Appraisal of the Economic Impact of Competition Policy Enforcement on the Functioning of Telecoms Markets in the EU.

Transcription

1 Appraisal of the Economic Impact of Competition Policy Enforcement on the Functioning of Telecoms Markets in the EU Matthew Weinberg Drexel University March 17, 2017 Drexel University, Gerri C. LeBow Hall, 3220 Market Street, Philadelphia PA

2 1 Overview The structure of the European telecom sector has changed over the past 20 years. A wave of liberalization policies, technological advances in various networks, and increased demand for telecom services has created the possibility for new firms to enter the sector. As a result, prices and the market shares of incumbent, ex monopoly telecom operators have declined across member countries. This is competition at work, and in order for this process to continue to benefit users of telecom services, the competitive process must be protected. The European Commission, national competition authorities (NCA's), and regulators must 1) prevent large, incumbent firms that still own infrastructure from foreclosing recent and potential entrants, 2) identify and block mergers of companies that would reduce competition, and 3) ensure that state aid decisions do not impede realizing the ultimate goal of a single market. The report Economic Impact of Competition Policy Enforcement on the Functioning of Telecoms Markets in the EU provides an overview of competition policy decisions meant to accomplish these goals along with three detailed case studies. The case studies attempt to quantify the impact of a single policy decision in each of these three types of interventions. I was asked to provide an impartial appraisal of this report. I received a draft of the report in September, 2016, and I gave comments on the draft at a workshop held at DG Comp later that month. This is my appraisal of the final report. The remainder of this report has three sections. First, I describe the three types of competition policies studied in the report and briefly discuss each of the case studies. The second section describes the data used in each of the quantitative case studies. The third section describes the methodology used in the ex post evaluations and discusses the interpretation of the results. 2 Typology of Competition Policy Interventions in Telecoms The report clearly explains the rationale for the three types of competition policy interventions. In the 1990's, it was typical for an incumbent former monopoly to have a large market share. Liberalization in part required the incumbent monopolists to allow downstream competitors access to their infrastructure. Competition policy, together with regulation, could be necessary to protect entrants relying on the incumbent's infrastructure from foreclosure or from the upstream firm anticompetitively raising entrants costs or reducing their service quality. Second, mergers, which occur frequently in industries undergoing changes in technology and liberalization, must be allowed when they would boost competition and blocked when they would reduce it. Finally, many European countries have subsidized the provision of basic broadband infrastructure, primarily in rural areas where demand would not be sufficient for a firm to privately reach its minimum viable scale. The European Commission aims to ensure that state aid furthers the objective of creating a single market, while not unfairly advantaging specific firms and distorting competition. In this section I discuss the importance of evaluating

3 the efficacy of each of the three types of competition policy interventions and briefly discuss the specific case in each of the three areas. The lion s share of competition policy decisions were on merger cases. 53 percent of the 1024 competition policy decisions undertaken by the Commission or the NCA's from were related to mergers, largely in mobile markets. In many of these cases an important issue involved preserving the competitive presence of small, but innovative and recent entrants that were aggressively pricing their services in an effort to gain share. Oftentimes this was done by allowing the mergers to proceed subject to remedies. While remedies are clearly an important tool for preserving competition, there are many challenges in implementing them successfully. If the remedy is a divestiture, finding a buyer that would successfully use the divested assets to preserve competition is likely the most challenging in the very markets where mergers are most problematic to start. Furthermore, the incentives driving the choice of the buyer may not be aligned between the competition authority and the merging parties. If the remedy involves the strengthening of a supply agreement, care must be taken that there is no wiggle room for the supplying firm to disadvantage its competitor and successful implementation may require further monitoring and actions. Because of the frequent occurrence of mergers and these challenges in enforcement, studies of the aftermath of competition policy decisions towards mergers are particularly important in my view. The report provides a detailed case study of the merger of Orange and T Mobile's United Kingdom divisions. This merger combined what were at the time the second and third largest of the five Mobile Network Operators (MNOs) operating in the UK. In addition to the five MNOs, consumers could choose the services of several Mobile Virtual Network Operators (MVNOs) providers that offer services over the networks of MNOs through supply agreements, rather than over their own networks. Aside from potentially reducing competition by combining two direct competitors, the transaction raised concerns that the combined firm could reduce competition through changing vertical agreements it had with one of their downstream competitors. Specifically, H3G relied upon Orange for 2G network services and on a joint venture with T Mobile for its 3G network. While the smallest of the 5 MNOs at the time of the merger, H3G was thought to be a close competitor to the merging firms and a leader in service innovations. The worry was that after merging T Mobile and Orange would reduce competition by raising H3G's costs. The merger was scrutinized by both OFT and the EC, and was ultimately approved subject to remedies meant to strengthen the supply agreements with H3G and an agreement to divest spectrum either through auction or an approved private sale. Since the merger was approved Orange and T Mobile introduced a new brand called Everything Everywhere, while gradually removing Orange and T Mobile branded services from the market. In addition, H3G purchased spectrum from Everything Everywhere, pursuant to the remedies. The Orange T Mobile retrospective studies the cumulative impact of the merger and the remedy on mobile prices and investment in mobile infrastructure. The research design contrasts the change in these outcomes before and after the merger in the UK to the change in

4 other European countries that did not experience major changes in market structure during this time period. The hope is that the change in prices and investment in other countries is a good estimate of what would have happened in the UK absent the merger. The second most frequent type of decisions were in other areas of antitrust, largely related to vertical issues in fixed telecoms markets. These accounted for 33 percent of the total enforcement decisions. The access network infrastructure in fixed telecoms markets is often owned by a former national monopolist that also competes in the provision of fixed telecom services. Most of these cases were related to the former monopolist allegedly refusing to allow entrants access to network infrastructure or raising their costs. Despite frequent allegations of anticompetitive vertical practices in fixed telecom markets and the number of cases investigated, there is little current research on these interventions. The report presents a case study of the Telekomunikacja Polska (TP) antitrust case. TP is the incumbent provider of fixed telecoms services in Poland, owning both nation wide fixed telephone and DSL networks. TP has obligations to provide access to its local networks. Beginning in 2004, TP has been subject to regulatory actions by the Polish regulator, Urzad Komunikacji Elektronicznej (UKE), for not meeting these obligations. The Commission began in investigation of the issue in April of 2009, culminating in a decision that TP had refused to supply alternative operators access to wholesale broadband products from August 2005 through October The decision was appealed but confirmed by the General Court in December, The antitrust case study estimates the impact of the Commission's decision on broadband penetration, prices, and connection speeds. The approach is to compare the change in each of these outcomes in Poland before and after the Commission opened its investigation to the concurrent change in a subset of other European countries. The specific comparison countries were selected because they had similar regulatory environments and did not experience any major changes in market structure that could cause their outcomes to diverge from those in Poland for reasons unrelated to the Commission s investigation. The third type of decision relates to state aid, which accounts for the remaining 14 percent of cases. Telecom services like high speed internet access have the potential of boosting employment and wages through reducing the costs of doing business, particularly in geographically isolated areas where private incentives may not be sufficient for investment in infrastructure. Because the benefits of increased economic activity may not only accrue to these areas, there is an argument for publicly funded investment. Studying whether these funds are actually having an impact on service coverage is a natural area for research. The final case study in the report studies the impact of a national and regional German aid schemes on municipality level broadband coverage and market structure. The national program was only implemented in areas that did not have an active broadband provider. The geographic areas where the aid programs were implemented are known and well defined. The impact of

5 the aid programs is estimated by comparing the change in coverage and market structure before and after in regions that received aid versus those that did not. 3 Data Used in the Case Studies Of course, the quality of any ex post evaluation is only as good as the data. While significant effort was made to obtain the best available data for each study, as is often true, some is missing in a way that creates limitations on what can be learned. This must be kept in mind when interpreting the results. This section discusses the data used in each of the three case studies, one by one, and highlights any potential limitations resulting from limited data availability. The merger study aims to determine whether the Orange/T Mobile joint venture caused prices and investment to change. The study uses quarterly data by operator and country that spans the first quarter of 2007 through the final quarter of This gives over three years of premerger data and over four years of post merger data. The authors construct price measures by calculating the cost of obtaining a particular basket of mobile services using tariff data. They then take the unweighted average of the six cheapest tariffs. The authors use capex as a measure of investment, and this data also spans quarter one of 2007 through quarter four of One concern is that the price measure may not reflect actual prices paid, so I think more robustness on the construction of the measure of price would be useful. For example, the study could use the cheapest possible tariff instead of the average of the lowest six. A larger concern is that the tariff data is only available for the two largest firms in each national market. While beyond the control of the authors, this presents three limitations. First, the largest two carriers in the U.K. were O2 and T Mobile, so prices of only one of the two merging firms is in the data. If the merger changed pricing for Orange products differently than T Mobile products, the estimates presented in the paper would not reflect that. Second, an interesting hypothesis is whether the remedies were sufficient to maintain H3G's competitive abilities, but without data on H3G only limited inferences based on market shares and rivals prices can be made. Third, and similarly, the prices of the comparison group may not be representative of typical prices paid by consumers in those markets. Furthermore, the measure of investment used in the study, capex, is not available for all firms in each market. In particular, it is missing for H3G in the UK. The antitrust study also attempts to estimate whether the Commission s decision changed prices, and in addition studies the impact on fixed broadband penetration. The time period in this study spans 2006 through This spans 14 quarters before the Commission began its investigation, and 22 quarters afterwards.

6 Unlike the merger case study, the antitrust case study uses revenue per subscriber as a measure of price. This was collected by operator/country/technology/quarter. An issue is that revenue may change over time because of changes in the composition of what was sold instead of changes in actual prices. If possible, more discussion of whether or not this is a potential concern would be useful. The state aid study examines how basic broadband coverage and market structure changed in response to the aid schemes. The data source is TUV Rheinland Consulting GmbH. Market structure is measured as the number of firms providing a particular service (eg DSL, mobile, fibre, or cable) by municipality, year, and speed. The data spans the years and covers municipalities located in West Germany. The aid schemes were approved between 2008 and While the exact date at which the investment resulting from the aid took place is not clear, it is possible that 2010 is not early enough to identify whether the comparison municipalities' outcomes track the outcomes of the municipalities before the programs took place as one would hope. Therefore the report supplements the TUV data with early data covering broadband availability and network information by municipality and year from 2005 to Methods and Interpretation Each of the three cases in the report is studied with the same statistical technique difference in differences. The basic idea is to use data from a time period before and after each competition policy decision took place for two groups of markets: 1) markets affected by the policy intervention and 2) markets that were not affected but otherwise experience some or all of the other influences as those where the intervention occurred. In its simplest form, the estimator contrasts the change in the average outcome between the two groups. Assuming that the change in the comparison markets is a good estimate of what would have happened in the absence of the intervention, and that unrelated events concurrent with the policy intervention did not impact markets where the decisions took place, the difference in differences estimates the effect of the program. The study builds on this basic approach in two ways. First, by putting the basic estimator into a regression framework so that other measurable drivers of outcomes can be controlled for. Second, the state aid and merger studies construct a composite comparison group by taking a weighted average of prices across the different potential comparison countries. Roughly, the weighted average is constructed so that it best approximates the pre merger evolution of prices in the countries where the mergers took place. The state aid case uses a matching procedure to construct a set of comparison municipalities that did not receive aid. A key advantage of the difference in difference approach compared to simple before and after comparisons is that it can control for events that change the outcomes over time that are common to the treatment and control markets. However, there are several threats to the validity of the results from differences in differences that must be examined. First, the

7 approach assumes that there are no systematic deviations between outcomes in the two groups for reasons unrelated to the competition policy interventions. A key step in validating this assumption is showing that this was indeed true in periods prior to when the intervention took place. Second, it is assumed that the comparison markets truly are unaffected by the interventions. If this is not true and they respond in the same direction as the primary markets targeted by the intervention but to a lesser extent, the difference in difference estimate will understate the impact of the competition events. Third, if there are large differences in the distribution of outcomes across the two groups of markets then the approach can be sensitive to how the outcome was measured. As in any research design, the extent to which any of these threats is an issue must be examined on a case by case basis. The rest of this section discusses these issues and then discusses the results, case by case. 5.1 The T Mobile/Orange Merger Taken at face value, the T Mobile/Orange retrospective estimates that the merger, together with the remedies, reduced prices by between 2 and 18 percent, depending on specification. There is some evidence that investment, as measured by capex, increased, but this result is more sensitive to specification. The main challenge that must be dealt with in any attempt to estimate how this merger changed prices is the presence of strong, pre existing trends in prices that were different across the various countries included in the sample. The issue can be seen in figure 6.1 of the report. Over the course of the three years preceding Orange/T Mobile, expenditures fell from 40 Euros per month to about 15 per month in the UK. The decline stopped roughly when then merger occurred and then remained relatively stable at 15 Euros per month over the four and a half years after the merger. Before discussing the difference in differences approach, note that a simple before and after comparison could be misleading. While it is clear that average quarterly UK prices are lower after the merger than they were beforehand, basically all of the reduction occurred before the merger could have had any impact on competition. The hope is that the difference in differences estimate will correct for this pre existing trend by purging the before and after comparison of the change in prices that was unrelated to the merger. This is done by subtracting off the change in average prices for the comparison countries. In order for the difference in differences to provide a good estimate, it must be that the change in the average price for the comparison countries is what would have been experienced by the UK in the absence of the merger. This is the so called common trend assumption. The plausibility of this assumption can be investigated using data in time periods before the merger could have had any impact. Figure 6.1 shows that the UK prices dropped more rapidly than the comparison countries, casting doubt on the assumption that the common trends assumption is satisfied. In fact, if only the pre merger data were used, a ``placebo'' difference in difference estimate of the impact of a fictitious UK merger consummated in the middle of the pre merger sample would result in sizable, negative price estimates instead of an estimate near zero.

8 The report is very clear about this issue, and is commendable in its transparency. The issue is addressed in two different ways. First, the basic difference in difference approach is put into a regression framework that controls for observable drivers of prices that are not determined by the merger, including linear trends that are allowed to vary freely across countries. Second, the report uses a shorter data window over which there is less of a pre merger difference in the evolution of UK prices and the comparison country prices. This is demonstrated in Figure 6.2. As expected, shortening the event window in this way increases the estimate of how the merger changed prices (i.e. makes the estimated price change less negative), and because there still is a relative decline in UK expenditures prior to the event (though smaller) shortening it even further would likely further increase the difference in difference estimates (i.e. further reduce the estimated price decline in absolute terms). A particularly informative feature of the report is the inclusion of graphs of how prices and capex evolved over the time period studied. This is crucial information in studies that use the difference in differences research design, as it transparently shows whether the comparison groups do a good job of tracking the treatment group prior to the event, and it also shows precisely when any relative change in outcomes took place afterwards. However, one way I think this case study could be improved is to make a tighter connection between these figures and the difference in difference estimates reported in the tables. For example, Figure 6.2 seems to show that on average UK mobile services are cheaper than in the average comparison country for each basket of services, over the entire time period considered. However, after the merger, UK prices increase relative to the average in the comparison countries, except perhaps the low usage basket 2010 basket. This is not reflected in the difference in difference estimates in Table 6.5, and it would be useful to explain why that is the case. For example, is the reason that the figures and regressions do not tell the same story because the outcomes are measured in logs in the regressions and in euros in the figures, or is it because of the regression adjustment for potential confounding determinants of prices. While the T Mobile/Orange merger is a challenging event to evaluate, the report does a good job of presenting the data used to construct its estimates transparently and carefully qualifies its results. This makes it a useful addition to the report. I hope that more studies like it will be completed going forward, and if possible I hope that the data used in this and similar studies will be made publicly available so that other researchers can explore alternative specifications and robustness. 5.2 The Telekomunikacja Polska Antitrust Case The antitrust case study estimates that the TP's refusal to apply reduced broadband penetration by about 3 percentage points. Reassuringly, the impact was concentrated on DLS penetration, precisely where TP was limiting access to its competitors. In that segment, it is estimated that the abused reduced penetration rates by about 7 percentage points. While

9 there is some evidence that prices were slightly increased during the abuse period, most of the results are not statistically significant at conventional levels. 1 The case study takes great care in demonstrating robustness to several important decisions, including the exact time period when the abuse took place and the set of comparison countries. The results suggest that the Commission's decision to initiate proceedings did not have an immediate impact, consistent with the 2010 conclusion from an investigation by the Polish national regulator that competition was still hindered just after the Commission initiated its proceedings. As in the merger study, the figures are a useful complement to the regression results. One thing that stands out is that the typical penetration in the comparison countries is about twice as high as the penetration rate in Poland throughout the time period studied. A technical comment is that when this is the case there is an argument for showing robustness of the results to transformations of the dependent variable. In particular, it would be useful to see regression results that use the log dependent variable as an outcome, as it may be more plausible that penetration rates in Poland and the comparison countries have common proportional changes instead of common changes in the rates. Overall, this is a thorough analysis of the Polish antitrust case. The results are carefully interpreted and presented are presented clearly. The main weakness is a data limitation revenues per user are used as prices instead of tariffs as in the merger study. With better data, more precise estimates of the price effects might be possible. 5.3 German State Aid Schemes The state aid case is a cleanly identified study. This study differs slightly from the other two in that the variation in the program is all within Germany, rather than across countries. Because of the large number of municipalities that did not receive state aid, the authors are able to use a matching procedure to construct a comparison group. The estimates imply that state aid increased broadband coverage by 12 percent for connections of 2 Mbits/s, and about 20 percent for connections of 6 and 16 Mbits/s. State aid is estimated to have increased the number of Mobile and DLS ISP's by.20 and.29 firms. For perspective,.2 is about 7 percent of the common increase in the number of Mobile firms across all regions (.07=.2/2.73), while.28 is 24 percent of the common trend (.24=.28/1.15). Reassuringly, the impact is much smaller on the number of Cable and Fibre ISP's, who were not likely to have received aid. This also shows that state aid did not cause recipients to displace firms using other types of technology. The study also explores heterogeneity in the response and finds that the municipalities that had the largest increases in coverage were those with the lowest pre intervention coverage levels and those that were furthest from main distribution frames. 1 The exception is Model 6 presented in annex Table D 3.

10 The results in this study are compelling. The impact of state aid is largest on the municipalities and for the types of technologies that one would expect. Amongst the municipalities receiving aid, those that received more of it had larger increases in coverage than those that received less. Further, the increases were bigger for Mobile and DSL than for Cable and Fibre ISP's, which were less likely to receive aid. This reduces concerns that pre existing trends are driving the results. The authors are also careful to document common trends in coverage between the municipalities that did and did not receive aid prior to the event. If anything, I think the concern is that the study actually understates the impact of aid. The regression estimates show that all regions, even those that did not receive aid, experienced large increases in coverage over the sample period. The maps documenting the treatment and comparison municipalities show that they are often close to one another. Perhaps the cost of increasing coverage in a municipality is reduced if a neighboring municipality receives aid. If this is the case, some of the comparison group's increase in coverage actually should be attributed to the treatment, and the difference in difference understates the impact. This could be explored by contrasting the change in coverage for municipalities that did not receive aid but neighbored those that did with the change in coverage for more isolated municipalities that did not receive aid. If spillovers on neighboring municipalities seem to exist, it would open up a lot of interesting questions about the optimal assignment of aid when trying to maximize coverage. It would also be interesting to explore whether boosting internet coverage impacts local labor market outcomes like employment or earnings. This might be the case if the internet reduces the costs of transactions, and would be in line with common arguments for why state aid is beneficial. 6 Conclusion In summary, I think this is a carefully executed and detailed examination of competition policy in a dynamic and important industry. My role as a reviewer, however, is to question the results and highlight some issues that might deserve further research, which I tried to do for each of the three cases. None of the skepticism in my report should be interpreted as a criticism of its overall goal of quantitatively evaluating competition policy decisions. The authors have done a commendable job of clearly stating the limitations of each study and they have presented the underlying data in a way that is transparent. Like most interesting research, however, it makes one want to see more work on these cases, either to replicate the results or to explore alternative specifications. Accordingly, it would be useful if the underlying data in the reports were made available to other researchers. In short, reports like this should become standard practice, and I hope to see more.