Tariff diversity and competition policy: drivers for broadband adoption in the European Union


While second-degree price discrimination is standard in commercial practice in many industries, consumer advocates and public interest groups have reacted with skepticism to tendencies to move away from flat rates and introduce greater tariff diversity. This paper uses time-series data to provide an empirical analysis of how the differentiation of broadband tariffs with respect to retail prices affects fixed broadband subscription. The empirical analysis is based on a unique dataset of 10,200 retail broadband offers spanning the 2003–2011 period and including 23 EU member states. Results show that an increase in tariff diversity provides a significant impetus to broadband adoption, wherefore demands by several public interest groups to limit price discrimination in broadband markets should be viewed with some caution as reduced price discrimination may come at the cost of lower penetration rates.

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  1. 1.

    FTTH Council Europe (2016), Der FTTH Markt in Europa: Status, Ausblick und die Position Deutschlands, only available in German, (see, https://langmatz.de/wp-content/uploads/2016/03/1-jan-schindler-ftthcouncil-der-ftth-markt-in-europa.pdf).

  2. 2.

    Howell (2008) emphasizes that with price structures, such as flat rates, where low-usage consumers extremely cross-subsidize high-usage customers, customers’ true valuations of access and usage are obfuscated. In view of a lack of more precise information operators, regulators, and policymakers might eventually make wrong decisions to invest or to regulate.

  3. 3.

    Bundles may include any combination of broadband internet, fixed-line telephony, delivered via PSTN or VoIP telephony, TV or entertainment services as well as mobile voice and data services.

  4. 4.

    Data Cap Integrity Act of 2012, S.3703 – 112th Congress (see, https://www.congress.gov/112/bills/s3703/BILLS-112s3703is.pdf).

  5. 5.

    See the Memorandum Opinion and Order of the FCC from May 2016, FCC 16.59 (see, http://transition.fcc.gov/Daily_Releases/Daily_Business/2016/db0510/FCC-16-59A1.pdf).

  6. 6.

    International Telecommunication Union (see, http://www.itu-coe.ofca.gov.hk/vtm/universal/faq/q1.htm).

  7. 7.

    Demand for diversified offers is also prevalent in the TV market. In the US, for instance, the cable companies Verizon, Dish, and Cablevision started offering cheaper, slimmed-down bundles of dozens of TV channels as opposed to hundreds, and immediately saw a substantial shift from their installed subscribers and at the same time gained new subscribers (The Washington Post (2015), Cable companies pare down bloated TV bundles to stem tide of cord-cutters (see, https://www.washingtonpost.com/business/economy/cable-companies-pare-down-bloated-tv-bundles-to-stem-tide-of-cord-cutters/2015/09/18/ac67a0a8-5e53-11e5-b38e-06883aacba64_story.html).

  8. 8.

    Broadband competition can occur as facilities-based competition between different technologies (e.g., DSL-, cable-, and fiber-based technologies), referred to as inter-platform competition, or as service-based competition over the same infrastructure through open access provisions at various network layers, referred to as intra-platform competition.

  9. 9.

    Although retail prices are no longer a matter of continuing regulatory concerns in the EU, they are assessed in order to prevent a “margin squeeze” which occurs when incumbents set wholesale and retail prices with a narrow margin such that a downstream firm cannot survive or effectively compete.

  10. 10.

    Note that the analysis does not directly test the effect of UBP versus flat rate pricing, as is nicely done in Nevo et al. (2016) for broadband usage. We rather look at price dispersion at an aggregated level, accounting for different forms of second-degree and third-degree price discrimination. Hence, the observed tariff diversity is inevitably influenced by the difference of metered and unlimited offers, but not exclusively.

  11. 11.

    The impact of bundles is evaluated as a robustness check, see Sect. 3.2.

  12. 12.

    To account for a potential non-linear effect of price discrimination on demand, as too much variety in pricing schemes may eventually make consumers reluctant to buy, a quadratic term was added which, however, turned out to be insignificant irrespective of the underlying measure. Results are not reported but are available upon request.

  13. 13.

    Results from a pooled OLS estimation are inconsistent because the unobserved time and regional effects are disregarded and the lagged dependent variable is correlated to the error term (Roodman 2007). Employing a fixed-effects model does not resolve the problem either. The demeaning transformation produces inconsistencies due to the large cross-sectional but small time dimension of the dataset (Nickell 1981). Finally, the LSDVC estimator for dynamic unbalanced panel-data models requires strict exogeneity of all regressors (Bruno 2005a, b), which is an unfulfillable assumption in the conducted study.

  14. 14.

    Estimating Eq. (1) in differences also avoids spurious correlations which occur when non-stationary time series are used in a regression model. For further information see Hamilton (1994). Testing for the presence of a stochastic trend in each variable, we find that the dependent variable is stationary whereas the explanatory variables are integrated of order-zero or order-one. Hence, the specification does not suffer from the spurious correlation problem and cointegration cannot be present. For brevity, results of the Maddala–Wu unit root test are not reported but are available upon request.

  15. 15.

    Analysys Mason’s ‘Tripleplay pricing study’ is an international benchmarking survey covering DSL, cable modem, and residential FTTB-based multiplay services for consumers. To ensure data reliability, the information is directly gathered from the companies profiled.

  16. 16.

    All countries included in this study are listed in Table 3. Not all countries enter the data in 2003, thus, we have an unbalanced panel.

  17. 17.

    Other metrics commonly used refer to fixed-line broadband penetration levels measured in 100 of population (e.g., used in Cava-Ferreruela and Alabau-Muñoz 2006; Lee et al. 2011; Gulati and Yates 2012; Lin and Wu 2013) or in 100 of households (Höffler 2007; Galperin and Ruzzier 2013). Results do not change qualitatively if the model is estimated with these alternative specifications.

  18. 18.

    Standardizing the price with the download speed is common in the empirical literature to capture quality differences (Kongaut and Bohlin 2014; Garcia-Murillo 2005; Lin and Wu 2013; Lee et al. 2011).

  19. 19.

    To illustrate some features of broadband tariffs that influence the price variable and the measures for tariff diversity, we take a closer look at the broadband plans offered by one Hungarian ISP in the fourth quarter of 2011. In total, the ISP markets 51 tariffs with monthly access prices ranging from 7.3 to 49.3 euro with an average of 27.8 euro. This price diversity can be attributed to second- and third-degree price discrimination. Regarding the former, the download speed ranges from 1 to 15 Mbps, resulting in significant differences in the average monthly access price (7.3 vs. 31.1 euro for stand-alone offers). In addition, contract durations vary between 12 and 24 months causing, on average, a price difference of 6 euro for contracts with a download speed of 1 Mbps. The ISP also offers seven volume-based plans that are considerably cheaper than flat rates with the same download speed of 1 Mbps (17.2 vs. 27.2 euro). Regarding third-degree price discrimination, there are two stand-alone offers with 5 Mbps download speed available to students only. In comparison to the regular plan a student saves 2 euro, or put differently, a non-student pays a price premium of 11%.

  20. 20.

    Note that the information presented only covers desktop PCs and that this particular market has been relatively stagnant in recent years as an increasing share of people have chosen to buy more portable formats, such as laptops, netbooks or tablets.

  21. 21.

    One advantage of the dynamic estimation approach is the possibility to disentangle short and long-run elasticities. While the short-run elasticities are directly estimated as the coefficients \(\gamma _i\), \(\delta _i\), and \(\varphi _i\), the long-run elasticities can be easily obtained as the fraction of the coefficient and the “speed of diffusion”, \(1-\beta \).

  22. 22.

    Considering the number of DSL, cable, and fiber subscribers separately as the dependent variable, yields comparable results: A positive statistically significant effect of price discrimination on the number of DSL and cable subscribers, and a positive, however, statistically insignificant effect on fiber. The latter at least suggests that price discrimination does not slow down NGA adoption.

  23. 23.

    From a dynamic perspective, as argued by Heatley and Howell (2010), price discrimination can also enable firms to increase welfare by accessing scale economies (static efficiency gains) and to introduce a new technology earlier than under the counterfactual of a single price by capitalizing on economies of scale arising from a steeply-decreasing average cost curve (dynamic efficiency gains). The latter aspect might be especially important for fiber-based technologies given that its demand is still modest in many countries.

  24. 24.

    Note that \(\overline{\text {fms }}\) is a simple average that gives equal weights to every country and period, independently of the population size, and potentially obfuscating considerable variation between countries and over time. In the beginning of the sample period a large share of fixed-line telephony was common. However, during the sample period and especially in recent years more and more subscribers have cut the cord. Given the significant decline in the number of fixed-line telephony subscribers, some countries went from “not enough” to “too much” competition in comparison to the estimated optimal competitive market condition for broadband adoption. Other countries approached the optimum in the last years of the sample period. The finding that the Schumpeterian effect dominates the escape competition holds for all included Central and Eastern European countries in all periods. Moreover, for example, in the Netherlands and in Finland market conditions significantly shifted toward mobile services, wherefore the Schumpeterian effect dominates since 2005/2006. In other countries such as Spain, France, and Sweden the measure for fms fell as well, but remained close to the optimal level. Only in the UK did the escape competition prevail in all years, however, closely approaching the estimated optimum.

  25. 25.

    Variable descriptions can be found in Table 4.

  26. 26.

    Stand-alone offers are by far the most common (46.2%), followed by double-play (28.9%) and triple-play offers (18.3%) of fixed broadband and fixed voice telephony and/or TV. Only a comparatively small share of offers include mobile services.

  27. 27.

    Note that even if price discrimination implies the existence of market power, a high degree of price differentiation does not provide proof that market power is substantial in antitrust trials (e.g., McAfee et al. 2006; McAfee 2008; Klein 2008).

  28. 28.

    Mobile broadband subscription is not part of the baseline specification as its inclusion results in a 20% sample size reduction.


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Corresponding author

Correspondence to Mirjam R. J. Lange.

Additional information

I gratefully acknowledge the hospitality of the Media and Information Department at Michigan State University (MSU) and, in particular, of Johannes M. Bauer, as this paper was partly written while I was a visiting scholar at MSU. For helpful and constructive comments and suggestions I thank Ulrich Heimeshoff, Amela Saric, and two anonymous referees.



See Tables 3, 4, 5, 6, 7, 8 and 9.

Table 3 Countries
Table 4 Variables description and source
Table 5 GDP per capita \(\ge \) 7000 euro
Table 6 Dimensions of fixed broadband plans 
Table 7 Additional cost and demand controls
Table 8 Trade-off competition and tariff diversity
Table 9 Mobile broadband subscription

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Lange, M.R.J. Tariff diversity and competition policy: drivers for broadband adoption in the European Union. J Regul Econ 52, 285–312 (2017). https://doi.org/10.1007/s11149-017-9344-8

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  • Broadband demand
  • Tariff diversity
  • Price discrimination
  • Dynamic panel data analysis

JEL Classification

  • L86
  • L96