Estimating the impact of FttH co-investment on coverage ... · Motivation Data and Statistics Econometric Model Estimation Results Conclusion EstimatingtheimpactofFttHco-investmentoncoverage,

MotivationData and StatisticsEconometric ModelEstimation Results

Conclusion

Estimating the impact of FttH co-investment on coverage,adoption and competition

Marc Lebourges & Julienne Liang

Orange

12th April 2018

Lebourges & Liang FttH co-investment coverage adoption competition 1 / 22


Conclusion

Outline

Motivation

Data and Statistics

Econometric Model

Estimation Results

Conclusion



Conclusion

European telecom regulatory framework for Very High ConnectivityNetworks deployment

I The principle of risk-sharing has been introduced in the 2009 update ofthe European telecom regulatory framework

I The most typical form of Risk-sharing arrangement is co-investment:operators competing downstream share the cost of the upstreaminvestment and all co-investors receive long term rights on the newlydeployed infrastructures

I European Commission has chosen in the Telecom Code proposal aco-investment solution for Very High Connectivity Networks deployment,which is an intermediate solution between two extreme options, pureaccess and no access, conciliates the safeguard of competition and thereward of investment

I But European Commission proposal in this respect is hotly questioned byBEREC and European Parliament as risking to lead to "remonopolisation"



Conclusion

French regulatory framework for FttH deployment in "ZMD" areas1

I Symmetric regulatory framework applicable to all undertakings rolling out FttH (not anasymmetric regulation applicable only to Orange, French incumbent)

I Meant to encourage co-investment: when an operator intends to roll-out FttH in a municipality, itmust inform other operators before and to give them the opportunity to share ab initio theinvestment cost in exchange of long term rights on the newly deployed FttH infrastructure

I Operators not co-investing ab initio can still enter and co-invest a posteriori, but at a higher pricein order to reward initial co-investors for the risk taken

I Detailed co-investment rules different between very dense areas ("ZTD") and less dense areas("ZMD"). Only "ZMD" rules are described because they are those applicable in geographicalareas of our empirical study and which have inspired co-investment provisions in the TelecomCode proposal

I In ZMD, co-investment concerns local areas behind concentration points ("PM: Point deMutualisation") serving at least 1000 customers (or 300 customers if cost oriented black fiberbackhaul is also provided). Undertakings may buy slices of 5% of FTTH capacity behind a "PM"and then extra slices of 5% if needed to serve extra customers. They can also buy directly a largeslice of 10%, 15% or more if they expect to have enough customers. Buying directly a larger sliceis cheaper

I In practice, undertakings have the same level of co-investment in all PMs of a municipality

1ZMD areas = ’Less Dense Areas’ in France in which this empirical study has been done.Description of FTTH regulation in ZMD is necessary to understand how co-investment in ourstudy: Terms of co-investment arrangements defined by FttH regulatory framework defined byFrench NRA (Decisions 2009-1106 and 2010-1312 - Recommendation 23rd December 2009)



Conclusion

FttH co-investment progression in FranceI Co-investment in FttH is recommended by public authorities. How this

policy impacts FttH deployment, adoption and competition?

0

50

100

150

200

250

2011 2012 2013 2014 2015 2016

nb_town_1coinv nb_town_2coinv nb_town_3coinv

Figure: Nb of municipalities with co-investment since 2011



Conclusion

Related literature

I Bourreau, Cambini and Hoernig 2017 : Cooperative investment, access,and uncertainty A theoretical model shows that "Co-investment withoutaccess obligations leads to risk sharing and eliminates the access option,implying highest network coverage"

I Bourreau , Grzybowski and Hasbi 2016 : Private Operators’ EntryStrategies in the FttH Market. The Case of France By using a data(2010-2014) the paper finds that local market presence of LLU operatorshas a positive impact on entry by fiber operators

I Lack of empirical evidence on co-investment efficiency. Our work providesthe first empirical evidence of the benefits of co-investment schemes asanticipated by theoretical literature on the subject.



Conclusion

What this paper does:

I Evaluates the impact of co-investment schema on FttH coverage, itsadoption and FBB market competition

I Detailed municipality-level data on co-investment share, FttH coverage, itsadoption by Orange customers and Orange FBB market penetration

I OLS and Instrumental variable estimation strategy

I Findings: 1% co-financing share by co-investors leads to

I 1.6% more in FttH coverage (measured with Orange fixed broadbandcustomers)

I 1.7% more in Orange’s customer FttH adoption

I Orange fixed broadband (ADSL and FttH) penetration is decreased by1.1%, leads to greater competition.



Conclusion

co-financing share by co-investors (Orange excluded)

Table: 75% of co-financing municipalities with 5% per co-investor

co-financing share with 1 co-investor 2 co-investors 3 co-investors Total

5% 24% 0% 0% 24%10% 5% 22% 0% 26%15% 1% 6% 29% 36%20% 0% 1% 6% 7%25% 0% 3% 2% 5%30% 0% 0% 1% 1%Total 30% 31% 39% 100%



Conclusion

Summary statistics

I Panel of 32685 municipalities over 4 years 2013-2016

I Represent 99.9% of the ZMD French population

Variable Obs Mean Std. Dev. Min Maxcofinancinga 1269 0.1238 0.0569 0.0500 0.3000coverage 130579 0.0023 0.0217 0.0000 0.8041adoption 130579 0.0011 0.0158 0.0000 0.7264Orange FBB penetration Paf 130479 0.3706 0.1063 0.0000 1.3584l4income (keuros) 130579 23.3 6.2 8.2 154.1l4unemployment 130579 0.0929 0.0408 0.0000 0.6100l4education 130579 0.5598 0.1638 0.1124 1.0000cable30 130579 0.02041 0.1305 0 1l4density 130579 0.0781 0.2480 0.0005 7.1813coverage (FranceTHD 2015-2016) 65292 0.02 0.12 0.00 1.00dnbsiteCO 130579 0.9689 4.6139 -79 345year 130579 2014,5 1 2013 2016housing 130579 835 2767 34 99692firm 130579 80 297 0 14415

aonly for observations with cofinancing>0



Conclusion

Data

I variable of interest

I co-financing share: sum of the co-financing share of all co-investors in themunicipality

I dependent variables: coverage, adoption, Orange FBB penetration

I coverage=(nb Orange customers eligible FttH)/(nb housings and firms)

I adoption=(nb Orange customers adopted FttH)/(nb housings and firms)

I Orange FBB penetration=(nb Orange FBB customers)/(nb housings andfirms)



Conclusion

Data

I instrumental variable for co-financing share

I nb of mobile antennas owned by co-investors (Orange excluded) in themunicipality

I control variables (lagged four years)

I mean income

I education level (share pop 15yo >= BAC)

I unemployment rate

I population density

I share of housing eligible to cable access



Conclusion

Identification strategy: finding sources of exogenous variationI Positive correlation between variation in cofinancing, coverage, adoption

and variation in nb of co-investors’ antennasI Negative correlation between variation in Orange FBB ADSL+FttH

penetration and variation in nb of co-investors’ antennas

-.05

0.0

5va

riatio

n in

cof

i cov

ado

paf

-100 0 100 200 300variation in dif of mobile antenna nb (between competitors and Orange)

FttH coverageFttH adoptioncofinancingOrange paf

a

aLinear fits of the first difference in 3 dependent variables, endogenous variable andinstrumental variable. We first exclude the time trend effects by regressing cofinancing,coverage, adoption, instrument (nb of co-investors’ antennas) and Orange FBB penetration Pafon time variable (year) and taking the first difference of residuals.



Conclusion

Empirical model

I Panel regression of following equation

Yit = αsit + βXit + µi + νt + εit (1)

I where Yit is coverage (adoption or Orange FBB penetration). sit iscofinancing share of co-investors in municipality i in period t.Unobservable determinants of FttH coverage (adoption) that are fixed atthe municipality level is controlled for through the municipality indicators(µi ). Time fixed effects are controlled by the year indicators (νt). Yearfixed effects control for unobserved factors affecting the likelihood of Yit

that are common to all municipalities in a given year.



Conclusion

Identification Strategy

I sit is endogenous: stemming from the correlation between the unobserveddeterminants of FttH coverage and consumers’ preferences for FttHtechnology and FttH providers

I co-investment share can be expressed as:

sit = γZit + λXit + τi + φt + εit (2)

I where Zit is the number of mobile antennas deployed by co-investors(Orange excluded) in the municipality –> Instrument for co-investmentshare sit

I This first stage equation indicates also the determinants of co-investmententry/share



Conclusion

Instrument for co-investment share: Z in equation (2)

I . The rational for the instrument: FttH investment may follow mobileinvestment

I Z are exogenous because they are constructed to provide mobile networkcoverage

I Mobile population coverage rate is imposed by the regulator with apredefined coverage timetable

I Mobile antennas are firstly deployed in the municipalities with short-termeconomic profitability. Co-investors may follow the same patterns for FttHinvestment. So that Z affects FttH coverage only through theco-investment, but probably does not affect directly FttH coverage. Inaddition, Orange should not take into account of co-investors’ antennas toinvest in FttH.



Conclusion

OLS estimation: sit is assumed exogenous

I co-investment increases FttH coverage adoption

VARIABLES coverage adoptioncofinancing 0.5244*** 0.4369***

(0.005) (0.005)l4income 0.0282 0.0247

(0.017) (0.018)l4unemployment -0.0012 -0.0010

(0.002) (0.002)l4edu 0.0016* 0.0010

(0.001) (0.001)l4density -0.0501*** -0.0802***

(0.006) (0.006)cable30 0.0054*** 0.0045**

(0.002) (0.002)dep_year dummies Y YObservations 130,578 130,578R-squared 0.175 0.134Number of municipality 32,685 32,685Standard errors in parentheses: *** p < 0.01, ** p < 0.05, * p < 0.1



Conclusion

2SLS estimation: sit is endogenous

first stage second stage second stageVARIABLES cofinancing coverage adoptionnbsiteComp 0.2520***

(0.007)cofinancing 1.6296*** 1.7117***

(0.052) (0.057)l4income -0.0191 0.0591*** 0.0604**

(0.012) (0.022) (0.024)l4unemployment 0.0033** -0.0062** -0.0068**

(0.001) (0.003) (0.003)l4edu -0.0008 0.0028** 0.0024**

(0.001) (0.001) (0.001)l4density -0.0096** -0.0303*** -0.0573***

(0.004) (0.007) (0.008)cable30 0.0092*** -0.0067*** -0.0095***

(0.001) (0.002) (0.003)dep_year dummies Y Y YObservations 130,578 130,578 130,578R-squared 0.058 -0.323 -0.483Number of municipality 32,685 32,685 32,685First-Stage F-statistic 1195 1195

I 2SLS regression results are in line with OLS. But OLS underestimates theco-investment impact



Conclusion

Impact of co-investment on FBB market competition

I 1% co-financing share decreases Orange’s fixed broadband penetration2 by1.1%

VARIABLES Pafcofinancing -1.0740***

(0.116)l4income 0.1381***

(0.049)l4unemployment -0.0111*

(0.006)l4edu 0.0012

(0.002)l4density -0.0619***

(0.016)cable30 -0.0060

(0.005)dep_year dummies YObservations 130,478R-squared 0.231Number of municipality 32,684First-Stage F-statistic 1194

2Orange fixed broadband penetration Paf is defined as the ratio of total Orange’s fixedbroadband customers (ADSL and FttH) to the number of housings and firms in themunicipality



Conclusion

Robustness checks 1/2: alternative instrument –> temperatureMax

First stage Second stage Second stage Second stageVARIABLES cofinancing coverage adoption Paf

cofinancing 1.9346*** 1.6494*** -1.8562**(0.426) (0.413) (0.910)

tempMax 0.0001***(0.000)

l4income -0.0052 0.0519* 0.0563** 0.0128(0.013) (0.027) (0.026) (0.057)

l4unemployment 0.0042*** -0.0086** -0.0083** -0.0091(0.002) (0.004) (0.004) (0.008)

l4edu -0.0008 0.0033** 0.0024* -0.0004(0.001) (0.001) (0.001) (0.003)

l4density -0.0131*** -0.0274*** -0.0668*** -0.0842***(0.004) (0.010) (0.010) (0.022)

cable30 0.0121*** -0.0097* -0.0083 -0.0018(0.001) (0.006) (0.006) (0.013)

year FE Y Y Y Y

Observations 117,382 117,382 117,382 117,280R-squared 0.009 -0.637 -0.461 0.081Number of municipality 32,313 32,313 32,313 32,308First-Stage F-statistic . 22.13 22.13 22.06



Conclusion

Robustness checks 2/2: alternative variable of interest–>coinv nbinv3

VARIABLES coverage coverage adoption adoption Paf Paf

coinv 0.1271*** 0.1335*** -0.0837***(0.003) (0.004) (0.009)

nbinv 0.0905*** 0.0951*** -0.0596***(0.003) (0.003) (0.006)

l4income 0.0584*** 0.0576*** 0.0597*** 0.0588** 0.1385*** 0.1391***(0.019) (0.022) (0.021) (0.024) (0.048) (0.048)

l4unemployment -0.0052** -0.0060** -0.0057** -0.0066** -0.0118** -0.0112*(0.002) (0.003) (0.002) (0.003) (0.006) (0.006)

l4edu 0.0025*** 0.0028*** 0.0021** 0.0024** 0.0014 0.0012(0.001) (0.001) (0.001) (0.001) (0.002) (0.002)

l4density -0.0246*** -0.0328*** -0.0514*** -0.0600*** -0.0656*** -0.0602***(0.006) (0.007) (0.007) (0.008) (0.016) (0.016)

cable30 -0.0053** -0.0086*** -0.0080*** -0.0114*** -0.0070 -0.0048(0.002) (0.002) (0.002) (0.003) (0.005) (0.005)

dep_year dum Y Y Y Y Y YObservations 130,578 130,578 130,578 130,578 130,478 130,478R-squared 0.050 -0.251 -0.080 -0.431 0.265 0.238Number muni. 32,685 32,685 32,685 32,685 32,684 32,684F-statistic 2498 1301 2498 1301 2495 1300

3’coinv’ dummy variable for FttH co-investment entry (0/1) in the municipality and ’nbinv’the number of co-investors (0, 1, 2, 3). ’nbinv’ is defined as the number of additional FttHinvestors beyond the first investor (Orange).



Conclusion

Conclusion

I Main findings: 1% co-financing effort by co-investors

I raises FttH coverage by 1.6%

I increases Orange’s customer FttH adoption by 1.7%

I decreases Orange’s fixed broadband penetration by approximately 1.1%.

I Results are robust to change of instrument and variable of interest andconsistent with theoretical findings

I Limits:

I our results only hold for France

I database at municipality-level from Orange (single operator) on a yearlybasis between 2013-2016

I extend the study to the efficiency of public investment and overall marketFttH adoption



Conclusion

MANY THANKS

Estimating the impact of FttH co-investment on coverage,adoption and competition

Marc Lebourges & Julienne Liang

Orange

12th April 2018


Documents

Estimating the impact of FttH co-investment on coverage ... · Motivation Data and Statistics Econometric Model Estimation Results Conclusion EstimatingtheimpactofFttHco-investmentoncoverage,