©Anupam Banerjee, Carnegie Mellon Issues in FTTP Industry Structure: Implications of a Wholesale-Retail Split (Pricing in Open Access Networks) Anupam Banerjee, Marvin Sirbu Department of Engineering and Public Policy Carnegie Mellon University

©Anupam Banerjee, Carnegie Mellon Some Background  Fiber to the Premise (FTTP) exhibits characteristics of a natural monopoly industry  Probably the only way to have competition, is service level competition – multiple retailers sharing one network  To encourage competition and thereby increase welfare, some states have mandated a Wholesale-Retail split for municipally owned FTTP infrastructure (in order to create a level playing field for retailer service providers): A municipality that owns a network cannot provide retail service – it is free, however, to decide if it wants to sell layer 2 service or dark fiber. Some municipalities choose to be wholesalers by choice.  This work studies the impact of different wholesale-retail arrangements on wholesaler profits and consumer welfare for different wholesaler objectives and compares it to a vertically integrated industry structure, where a network owner can also offer retail voice, video and data services.

©Anupam Banerjee, Carnegie Mellon Motivating Question  Open Access: Network operator provides wholesale transport to service providers  Industry structure: Do we want to impose structural separation between infrastructure ownership and service provisioning? –Do sustainable prices exist for an infrastructure-only provider?  Build a supply/demand model and calculate welfare effects for different industry structure models

©Anupam Banerjee, Carnegie Mellon Two-service model for the Wholesale-Retail Split  Demand Model –Consumers have different willingness to pay for voice, video and data services: Willingness to pay for a particular service can be modeled by a statistical distribution for a particular market –There is correlation between the willingness to pay for voice, video and data for one particular consumer: One can imagine a 3-space where the coordinates of each point give her willingness to pay for voice, video and data services –For simplicity, here we assume everyone wants voice – so our demand model is 2-space, where the coordinates of each point give the willingness to pay for data and video

©Anupam Banerjee, Carnegie Mellon X 1 =Homes taking service1 (data) at price P 1 (Area BDP 1 P 3 ) X 2 =Homes taking service2 (video) at price P 2 (Area ACP 2 P 3 ) X 3 =Homes taking service3 (video and data) at price P 3 (Area ACDBZ) Demand Model.. P1P1 P2P2 A B C D P3P3 P3P3 Z

©Anupam Banerjee, Carnegie Mellon Supply Model  Annualized Fixed cost for wiring up the entire market consisting of X homes = F  Annualized Fixed Cost of installing CPE and drop loop = C 0  Annual incremental cost of providing data service (Service 1) per home = C 1  Annual incremental cost of providing video service (Service 2) per home = C 2  Observation: Marginal Cost of Bundle (C 0 +C 1 +C 2 ) is less than the sum of Marginal Cost of Data (C 0 +C 1 ) and Marginal Cost of Video(C 0 +C 2 )  If X 1 homes take data service, X 2 homes take video service and X 3 take both, annual cost of providing service = F + C 0 (X 1 +X 2 +X 3 ) + C 1 X 1 + C 2 X 2 + (C 1 +C 2 )X 3

©Anupam Banerjee, Carnegie Mellon Possible Industry Structures  Vertically Integrated entity (Network owner provides retail service) –‘Verizon’ Model (Profit Maximizing) –‘Bristol’ Model (Welfare Maximizing)  Structurally Separated entities (Network owner, either by regulation or choice, is only a wholesaler. The retail market is assumed to be competitive/contestable) –‘Grant County Welfare’ (Welfare Maximizing Wholesaler selling layer 2 service) –‘Grant County Profit’ (Profit Maximizing Wholesaler selling layer 2 service) –‘Stockholm’ Model (Wholesaler selling UNEs or Layer2 access only directly to consumers; consumers buy service from retailers)

©Anupam Banerjee, Carnegie Mellon Notation  P 0 W = Wholesaler’s price of UNE loop  P A W = Wholesaler’s price of Layer2 access  P i W = Wholesaler’s price of (layer 2) service i; i = 1, 2, 3  P j R = Retailer’s price of service j; j = 1, 2, 3 j = 1 => Data Service j = 2 => Video Service j = 3 => Data-Video Bundle  W i k = Willingness of pay for kth consumer for ith service  F, C 0, C 1, C 2, X 1, X 2, X 3 as described earlier

©Anupam Banerjee, Carnegie Mellon  Total Cost of Providing service = F + C 0 (X 1 +X 2 +X 3 )+ C 1 X 1 + C 2 X 2 + (C 1 +C 2 )X 3 –MC 1 (data service)=C 0 +C 1 –MC 2 (video service)=C 0 +C 2 –MC 3 (data and video)=C 0 +C 1 +C 2 –MC 1 +MC 2 >MC 3  Revenue = P 1 R X 1 + P 2 R X 2 + P 3 R X 3  ‘Verizon’ chooses P 1 R, P 2 R, P 3 R to maximize Profit = (Revenue – Cost)  P 1 R >C 0 +C 1 or, P 1 R =C 0 +C 1 +  1  1 >0  P 2 R >C 0 +C 2 or, P 2 R =C 0 +C 1 +  2  2 >0  P 3 R >C 0 +C 1 +C 2 or, P 3 R =C 0 +C 1 +C 2 +  3  3 >0  Where  i is the elasticity of demand for service i Industry Structure 1: The ‘Verizon’ Model

©Anupam Banerjee, Carnegie Mellon  Total Profit from Providing service = {P 1 R X 1 + P 2 R X 2 + P 3 R X 3 } - {F + C 0 (X 1 +X 2 +X 3 )+ C 1 X 1 + C 2 X 2 }  Social Welfare = –Where K i is the set of subscribers taking ith service and K i ∩K j =   ‘Bristol’ chooses P 1 R, P 2 R, P 3 R to maximize Social Welfare subject to a cost recovery constraint (Profit ≥ 0)  P 1 R >C 0 +C 1 or, P 1 R =C 0 +C 1 +  1  1 >0  P 2 R >C 0 +C 2 or, P 2 R =C 0 +C 1 +  2  2 >0  P 3 R >C 0 +C 1 +C 2 or, P 3 R =C 0 +C 1 +C 2 +  3  3 >0  Where  i is the elasticity of demand for service i Industry Structure 2: The ‘Bristol’ Model

©Anupam Banerjee, Carnegie Mellon What is Service Arbitrage?  Verizon/ Bristol can differentiate between data, video and video & data bundle customers engage in third degree price discrimination.  Grant County Profit/ Welfare can potentially sell data capability, video capability and video & data bundle capability. Since the bandwidth associated with the video capability 1 is sufficient to also support data, a retailer can use a video capability to sell a video& data bundle to a subscriber without Grant County Profit/ Welfare being able to discriminate between a only video subscriber and a video & data bundle subscriber – this is service arbitrage.  Therefore a wholesale retail split interferes with the ability of a wholesaler to price discriminate. 1 We assume here that the wholesaler always sells symmetric bandwidth (see caveats at the end)

©Anupam Banerjee, Carnegie Mellon Implications of Service Arbitrage Video C1C1 P 3 R =P 1 R +P 2 R -2  P 1 R =P* 1 R (assume) P2P2 Data P* 2 P* 3 P 3 R =P 1 R +P 2 R -2  Grant County VZ/ Bristol P i R =Retail price of ith service in vertically integrated industry structure (VZ/ Bristol) P* i R =Retail price of ith service in in wholesale/retail split structure (Grant County Profit/ Welfare)  If we assume that the retail price of data remains the same, i.e. P 1 R =P* 1 R, then in trying to maximize profits, P 3 R will be > P* 3 there will be more consumers that consume the bundle at a lower price, leading to an increase in welfare in the W/R split structure.  However, the number of consumers taking video only service will decrease, leading to lower welfare in the w/r split structure.

©Anupam Banerjee, Carnegie Mellon Industry Structure 3: The ‘Grant County Profit’ Model  ‘Grant County’ can sell only two services:  (1) a data capability service; and (2) a video capability service. The wholesale video service provides sufficient bandwidth to also offer data. Service arbitrage forces P 2 =P 3  Total Cost of Providing service = F + C 0 (X 1 +X 2 +X 3 )  Revenue = P 1 W X 1 + P 2 W X 2 + P 3 W X 3 but, due to arbitrage,  Revenue = P 1 W X 1 + P 2 W (X 2 + X 3 )  Grant County’ chooses P 1 W, P 2 W to maximize Profit = (Revenue – Cost)  Where X 1, X 2, X 3 determined by  P 1 R = P 1 W +C 1  P 2 R = P 2 W +C 2  P 3 R = P 2 W +C 1 +C 2  Notice that in this case, due to service arbitrage, the profit maximizing price P 2 W may get set high enough to ‘kill’ the “video only” service (or service 2) – Welfare Implications?

©Anupam Banerjee, Carnegie Mellon Industry Structure 4: The ‘Grant County Welfare’ Model  ‘Grant County’ can sell only two services: (1) a data capability service and (2) a video capability service. Due to service arbitrage, once a video capability service is sold, data is automatic.  Total Cost of Providing service = F + C 0 (X 1 +X 2 +X 3 )  Revenue = P 1 W X 1 + P 2 W (X 2 + X 3 )  Social Welfare =  Where X 1, X 2, X 3 determined by  P 1 R = P 1 W +C 1  P 2 R = P 2 W +C 2  P 3 R = P 2 W +C 1 +C 2  Grant County’ chooses P 1 W, P 2 W to maximize Social Welfare subject to the cost recovery constraint (Profit ≥0)

©Anupam Banerjee, Carnegie Mellon  ‘Condo’ sells UNE loop (access) at a price P 0 W (P A W ) directly to the customer  Total Profit from Providing wholesale service = P 0 W ( X 1 + X 2 + X 3 ) – F (P A W ( X 1 + X 2 + X 3 ) - F - ( X 1 + X 2 + X 3 ) C 0 )  Social Welfare =  Where, –P 1 R = P 0 W + C 0 + C 1 orP 1 R = P A W + C 1 –P 2 R = P 0 W + C 0 + C 2 P 2 R = P A W + C 2 –P 3 R = P 0 W + C 0 + C 1 + C 2 P 3 R = P A W + C 1 + C 2  If ‘Stockholm’ is to maximize social welfare, it has to choose P 0 W (P A W ) such that social welfare is maximized subject to the cost recovery constraint  Because of retail competition, retail price is driven to incremental cost  Note that result is the same whether Stockholm sells dark fiber, P 0 W, or layer 2 service, P A W Industry Structure 5: The ‘Stockholm’ Model

©Anupam Banerjee, Carnegie Mellon Welfare Implications of the different Industry Structures Base Case F=5x10 4 C0=8 C1=20 C2=30  1 = 35 σ 1 = 10  2 = 45 σ 2 = 10 As expected, welfare maximizing industry structures (Bristol, GCW, Stockholm) create significantly more welfare ($2-$5 per subscriber per month) than their profit maximizing counterparts (Verizon, GCP) Bristol creates more welfare (up to $0.60 per subscriber per month) than GCW or Stockholm due to its greater ability to price discriminate Verizon’s profit is marginally higher than GCP’s Profit (up to $0.10 per subscriber per month) because of Verizon’s greater ability to price discriminate

©Anupam Banerjee, Carnegie Mellon Comparing VZ and GCP.. Both VZ and GCP industry structures produce the same amount of consumer surplus in spite of individual prices being different.. Base Case F=5x10 4 C0=8 C1=20 C2=30  1 = 35 σ 1 = 10  2 = 45 σ 2 = 10

©Anupam Banerjee, Carnegie Mellon Comparing Verizon and Grant County Profit Prices.. –VZ sets lower price for Video (by up to $8 per subscriber per month) and has more “only” video subscribers. GCP has a lower Bundle price (by up to $0.50 per sub per month) and has more Video & Data Bundle subscribers. GCP CAN realize sustainable prices.

©Anupam Banerjee, Carnegie Mellon Comparing VZ and GCP..  VZ/ GCP consumer welfare increases with rho; while the profits decrease with rho; total welfare decreases with rho  VZ is able to earn higher profits vis-à-vis GCP (of about $0.10 per subscriber per month) only when -0.7<rho<0.7 due to its greater ability to price discriminate, for the above model parameter values  VZ and GCP create almost the same amount of consumer welfare – the increase in welfare due to lower GCP bundle prices trades off with the decrease in welfare that comes from GCP serving fewer video subscribers, for the above model parameter values.  All industry structures create exactly the same amount of consumer welfare and producer profits for rho>0.7, for the above model parameter values

©Anupam Banerjee, Carnegie Mellon Comparing VZ and GCP for different values for the mean willingness to pay for data service  Total surplus associated with the video only service increases as the mean willingness to pay for data decreases from 35 to 15,  For the same incremental cost of providing data service (C 1 =10), the difference between Verizon’s profits and Grant Count’s profits increases from almost zero cents per home per month (  1=35), to 10 cents per home per month (  1=25) to 30 cents per home per month (  1=15)

©Anupam Banerjee, Carnegie Mellon Caveats  We have considered a simplified 2-service model. The next step would be to consider a “more realistic” 3-service model  We assume incremental costs, C i, are the same in both vertically integrated and competitive retail cases –Competition should drive down incremental costs of services  We assume layer 2 costs, C 0, are the same whether supplied competitively or by wholesaler –See above  Double Marginalization: We have assumed a competitive retail industry – how does the above change when it isn’t? –Retailers offer differentiated, imperfectly substitutable products –Retail entry barriers lead to oligopolistic competition  We assume that the wholesaler only sells symmetric bandwidth. For example, the wholesaler could sell an asymmetric connection (of 32Kbps upstream and 4Mbps downstream) as the ‘video capability’ making it impossible for the ‘video capability’ to carry both video and data.