Quantitative analysis in M&As evaluation

1. Quantitative analysis in M&As evaluation Ha Long, Vietnam – 13&14 August 2005 Dr. Patrick Krauskopf, Vice-Director, Fanny Raess, Swiss Competition Commission

2. Structure of Presentation • Introduction • Role of quantitative techniques • Frequently used quantitative analysis tools • Price correlation analysis • Own-price and Cross-price elasticity analysis • SSNIP Test • HHI • Analysis of the modification of the competition structure 4. Conclusion

3. 1. Introduction • Objectives of the presentation • Preliminary comment: Description of the pre-merger situation to analyse the behavior of the competitors • Perfect competition • Monopolistic/Oligopolistic competition • Contestable markets • Dominance assessment (single vs collective)

4. 2. Role of quantitative analysis • Quantitative analyses can (and should) provide important evidence in an merger evaluation • Quantitative evidence should be viewed as complementary to the qualitative evidence

5. 3. Frequently-used quantitative analysis tools • Using quantitative approach to: • Define the relevant market • Evaluate the merger impact • The choice of technique will depend on • the specific circumstances of the case • the availability of data • It is possible that more than one technique could be usefully applied to any particular case

6. a) Price Correlation - definition • Standard tool in evaluating product market definition • Prices of products in the same market are expected to move together over time • Basis of the approach: • Examine whether price levels move together • Quantify the extent to which price levels move together over time. This is measured by the correlation coefficient • The correlation coefficient can vary between + 1 and –1 • correlation of +1 => prices moving perfectly together • correlation of -1 => prices moving perfecty inversely to one another • correlation of 0 => no statistical association between the two series

7. a) Price Correlation - Example • Are still water, sparkling water and soft drinks in the same relevant product market? • The price correlation analysis showed that: • Panel A: Correlation between prices of water brands and soft drinks is weak • Panel B: Correlation between prices of still and sparkling water brands is high => the market should include still and sparkling waters but should exclude soft drinks. Illustration (source: Lexecon) Panel A: Low correlation coefficient (< 0.3) Panel B: High correlation coefficient (> 0.9)

8. b) Own and cross-price elasticities (ε) - definitions • Standard tools in evaluating product market definition • The own-price elasticity measures the percentage change in quantity (Q) of good X for each percentage change in the price (P) of good X • If ε is high => P increase is not likely to be profitable (ex: Pepsi) • If ε is low => P increase is likely to be profitable (ex: Petrol) • The cross-price elasticity measures the percentage change in quantity (Q) of good X for each percentage change in the price (P) of good Y

9. b) Own and cross-price elasticities – example (1) Market: Petrol Companies: Shell, Agip, Esso, BP, Totalfina • If Pshellincreases => Qshell decreases and Qotherbrands increases => εShellis high • If Pmarket increases =>Qmarketis only sligthly decreased => εmarketis low

10. b) Own and cross-price elasticities – example (2) • Pepsi - Coca-Cola If Ppepsiincreases => consumers will switch to Coca-Cola => Q Coca-colawill increase => Pepsi and Coca-Cola are substitutes (εqp > o) • Wine - Water If P Wine increases => consumer will not change their water consumption => Qwater will stay constant => Wine and Water are not substitutes (ε qp = o)

11. c) SSNIP Test (small but significant non-transitory increase in price) - definition • Standard tool in evaluating product market definition • It is a « hypothetical monopolist test » • Tests whether a good or a set of goods define a relevant product market • The question is: « what type of constraints does the presence of other goods place on the producer of the good in question, when he decides to increase his price by 5-10%? »

12. c) SSNIP Test - example • 3 goods: Apple (A), Pear (P) and Banana (B) Are they part of the same relevant product market? • If all the producers of A can profitably introduce a small but significant and non-transitory increase in price, despite the existence of P and B => the relevant market is made of A only • However, if consumers, on reaction to this increase of price of A, significantly shift to P => P are added to the relevant market, as the producers of A have no market power (unprofitable price increase) • Same process with A and P together, until a profitable price increase is found

13. d) HHI - Herfindahl-Hirschman index – defintion (1) • Measure of market concentration HHI = Sum of the squares of the market shares • The closer the market structure is to a monopoly, the higher the market concentration (and the lower the assumed degree of competition) • In many juridictions, HHI is not considered as direct evidence, but as an indicator for further analysis

14. d) HHI as a screening device (EU) • HHI < 1000 => Unlike to challenge • 1000 < HHI < 1800 and ΔHHI < 100 => Unlike to challenge 1000 < HHI < 1800 and ΔHHI > 100 => Likely to challenge => Further analysis needed • HHI > 1800 and ΔHHI < 50 => Unlike to challenge HHI > 1800 and < 50ΔHHI < 100 => Likely to challenge => Further analysis needed HHI > 1800 and ΔHHI > 100 =>Likely to challenge

15. d) HHI -Example • Pre-merger: 5 firms A 30%, B 25%, C 25%, D 10%, E 10% The HHI is: 302 + 252 + 252 + 102 + 102 = 2350 • If B mergers with D, 4 firms A 30%, B/D 35%, C 25 %, E 10% The HHI is 352 + 302 + 252 + 102= 2850 Δ HHI is 2850-2350 = 500 • Interpretation: HHI > 1800 and ΔHHI > 100 =>Likely to challenge

16. e) Analysis of the modification of the competition structure • Based on the market shares, is the merger likely to induce a structural change in the market structure? • Examples: • Perfect → Oligopolistic competition? • Increased probability of collective dominance or cartellization?

17. 4. Conclusion • Empirical economic analysis lies at the heart of modern competition policy • Econometric analyses does not “come from out of the blue” • Potential weakness of the tools: lack of data, asymmetry of data (firm/authority) • Role of economists is complementary to the role of lawyers