Briefing. Mobile prices in Austria

Transcription

1 1 Frontier Economics May 2015 Briefing Water Energy Environment Retail and Consumer Transport Financial services Healthcare Telecoms Media Post Competition policy Policy analysis and design Regulation Strategy Behavioural Economics Dispute support services Market design and auctions MAY 2015 Mobile prices in Austria CONSUMER IMPACT OF THE MOBILE MERGER IN AUSTRIA There has been considerable interest and debate on what has happened to mobile prices and consumer welfare in Austria since Hutchison and Orange merged their operations in late This topic is important not only for consumers in Austria, but also for those contemplating similar mergers in other European markets and the public authorities who will be required to review them. This briefing is intended to help set out what can be said with confidence given the data that is available today. Our key conclusion is that the average mobile consumer in Austria is likely to be better off than they were before the merger, as they are consuming significantly more data, whilst spending about the same on mobile services. 1 Frontier Economics provided a view on this topic in our report for the GSMA published in The Austrian regulator, the RTR, has since published its own analysis at Rewheel, has published various notes, including one critical of the Frontier analysis. 2 For this note, Frontier has relied upon the RTR s published data which covers the period until Q The Austrian operators have also provided data for to both RTR and to us which has yet to been published by the RTR but which we include in our analysis to ensure that it is as contemporary as possible.

2 MERGER MERGER MERGER MERGER LITTLE DOUBT ABOUT THE BASIC FACTS IN AUSTRIA Disagreement ought not to arise over the basic facts of the Austrian mobile market. Using data received from mobile operators, the Austrian regulator, RTR, publishes data about the industry s performance on a regular basis 2. The following graphs, which are based on RTR data, show that: Steady revenues. Total mobile industry revenues have fluctuated since the merger but were at broadly the same level in as they were when the merger was approved in late 2012, although the rate of decline in revenues has reduced relative to trends prior to the merger. Similar consumer expenditure. Revenues per SIM card and the number of SIM cards used in Austria are also both broadly the same in as before the merger, which suggests that the average consumer is not spending any more on mobile services today than they were before the merger. Rapid increase in data usage. Data usage has more than doubled since the merger. Significant increase in download speeds. Download speeds on mobile data networks have increased from under 5 Mb/s in late 2012 to over 16 Mb/s in December Figure 1. Market trends in Austria TOTAL REVENUE AVERAGE REVENUE PER SIM (per month) 573m m m Q Q Q Q Q Q Q Q Q Q bn 6.6bn 23.4bn 4.66 mbps mbps DATA USAGE MOBILE DOWNLOAD SPEEDS Q Q Q Q Q Q For this note, Frontier has relied upon the RTR s published data which covers the period until Q The Austrian operators have also provided data for to both RTR and to us which has yet to been published by the RTR but which we include in our analysis to ensure that it is as contemporary as possible.

3 Source: RTR Data ( and Ookla ( for download speeds WHAT DETERMINES CONSUMER WELFARE IN MOBILE MARKETS? Economists and public authorities are generally concerned with consumer welfare. This is a difficult concept to capture because only consumers themselves really know what makes them better off (and sometimes even then they are mistaken!) and because this can vary enormously between individuals. Nonetheless, we can begin to gain some insights about changes in welfare and attempt to quantify them by considering what consumers are prepared to pay for services, and what they get in return for their money. Unfortunately, although it is relatively easy to get information on what consumers pay, it is often harder to measure what they get in return. Quality One aspect of what consumers get for their money relates to the quality of a service. This is relevant to the Austrian mobile market, given the significant increase in download speeds since the merger. Benefits from changes in quality can be difficult to value and measure. No commentary on the development of the Austrian mobile market that we have seen to date attempts to do so. However, increases in speed are often associated with increases in data volume consumed by users. As such, changes in consumed data volume (which we can measure) provide us with an indirect indication of changes in quality even if it may not fully capture this effect. Potential or actual volumes A large number of mobile tariffs are characterised by flat charges for a bundle of voice calls, messages, and data, with charges per unit of consumption applying outside the bundle. This raises the question of whether what consumers get in return for their money is better measured by the size of their bundle or by their actual usage of voice, messages and data. Changes in actual usage are relevant to any attempt to measure changes in consumer welfare over time. For example, a consumer who pays the same as before and now uses more data is unambiguously better off and a consumer who pays more but uses more data is not necessarily worse off. It is less clear how changes to the volume of data purchased as part of a bundle, but not used, is relevant to consumer welfare. Many will attach some value to having a bundled tariff which exceeds their expected usage. This allows them to avoid overage charges or to vary their usage from one month to the next without having to constantly change tariff. So a consumer who pays the same as before for a bundle which now has a smaller data volume limit may be worse off, even if their usage never exceeds either limit. However, any welfare changes that derive from changes in unused data volumes are likely to be far outweighed by changes in welfare associated with changes in used data volumes. Whereas usage can also be expected to change over time, benefits from unused usage are unlikely to change very much over time. This is

4 why changes to actual consumption, absent any evidence to the contrary, are likely to be the most appropriate measure of changes in consumers welfare. Average or individual welfare Another aspect of this debate relates to whether the concern should be about changes to the welfare of Austrian mobile consumers in general (or average consumer), or whether the concern should be about the welfare of a particular sub-group of consumers, such as those on a particular tariff or those taking new subscriptions. Public authorities might legitimately be concerned with both, although competition authorities reviewing mergers will generally focus predominantly on the impact of a merger on overall welfare, recognising that any changes in the structure of tariffs in markets will invariably favour some consumers over others. Mergers may lead to such changes as a result, for example, of the merged entity changing its strategic focus or being able to compete more strongly for higher value customers. The only analysis that can be reliably undertaken using the published RTR data for Austria is to consider overall consumer welfare, since the RTR only publishes data on volumes consumed by all Austrian consumers. In order to understand what is happening to the welfare of consumers on individual tariffs 3, or other sub-groups of consumers, the RTR would need to publish data on consumption levels and patterns by tariff and unit prices for each type of user or tariff would need to be derived. HOW TO MEASURE CONSUMER WELFARE IN MOBILE MARKETS Mobile markets tend to be characterised by a large number of tariffs. Such tariffs will typically include varying allowances for voice, messaging and data usage included with the bundle. In addition, there will typically be charges for out-ofbundle usage with the charges depending on the type of usage. All of these factors mean that it is not straightforward to calculate a single and accurate measure of prices in mobile markets. There are various ways in which prices can be measured in mobile markets, including: Price indices. These indices try to calculate how prices change over time for different groups of hypothetical subscribers, who consume different baskets of mobile services, by using different actual tariffs. The key challenges are working out how the usage of these consumers could be expected to change over time, and what tariffs they would choose as a result. The RTR itself adopts this approach. One of the key issues with RTR s approach is that the consumption baskets of the hypothetical consumers get larger over time, 3 Note that even in this case, examining how an individual tariff may change over time may not provide a reliable indication of whether consumers are better off, as consumers will in general be expected to change tariffs over their lifecycle as mobile subscribers.

5 given that data usage is rapidly increasing 4. This means that it is difficult to infer consumer welfare changes from RTR s price indices, because even if consumer expenditure were increasing (which is not the case based on Figure 1), then it is unclear that consumers are worse off because they are also consuming more 5. Average Revenue Per User (ARPU). Rather than relying on hypothetical consumers, an alternative approach is to calculate consumers actual average expenditure. This is done by dividing total revenues by the actual number of users. This approach may provide a reasonable measure of prices when the amount of usage is relatively constant, but given the rapid increases in data usage in many mobile markets, ARPUs may not accurately capture unit price changes. Average Revenue Per Minute (ARPM). This involves dividing total revenues by actual voice usage. Estimating the ARPM will capture changes in voice usage, which may be considered an improvement compared to estimating ARPU, but such a measure will not reflect changes in the number of messages and, more importantly for recent years, changes in data usage. Average Revenue Per Megabyte (). It is possible to convert voice minutes and messages into data equivalents and then add these to the volume of data usage. This allows the Average Revenue Per to be calculated by dividing total revenues by the total number of megabytes. This is likely to represent the most appropriate measure of changes in unit prices because it will capture the impact of increasing data usage on unit prices. However, it is still not a perfect measure of consumer welfare, as it does not directly capture other changes, such as improvements in network quality 6. SO WHAT HAS HAPPENED IN AUSTRIA? Our analysis of RTR data, which measures changes in prices paid and changes in actual consumption by Austrian consumers as a whole, reveals that unit prices (Average Revenue Per Megabyte) for mobile services have unambiguously and consistently fallen throughout the period between the merger in late 2012 and Q The size of RTR s consumption baskets rely upon data on actual usage for different groups of consumers in the previous year. Therefore, a further issue is that there is a mismatch between current tariffs and historic consumption patterns. However, even if actual usage from the current year were used, the indices would still be an unreliable indicator of consumer welfare, given that consumers could be better off, even if the price indices are increasing due to rising usage. 5 Rewheel s analysis of prices in Austria relies on an analysis of tariff data. In particular, it focusses on SIM-only tariffs with unlimited (>1000) minutes and messages, and at least 2GB of data. Given that the average data usage of an Austrian mobile consumer was 0.6GB at the time of the merger (1.3GB in 2014Q4) 5, the tariffs analysed by Rewheel are unlikely to be reflective of the consumption of the average Austrian mobile subscriber. Take-up of the tariffs used by Rewheel is also likely to be low as it focusses on SIM-only tariffs, which only a subset of consumers are likely to use data from the UK indicates that 8% of consumers are on SIM-only tariffs. 6 It will also not reflect changes in the relative valuation of voice and data by consumers over time.

6 Price per (EUR) This means that Austrian consumers in general pay less now for the same service as before or, more likely, get and use much more data now whilst paying about the same. Figure 2. Price per Megabyte in Austria announces acquisition EU approval Source: Frontier based on RTR data The improvement in overall consumer welfare in Austria after the merger is an important conclusion and not one which some others draw. But it does not necessarily mean that all Austrian mobile consumers have found themselves better off in this period. And on the basis of this analysis, a definite conclusion cannot be drawn as to whether unit prices in Austria would have fallen by more or less absent the merger. These are more complex questions which would require more detailed data than is available publicly today to be addressed fully.

7 UNDERSTANDING THE IMPACT OF THE HUTCHISON-ORANGE MERGER IN AUSTRIA HUTCHISON ACQUIRED ORANGE IN THERE HAVE BEEN CONCERNS ABOUT CHANGES IN PRICE INDICES AND THE IMPACT THIS HAS ON CONSUMER WELFARE AUSTRIAN MOBILE MARKET TRENDS AVERAGE REVENUE PER SIM (per month) WHAT IS CONSUMER WELFARE? 18.2 Q WHAT CONSUMERS PAY WHAT CONSUMERS GET 619m Q TOTAL REVENUE Q bn 23.4bn 577m 573m 53.2bn DATA USAGE HOW DO WE MEASURE THIS? TARIFF DATA OR ACTUAL REVENUES? divided by ACTUAL USAGE OR ACTUAL USAGE BUNDLE ALLOWANCES? OF VOICE SMS AND DATA (IN ) AVERAGE OR INDIVIDUAL WELFARE? 0.09 CONCLUSION We use TOTAL REVENUES This gives us AVERAGE PRICE PER PRICE PER HAS FALLEN DOWNLOAD SPEEDS 4.7 Mbps 16.3 Mbps We cannot directly take account of QUALITY although improvements would increase welfare 0.01 CONSUMERS ARE BETTER OFF CONTACT Tom Ovington: Frontier Economics Ltd FRONTIER ECONOMICS EUROPE BRUSSELS COLOGNE LONDON MADRID