of specifications which
performed better on the concavity criterion8. In all cases the key results on the impact ofrailway structure were little affected; and we thus retain model 5 as our preferred model.
Based on likelihood ratio tests of the five cases we can say the following. First, theaddition of the holding company institutional form (Case 2) adds to the model statistically (atthe 1% level) compared to Case 1, so this appears to be a useful innovation both statisticallyand from an a prior perspective. Case 3 (the addition of the freight proportion interaction)

8

These included the three input price alternative model specification shown in Mizutani and Uranishi (2013), a

Cobb-Douglas model, and a model in which concavity was imposed at a single point, following Ryan and Wales(2000). Further, as Wales (1977) notes, violations of concavity do not necessarily imply that there is nounderlying optimisation (in this case, cost minimisation) process.

24likewise adds to the model compared to Case 2. Case 4 (adding competition variables, but not
the freight interaction term) to Case 2 also adds to the model (at the 5% level but not at the
1% level). Finally, Case 5, which includes all innovations together, is clearly preferred to allof the other models based on likelihood ratio tests (at the 1% level in all cases except thecomparison against model 3, where Case 5 is preferred at the 5% level). Case 5 is therefore
preferred from a statistical and a priori perspective. It is perhaps the competition variables
where there is some doubt – these variables are individually statistically insignificant, though
jointly significant (at least at the 5% level).
[Table 2 here]
Based on the preferred model (Case 5), our results are as follows. First, the effect ofvertical separation on costs (compared to vertical integration, the omitted dummy variable) at
the sample mean is not significantly different from zero (the coefficient on (DVS) is 0.0042
and is not statistically significant). However, the interaction term of vertical separation andtrain density (VDVS) is statistically significant at the 1% level, which means that the effect of
separation varies with train density. For average train density levels9, vertical separation
therefore has little effect. Below that level, vertical separation reduces costs and above thatlevel, vertical separation increases costs. This finding is in line with that of Mizutani andUranishi (2013), though vertical separation starts to raise cost at lower density levels than in

9More precisely, the break-even point is at 0.99 times the sample mean.
25

the latter paper (where vertical separation did not start to raise costs until density levels
reached around 1.5-1.9 times the sample mean). It could be that the addition of Britain, avertically-separated railway where costs have increased very sharply, has led to this change inthe break-even point.
The finding that vertical separation raises costs at high train density levels is intuitivein that the coordination problems associated with vertical separation might be expected to be
more severe when there are high levels of traffic relative to the size of the network. It may beless clear why vertical separation reduces costs on more lightly used networks, given that wehave sought to account separately for the impact of competition. We speculate that thisfinding may result from the increased cost and public subsidy transparency brought about by
separation.
Second, the effect of the holding company model is to reduce costs by around 5% at
the sample mean (compared to vertical integration, the omitted dummy). This effect isstatistically significant at the 10% level (but not at the 5% level). The interaction term ofholding company and train density (VDHC) is also not statistically significant. Thus, overall,
we conclude that the holding company model has a small impact on costs, though at themargins of statistical significance; and this effect does not very with train density. The cost
reduction could result from increased transparency resulting from the internal separation,whilst any loss of coordination benefits is avoided (though it should be recognised that in26

practice the degree of coordination within the holding model varies considerably from country
to country and that is has not yet been possible to include this factor in our analysis).
Third, the interaction term of vertical separation and proportion of freight revenues(RDVS) is positive and statistically significant at the 1% level, indicating that where there is ahigher proportion of freight revenues on the network, vertical separation tends to increase
costs. Thus, for a given level of train density, it seems that freight traffic causes morecoordination problems in a separated environment than passenger traffic. This finding appears
to be intuitive, and could result from the fact that typically passenger services on a route areprovided by a single operator, whereas freight may involve multiple operators. Further, freight
services are not set by a rigid timetable but vary from day to day. It could also reflect theincreased problems of handling mixed traffic.
Fourth, horizontal separation reduces costs. The effect of horizontal separation is to
reduce costs, other things equal, by 24%10. This effect is statistically significant at the 1%
level. An explanation might be that in a number of cases cost reductions took place because
freight divisions were sold to new owners rather than as a direct consequence of horizontal
separation. Another explanation is that there could be diseconomies of scope between
passenger and freight services, as Kim (1987) finds.
Last, the variables representing the introduction of freight and passenger competition

10

The effect is computed as exp (-0.2719) -1.

27

do not have any statistically significant impact on costs. This finding is surprising, though it
might reflect the problem mentioned earlier of specifying appropriate competition measuresand it may be that the impacts of competition are in part being picked up by other variables
because of this problem.
It should be noted that the above findings are robust to alternative model
specifications. In particular, the single output hedonic model (see Mizutani and Uranishi,2013), which includes total train-km as the single output variable, but adds in hedonic
variables capturing passenger revenue share, passenger loads, average trip length, and thenumber of freight cars per train, produces very similar results. Further, to guard against thedanger that our results are picking up differences between non-EU and EU railways, rather
than industry structure effects, we tested the model without Japan, South Korea and Turkey,
and found the results to be very similar.
Returning to the question of which institutional form is preferred, on cost grounds, it
is clear first of all that the holding company model only has a marginal (and weakly
significant) cost advantage relative to vertical integration. On the other hand, when comparing
vertical separation and vertical integration, it is clear from the results that the impact depends
on how intensely the network is used (as Mizutani and Uranishi (2013) find) and also howmuch freight is running on the network. Taking account solely of the former effect (i.e. (+VS1VS2lnV) DVS in Equation (2)), the train density at the break-even point is 62.72 (or 0.99

28

times the sample mean train density), which is lower than found by Mizutani and Uranishi(2013) as noted earlier. Other things equal, when the train density is above this level, verticalseparation starts to increase costs. We note that for most of the railways in the sample the costdifference between vertical separation and the holding company model is statisticallysignificant.
Many railway networks are included in this latter category, for example those ofBelgium, Switzerland (both BLS and SBB CFF FFS), Germany, Great Britain, Japan (except
JR Hokkaido), South Korea, Netherlands and so on. However, the overall effect on costs ofvertical separation also depends on the amount of freight running on the network, withincreased amounts of freight leading to higher costs under vertical separation. Countries witha higher than average value for the freight revenue proportion include, for example, Germany,
Austria, Czech Republic, Poland, and Hungary.
Recall that our objective in this paper is to consider the impact of the European
Commission’s policy with respect to reforming Europe’s railways. We have noted theCommission’s preference for full vertical separation, over vertical integration and alternativemodels such as the holding company model. In Table 3 we therefore use our model tocompute the cost of imposing vertical separation across the EU (i.e. for those countries thatare not already vertically separated). This calculation therefore includes imposing verticalseparation on countries that have gone part way to reforming their railways through29

implementing the holding company model. The results show that the cost of such a policy
would be around 6 billion euro/ year at 2010 traffic density levels (see Table 3). Further,bearing in mind the Commission’s aims for future traffic growth as stated in the 2011
Transport White Paper, we also show the cost of imposing vertical separation assuming thattrain density levels increase by 10%, 20% and 50% respectively. Since the model shows thecost of separation increasing with train density levels, the cost of vertical separation at thesehigher density levels is correspondingly higher, at nearly 8 billion, 10 billion and 15 billion
euro respectively on a year basis. Thus, imposing vertical separation across all railways in
Europe is not an appropriate policy when viewed purely from a cost perspective (though there
could, potentially be other benefits of separation).
[Table 3 here]
5.0 Conclusion
The main contributions of this paper are as follows:
1. Our paper is the first econometric study in an established literature to compare theeffects of the holding company model as well full, legal vertical separation andvertical integration on costs, using a sample of European and East Asian railways. The
previous literature has focused on only the latter two forms. The choice between theholding company model and vertical separation lies at the heart of a major policy
debate within Europe on how best to promote within-mode competition on rail30

networks, whilst minimising system costs. We find that the holding company model
does reduce costs compared to vertical integration but this effect is small (around 5%)
and this finding is statistically significant only at the 10% level (but not at the 5%
level). The effects of this model also do not change appreciably as train density on the
network changes.
2. On the other hand we find that the effects of full, legal vertical separation depends on
the intensity of usage of the network with vertical separation increasing costs (relative
to vertical integration) on intensely used networks and reducing them on lightly used
networks. This latter finding is intuitive in that the coordination problems associatedwith vertical separation might be expected to be more severe when there are highlevels of traffic relative to the size of the network. This finding is in line with that in
Mizutani and Uranishi (2013), directionally, but importantly the train density
break-even point is lower in our study. Thus, other things equal, our model predicts
that vertical separation will increase costs for more railways than in Mizutani andUranishi (2013); see also point 4 below.
3. Second, in this paper we further develop the ideas in Mizutani and Uranishi (2013) bytesting whether the type of traffic running on the network, as well as the intensity of its
use overall, impacts on the cost effects of different railway structures. We find that that
where there is a higher proportion of freight on the network, vertical separation tends
31to increase costs. The finding that freight traffic causes more coordination problems ina separated environment than passenger traffic seems intuitive given that freight
services are not set by a rigid timetable and also may involve several different
operators. It could also partly reflect the challenges raised by managing mixed traffic.
4. The paper estimates the EU-wide cost implications of enforcing full, legal verticalseparation across the EU (the policy preference expressed by the European
Commission). Based on our model, the cost of imposing vertical separation, where it
is not already in place, would increase EU-wide rail costs by around 6 billion Eurosper year; with this cost likely to be higher in future years if the Commission’s
ambitious growth targets for rail are achieved. The clear policy conclusion from thiswork is that a one-size fits all policy is not appropriate. Our research suggests that, atleast on cost grounds, countries should be free to choose between vertical integration,
the holding company or vertical separation.
5. It is important to note that the model and data used to derive the above results havebeen developed in a number of important ways. The paper is the first to include
Britain and updates the previous literature with data extending to 2010. Both these
extensions are important. Britain was one of the pioneers in Europe (along with
Sweden) of the vertically-separated model and its inclusion thus enhances ourunderstanding of the impact of this model on costs. There have also been a number of32

reforms in recent years, and it is important to study those effects. The paper alsoenhances the modelling of market opening by considering whether actual entry infreight has occurred (rather than potentially entry as in previous studies) anddistinguishing between degrees of entry in passenger, given the vastly different extents
of market entry in the sample (previous studies have treated passenger competition asa binary variable). That said, in our estimations we were unable to find strong
evidence that competition has any cost reducing effects.
In the 2013 Fourth Railway Package proposals the European Commission articulated its
preference for the Swedish, full legal separation model as the best means of guaranteeing fair
access to the network for new entrants. However, under pressure from some European
countries, it stopped short of requiring all railways to implement the Swedish model.
Potentially the cost effects of vertical separation, compared to the other structural forms maychange in future as the market develops. On the one hand, our model suggests that the costs ofimplementing vertical separation will increase in future as traffic growth leads to networks
being more intensively used. On the other hand, as competitive entry expands across the EU,
as envisaged by the 4th Railway package, the power of the holding company model – based ona dominant operator, combined in the same holding company as the infrastructure company –loses some of its appeal, as new entrants take a much more significant market share. It
remains to be seen how the European Commission’s policy will develop over time in response33

to market developments.
We consider that new work on the dataset would be useful (to all researchers in this area),in particular in obtaining more comparable measures of capital and capital costs. It would also
be interesting to explore (either statistically or via case studies) the relationship between costs,
competition, railway structure and economic regulation in future work, as well as considering
different types of holding company arrangement, as no two counties are the same in thatregard.
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Mizutani, F. and S. Uranishi (2013): Does vertical separation reduce cost? An empiricalanalysis of the rail industry in European and east Asian OECD countries, Journal ofRegulatory Economics, 43 (1), 31-59.
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37

Table 1 Structural Types and Competition from 1994 to 2011
Country Network
Austria (OBB)
Belgium(SNCB/NMBS)
Bulgaria (BDZ)
Switzerland (SBB
CFF FFS)
Switzerland (BLS)
Czech Rep. (CD)Germany (DBAG)
Denmark (DSB)
Spain (RENFE)
Finland (VR)France (SNCF)
Great Britain(TOC)
Greece (OSE)
Hungary(GySEV/ROEE)
Hungary (MAV)
Ireland (CIE)
Italy (FS)Japan (JRHokkaido)
Japan (JR East)
Japan (JR Central)
Japan (JR West)Japan (JR Shikoku)
Japan (JR Kyushu)
South Korea(KORAIL)
Latvia (LDz)
Luxembourg (CFL)
Netherlands (NS)
Norway (NSB)
Poland (PKP)
Portugal (CP)Sweden (SJ)
Slovakia (ZSSK)
Turkey (TCDD)

Full
Integration- 2004- 2004Structural Types
Holding
VerticalCompany
Separation2005 2005 -Horizontal
Separation-

Competition
Passenger
Freight
Entry
Entry
1999 2006 --2001- 20082009 -

2001 ---

2007 2004 -- 2011- 2002- 1999- 1997- 2004- 1994- 1996- 19942000 -

2003 1998 2005 1995 1997 1994 -2001 1996 -

2000 2003 1996 -2004 1995 1994 1999 20072006 1994 -- 20062010 ----

1994 -

2007 2009
-

-

-

-

2006 -- 2006
1994 - 2000
1987 -

2007 2001 --2008 1987 -2001 -

2004 2002 -1987 1987 1987 1987 1987 1994 ---1987 1987 1987 1987 1987 ---- 2006
1994 - 1994

2007 1995 2001
2001 -

2002 -

2001 -

1999 -

2007 2007 1998 -1997 1997 1988 2002 -2002 - 2009
2002 2006 -2005 2008 1999 1990 -2007 2003 1996 2004 -- 1996- 2000- 1996- 2001
1994 -

38

Table 2 Full Econometric Estimation Results
Parameters
QP
QF
wL
wE
wM
wK
N
T
QP QP
QF QF
NN
wL wL
wL wE
wL wM
wL wK
wE wE
wE wM
wE wK
wM wM
wM wK
wK wK
QP QF
QP wL
QP wE
QP wM
QP wK
QP N
QP T

Case 10.1345***(0.0132)
0.3717***(0.0235)
0.3327***(0.0054)0.0383***(0.0035)
0.3108***(0.0069)
0.3183***(0.0050)
0.4786***(0.0278)-0.0748**(0.0299)0.0479***(0.0158)-0.0293(0.0189)-0.3862***(0.0587)
0.1599***(0.0076)-0.0041(0.0034)-0.0537***(0.0052)-0.1021***(0.0049)0.0479***(0.0031)-0.0131***(0.0032)-0.0307***(0.0027)0.1057***(0.0065)-0.0389***(0.0041)0.1716***(0.0048)-0.0279*(0.0156)
0.0391***(0.0044)0.0112***(0.0028)0.0056(0.0051)-0.0560***(0.0040)-0.0072(0.0217)-0.0097

Case 20.1263***(0.0139)0.3708***(0.0236)
0.3324***(0.0054)0.0385***(0.0035)
0.3101***(0.0070)0.3190***(0.0050)
0.4927***(0.0287)-0.0539*(0.0313)0.0546***(0.0169)-0.0252(0.0188)-0.3625***(0.0602)
0.1596***(0.0076)-0.0039(0.0034)-0.0534***(0.0052)-0.1023***(0.0049)0.0481***(0.0031)-0.0132***(0.0033)-0.0310***(0.0027)0.1052***(0.0067)-0.0387***(0.0042)0.1720***(0.0048)-0.0298*(0.0155)
0.0391***(0.0044)0.0109***(0.0029)0.0070(0.0052)-0.0570***(0.0041)-0.0139(0.0225)-0.0099
39

Case 30.1227***(0.0139)0.3629***(0.0250)
0.3323***(0.0054)0.0380***(0.0033)
0.3112***(0.0069)
0.3185***(0.0050)
0.5092***(0.0295)-0.0290(0.0322)0.0504***(0.0169)-0.0217(0.0189)-0.3214***(0.0617)0.1579***(0.0077)-0.0034(0.0033)-0.0537***(0.0052)-0.1007***(0.0049)0.0473***(0.0030)-0.0128***(0.0031)-0.0311***(0.0026)
0.1048***(0.0066)-0.0383***(0.0042)0.1702***(0.0048)-0.0170(0.0159)
0.0382***(0.0044)0.0119***(0.0027)0.0057(0.0051)-0.0558***(0.0040)-0.0217(0.0226)-0.0047

Case 40.1317***(0.0146)0.3648***(0.0243)
0.3321***(0.0054)0.0384***(0.0034)
0.3104***(0.0070)0.3192***(0.0050)0.4949***(0.0288)-0.0593*(0.0315)
0.0541***(0.0169)-0.0290(0.0190)-0.3743***(0.0604)
0.1594***(0.0077)-0.0037(0.0034)-0.0538***(0.0052)-0.1019***(0.0050)0.0478***(0.0030)-0.0133***(0.0032)-0.0308***(0.0027)0.1056***(0.0067)-0.0385***(0.0042)0.1713***(0.0048)-0.0314**(0.0156)
0.0389***(0.0044)0.0111***(0.0028)0.0067(0.0052)-0.0567***(0.0041)-0.0111(0.0225)-0.0099

Case 50.1281***(0.0146)
0.3574***(0.0258)
0.3320***(0.0055)
0.0380***(0.0032)
0.3113***(0.0069)
0.3187***(0.0050)
0.5097***(0.0295)-0.0345(0.0324)0.0503***(0.0169)-0.0249(0.0191)-0.3332***(0.0619)0.1579***(0.0077)-0.0033(0.0033)-0.0540***(0.0053)-0.1006***(0.0050)0.0471***(0.0029)-0.0129***(0.0030)-0.0310***(0.0026)
0.1051***(0.0066)-0.0382***(0.0042)0.1697***(0.0048)-0.0190(0.0160)
0.0380***(0.0044)0.0119***(0.0027)0.0057(0.0051)-0.0557***(0.0040)-0.0189(0.0226)-0.0050(0.0210)0.0351***(0.0056)0.0015(0.0035)
0.0369***(0.0068)-0.0735***(0.0054)0.1974***(0.0327)
0.0763***(0.0186)-0.0975***(0.0086)-0.0190***(0.0046)-0.0155***(0.0051)
0.0054*(0.0028)-0.0280***(0.0098)-0.0138**(0.0056)0.1410***(0.0078)0.0275***(0.0043)-0.2176***(0.0348)-0.0032(0.0082)-0.0536**(0.0239)
0.2366***(0.0356)(0.0209)
0.0353***(0.0057)0.0014(0.0035)
0.0371***(0.0070)-0.0738***(0.0054)
0.1921***(0.0324)
0.0711***(0.0185)-0.0983***(0.0086)-0.0190***(0.0046)-0.0152***(0.0052)
0.0057**(0.0029)-0.0287***(0.0100)-0.0145**(0.0057)
0.1422***(0.0079)
0.0278***(0.0043)-0.1923***(0.0368)-0.0005(0.0082)-0.0585**(0.0239)0.2578***(0.0371)

RDVS

-

-

DHC

-

VDHC

-

RDHC

-

-

DHS

-0.2693***(0.0241)-0.2717***(0.0238)(0.0209)
0.0350***(0.0057)0.0014(0.0033)
0.0377***(0.0069)-0.0741***(0.0054)0.1693***(0.0331)0.0595***(0.0188)-0.0981***(0.0087)-0.0190***(0.0046)-0.0159***(0.0049)
0.0050*(0.0027)-0.0273***(0.0099)-0.0142**(0.0057)
0.1412***(0.0079)
0.0281***(0.0043)-0.1702***(0.0375)
0.0049(0.0083)
0.0171(0.0328)0.3905***(0.0528)0.1261***(0.0363)-0.0413(0.0269)0.0405(0.0540)-0.0113(0.0421)-0.2636***(0.0244)

CMP

-

-

-

DCF

-

-

-

8.8617***(0.0156)
107.7420.979
481

8.8640***(0.0168)
112.695
0.979
481

8.8660***(0.0167)
119.846
0.980
481

QF wL
QF wE
QF wM
QF wK
QF N
QF T
wL N
wL T
wE N
wE T
wM N
wM T
wK N
wK T
NT
TT
DVS
VDVS

C0
Log of likelihood
Pseudo R2
Number of observations-0.0388(0.0266)
0.0586(0.0457)40(0.0209)
0.0351***(0.0057)0.0016(0.0035)
0.0367***(0.0070)-0.0734***(0.0054)0.1993***(0.0326)
0.0727***(0.0185)-0.0984***(0.0086)-0.0188***(0.0046)-0.0156***(0.0050)
0.0055**(0.0028)-0.0275***(0.0100)-0.0145**(0.0057)
0.1416***(0.0079)
0.0277***(0.0043)-0.1982***(0.0369)-0.0015(0.0082)-0.0667**(0.0280)0.2485***(0.0396)-0.0507*(0.0301)
0.0594(0.0461)-0.2796***(0.0253)-0.0127(0.0108)
0.0460*(0.0236)8.8640***(0.0170)
117.0910.980
481(0.0209)
0.0348***(0.0057)0.0016(0.0033)
0.0373***(0.0069)-0.0737***(0.0054)0.1761***(0.0333)
0.0609***(0.0189)-0.0982***(0.0087)-0.0189***(0.0046)-0.0161***(0.0048)0.0049*(0.0026)-0.0267***(0.0100)-0.0141**(0.0057)0.1409***(0.0079)
0.0280***(0.0043)-0.1752***(0.0377)
0.0039(0.0084)0.0042(0.0352)
0.3758***(0.0546)
0.1222***(0.0368)-0.0546*(0.0302)
0.0387(0.0541)-0.0133(0.0424)-0.2719***(0.0259)-0.0081(0.0110)0.0388(0.0236)8.8653***(0.0169)
123.194
0.980
481

Table 3 Cost Changes Relative to the Status Quo of Imposing Vertical Separation
on All EU-Railways
Billions of Euros (2005 constantprices)Yearly cost of imposing verticalseparation across EU (for thosecountries not already separated)

Current level
5.8

Train density level
+10%
+20%

+50%

7.8

14.5

9.6

∆C of verticalseparation c.f.
alternatives

Vertical integration
is desirable
Verticalseparation isdesirable

Train density

Break-even point

Figure 1: The cost difference between vertical separation and vertical integration and its relationship withtrain density[2014.11.28 1184]

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