Collusion in the French mobile telecomes market: a theoretical and empirical analysis

Collusion in the French mobile telecoms market: a theoretical

and empirical analysis Roberto Alimonti, Francesco Rieppi

Master in Competition and Market Regulation Master Project

Outline of the presentation

•  Overview of the European mobile telecoms market

•  Collusion in the French mobile market

•  Collusion in theory

•  Empirical evidence

•  Conclusions

Mobile market overview

Demand side

•  Penetration rate ↑ (121.9%)

•  Volumes of calls & data ↑ •  Supply side

•  3-4 operators

•  Mkt concentration ↓ (MVNOs)

•  Average price ↓ (MTRs)

•  Revenues ↑ (mostly from data)


Demand side


•  Volumes of calls & data ↑ •  Supply side






Demand side


•  Volumes of calls & data ↑

Supply side






Demand side



Supply side






Demand side



Supply side






Demand side



Supply side



•  Average price ↓ (MTRs, flat-rates)



Demand side



Supply side



•  Average price ↓ (MTRs, flat-rates)


Collusion in the French market (1/2)

Parties and facts •  In August 2001, the Coinseil de la Concurrence (French

CA) found an hardcore cartel in the national mobile market

•  Parties: Orange, SFR and Bouygues Telecom

•  1997-2003: proof of exchange of strategic information (new subscriptions and cancellations of previous month)

•  2000-2002: agreement to stabilize mkt shares

➡  Information exchanged used as a monitor device

Collusion in the French market (2/2)

•  Evidence of constant mkt shares during (and after) the cartel

•  Price increase & adoption of particular commercial strategies (i.e. billing per 30-seconds after first min of call)

Collusion in theory: ability (1/2) Factors that facilitate collusion

•  Number of operators and concentration: only 3 firms from 1996; high HHI (MVNOs only have 7.5% mkt shares) ⇒ coordination and monitoring is easier

•  Presence of barriers to entry

•  High fixed and sunk costs

•  Spectrum allocation (not frequent)

•  Network effects (customer base)

•  Switching costs

⇒ more easy to collude

Collusion in theory: ability (2/2) Factors that facilitate collusion

•  Evolution of demand: slightly increased during the cartel ⇒ deviation is less profitable; more easy to monitor

•  New subscribers, calls and data consumption is very frequent and regular ⇒ easier to monitor and retaliate

•  Multi-mkts contacts: operators are present both on mobile and fixed segment, in several national mkts.

•  Moreover, Orange and SFR (Vodafone) have symmetrical mkt shares at an aggregate level

•  Countervailing buyer power: low in retail mkt, but higher in wholesale mkt (i.e. Tele2 Mobile, Carrefour, Auchan, Virgin and Universal Music) ⇒ more difficult to collude

Collusion in theory: incentives

•  Firms involved in the cartel have different mkt shares

•  The smallest (biggest) firm would not have incentives to collude with Cournot competition and equal (unequal) costs

•  Collusion can be explained with a Stackelberg model

Cartel Stackelberg

Mkt shares

Costs

Profits

Incentive comparison (1/2)

•  Mkt shares before and during the cartel are

Incentive comparison (2/2)

•  Positive difference between profits under collusion and Stackelberg competition:

➡  Therefore, all the firms have incentives to collude

Empirical evidence •  Time series econometric analysis, French mobile market 2000-2010

•  Two models, with and without costs

•  Dependent variable: monthly revenues per subscription (no internet revenues)

•  Independent variables: competition and mobile sector variables, costs









Summary statistics

Independent VariableAverage

2000Average

2010Whole Period

Monthly revenues per subscriber (MREV) 26.63 19.5 23.82

Monthly voice volume per subscriber (VOC) 116 136 137

Monthly SMS volume per subscriber (SMS) 5 137 38

Herfindahl index (HHI) 3813 3252 3634

Termination rate (TR) 0.296 0.026 0.14

Cost of labour (LAB) 81.5 87.7 83.97

Cost of energy (ENE) 0.0553 0.0552 0.0512

Results Independent Variable

Coefficient (Standard Error)

Coefficient (Standard Error)

Monthly voice volume per subscriber (VOC) 0.071** (0.019) 0.067** (0.020)

Monthly SMS volume per subscriber (SMS) -0.002 (0.006) -0.003 (0.010)

Herfindahl index (HHI) 0.005*** (0.001) 0.005*** (0.001)

Termination rate (TR) 20.201*** (4.059) 21.92*** (4.777)

Cartel (CRT) -0.306 (0.555) -0.325 (0.562)

Financial crisis (FIN) 0.105 (0.261) 0.082 (0.256)

Cost of labour (LAB) - 0.081 (0.204)

Cost of energy (ENE) - -36.036 (31.207)

Constant -8.059 (5.033) -11.506 (16.716)

Number of observations 44 44

Conclusions

•  Evidence of ability and incentives to collude

•  Empirical evidence of no change in revenues due to the end of the cartel

•  Likely effectiveness of the cartel before 2003 suggest tacit collusion was the outcome after that year

•  Research based on international comparison suggested to check the effects of tacit collusion

Education

Collusion in the French mobile telecomes market: a theoretical and empirical analysis