Right decision, wrong reasons

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Naomi Palmer
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1 Right decision, wrong reasons Economic issues in the Poundland/99p Stores merger 28 November 2015

2 A wise and sensible decision

3 for in my view the wrong reasons Failure to properly assess barriers to entry/expansion No analysis of real question of interest particularly in a Phase 2 context

4 Entry and expansion

5 Hard to think of a market where entry and expansion are easier (1) Small high street stores Lots of vacancies

Hard to think of a market where entry and expansion are easier (2) Easy to get hold of stock http://www.thewholesaler.co.

6 Hard to think of a market where entry and expansion are easier (2) Easy to get hold of stock Fit out costs trivial Leases easy to arrange Low-skilled staff on minimum wage

7 Levels of entry/expansion are extremely high at a national level CMA s revenue impact analysis had 596 Poundland stores facing 923 entry events within 0.5 miles over the last 5 years and p stores facing 345 entry events within 0.5 miles over the last 5 years

and the parties presented extensive evidence on options in each overlap area Retailer Key Competing Retailers within the Watford Retail Area (c 3m Number on Map Retailer Name Number of Competing

1 15 Wilkinsons Stores 1 17 Best One Stores 1 18 Costcutter Stores 6 19 Musgrave Stores 13 20 Nisa Stores 3 22 Premier Stores 4 23 Spar Stores 3 26 Iceland Stores 1 28 Boots Stores 3 29 Superdrug

8 and the parties presented extensive evidence on options in each overlap area Retailer Key Competing Retailers within the Watford Retail Area (c 3m Number on Map Retailer Name Number of Competing Retailer Units 1 Tesco Stores 1 2 Asda Stores 1 3 Morrisons Stores 1 4 Sainsburys Stores 2 5 Tesco Convenience Stores 6 9 Poundland P Stores 1 11 B&M Stores 1 13 Poundworld/Discount UK Stores 1 15 Wilkinsons Stores 1 17 Best One Stores 1 18 Costcutter Stores 6 19 Musgrave Stores Nisa Stores 3 22 Premier Stores 4 23 Spar Stores 3 26 Iceland Stores 1 28 Boots Stores 3 29 Superdrug Stores 2 31 WH Smith Stores 3 32 Rymans Stores 2 33 Card Factory 1 34 Argos 1 35 Marks and Spencer 1 36 Primark 1 37 Greggs Total 3 64 Maps of retail sites in each local area GOAD data on vacant sites in each High Street (marked in purple)

9 The barriers to entry analysis in full

10 Failure to acknowledge this is a problem for the rest of the analysis Low barriers to entry sufficient to clear merger by themselves remaining analysis superfluous CMA s proposed analytical framework makes little sense when there are low barriers to entry Important to start with a view on entry barriers when considering how to approach case Joint Merger Guidelines place entry barriers after efficiencies does this make sense?

11 What the CMA did and why I don t like it

12 Two approaches to the key merger issue Would prices have gone up after the merger? 1. Simulation approach 2. Outcomes approach CMA did this I prefer this

13 Simulation approaches Full merger simulation Proxy merger simulation (GUPPI, UPP, IPR etc.) Demand estimation (or other way to back out cross-price elasticities) Diversion ratio estimates Marginal costs (or margins) Margins Can t do this data limitations Model of competition Change in ownership structure Assumption of differentiated Bertrand Assumption on cost passthrough (shape of demand curve CMA did this

14 Proxy merger simulation uses common data Proxy merger simulation (GUPPI, UPP, IPR etc.) Aggregate diversion ratio estimates Margins Assumption of differentiated Bertrand Formula (which variants?) Based on revenue impact analysis Adjusted with data from CC survey Parties estimates of variable margins Used linear IPR

15 of which the most difficult data point is the aggregate diversion ratio 1. Identify competing fascia 2. Assume DR = 0 for stores more than 1 mile apart Proximity weight Give a store a weighting of 1 if it was between 0 and 0.5 miles away Give a store a weighting of 0.5 if it was between 0.5 and 1 miles away Fascia weight Give an SPP (Poundworld or 99p store) a weighting of 1 Give a B&M, Bargain Buys, Home Bargains and Wilkinson a weighting of 0.5 Tesco and Asda - weighting of 0.5 Weights drawn from qualitative findings of revenue impact analysis cross-checked against survey evidence.. except for supermarkets, which were added on the basis of benchmarking

16 which then feeds in to the calculation of the national IPR Aggregate diversion ratio 10% from Poundland to 99p Stores and 21% from 99p Stores to Poundland Use variable margins and relative prices NB Aggregate DR takes account of proportion of overlap areas Aggregate price increase c. 1%-2% No problem! Really? Groceries found problems at 0.6% per local area

17 This approach has many problems Aggregate diversion ratio essentially made up Largely arbitrary fascia weights Largely arbitrary proximity weights Results impossible to interpret No attempt to calibrate results Whole number fascia counting is clear But how do we interpret the observation that 150 stores faced less than 1 competitor pre-merger and 292 postmerger? What is meant by a quarter of a competitor? Data available over on competitor set over time from revenue impact analysis Extensive entry means can see differences in aggregate diversions (using CMA approach) Could test impact of predictions on reality

18 particularly failing to deal with easy entry The whole approach is static IPR analysis gives price prediction based on no change in market structure When entry is easy, this approach makes no sense Entry question is different If, post-merger, the merging parties were to increase their prices, would rivals enter in response, to an extent that would offset the price increase? We used to explore this question. Apparently we don t any more. Why not? CMA doesn t recognise this adequately we expected that the expansion of competitors would reduce the aggregate diversion ratio between the Parties compared to the aggregate diversion ratio between Poundland and these expanding competitors (6.152) This is again a static analysis assumes entry plans are fixed but entry plans would not be static in response to any price change this would just create more profitable opportunities is this basically a Phase 1 approach?

19 5 x 100 does not equal 1 x 500 CMA appears to differentiate between the following situations 1. A 5% price increase in 100 locations 2. A 1% price increase in 500 locations This appears to be an SLC in 100 areas This appears to be fine blame the lawyers?

20 My preferred approach

21 A PCA approach is data-based way Would prices have gone up after the merger? 1. Cross-sectional PCA do areas of high concentration have worse performance? 2. Time series PCA do increases in average level of local concentration give rise to reduced performance (or vice versa) We did this CMA could have done this, but didn t of answering the merger question

22 Cross-sectional PCA Performance f Concentration Store characteristics Local area characteristics Proxied by gross margin (cf Groceries) and variable margin - can t use price as national pricing policies Various measures SPP, all VGM, VGM+, presence or absence Size, sales/sq ft., store type, age, time since refurbishment, recently opened Unemployment rate, average earnings, population density, % ethnic minority OLS approach plus IV using doughnut instruments, i.e. population just outside catchment (cf Groceries) argued correlated with concentration as in rivals catchments but not with margins no effect of concentration on margins

23 CMA criticisms not sensible in my view If PQRS is set nationally, then the gross and variable margins and ranges of products will not be determined at the local level so you can t do a PCA (Final Report, Appendix E) True if policy is identical everywhere (e.g. price) Not true if policy is differs but not due to competition but due to e.g. size Margins capture all other factors a la Groceries CMA does its own X-sectional PCA on other characteristics (gross margin, range, store refurbishments etc.) (Appendix F) CMA concludes there is no variation in the offer locally this is the conclusion of our PCA rejection of our approach seems strange Shouldn t include sales/sq ft. (Phase 1 Decision) Demographic controls largely insignificant (Phase 1 Decision) Endogeneity problem instruments used suffer from weak instruments (Phase 1 Decision) Fair enough, but CMA redid the analysis without it no difference So what? Sometimes instruments are weak, sometimes not, results don t change

24 and endogeneity concern irrelevant in the merger context Endogeneity issue: high margin areas (unobserved) attracts entry, distorts pure estimate of concentration effect Argued that need to control for this using instruments I disagree we should be trying to estimate the post-entry effect why are we assuming entry won t happen? IV approach OLS approach Measures effect of change in number of fascia absent entry Standard approach (e.g. Groceries) is to do this but this is the right question Measures combination of change in concentration and any offsetting entry and good instruments are rarely available

25 One relevant criticism remains Cost or demand factors mean that offer doesn t change locally today Might change to local flexing tomorrow? (NB Poundland approach unchanged in 25 years) National price level set at average level of competition could reduce offer across the board CMA approach bottom up analysis of costs of flexing (e.g. complexity, brand damage) CMA approach revenue diversion analysis

past 5 years see entry chart We only had data on competition from 99p Stores CMA had

26 could deal with this using time series PCA Source: Companies House, data not available for 2002 There has been material change in the proportion of competed stores over the past 5 years see entry chart We only had data on competition from 99p Stores CMA had full competitor dataset Did this lead to any change in performance, here measured by margin?

27 CMA didn t try to explore this We accepted that there had been little change in Poundland s gross margins over time and also that since 2000, Poundland had faced increased competition (in terms of a greater number of local overlaps) from both SPP and VGM retailers. However, this analysis does not control for other factors that have also changed over this period. For example, Poundland has significantly expanded its network of stores and the sector has seen shifts in consumer behaviour. We considered that without controlling for these other factors, it was not possible to identify a relationship between gross margins and intensity of competition. Poundland has significantly expanded its network of stores The sector has seen shifts in consumer behaviour Why would this affect margins? Why can t you control for this? Why would this affect margins? What is a potential factor that exactly offsets the massive reduction in concentration? (As a matter of balance of probabilities.) This criticism affects the revenue impact analysis as well Counsel of despair?

28 Conclusion

29 Methodology and precedent troubling Aggregate diversion ratio approach is worrying Heavily assumption driven, no idea how to interpret the results, no attempt at calibration to reality Potentially relevant where you can t do a PCA (not the case) Like trying to do a Phase 1 approach in Phase 2? Rejection of PCA is worrying Approach to entry is terrifying Contradicts identical approach used in previous cases e.g. Groceries Internally inconsistent arguments within CMA report, which comes to the same conclusion on X-sectional PCA Endogeneity concern is not relevant with low barriers to entry Over 1,000 entries in 5 years still not enough for barriers to be low can we imagine a situation with lower barriers? Entire methodology assumes static concentration picture Choice not to write up awkward evidence? If so, why? even if outcome was correct

Frontier Economics Limited in Europe is a member of the Frontier Economics network, which consists of separate companies based in Europe (Brussels, Cologne, London and Madrid) and Australia

30 Frontier Economics Limited in Europe is a member of the Frontier Economics network, which consists of separate companies based in Europe (Brussels, Cologne, London and Madrid) and Australia (Melbourne & Sydney). The companies are independently owned, and legal commitments entered into by any one company do not impose any obligations on other companies in the network. All views expressed in this document are the views of Frontier Economics Limited.

31 FRONTIER ECONOMICS EUROPE LTD. BRUSSELS COLOGNE LONDON MADRID Frontier Economics Ltd, 71 High Holborn, London, WC1V 6DA Tel. +44 (0) Fax. +44 (0)

The G roceries Groceries Remittal Decision Decision Some concerns 12 November 2010

The G roceries Groceries Remittal Decision Decision Some concerns 12 November 2010 The Groceries Remittal Decision Some concerns 12 November 2010 Disclaimer My views Not the views of Frontier Or of Tesco My conclusion: the remedy is unsafe Based on a misreading of the analysis in the