estimating the cost of fixed call termination on bezeq’s ...in respect of other data traffic the...

Confidential November 2013 1

Estimating the cost of fixed call termination

on Bezeq’s network

A REPORT ON THE CONSULTATION

This paper responds to some of the stakeholder comments on the MOC’s consultation on fixed

termination rates in Israel and the accompanying consultant report. Specifically, it focuses on the

comments made by PwC in its report prepared for Bezeq and the reports made by Aetha in its

report prepared for Cellcom, along with the related parts of the main Bezeq and Cellcom

submissions, and TASC’s report prepared for HOT. Comments by Partner regarding the cost

of capital and the modelling methodology are also briefly considered. The paper further covers

responses received as part of the second hearing and further submissions on the WACC.

The MOC consultation on fixed termination rates (FTR) was accompanied by a

report which estimated the cost of the fixed call termination service provided

over Bezeq’s network. This estimation was based on a bottom-up (BU) LRIC

model.

In this paper we respond to the comments made by parties responding to the

consultation which relate to the BU-LRIC model. These are as set out in reports

prepared for Bezeq by PwC, for Cellcom by Aetha Consulting and for HOT by

TASC.1 In addition, we also take account of a report prepared by Cellcom which

examines the optimal network design for a new national fixed line operator in

Israel. This report then describes the changes to the model made in response to

the stakeholder comments. Where appropriate, we provide an indication of the

impact of these changes on the cost of fixed termination.2

In addition, in this paper we provide a brief response on PwC’s presentation of

August 26 2013 at the MOC’s second hearing and additional submissions

received in relation to the WACC.

Respondents’ submissions also cover issues not directly related to the model

itself, most notably around the transparency of the consultation and the level of

redactions included in the published report / model. These points will be

covered by the response produced by MOC and therefore are not further

discussed here.

1 Where highlighted in this paper we have also taken into account parts of Bezeq’s own response.

2 The impact is individually measured, i.e. the model results are compared with only one change

applied at a time. The combined impact of all changes on the cost of fixed termination differs from

the sum of individual impacts resulting from each change. This is because a number of changes

applied in the model are interdependent.

2 November 2013 Confidential

Estimating the cost of fixed call termination on

Bezeq’s network

Implementing the changes discussed in this report relating to the initial responses

results in a cost of fixed termination for 2013 of 0.98 Agorot per minute (in 2012

real terms), approximately 5.5% lower than the rate initially suggested in the

consultation.

1. Response to PwC report prepared for Bezeq

This section addresses the initial report PwC prepared for Bezeq. PwC’s later

presentation is briefly discussed in Section 2 of this paper.

The PwC report prepared for Bezeq raised a number of issues with the BU-LRIC

model which it felt resulted in the model underestimating the cost of fixed

termination services, along with other comments about the presentation of the

model in the consultation process. Its comments were summarised at pages 11

and 12 of its report as follows:

1. While [as previously discussed], the methodology indicates that broadband and leased lines

have been included in the modelling exercise, it is not possible to corroborate this as the piece of

the model that has been provided to Bezeq does not include any information on data volumes or

leased lines;

2. because the dimensioning part of the model was not made available it is not possible to

establish whether the dimensioning rules that were used in the model are appropriate;

3. the mark-ups for the estimation of operating and common costs have been based on

benchmarks from Nordic countries. These result in a significant underestimate of costs compared

to Bezeq’s actual cost levels;

4. it has not been possible to review the basis of allocation of costs to voice services as only hard

coded percentages rather than their derivation has been provided [As will be discussed later in

this document], these allocations do not seem to be consistent with actual engineering causality

and planning rules;

5. the annualisation of capital investments mechanism does not take into account the cost of

capital incurred between the moment when an asset is purchased to the moment when it becomes

operational; and

6. the suggested methodology for the estimation of the cost of capital, while generally correct,

requires the reassessment of the way in which some of the parameters were determined, namely

the risk free rate, the beta and the long term inflation.

In this section we respond to points 3, 4 (focusing on the consistency of the cost

allocations with actual engineering causality and planning rules) and 5. Points 1

and 2 relate to the transparency of the consultation and as such are not dealt with

here. Point 6 refers to the cost of capital and is discussed in section 5 of this

report, together with comments from TASC and Partner.



Bezeq’s network

Following the order of the PwC report, we consider firstly the allocations derived

in the model and then respond to the points made by PwC in relation to

operating expenses and the annualisation of capital investments.

Cost allocation between voice and non-voice services

A number of elements in the modelled network are used to provide voice and

non-voice (broadband and data) services. In a LRAIC+ model such as that built

for determining appropriate FTRs in Israel, the costs of these shared elements

must therefore be allocated between voice and non-voice services.

In its report, PwC has proposed a series of alternative allocations to those

derived in the model. Its proposals, in terms of the proportion of costs of

particular components which should be allocated to voice services, were

summarised in Table 10 of its report, which is reproduced below.

Table 1. PwC proposed allocation of costs to voice service

Item Original allocation to

voice traffic

Bezeq / PwC proposal

MSAN […] […]

Aggregation switch […] […]

Edge routers […] […]

Core routers […] […]

Common site costs:

DSLAM / MSAN

[…] […]

Common site costs:

Edge routers

[…] […]

Common site costs:

Core routers

[…] […]

Trench/cable MSAN to

Edge router

[…] […]

Trench/cable Edge

router to Core router-

infra

[…] […]

Source: Reproduction of Table 10 from PwC report

Below, we review PwC’s proposals for each item. In so doing, we note that

Bezeq’s main response includes its own estimates of appropriate cost allocations,



Bezeq’s network

which in many places differ from those presented by PwC. Whilst we

concentrate on the PwC estimates (and not the Bezeq estimates) in this paper, we

believe this highlights the potential subjectivity that surrounds some aspects of

cost allocation and indeed, reduces the reliance that can be placed on any one

alternative estimate.

Overall, for the reasons set out below, we do not believe that the comments of

PwC merit changing the allocations in line with their proposals. Rather we

believe that the initial allocations included in the model reasonably reflect the

principles of cost causality and objectivity.

However, some additional information on voice and data traffic for 2011, 2012

and 2013 (not yet available during the initial development phase of the model)

was now submitted by Bezeq/PwC. This has been taken into account as

described in the following section for adjusting the demand considered in the

model up to 2012 and the forecasts for years after 2012.

Revised voice and data traffic

As part of its response on the allocation of costs of aggregation switches to voice

and data PwC/Bezeq also submitted more recent information about the ISP and

other data traffic. It submits that the traffic at the aggregation switch level is

[…]Gbps for ISP data traffic and […]Gbps for other data traffic.

These figures are considerably higher than the figures used in the model. In

respect of ISP data traffic, the figure in the model is […]Gbps in 2012 and

[…]Gbps in 2013. There are a number of reasons why this figure may be lower

than the actual capacity in Bezeq's network. In particular:

the figure in Bezeq's network presumably reflects the current situation

so would be more comparable to the 2013 figure from the model;

the capacity estimate in the model is based on usage per subscriber

information provided by Bezeq in September 2011. While the model

assumes that usage per subscriber increases over time, it appears that

usage levels in Israel may have increased more rapidly than estimated.

a further factor may be that the estimate in the model does not reflect

the mix of business and residential broadband customers and its impact

on the average capacity per subscriber (such breakdown and

corresponding capacity information had not been provided by Bezeq).

Thus, for the reasons outlined above, we have updated the model to correspond

to Bezeq’s information of ISP data traffic. This implies an average capacity per

subscriber of […]kbps. This appears reasonable in comparison to models in

other jurisdictions.

In respect of other data traffic the model estimates leased line traffic based on

information provided by Bezeq on the numbers of leased lines by type



Bezeq’s network

(unfortunately, Bezeq was unable to provide information on the average capacity

of leased lines). The model assumed that 25% of leased lines use the NGN and

that these leased lines connect at the level of aggregation switches (and therefore

do not use the MSAN). Based on our estimates of capacity per line, this results

in approximately […] Gbps of other data traffic at the aggregation switches. The

percentage of leased lines using the NGN will though be increased to ensure

consistency with Bezeq’s information of […]Gbps total other data traffic.

As part of this update, we also consider information on voice traffic that Bezeq

submitted in its own report. Bezeq suggested that the significant decrease in

voice traffic in 2013 will continue in years after 2013 suggesting significantly

smaller amounts of traffic in years after 2013 compared to the forecasts

previously used in the model. We have updated the model to take account of the

most recent data available including the reduction in traffic volumes in 2013.

However, we do not believe that a single year of significant reductions in traffic

volumes can be used as a basis for a long term trend. We therefore continue to

apply a trend based on the development of traffic volumes since 2007. 3

The adjustment in ISP and other data traffic results in a decrease of fixed

termination costs of approximately 1.5%.4 The update of voice traffic results in

an increase of fixed termination costs of approximately 10%.

MSAN cost allocation

PwC proposes that 25% of the costs of voice cards and voice components of

combo cards are related to traffic. Consequently, by estimating the number of

ports in a typical MSAN which are used for voice, PwC estimates the proportion

of costs which should be allocated to voice traffic services.5

This contrasts with the model approach which split MSAN costs into two

components: line cards and chassis (including upstream cards). Line card costs

are driven by the number of lines and were therefore allocated in the model in

entirety to either telephony or broadband subscription services.

With regards to the chassis, in some models the upstream cards are included in

the chassis cost and in such cases one can argue that all chassis costs are also

driven entirely by the number of subscribers and therefore that no chassis costs

3 Bezeq has also claimed that the model does not take into account VOB traffic. We believe this claim

is invalid since a) actual Bezeq voice traffic has been used and b) VOB phone connections are not

physical network endpoints and corresponding network traffic is already included as part of

broadband subscriber traffic at the same best effort quality of service.

4 The draft version of this response previously submitted by the Ministry to respondents incorrectly

referred to a decrease of 3%.

5 In an average MSAN, Bezeq estimates that […] out of […] cards are POTS cards. Multiplying

[…]/[…]x 25% gives […]% as the percentage of cost which should be allocated to voice



Bezeq’s network

should be allocated to voice traffic. This is because an increase in the number of

subscribers would increase the number of line cards and hence the number of

chassis’ needed; an increase in traffic would be extremely unlikely to do so – in

no circumstances would an increase in the calling rate increase the number of

chassis’ required. We are aware, for example, of two BU-LRIC models which

take this approach.

However, most of the functionality in the chassis is related to call and data

processing and transmission for all subscribers attached and it could therefore be

considered appropriate to allocate some chassis costs to voice and data traffic.

But this approach needs to be taken with caution because it may be inconsistent

with the principles of cost causation. Taking these two approaches into account

and given the fact that the information provided by Bezeq separately identifies

the cost of the upstream cards the original model adopted an intermediate

approach allocating 75% of chassis costs to lines and 25% to traffic (with that

25% then further split between voice and non-voice traffic). This reflected the

importance of line card costs and the fact that there are no chassis costs, aside

from the uplink cards, which are clearly related to calls.

Final view

We believe that PwC’s argument that some line card costs should be allocated to

voice traffic services confuses the consumption of services with the costing of

services. For example, a call involves the use of the access network (the line to

the subscriber and the line card) and the use of the core network (MSANs,

aggregation switches, routers and transmission). However, the access network

elements have no impact on the cost of a call.

This is because in a LRIC model it is important to consider how costs change

with demand. Holding subscribers constant and increasing the calling rate will

have no impact on the number of MSAN line cards (and access lines) required

and hence no impact on line card costs. This is the case even though some of

the functionality of the line card is only required when a call is actually made. In

contrast, if the volume of calls carried over the network is held constant but the

number of customers increases, then additional line cards (and also additional

chassis’) would be required.

We therefore conclude that all POTS line card costs should be allocated to the

access network. This is consistent with how line cards are treated in all other BU-

LRIC models with which we are familiar and indeed, we note that such allocation

has tended to be accepted by operators.

We have also reviewed a considerable number of top-down models. In all cases

the whole of the line card cost was allocated to the access network. We are aware

of only one case (many years ago) where an operator argued for an alternative

approach. The regulator in this case correctly ruled that all line cards must be

allocated to the access network.



Bezeq’s network

Finally, we do not accept the figures shown in Table 10 of Bezeq’s response.

According to the model voice accounts for approximately […]% of traffic related

costs. However, for MSANs this percentage is increased because the allocation

takes account of past build which took place at a time in which the percentage of

voice traffic was higher than is currently the case. Thus, in 2012, as can be

calculated from the information provided to Bezeq, the percentage of traffic

related costs allocated to voice is over […]%. However, as stated:

all line card costs are allocated to access; and

only 25% of the chassis cost is allocated to traffic.

Hence, the overall allocation of MSAN costs to voice is approximately 2%.

Indeed, this is in line with the initial cost allocation as quoted by Bezeq in its

(Hebrew) submission to the MoC.

Rather than understating the costs attributable to voice, we believe the approach

set out above gives a conservative estimate of MSAN costs which should be

allocated to voice. That is, the methodology currently used in the model may be

more likely to overstate the true allocation of total MSAN costs to voice than to

understate it. This is because it is possible to reallocate traffic capacity at the

MSAN level between voice and broadband.

In light of the above, the allocation assumptions used in the final version of the

model are as follows:

as before, all line card costs are allocated to access;

the cost of the chassis uplink cards has now been separately identified

and allocated to voice and broadband;6 other chassis costs have been

allocated on a pro-rata basis to lines and traffic; and

as before, the allocation between voice traffic and broadband reflects

the actual estimated traffic mix in the year in question.

The change in the treatment of chassis uplink cards increases the cost of fixed

termination by less than 0.5%.

Aggregation switch cost allocation

The allocation of aggregation switch costs between voice and broadband was

determined on the basis of the respective volumes of dimensioned voice and

broadband traffic.

6 The cost of uplink cards have previously been part of total chassis costs and allocated on a pro rata

basis to lines and traffic. These costs are now identified separately and are fully allocated on the

basis of voice and data traffic.



Bezeq’s network

Bezeq / PwC argue that the allocation in the model is not consistent with the

traffic mix in its own network. Instead, it looks at the mix of traffic generated at

the MSAN layer for different services and adjusts this to take account of the fact

that approximately 25% of calls are on-net and therefore use the aggregation

switch layer twice. Based on its analysis of traffic at the MSAN layer it estimates

the proportion of voice traffic to be […]

%.

Final view

We believe that Bezeq / PwC’s proposed allocation should not be used in the

model. This is for a number of reasons.

Firstly, PwC’s response uses the term ‘voice traffic generated at the MSAN

level’. We believe the meaning of the word ‘generated’ is ambiguous. On

one hand it could mean traffic originated at the MSAN level. On the other

hand it could mean total (originated and terminated traffic) at the MSAN

level. In the former case, we accept that on-net traffic should be doubled at

the aggregation switch layer. In the latter case doubling of on-net traffic at

the aggregation switch layer would be incorrect. This is because on-net

traffic would already be counted twice – once on the origination leg and

once on the termination leg. We note that later in its response PwC suggests

that this is incoming traffic.

Secondly, voice traffic needs to be carried in real time. In order to take

account of this fact the bottom-up model applies an Erlang formula to

estimate the actual capacity which needs to be provided for voice. The

percentage mark-up (actual capacity / (Erlangs x bandwidth)-1) will vary by

network element since the Erlang formula is non-linear. The mark-up will

be highest at the MSAN level, where the amount of voice traffic carried per

MSAN is very low. The amount of voice traffic per unit of equipment will

be higher at the first aggregation switch level and higher still at the second

aggregation switch level and hence lead to lower mark-ups at each layer

further up in the network hierarchy. Since broadband is carried on a best

effort basis a similar adjustment is not necessary. As a result the percentage

allocated to voice traffic will vary by network element. The considerations

outlined above are not covered in PwC’s analysis.

Thirdly, the bottom-up model assumes that the part of other data traffic

which uses the NGN only comes onto the NGN at the aggregation switch

level. Hence, this factor will also mean that the percentage of voice traffic

will be lower at the aggregation switch level than the MSAN level.



Bezeq’s network

Fourthly, given the call minutes using Bezeq’s network, the amount of voice

traffic ‘generated’ at the MSAN level appears somewhat higher than we

would have expected. One possible factor could be that the voice

bandwidth used in the model is different from that used in Bezeq’s network.

As stated in the Consultation Document, the model assumes that the

bandwidth of a voice call is 98.74 kbits, assuming bi-directional capacity.

This assumption is based upon our knowledge of voice bandwidths used by

operators in a number of other jurisdictions, many of which use the same

equipment types as those used in Bezeq’s network. Indeed, we believe that

this is a reasonable, even possibly a conservative assumption, for an efficient

network operator.

Further, we note that PwC’s allocation at the MSAN level is based on the

assumption that a proportion of the line card cost should be allocated to the

core network. As previously discussed we do not consider this to be

appropriate. At the aggregation switch level, PwC argues for an allocation

based on traffic usage. In respect of voice it takes capacity at the MSAN

level and adjusts this for network routings. For reasons previously discussed

we do not believe that this is appropriate.

In light of all of the above points, we believe that the allocation methodology

used in the model is essentially correct. However, we believe it is appropriate to

adjust the allocation approach used in the model so that the cost of aggregation

switches attributed to voice is based on an average of the uplink and downlink

voice traffic.7 This adjustment has been made in the final version of the model

and accounts for an increase in the cost of fixed termination of less than 0.5%.

Edge router cost allocation

The allocation of edge router costs between voice and non-voice (broadband)

services was determined on the basis of the respective volumes of dimensioned

voice and broadband traffic, similar to the approach for aggregation switches.

The allocation differs from other elements because:

voice traffic is greater on a per router basis than at either the MSAN or

aggregation switch layer; and

some traffic is assumed to use aggregation switches and edge routers

but not MSANs.

7 The previous version of the model used only the uplink traffic as a basis for allocating the cost of

aggregation switches.



Bezeq’s network

However, in its paper, PwC states that Bezeq’s network includes separate edge

routers for voice services and data services, and that the allocation should reflect

this fact.

Final view

We do not consider that Bezeq has provided a convincing case for having

separate edge routers for serving voice and broadband traffic. Multi-protocol

Label Switching, which is used at the router level and increasingly at the

aggregation switch level in many networks, allows real time services to be

identified and passed through the network in real time while non-real time

services, such as best-effort broadband, can be delayed. Virtual circuits can

otherwise ensure the separation of services on shared network equipment. The

focus of the current model is on capturing the costs of a reasonably efficient

hypothetical operator, thus reflecting the network an operator would deploy

today. Thus we note that while some networks (and models) do differentiate

between, for example, business and non-business traffic, most bottom-up models

assume that voice and broadband traffic are carried by the same edge routers.

In light of the above we believe that the approach adopted in the model is

essentially reasonable. However, we note that Bezeq’s actual network structure

appears to differ from that in the model (namely with a greater use of core

routers in the network than assumed in the model and a single level of edge

routers). The model now estimates a total number of 6 Core IP routers and 45

Edge routers but no IP distribution routers. As a result, IP Edge link directly to

IP Core routers. The cost of fixed termination increases by less than 0.5% as a

result of that change.

Core router cost allocation

The allocation of core router costs between voice and non-voice (broadband)

services was determined on the basis of the respective volumes of dimensioned

voice and broadband traffic, similar to the approach for aggregation switches and

edge routers. For the reasons set out above in the analysis of aggregation switch

costs, the percentage of core router costs allocated to voice is lower than the

percentage of aggregation switch costs allocated to voice.

In its report, PwC presents Bezeq information on the amount of traffic for which

Bezeq core network routers are dimensioned and argues this should be used as

the allocation basis. It also provides an alternative approach for determining the

appropriate cost allocation based on total incoming traffic during the busy hour

at the MSAN level.



Bezeq’s network

Final view

We do not believe that the allocations presented by Bezeq are likely to be

appropriate and therefore believe that it is reasonable to maintain the allocation

set out in the original model. This is for two reasons.

Firstly, the amount of capacity dimensioned appears extremely high

compared to the actual traffic being carried on Bezeq’s network. Without

prejudice to other concerns, and because no further evidence to demonstrate

that the dimensioned capacity is efficient, given the level of traffic carried on

the network (and expected to be carried on the network over the next few

years), has been supplied by Bezeq, this cannot be accepted.

Secondly, we do not believe that the alternative methodology presented by

Bezeq / PwC is appropriate. As pointed out above, this is because it is not

appropriate to compare traffic at the MSAN level with traffic at other

network levels.

However, we do note that the routings in the model do not appear to be

consistent with Bezeq’s actual network structure and for this reason the

percentage of voice traffic at the core router level is understated in the model to

some degree. This has been updated in the final version of the model and has

resulted in some increase in the percentage of voice traffic at the core router.

The adjustment in the edge and core routers discussed in the previous section

and the routing factors discussed in this section led to a decrease in the cost of

fixed termination of less than 1%.

Common site costs (MSAN, Edge router and Core router)

In principle, site costs at each level of the network are allocated using the same

approach as the equipment costs themselves. Within this, some differences

between the equipment costs and common site cost allocations exist because

information on space, power and air conditioning usage shows that this is not

always proportional to costs. Nevertheless, the allocations of site costs will be

similar to the allocations of equipment costs and this can be seen in the original

model allocations (as set out in Table 10 of the PwC report).

The PwC report follows this approach for MSANs and core routers. For

example, it proposes an allocation of common MSAN site costs to the core

network in the same proportion as the costs of the MSAN equipment itself.

Thus, in keeping with its views on the allocations of costs, the PwC report for

Bezeq argues that the percentage of MSAN site costs allocated to the core

network and hence to voice traffic, is too low.

The Bezeq / PwC allocation of edge router common site costs is driven by

Bezeq’s apparent use of different edge routers for voice and broadband services.

As the physical size of each router type is the same, PwC proposes that common



Bezeq’s network

site costs should be allocated to voice services in direct proportion to the number

of edge routers in Bezeq’s network which are used for voice services.

Final view

We note broad acceptance by Bezeq / PwC of the original approach taken in the

model to allocate common site costs. Whereas the PwC report does present

alternative allocation percentages, these are all driven from their proposed

allocation of the actual equipment costs. For the reasons set out above, we do

not believe that the equipment cost allocations should be changed to reflect

those proposed in the PwC report. We therefore consider that the original model

allocations of common site costs continue to be appropriate subject to those

changes of the allocations outline above.

Trench costs – trench and cable length

Bezeq / PwC have also commented on the allocation of trench costs in the

model. This includes comments on the total trench lengths included in the

model. We therefore respond firstly to the comments on total trench lengths and

then turn to the allocation of trench costs.

As part of the data requests sent to Bezeq by the MOC to support the

development of the original model, Bezeq was asked to provide detailed

information on its trench network. In response, Bezeq provided information on

its total trench and overhead length but did not provide any information on the

respective lengths of its access and core networks.

In coming to a view on trench length, we carried out an analysis of the length of

the access network based on a sample of different areas. It also carried out an

analysis of the trench required to link up aggregation switches, assuming optimal

routing. Finally it estimated the average trench length required to link up

MSANs and also MSANs to aggregation switches based on international

benchmark data for countries of similar size to Israel. Altogether, this yielded

estimated trench length (before sharing) of approximately 15,000 kilometres for

the core network (MSAN upwards) and 30,000 for the access network. The

model then examined the likely degree of sharing between the core and access

networks. The following assumptions were used:

Sharing between old RCU sites and MSAN on the one hand and the

access network on the other of 85%. This reflects that the fact that

most of this area is populated and, further, that even where overhead

cable is used this can be shared;

Sharing between other parts of the core network and the access network

of 40%;

Sharing between different levels of the core network of 25%.



Bezeq’s network

After sharing the estimated distance for the core network is 7,800 kilometres and

that for access 27,491 kilometres. Adding these figures together gives 35,291

kilometres, which is approximately […]% less than the information provided by

Bezeq on the total length of its trench and overhead network.

However, Bezeq has provided information in the PwC report which shows a

significantly different split of trench between the core and access network, and

considerably less shared trench than that assumed in the original model. Bezeq’s

data and the data thus far used in the model is summarised in the table below.

Table 2. Trench assumptions, kilometres

Original model

(accounting for shared

trench)

Bezeq data (PwC report)

(not accounting for

shared trench)

Core 7,800 […]

Access 27,491 […]

Total 35,291 […]

Source: PwC report and MOC BU-LRIC model

Final view

On the face of it, the data provided by Bezeq in the PwC report suggests that

there may be a case for revising the total trench length assumptions in the model

but not its allocation to access or core. This is because:

Bezeq has provided information on the split of trench between its core and

access networks which it was previously unable to provide. It has not

explained why it has now provided information which was previously

unavailable and further the basis on which the figures are calculated.

Secondly, there are some inconsistencies in the table. For example, the core

network provided on overhead before sharing is shown as being […]

kilometres whereas the core network provided on overhead after sharing is

shown as being […] kilometres.

Thirdly, the degree of sharing between the access and core network

estimated by Bezeq is significantly below that seen in other networks and

less than could be expected in an optimal network. Other models assume a



Bezeq’s network

much higher percentage sharing between access and core (50% Denmark8,

41% Sweden9 with a further 5% sharing with utilities in both models). Data

for BT (Ofcom ‘Valuing Copper Access – A Consultation on Principles’ 9

December 2004) shows that almost all of BT’s core network is shared with

its access network (51% duct – access only; 9% duct – core only; 40%

shared core and access). There are in theory two reasons why the degree of

sharing in Israel may differ from that in other markets.

Firstly, the quantity of overhead cable may be much greater and

secondly, the boundary between the core and access network may be

much closer to customer. Whilst the former could reduce the degree of

sharing, the trench and potentially the overhead cables between the old

concentrator buildings and the MSANs could still be shared with the

core network.

The second factor should actually increase the degree of sharing. This

is because most of the distance between old concentrator building and

MSAN is likely to be populated and could therefore be shared with the

access network.

Bezeq has not explained why the very limited degree of sharing in its

network is optimal (and should therefore be replicated in a BU-LRIC model)

and why this differs to what has been seen in other markets. Further, we

note that the data on the quantity of shared trench appears to have been

rounded, whilst actual figures are used for other trench lengths.

Fourthly, although the boundary between the core and access network has

moved closer to the customer, we understand that by far the largest part of

the traditional access network falls between the primary distribution point

and the customer (which remains in the access network) rather than between

concentrator and primary distribution point. This is because there are

relatively few links between the old concentrator site and primary

distribution points (now cabinets) whereas the links between primary

distribution points (cabinets) and the customer must traverse every

populated street including most of the streets between the old concentrator

site and the primary distribution points (cabinets). We therefore believe that

Bezeq data showing more trench in the core network than the access

network is counterintuitive.

8 http://erhvervsstyrelsen.dk/lraic-fastnet-modelarbejde

9 http://www.pts.se/sv/Bransch/Telefoni/SMP---Prisreglering/Kalkylarbete-fasta-

natet/Hybridmodellen

http://erhvervsstyrelsen.dk/lraic-fastnet-modelarbejde

http://www.pts.se/sv/Bransch/Telefoni/SMP---Prisreglering/Kalkylarbete-fasta-natet/Hybridmodellen

http://www.pts.se/sv/Bransch/Telefoni/SMP---Prisreglering/Kalkylarbete-fasta-natet/Hybridmodellen



Bezeq’s network

Finally, we note that Cellcom has provided to the MOC the results of a

study it undertook on the optimal design of a new fixed network in Israel.

This design estimates that the length of trench required (before adjusting for

sharing) to get to within 500 metres of buildings is […] kilometres. This is

significantly lower than the original estimate in the model (approximately

15,000 kilometres before sharing). Although Cellcom has not provided the

detailed calculations underlying its estimate, it has provided a thorough

methodological description and illustrations of its approach. For reasons set

out below, we do not believe it would be appropriate to base the model on

Cellcom’s analysis without further adjustment. Nevertheless, this does

provide some comfort that the model is unlikely to be systematically

understating the quantity of trench required to serve all customers.

In the absence of detailed evidence of the structure of Bezeq’s network (and

without prejudice to other considerations), we do not believe that it would be

appropriate to adjust the amount of core trench figures in the model in the way

as suggested by Bezeq. However, we do recognise the total distance provided by

Bezeq (without taking account of sharing between the core and access network)

of […] km, is lower than the total distance (without taking account of sharing)

considered in the previous version of the model of 44,977 km. We have adjusted

the estimation in the model to take account of this difference.

The revised lengths are outlined in Table 2 below. The impact of changing the

trench length on the cost of fixed termination is a decrease of less than 1%.

Table 3. Trench assumptions, kilometres

Original model

(accounting for

shared trench)

Bezeq data

(PwC report)

(not

accounting for

shared trench)

Revised model

(not

accounting for

shared trench)

Revised model

(accounting for

shared trench)

Core 7,800 […] 11,945 7,487

Access 27,491 […] 28,044 24,534

Total 35,291 […] 39,989 31,894

Source: PwC report and MOC BU-LRIC model



Bezeq’s network

Allocation of trench and cable costs

The model allocates trench and cable costs based on traffic allocations – noting

that these allocations vary between different levels of the network hierarchy.10

In its report for Bezeq, PwC suggests that there is no unique way of allocating

trench and fibre cost, recognising that in reality there is no causal relationship

between fibre pairs and cables onto duct numbers and trench costs.11 However,

it points out that in some cases there is an argument for allocating fibre and

perhaps trench on the basis of the number of fibres used by different services.

Final view

We recognise that Bezeq’s argument has some merit and has indeed reflected this

in its weighting for leased lines not using the NGN. However, it does not believe

that the approach is appropriate for dealing with traffic which shares (or could

share) the same network elements. As such, we do not believe it would be

appropriate to change the allocation approach used in the model. This is for

three reasons:

Firstly, an examination of Bezeq’s response suggests that it does not separate

out voice and broadband traffic, except at the edge router level and possibly

by using different ports at the core router level. As such, it would not be

possible to identify fibres used by different services.

Secondly and more fundamentally, there is no need to differentiate by traffic

streams, although some operators may choose to do so. For example, in the

case of the MSAN layer, different contention ratios in combination with

separate VLANs can be used to ensure service quality; while for other levels

of the network hierarchy MPLS can be used. In addition, the network

modelled in the bottom-up model contains a high level of resilience and

redundancy.

Thirdly, allocating costs on the basis of cable numbers could provide

incentives for operators to configure their networks in a particular way

purely with the intention of increasing the cost of some services and

reducing that of others.

Finally, we are aware of several other bottom-up models allocating transmission

capacity on the basis of traffic rather than cable numbers.

10 In the case of leased lines which are presumed not to use the NGN it has assumed that these should

be weighted by a factor 2 reflecting the fact that they will use smaller transmission systems.

11 This is because the amount of capacity that can be carried on a fibre cable is such that additional

fibres are often not needed.



Bezeq’s network

Core network operating costs included in the model

The model also includes cost estimates for operating and maintaining the

network. Again, this can require an allocation of network costs between the core

network (traffic services) and access network (subscriber related costs).

During the data collection phase for the modelling work Bezeq was asked on a

number of occasions to provide data on operating costs. However, it did not

provide any information on opex/capex ratios by network element or on

overheads. The only information it was able to provide on operating costs was

inconsistent with its own fixed line business financial report and accounts.

As a result of this, operating costs included in the model were based on

international benchmarks. Given the benchmarks available, a 20% opex/capex

ratio was used for most active network elements, along with a 3% uplift for

common costs in the core network and a 25% uplift for interconnection specific

costs.

Other costs such as power and air conditioning running costs were based on

specific international benchmarks.

In its report, PwC has proposed a series of alternative core network operating

cost figures to those used in the model. Its proposals were summarised in Table

11 of its report, which is reproduced below. As can be seen from this, Bezeq /

PwC believe that the core network operating costs are understated and propose

(without limitation) that maintenance costs should be increased by around

ILS[…]million, accommodation costs by around ILS[…] million and overheads

by ILS[…] million. The figures in the PwC report were based in some form on

Bezeq cost data.

Table 4. PwC proposal on core network operating costs

Item Original amount

(ILS,000)

Pwc / Bezeq proposal

(ILS,000)

Maintenance (labour) 216,895 […]12

Power 45,529

[…]

Air conditioning13

14,487

Accommodation 11,902 […]

12 Includes […] million for salaries as well as […]million for pension liabilities.

13 Bezeq is not able to differentiate the costs of air conditioning from other costs. However, the

estimations presented below include the cost of power.



Bezeq’s network

Adjustment for 2nd

level

aggregation switches14

11,318 […]

Vehicles / […]

Total missing opex15

/ […]

Contractors for

network maintenance

[…]

Materials for network

maintenance

[…]

Other (parking,

security, clothing,

training, tools)

[…]

IT contractors […]

Total 300,102 […]

Source: Bezeq

Final view

We believe it is unfortunate that Bezeq has only been able to provide the

information set out above at the consultation stage on proposed FTRs, rather

than in the development of the model when it was repeatedly requested. That

said, we have examined whether the data provided would represent a more

reasonable estimate of the operating costs of a reasonably efficient network

operator. Without prejudice to procedural aspects of this consultation, our review

of the Bezeq data, together also with the points made by Cellcom in its response,

suggest there may be some merit in making limited changes to the operating cost

assumptions in the model. However, we have significant doubts over much of

the information provided by Bezeq, which means we believe any changes to the

model should be limited.

Maintenance and vehicle costs

The operating costs set out in the PwC report seem to be based on an allocation

of overall Bezeq operating costs which is set out on page 17 of Bezeq’s full

14 See model, sheet “core costs 2012”, cell P16 where a manual adjustment to the total operational

costs of aggregation switches is made.

15 Include only core network and excludes 17 million of access related opex.



Bezeq’s network

submission (available in Hebrew only). This split appears to suggest that access

network maintenance costs are only ILS[…] million. This is only a fraction of

core network costs and seems implausible given the lack of any further

explanation in Bezeq’s/PwC’s submission. For example, it is inconsistent with a

wide range of international experience and inconsistent with data we have

received for Israel. If access network costs are understated in Bezeq’s submission

then the corollary of this is that core network costs are overstated.

Furthermore, since the model was developed, we note that a number of

additional bottom-up models have come into the public domain. These suggest

that the opex/capex ratios used in the Israel model are reasonable. In contrast,

the data provided by Bezeq would result in opex/capex ratios out of line with

international experience for the core network (too high) and the access network

(too low). For this reason, we have not made any adjustments in relation to the

maintenance costs considered in the model.

In respect of vehicle related operating costs we have examined the opex/capex

ratios in those countries from which our benchmarks are taken and believe that

these include vehicle related operating costs. As such, including an additional

element in the model for vehicle costs would constitute double counting. This

cost therefore considered to be included in the mark-up for maintenance.

Accommodation, power and air-conditioning costs

In respect of accommodation costs, we note that the accommodation cost

provided per square metre is considerably higher than the benchmarks previously

used due to the lack of this data initially being provided. However, given

significant variations in accommodation costs across countries the final model

conservatively considers the unit costs now provided by Bezeq.

We also note that while the model currently shows operating costs based on pro-

rata costs for edge routers, these costs should be explicitly modelled. This has

been done in the final version of the model. However, we note that while Bezeq

has provided figures on its number and size of sites it has provided no

information supporting that this size is actually optimal. The model is based on

the space needed to house equipment, including power, air conditioning and

back-up power and with an allowance for walk-way access. The final amount of

accommodation is therefore estimated based on these measurements rather than

Bezeq’s information on location sizes (which could be upward biased due to

accommodation being based on larger footprints of legacy equipment). We

believe that this approach is reasonable and the calculation of total costs has

therefore only been changed in relation to accommodation unit costs; not

according to the size of buildings suggested in PwC/Bezeq’s submission.

In respect of power and air conditioning running costs we note that these were

treated as a mark-up factor in the original model. The final version of the model

has been revised to reflect actual power and air conditioning consumption figures



Bezeq’s network

and is now based on costs per kWh in Israel (again, these are based on alternative

equipment information available to us as Bezeq was only able to provide a total

cost rather than equipment specific consumption values and unit costs on which

that total is based). On average this implies an annual consumption of Access

and Aggregation equipment of approximately 4500kwh per unit and

approximately 13000kwh per unit for IP and media gateway equipment and

approximately 65000kwh per unit for soft-switches. The final model also

includes a mark-up to take account of significant climatic differences between

Israel and benchmark countries.

The changes outlined above result in an overall decrease in the fixed termination

costs of approximately 6%. This is primarily the result of moving from a mark-

up based approach to an approach reflecting as much as possible the equipment

specific characteristics and unit costs.

Overhead and interconnection specific costs

Bezeq has further stated that there are some costs missing from the model such

as contractors for network maintenance. The total of these costs is […]million

NIS. In fact, Bezeq is incorrect in stating that the model does not take account

of overhead costs since it does include a mark-up of 3% which is applied to both

core operating cost and core annualised capital cost. However, the information

provided by Bezeq suggests that the mark-up of 3% may be too low (these

operating costs are approximately 7% of the other core operating costs of Bezeq

according to its estimate and 12% of other core operating costs in the model)

although Bezeq's response makes no reference to a mark-up for capital costs.

An examination of international benchmarks shows significant variation in

overhead mark-ups. For example, the figure for the core network varies from

approximately 3% in the Swedish model to 5% in the French model, 15% in

model in Norway and 17% in the Danish model (the mark-up also varies

between version of models and in one case by year). There is also some lack of

clarity about what is covered in the mark-up although, at least, in the Swedish

model it clearly includes outsourced staff.

Based on examination of international benchmarks and information provided by

Bezeq we are of the view that the mark-up should be increased and have used a

figure of 10% in the final version of the model which is broadly consistent with

an average of international benchmarks. This mark-up covers other costs,

including some mentioned by Bezeq, such as security and network redundancy.

The impact of the change is an increase in the termination cost of approximately

5%.



Bezeq’s network

In addition, we have also examined interconnection specific mark-ups in a

number of different models. We have noted that a number of models (e.g. those

for France16 and Norway17) include a billing charge but no other interconnection

specific charges. In the former model the charge is around 8% while in the latter

is around 4%. In light of this point, comments received from Cellcom (see

below), and the fact that other models appear to have no interconnection specific

mark-up at all (e.g. the UK model) we have reduced the interconnection specific

mark-up to 10% in the final version of the model. This results in a reduction of

the fixed termination costs of approximately 11%.

Capital Charge for Work in Progress

The model annualises capital cost using the tilted annuity formula. According to

this formula, for an investment made at the start of year t the charge will be

Investment x (cost of capital – input price trend)

————————————————————

1 - ((1 + input price trend)/(1 + cost of capital))Asset Lifetime

Thereafter the charge changes at the rate of change of the input price. Hence, if

input prices are falling by 5% the charge in the second year will be 5% less than

that in the first year.

Bezeq states that the formula ‘does not take into account the effect of a lag

between the moment when the investment is made and when it becomes

operational’.

This is not the case. The annuity formula implicitly assumes a one year lag

between the time at which the investment is paid for and the time at which

revenues from that investment are received. This is a point which has been

recognised by a number of regulators, including those in France, Belgium and

Ireland and in some cases the formula has been adjusted to reduce the length of

the lag. One approach has been to divide the normal formula by (1 + cost of

capital)1/2 to reduce the effect lag to six months while a more radical approach

involves dividing the formula by (1 + cost of capital).

In practice since payments are spaced out of the year one would expect a delay of

approximately 6 months between the investment coming into operation and

average receipts from the investment. In addition, the investment may be paid

for before it comes into operation. Hence, for these reasons the assumption of a

one year lag is reasonable.

16 Not available on Arcep website, available upon request

17 http://www.npt.no/marked/markedsregulering-smp/kostnadsmodeller/lric-fastnett-kjerne

http://www.npt.no/marked/markedsregulering-smp/kostnadsmodeller/lric-fastnett-kjerne



Bezeq’s network

Final view

As noted above Bezeq is incorrect in stating that the annuity formula does not

take into account a lag between when an investment is planned (or paid for) and

when it becomes operational. Indeed, as noted, there have been instances of

regulators modifying the annuity formula to reduce the length of the lag. As a

result, no changes have been made to the structure of the annuity formula used

to calculate annual capital costs in the model.

2. Response to PwC’s 2nd

submission

In its further submission prepared for the Ministry’s 2nd hearing, PwC, on behalf

of Bezeq, raises a number of points that are discussed in this section. For

reasons outlined above, this response does not discuss those points relating to

the transparency and schedule of the regulatory procedure.

General Concerns

PwC then raises three general concerns with the model. Specifically:

Actual operating parameters of the network have been disregarded (e.g. the

decision to manage a certain quality of service through voice-specific

equipment);

The actual degree of sharing of duct and trenches has not been taken into

account;

The model does not take account of the fact that the network has been built

for maximum demand faced.

In respect of the first issue, in its previous response PwC pointed out that Bezeq

uses separate edge routers for voice and data traffic. We discussed this issue in

the section on Edge Router Cost Allocation where we noted that PwC’s

submission did not provide sufficient justification for having separate routers for

voice and data traffic and, further, that equivalent voice quality could be provided

in other ways. PwC’s further submission again provides no evidence to support

its view that separate edge routers are required for voice and data traffic.

In respect of duct and trench sharing, this was discussed in the section on Trench

Costs – Trench and Cable Length. In that section it was noted that the sharing

figures provided by PwC in respect of Bezeq’s network are extremely low by

international standards. Since the model is designed to produce the cost of a

reasonably efficient network in our view it is therefore reasonable to assume a

higher degree of duct and trench sharing than may exist in Bezeq’s actual

network. It can be noted that PwC’s later submission provides no evidence to

show that Bezeq’s duct and trench sharing is optimal.



Bezeq’s network

Finally, in respect of the network being built for maximum demand this assertion

is not correct. The model uses demand data from 2007 onwards with

appropriate forecast suggesting increasing data traffic and falling voice traffic. In

combination with a ‘build-ahead’ approach to dimension the corresponding

network, the model ensures that past and future traffic is accurately taken into

account when deriving the service costs.

Allocations

PwC’s submission also raises further concerns relating to allocations. In the first

place it states that the model assumes that all network elements are bandwidth

driven. In doing so it further alludes to edge routers where separate routers are

used for voice and data routers.

In response we would make two points:

Firstly, overhead costs, such as accommodation, power and air conditioning

are based on usage by particular sub-components of a particular network

element. This means that these costs are not necessarily allocated in the

same way as the equipment cost itself. For example, the overhead costs of

the MSAN are not allocated in the same way as the costs of the MSAN

itself.

Secondly and more fundamentally, PwC’s example refers to the edge router.

As discussed above, PwC’s initial submission did not provide appropriate

justification for using separate edge routers for voice and data traffic.

Further, it has provided no additional information to support such an

approach. This being the case we believe it is appropriate to allocate both

the costs of the edge routers and the costs of the associated overheads on

the basis of bandwidth.

As a further example, PwC argues that the bandwidth approach is not

appropriate in respect of duct and trench. The allocation of duct and trench

costs is discussed in some detail in the section on Allocation of Trench and Cable

Costs. This section identified three reasons for using a bandwidth based

allocation approach and also noted that this was the approach adopted in a

number of other bottom-up models. PwC’s further submission does not address

these arguments and hence our previous view still stands.

Operating Costs

PwC also argues that operating costs in the latest version of the model, while

higher than in the previous version, are incomplete. While PwC has in this

instance taken into account the latest assumptions made in the model it has not

taken account of the discussion of the section of this document on operating

costs. In that section it is pointed out that on the basis of both international



Bezeq’s network

benchmarks and data we have received in relation to Israel, the breakdown of

operating costs provided by PwC is implausible. In particular, while the overall

level of operating costs for Bezeq’s network business seems reasonable the

breakdown provided suggests an implausibly high level of core related costs and

an implausibly low level of access related costs. PwC has provided no additional

information in support of its view that the split of operating costs it previously

provided is reasonable. Hence, we see no reason to change operating costs

within the model.

3. Response to Aetha report for Cellcom

As part of its consultation response, Cellcom has submitted an expert report

prepared by Aetha Consulting (Aetha) which compares the approach and results

of the BU LRIC model with those prepared in other jurisdictions. The report

does not make specific proposals for changes to the Israel model and therefore in

this paper we do not respond to all the commentary in the Aetha report.

Nevertheless, we note that:

Aetha has, in a number of places, queried the estimated cost for fixed

termination services arising from the model, noting that FTRs in a

number of European markets have been set at lower levels; and

Aetha queries the 25% mark-up included in the model to cover

interconnect specific costs.

Final view

The Aetha report provides a number of potentially useful comparators for the

MOC model. However, in a number of areas we believe that the comparisons

made by Aetha appear to be based on incorrect assumptions and as such do not

believe that the model should be adjusted to reflect more closely these

comparators:

According to the version of the French model in our possession the cost of

trench is Euro 60,000 per kilometre in 2009 and not 30,000 per kilometre, as

stated on page 5 of Aetha’s response. More generally, we note that trenching

costs can vary significantly between countries.

To our knowledge, the peak broadband capacity requirement per subscriber

in the Spanish BU-LRIC model is not 300kpbs (as stated on page 11 of

Aetha’s response), except on a small sub-segment of lines Furthermore,

comparisons between the results of the Spanish model (in terms of

estimated fixed termination cost, noting that the model did not formally

estimate the costs of these services) and the Israel model are somewhat

misleading, as the Spanish model does not include either soft-switches or



Bezeq’s network

media-gateways, which make up a significant proportion of the costs of

termination services in the Israel model.

The Aetha report also queried the 25% mark-up included in the model for

interconnect specific costs. However, rather than including a mark-up, Aetha

believed that these costs should be based on the actual costs of Bezeq’s

interconnection department. In principle, we believe the point made by Aetha is

correct, assuming those actual costs represent a reasonably efficient cost set.

However, Bezeq was unable to provide data on the interconnection specific costs

it incurs. We therefore believe it would be appropriate to reduce the mark-up

included in the model to ensure it is representative of a reasonably efficient cost

base. As such, this mark-up has been reduced to 10% (see previous section).

4. Response to Cellcom network design report

Alongside its response, Cellcom also submitted another report which examines

the optimal network design for a new national fixed line operator in Israel. Again,

this does not make specific proposals for changes to the Israel model and

therefore in this paper we do not provide a detailed commentary on the Cellcom

report.

Whilst the paper does provide a useful comparator for the network design on

which the model is based, we note that both have been developed under

different assumptions. In particular, the modelled network is a scorched node

network based on Bezeq’s actual network architecture. This ensures the model

reflects the realities of operating in Israel and recognises that networks are built

gradually over time, without perfect foresight of demographic and technological

changes. In contrast, the Cellcom model does not reflect existing Bezeq

infrastructure, nor does it reflect the alternate reality that would be faced by a

new operator. This is because, a new operator would need to take into account

the constraints involved in building a network in a built environment. We believe

the approach in the model is appropriate and consistent with BU-LRIC models

developed elsewhere.

Furthermore, there are a number of assumptions and parameters in the Cellcom

document which are insufficiently detailed and therefore not considered. In

particular:

the estimate of trench length. Cellcom has not provided compelling

evidence that the trench and overhead network can get to within 500

metres of areas with buildings under real world conditions, as stated in

4.11.

the source of the capital equipment costs shown on page 9 of the

document (as well as the associated capacities).



Bezeq’s network

the source of the cost figures for the aggregation switch and router

costs shown on page 10 of the document.

Therefore, we do not make adjustments to the model to reflect Cellcom’s

hypothetical network design. Nevertheless, we do note that the Cellcom design

can give comfort to the MoC that its model does not systematically understate

the costs of building and operating a network in Israel, as has been implied in

Bezeq’s consultation response.

We also note that Cellcom has argued that an FTTH network is now optimal.

An examination of the approaches taken in a number of different countries

shows that the extent to which FTTC and FTTH are being rolled-out varies

significantly, indicating the fact that there is a degree of uncertainty as to the

optimum roll-out strategy. Given that the costs of moving from FTTC to FTTH

appear to be extremely expensive – the estimates we have seen suggest that these

may be several times more expensive than rolling out FTTC – we believe it is

premature to assume that FTTH is the optimal technology.

5. Response to comments made in relation to the

WACC18

This section responds to all submissions received in relation to the WACC

estimated for the model. This covers PWC’s and TASC’s initial submission on

the WACC as well as further submissions from Bezeq. Following best regulatory

practice in Israel and other jurisdictions, the approach used in the determination

of the WACC is based on the CAPM principle. This document does therefore

not provide comments in response to submissions that suggest a departure from

that principle.

The risk free rate

A number of submission where made in relation to the risk free rate. These

cover issues such as the approach for measuring the rate as well as data sources

used in the calculation.

Yields from long term government bonds

One submission suggests that the risk free rate should be based exclusively on 10

or 20 year government bond yields, in order to neutralise the effect of the current

low interest rate environment.

18 We note that Partner also commented briefly on parameters that affect the cost of capital,

including the risk free rate, the country risk premium, Beta, gearing, and Bezeq’s cost of debt. Our

responses to Bezeq/PWC and HOT/TASC cover the issues raised by Partner as well.



Bezeq’s network

We do not believe it is necessary to amend the calculation of the risk free rate to

“compensate” Bezeq for a low interest rate environment. The present

environment is also the one in which Bezeq is issuing bonds at interest rates

which reflect current market conditions. As such, we believe it is appropriate

that this is reflected in the WACC used to calculate fixed termination rates.

In support of its suggested approach the respondent (TASC) presents a table

outlining precedent from other regulatory decisions on the tenors of government

bonds considered in the calculation of the WACC. We note that none of the

quoted decisions consider a 20 year bond and one of 5 regulatory decisions uses

a 5 year bond in its calculation.

Other comments referred to a mismatch between the maturity of bonds chosen

for the estimation and the lifetime of the modelled assets with a view that only

bonds with longer terms to maturity should be used in the calculation of the risk

free rate.

We note that the lifetime of cash flows generated by the assets is only one factor

to consider in the development of a reasonable WACC estimate. Other factors

to consider include the expected revenue profile of assets (which in turn depends

on customer demand), cycles in financial markets that an investor would

reasonably take into account and the reliability of market data available with

which to perform the estimation of the risk free rate. We also note that other

regulators have chosen approaches that focus only on the duration of the

regulatory period rather than the lifetime of the underlying asset base in choosing

appropriate types of bonds.

Averaging of risk free rates

A number of respondents comment that an average of 5 and 10 or 15 year bond

yields is inappropriate as a basis for estimating the risk free rate. In particular

some submissions considered that by choosing the midpoint of a WACC range

that we were attempting to estimate a WACC with a 7.5 (average of 5 and 10) or

10 (average of 5 and 15) year maturity. One submitter argued that due to the

apparent concavity of the yield curve, we had under-estimated the WACC

because the average between the lower bound estimate of the risk free rate (based

on a 5 year maturity) and the upper bound estimate of the risk free rate (15 years)

is lower than the 10 year rate implied by current estimates of the yield curve on

Israeli government bond yields.

We believe that the authors of these submissions have misunderstood the

approach used to derive the risk free rate used in the calculation of the WACC.

We have not attempted to determine a WACC that is consistent with a 7.5 year

or 10 year risk free rate. Rather, we have developed a WACC range (the lower

bound of which is estimated using a 5 year maturity assumption, and the upper

bound of which is estimated using a 15 year maturity assumption). We have then

selected the midpoint of that range as a plausible point estimate of the WACC.



Bezeq’s network

This approach is consistent with regulatory practice around the world, and we do

not think there is any reason to depart from this approach.

Real vs. nominal estimation of the risk free rate

Another response criticised the use of index linked bond yields as a way of

estimating the real risk free rate directly because the taxation of inflation based

returns would not be reflected appropriately. The submitter argued that the

correct approach would be to adjust a nominal rate for corporate taxation (i.e. by

converting a post-tax rate into a pre-tax rate), and then deflate this figure to

obtain a real rate. We agree that this approach would be more appropriate than

our original one, and have adopted it in our latest calculations.

Data used in the estimation of the risk free rate

Another response argued that there was a discrepancy between the government

bond yield data used by us originally in the estimation of the risk free rate and

those published by the Bank of Israel (BoI). The data we used originally were

obtained from Bloomberg, a reputable, global data service.

We have investigated this claim and agree that a discrepancy does appear to exist,

although it was not possible to confirm the source of that difference. Given that

the BOI publish government bond yield data transparently, we consider that it

would be appropriate to use these data, rather than the original Bloomberg data,

in our analysis. We have therefore used data published by BoI on yields for

bonds of terms to maturity of 5 and 15 years.19

Final view

In light of the comments above, we do not believe it is necessary to amend the

general principles of our approach but consider it reasonable to make two

adjustments to the approach:

We estimated the risk free rate using yields on non-indexed Israeli

government bonds obtained from the BoI.

We calculated the lower bound of the risk free rate using the yields on

government bonds with a 5 year term to maturity, and the upper bound

using yields on government bonds with a 15 year (rather than a 10 year)

term to maturity.20

19 http://www.boi.org.il/en/DataAndStatistics/Lists/BoiTablesAndGraphs/shcd04ee.xls accessed on

20/09/2013

20 This is partly in recognition that a significant proportion of Bezeq’s asset base includes assets with

an expected lifetime in excess of 10 years.

http://www.boi.org.il/en/DataAndStatistics/Lists/BoiTablesAndGraphs/shcd04ee.xls



Bezeq’s network

Beta

Respondents provided comments in relation to different sources of beta

estimates and alternative methods to estimate the beta.

Adjustment of beta to account for current sources of risk

One respondent criticised the estimation of the beta and suggests that a beta of 1

should be used in the calculation of the WACC. We note that this is based on

comparisons of the estimate in the original WACC and other sources of beta

focussing primarily on absolute sources of risk (reference is made to market

turmoil, uncertain regulation and increased competition).

Beta is a measure of the sensitivity of company returns to market movements.

To the extent that the factors mentioned above contribute to the non-

diversifiable risk faced by the business, this should be reflected in the betas

estimated empirically using Bezeq returns data. It does not seem appropriate that

compensation for any additional risks should be imputed in the betas estimated

directly from company and market data.

Blume adjustment for estimating the beta

Another respondent suggested that the beta estimate included in the WACC

should be adjusted further using the Blume adjustment. Under this approach,

the adjusted beta is a weighted average of the ‘raw’ beta estimate and the beta of

the market portfolio (i.e. 1), where 2/3rd of the weighting is attached to the

former, and 1/3rd of the weighting is given to the latter. In support of its

position, reference was made to our own report for Ficora that also considered

the Blume adjustment.

We note that the Blume adjustment is only one of many factors that were

considered in the calculation of the WACC for Ficora, to which the comment

refers. In that same report, we further explained that both raw betas and

adjusted betas (adjusted either by the Blume method or other methods) can be

considered in the context of deriving the WACC. The report further considered

benchmarks from regulatory decisions in other jurisdictions to establish a

plausible range for the WACC, rather than relying on a single method alone.

However, we do consider there is some merit to using the Blume adjustment as

one element in the determination of a plausible range for the WACC.

Reliability of the beta estimate

The respondent further argued that the beta calculated for Bezeq is not reliable

due to its low R-square values. For this reason, the submitter believed that a beta

based on a global average of 325 telecommunication service companies should be

used. We have reviewed the evidence put forward and we have concluded that

the use of this average is inappropriate. This is for three reasons:



Bezeq’s network

Firstly, the respondent does not explain how the use of a global average

improves the R-square of the beta estimation. There is no evidence that

the average R-square of the 325 companies is better than that for Bezeq.

Secondly, the CAPM, which the respondent accepts, is a single-factor

model. We have applied a standard approach to estimating the CAPM

beta. There is no reason to suppose that a single-factor model should

produce high R-square values.

Moreover, a high R-square value is not necessarily a good indicator of

the reliability of the beta estimate. A low R-square simply indicates that

much of the total risk that Bezeq is exposed to is diversifiable (i.e. a

large proportion of the variation in company returns is uncorrelated

with the variation in market returns). A low R-square value does not

provide conclusive evidence on the suitability of model specification.

For example, it might be possible to add a large number of spurious

factors to the model used to estimate beta that happen to increase the

R-square of the model. A higher R-square value in those circumstances

would not mean an improvement in the estimate of beta.

Finally, the use of a global estimate of beta for 325 telecommunications

companies is likely to include companies in countries that are less

comparable to Bezeq and therefore less appropriate as a basis for

calculating a beta appropriate for a fixed telecommunications operator

in Israel.

We therefore conclude that a beta based on Bezeq’s stock against an Israel based

equity index is a reasonable basis for the calculation of the WACC.

Impact of changes in Bezeq’s financial structure on beta estimate

One response pointed out that Bezeq’s gearing had increased significantly over

the period used for estimating the beta, and argued that we should reflect this in

our estimate. We have taken this submission into account by:

first de-levering our equity betas for Bezeq using Bezeq’s average

gearing level over the relevant estimation period (two years and five

years); and then

re-levering the resulting asset beta using Bezeq’s 2012 gearing level.

Disaggregating Bezeq’s group beta

The respondent further suggests that the beta estimation should take into

account that Bezeq consists of a number of different business units, most notably

mobile and fixed. The respondent provided the results of an estimation that

indicated a lower mobile beta and therefore a Bezeq fixed line beta in excess of



Bezeq’s network

the estimated Bezeq group beta. We were unable to verify the numbers

submitted as part of that response.

We have therefore estimated the betas of Partner and Cellcom, two pure play

mobile operators, and used these as a basis for estimating the mobile part of

Bezeq’s group beta. The approach we used to estimate the mobile betas is

equivalent to the procedure we used to estimate Bezeq’s group beta:

a weighted average of the 5 and 2 year average weekly betas is used; and

the betas are delevered according to the average gearing for each

company over the 2 year and 5 year estimation period.21

We use the average of Partner and Cellcom asset betas at 0.55 as a proxy for the

beta of the mobile part in Bezeq. We then solved for Bezeq’s fixed line

beta. The weighting of the fixed and mobile asset beta within the group beta is

assumed to be based on the 2012 net profits of each business unit (at 1.2bn NIS

and 0.7bn NIS for fixed and mobile respectively). The corresponding

unleveraged beta for Bezeq fixed is equal to 0.54. 22 Our finding suggests that the

respondents claim is unfounded.

Final view

We consider it appropriate to continue to use a beta that is based on the Bezeq

stock and an Israeli equity index. We consider it appropriate to apply the Blume

adjustment as an additional consideration in our assessment of WACC. We

applied the Blume adjustment to estimate the upper bound of our WACC range,

but not the lower bound. The lower bound range of the WACC continues to be

based on a raw beta estimate. The raw beta is further adjusted to reflect only the

fixed line business of Bezeq. Our revised beta estimate has taken into account

the fact that Bezeq’s gearing has increased significantly over time. In

consideration with the Ministry, we have further adjusted the lower bound of the

beta by increasing the weight of the 5 year beta.23 This is done to mitigate the

risk of putting too much weight in the beta estimation on a period that is

generally characteristic for higher stock risks and increased market volatility.

21 The data used for the estimation exercise were sourced from Bloomberg.

22 0.54 = unleveraged beta Bezeq group (0.545) – unleveraged mobile beta (0.552) x mobile share of

net profits (36%) / fixed share of net profits (64%).

23 The beta for the lower bound is based on a 2/3 and 1/3 weighting of the 5 year and 2 year based

beta estimates respectively. The upper bound remains based on a 1/3 and 2/3 weighting of the 5

year and 2 year based beta estimates respectively.



Bezeq’s network

Equity risk premium

Our estimate of the equity risk premium is based on a premium for mature

markets and an equity country risk premium for Israel. Comments in relation to

the equity risk premium relate primarily to the raw data considered for the

estimation of the premium.

One respondent commented that the equity risk premium considered in the

original WACC calculation is based on US and UK evidence and therefore

underestimates the risk involved in investing in Israeli equities, as evidenced by

several alternative Israel specific risk assessments.

We do not believe this criticism is valid. We note that our estimate of WACC

takes account explicitly of an Israel specific risk premium in addition to the

equity market returns considered. The respondent ignores this in its comparison.

A number of respondents suggest that a 10 year average return of the Tel Aviv

stock market should be used as the basis for the equity risk premium. We

consider this inappropriate as such estimate will be upward biased, due to a

period of exceptional returns at the beginning of the 10 year period considered.

Country risk premium

In finalising the WACC we have also reviewed the application of the country risk

premium to ensure this is reflected appropriately and is not double counted in

both the risk free rate and the equity risk premium. This is important because

such double counting would lead to an overestimate of the WACC.

We have based our approach to the calculation and treatment of the country risk

premium on a paper prepared by Professor Aswath Damodaran (Stern Business

School, New York University), whose estimates of the Israeli country risk

premium we had relied upon.24 This paper proposes a three step approach to

determining the appropriate treatment of these factors:

Use local (i.e. Israeli) government bond yields as a starting point for

measuring the risk free rate.

Subtract from these yields a premium for (Israeli) sovereign default risk,

based on the country’s local currency rating. Professor Damodaran

estimated that the sovereign default risk for Israel, as at January 2013,

was 0.85%. This should result in a rate that is closer to a true risk free

rate of borrowing.

24 Damodaran, A. (2008), ‘What is the riskfree rate? A Search for the Basic Building Block’, working

paper.



Bezeq’s network

Add an explicit country risk premium (1.28% for Israel, as at January

2013) to a mature markets equity risk premium (as per our original

approach).

We have followed this approach in our final WACC calculation. In practice, this

involved maintaining our existing estimate of the equity risk premium (inclusive

of a country risk premium for Israel), and determining the risk free rate used in

our estimates of the cost of debt and the cost of equity by deducting from the

relevant Israeli government bond yields a sovereign default risk premium of

0.85%.

Final view

The mature market equity premium of 5.5% is based on a number of sources as

set out in the original documentation of the model. We believe that this remains

a reasonable estimate for the equity premium. We have continued to apply an

explicit country risk premium for Israel remains of 1.28%. However, to mitigate

double counting of the country risk premium, our estimate of the risk free rate

was determined by deducting from the relevant Israeli government bond yields a

sovereign default risk premium of 0.85%.

Debt premium

Previously, our estimate of the debt premium was derived using UK evidence of

the spread between the yields of A/BBB rated corporate bonds and government

bonds. We note that Bezeq’s current credit rating (by S&P Maalot), ilAA stable,

is considerably stronger than the rating assumed in our preliminary analysis.

Given this, it would be inappropriate to base the debt premium on the

assumption of A/BBB rated corporate debt. The final estimate uses the spread

of Bezeq corporate bonds and Israeli government bond yields of a similar tenor

as a basis for estimating the debt premium.

Respondents’ comments focussed on the data used for measuring the debt

premium and considered alternative ways of estimating the rate.

Mismatch between corporate and government bonds

One respondent criticises the approach for a mismatch between the “duration” of

corporate and government bonds considered for estimating the debt risk

premium and bonds used for the purpose of measuring the risk free rate.

The approach applied in the calculation tried to match the terms to maturity of

corporate and government bonds as closely as possible. This was possible for

Bezeq bonds with a five remaining term to maturity in 2012 since we were able to

also identify an Israeli government bond a very similar term to maturity. The

resulting rate was used to determine the lower bound cost of debt estimate.



Bezeq’s network

Applying this rate to our estimate of the risk free rate based on five year Israeli

government bonds was internally consistent.

A debt risk premium for the upper bound was based on the spread between a

Bezeq bond with a 10 year term to maturity in 2012 and an Israeli government

bond yield with a very similar term to maturity. However, we applied this 10 year

debt premium to a risk free rate based on 15 year government bond yields. We

agree that this represents a mismatch of terms. However, we are limited by data

availability: Bezeq did not have outstanding any bonds with a 15 year term to

maturity in 2012. Therefore, we were unable to estimate a 15 year debt premium

directly.

Having given this further consideration, to avoid this mismatch of terms, we

have decided to estimate a 15 year debt premium indirectly by adding to our

estimate of the 10 year debt premium the difference between the five year and 10

year debt premiums estimated. We recognise that this approach has some

limitations:

It assumes that the term structure of the debt premium is upward

sloping, which is a reasonable assumption in normal economic

circumstances. However, during periods of economic crisis, the yield

curve on sovereign and corporate debt has been known in many

countries to become ‘inverted’.

The approach is essentially a linear extrapolation of the debt premium.

In practice, the yield curve may be non-linear.

Notwithstanding, given the data limitations, we think that this is a reasonable and

pragmatic way to estimate a 15 year debt premium.

Data used for calculating the cost of debt

The respondent also commented that the use of short term bonds (referring to

bonds with terms to maturity of 5 years) is inappropriate for calculating the cost

of debt. No justification to support this statement was provided. This response

appears inconclusive given the mix of debt issued by Bezeq. We therefore

believe it is reasonable to use a mix of bonds of different maturities as a basis for

estimating the cost of debt range.

The respondent further alleged that the debt premium for the 10 year bond

(series 6) is 1.56% and that this value should be used together with the actual cost

of debt of Bezeq as a basis for the debt premium. We were unable to verify this

estimate for the series 6 due to the lack of data and methodology provided as

part of the response.

Finally, the respondent argued that the cost of debt should be determined by

taking an average of Bezeq’s embedded (historic) debt cost and the prevailing

yields on its outstanding bonds. As the WACC is a forward-looking concept, we



Bezeq’s network

consider that it is more appropriate to base the cost of debt estimate on the

current rather than embedded debt costs.

Consistency with our approach to the risk free rate

We explained above that our new estimates of the risk free rate were determined

by deducting a sovereign default risk premium from prevailing Israeli

government bonds. For the sake of internal consistency, we removed also

removed this default risk premium from the government bond yields used to

estimate the upper and lower bounds of the debt premium.

Final view

We have estimated the range for the debt premium as follows.

We have based our lower bound estimate of the debt premium on the

2012 average spread between a Bezeq non-indexed bond (BEZQI 5.7

06/01/2017 Corp) and an Israeli government non-indexed bond

(ILGOV 5.5 02/28/2017 Govt). The government bond yields used in

this calculation were adjusted by subtracting an estimate of the Israeli

sovereign default risk premium of 0.85%. Calculating the average debt

premium results in an estimate of 2.12%.

We then estimated the 2012 average spread between a Bezeq indexed

bond (BEZQIT 3.7 12/01/2022 Corp) and 2011-22 Israeli government

indexed bond (ILCPI 2.75 09/30/2022 Govt) using the same

adjustment for the sovereign risk premium described above. This

resulted in an average 10 year debt premium of 2.14%.

We then calculated the upper bound of the debt premium by adding the

difference between the 10 and 5 year spread to the 10 year spread. The

resulting figure represents a proxy for a 15 year debt premium. The

corresponding debt premium for the upper bound of the WACC

estimate is 2.16%.

We have not used Bezeq’s embedded borrowing costs in our WACC

calculations.

Corporate tax rate

One respondent commented that the effective tax rate considered in the

calculation is incorrect in two ways:

We should have used Bezeq’s effective tax rate (which the respondent

estimated to be 29.42%) rather than the statutory corporate tax rate.

The Israeli government has recently approved an increase of 1.5% to

the statutory tax rate.



Bezeq’s network

We understand that due to decision by the tax authorities, Bezeq was unable to

claim as costs against its taxable income certain expenses for dividends, losses of

subsidiaries, options and bonuses which imply that its effective tax rate is higher

than the statutory tax rate. However, we understand that none of these expenses

are related to the normal activities and corresponding taxable income of Bezeq’s

fixed line business. We therefore consider that Bezeq’s effective tax rate is

inappropriate as a basis for calculating the WACC for the purpose of estimating

the cost of fixed termination.

The planned tax increase of 1.5% should be taken into account when making

forward looking cost estimates. Therefore, we have revised our calculations by

using a corporate tax rate of 26.5%, rather than 25%.

Final view

We have used a corporate tax rate of 26.5% when estimating the pre-tax WACC.

Real and nominal WACC

One respondent commented that the use of a real WACC resulted in under-

compensation for the operator. We believe this comment is invalid. Provided

inflation is equal to the forecast, the model, using a tilted annuity approach for

the calculation of annual capital charges (using real or nominal price trends

respectively), leads to the same cost recover profile using a nominal or real

WACC in every given year of the modelled period.

Inflation expectations

As noted above, we derive the real WACC used in our model by first estimating a

nominal (pre-tax) WACC and then deflating this using an appropriate estimate of

inflation.

In order to implement this approach, it is necessary to have estimates of inflation

expectations, and these expectations must match the term of the rate used. So, a

5 year nominal rate must be deflated using the expected annual rate of inflation

over a 5 year horizon. A conventional way of obtaining these inflation

expectations is to calculate the implied rate of inflation between nominal and real

inflation indexed bonds issued by the same entity, e.g. the government. We have

calculated implied inflation using Israeli government bond yields.

As noted above, the lower bound of our WACC range was estimated using a 5

year term assumption, and the upper bound using a 15 year term assumption.

Yield data on 5 year indexed and non-indexed government bonds were available,

so we were able to obtain an estimate of annualised 5 year inflation expectations

that could be applied to the lower bound of the WACC range. In respect of the

estimate of inflation for the upper bound of the WACC range, data were

available on 15 year non-indexed government bonds, but no data were available

on 15 year indexed government bonds. Hence, we could not obtain an estimate



Bezeq’s network

of implied inflation from traded 15 year government bonds. In the absence of

such data, we estimated (annualised) 15 year implied inflation using the BoI’s

yield curve estimates.

Final view

We continue to use a real WACC. The real WACC used in our calculations is

determined by first estimating a nominal (pre-tax) WACC and then deflating this

using an expected rate of inflation.

The expected rate of inflation used to set the lower bound of the WACC is

2.79%. The expected rate of inflation used to set the upper bound of the WACC

is 2.57%.

WACC estimates

Our estimated WACC range and final point estimate is presented in Table 5

below.

Table 5. WACC calculation

Parameter Low estimate High estimate

Government bond yields 3.30% 5.00%

Adjustment for country risk 0.85% 0.85%

Risk free rate (nominal) 2.45% 4.15%

ERP 5.50%

Country risk premium 1.28% 1.28%

Equity beta (Bezeq fixed) 0.76 0.94

Cost of equity (nominal, post-tax) 7.62% 10.54%

Corporate tax rate 26.5% 26.5%

Cost of equity (nominal, pre-tax) 10.37% 14.34%

Debt premium 2.12% 2.16%

Cost of debt (nominal, pre-tax) 4.57% 6.31%

Gearing 40.7% 40.7%

WACC (nominal, pre-tax) 8.01% 11.07%

Forecast inflation 2.79% 2.57%



Bezeq’s network

WACC (real, pre-tax) 5.08% 8.29%

Midpoint 6.68%

6. Estimating costs based on LRAIC

The model has been developed based on the LRAIC standard and service costs

estimated also include a share of fixed and common costs. This is contrary to a

pure LRIC approach where service costs only include those costs that are

avoidable when removing the costed service volumes from the network.

While there is recent precedent for the pure-LRIC approach in the context of

mobile and fixed voice termination primarily in Europe, the LRAIC approach

remains a widely accepted principle consistent across a range of services and

regulatory decisions.

We believe that the LRAIC approach also remains appropriate for the calculation

of the cost of fixed termination in Israel. It ensures that a reasonable amount of

fixed and common costs continues to be recovered from regulated wholesale

services. The modelled fixed termination costs are therefore based on the

LRAIC approach.

estimating the cost of fixed call termination on bezeq’s ...in respect of other data traffic the...

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