EC930 Theory of Industrial Organisation

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EC930 Theory of Industrial Organisation
Mergers and Merger Control , spring term

Outline: Market Power Gains of (Horizontal) Merger Merger Paradox Merger Efficiencies Pass Through Market Power and Efficiencies in an Equilibrium Context Merger Approval Measuring the Effect of Merger Market Definition Readings: Lecture notes 9 Optional: Cabral – chs 9, 15

The contract curve traces out the tangencies of the
isoprofit contours. As profits increase according to a negative relation between q1 and q2, the tangency cannot occur at a point of negative slope of the isoprofit contour. A point of zero or infinite slope cannot be a point of tangency, as it is never the case that both isoprofits have zero or both have infinite slope. It is possible, however, for both to have positive slope and be tangent. All such points lie to the left of the reaction functions. Furthermore, the total output must sum to QM, where the merged firm is indifferent about which “unit” produces the output if both “units” have the same marginal cost. Effects of Merger: Output Reduction q2 R1 q2M R2 q1M q1 Contract curve

Merger Paradox Example: P = 1-Q; c = 0; N identical Cournot competitors 𝜋 𝑖 = 1 (1+𝑁) 2 . Let two firms merge in each configuration (to create N-1 identical Cournot firms): N pre-merger Firm i profit per firm pre-merger Pre-merger total profit Post-merger total profit per firm Post-merger profit per merged firm 1 1/4 2 1/9 2/9 1/8 3 1/16 3/16 1/18 4 1/25 4/25 1/32 5 1/36 5/36 1/50

Intuition: When firms merge in a Cournot industry, they tend to cut output (as we saw above) But this induces the rival(s) to increase output since the reaction functions slope down. This means that the merged entity creates a positive externality on rivals by decreasing output and so raising market price – but they “take advantage of this”, creating a negative externality on the merged entity when they increase output and so lower price. Clearly, this reasoning doesn’t hold in the case when no rivals remain after merger.

But firms do merge…so how can we resolve this paradox? Price competition with product differentiation: Reaction functions slope upwards, so any merger must be profitable, even without efficiencies, as the reaction of rivals tends to raise price even further. Capacity constraints can limit rivals’ reactions. If no increase in rival output under Cournot, then merger must be profitable. But unconstrained Cournot still seems like a reasonable model…so what is wrong?

Efficiency Vs. Market Power in Merger
One solution is cost efficiencies… While it is clear that this can create an incentive to merge for the firms, does it also create a benefit for consumers? If total output falls along this contract curve compared to the non-merger output, then consumer surplus will tend to fall. However; clearly, if one “unit” faces lower marginal cost, allocating all production to that unit is the Pareto efficient allocation between the two firms, assuming that profits can be transferred easily across units. Output may rise in this case, so consumer surplus may also rise. This is an example of merger-specific efficiencies that can offset the market power effect of a merger.

Pass Through and Merger Efficiency Gains
Competition authorities value such efficiencies and may clear a merger if they exist. This assumes efficiencies apply to marginal cost. If fixed costs are saved, then the price effect of the merger is less clear and so approval is less clear as well. Further, it assumes that some of the cost saving is “passed through” to consumers via lower prices. This depends on the elasticity of the residual demand of the firm: Recall from lecture 2: first order condition of firm i in a Cournot setting is: 𝑃 𝑖 1− 1 𝜀 𝑖 = 𝑀𝐶 𝑖 Where 𝜀 𝑖 =− 𝜕 𝑞 𝑖 𝜕 𝑝 𝑖 𝑝 𝑖 𝑞 𝑖 . Hence, the larger is the elasticity of residual demand, the larger the effect of a (marginal) cost reduction on price. This, in turn depends on overall demand elasticity and number of competitors.

Balancing Market Power and Efficiencies (Farrell and Shapiro, AER, 1990)
HHI/CR based rules (lecture 2): 1. Market Shares may be wrong Suppose we use change in HHI or CRi as basis for rejecting merger. But these assume that post-merger shares are just sum of pre-merger shares. Eg. In ten firm industry with equal market shares  CR3 = 30% pre-merger of any pair of firms and CR = 40% post-merger. But if market shares equalise, post-merger then CR3 should only be 34%... Hence, we need to conduct equilibrium analysis to know what true market shares will be. Rise in HHI/CR may not decrease welfare under asymmetries While HHI rules justified by Cournot behaviour when identical firms, if some have lower cost, then transfer of output towards more efficient producers may raise consumer surplus.

Suppose, then, that two firms merge that have different costs
Suppose, then, that two firms merge that have different costs. They can reallocate production after merger across the “units” but obtain no other cost benefits (“rationalisation” of production); then: the merger will cause price to rise when it allows rationalisation of production. In other words, the effect of decreasing market competition always dominates the effect of rationalising production. This is bad for consumers. Example: Two Cournot competitors merge to monopoly. c1 < c2. The merged firm will allocate all production to unit with lower cost. Pre-merger: Ppre = (1+c1+c2)/3 Post-merger: Ppost = (1+c1)/2 If 1-2c2 +c1 > 0 then post merger price is higher. But (1- 2c2+c1)/3 is pre-merger output of firm 2, so if firm 2 was producing pre-merger, as we have assumed, price must rise.

If we allow for synergies beyond rationalisation (so that costs fall in the post-merger
firm beyond what the constituent parts could obtain pre-merger) then the larger the market shares of the merging firms, or the smaller the industry price elasticity of demand, the greater must be the synergies in order for price to fall post-merger. Specifically: 𝑐 𝑀 <𝑝(1− 𝑠 𝑖 𝜀 ) where cM is merged cost, i firms merge and the sum of market shares is taken over these i firms; ε is price elasticity of demand, and p is pre-merger price. All variables are measured pre-merger. Recall that the usual first order condition in the Cournot equilibrium sets: ci = p(1-si/ε). Farrell and Shapiro’s condition observes that pre-merger price must be “too high” if the outputs that generate it (and the consequent market shares) don’t generate equality for the merged entity. The merged entity will have an incentive to increase output so price must fall (compared to pre-merger levels) – in equilibrium.

Generally, cost savings must be substantial for cost effects to dominate
price effects (so that consumers are helped by the merger). This is confirmed in linear examples, for instance. Furthermore, from the F&S condition: If elasticity is small then price effects of changing output are likely to be large – so cost savings must rise. If market shares are large, then the effect on output when they merge is also is large, so the price effect is large -- and cost savings must rise. Elasticities will depend on the number of firms in the industry, so indirectly we still have some reason to look at concentration and market shares.

Finally, a (Cournot) merger will tend to (1) decrease merged firm total output compared
to individual outputs pre-merger, (2) increase non-merged firm total output, (3) raise price. If we take the perspective of total welfare of all firms and consumers, does the negative effect on consumers dominate the positive effect on non-merged firms? No. The reason is that the increase in non-merged firm output raises both consumer welfare and non-merged firm welfare share. Indeed, Farrell and Shapiro find that: If m of the N firms in a Cournot market merge, then as long as their initial joint market share is not too large, any profitable merger that raises price also raises total welfare. Indeed, if the external market share is large, then the output effect on outsiders is large compared to the output reduction effect of insiders, triggering welfare gains. (Notice that if we just merged firms with no cost saving, the merger would not be “profitable”, so we should not see any gains. This condition requires some kind of improvement in cost.)

Methods for deciding whether a merger will create harm:
Merger simulation (see Salmon/Deodorant cases, reviewed earlier): calculate equilibrium pre- and post-merger and compare welfare (examples in notes). These are time-consuming and must necessarily rely on a lot of assumptions. Robustness checks increase time involved. Mergers often require some speed to maintain potential profitability/interest. This method is the best justified by theory, however. Consultation exercises with industry/consumer/buyer groups These are interested parties, so teasing out unbiased information is hard and final consumers tend to be poorly informed about merger effects.

HHI/CR We have just seen this is not equilibrium analysis, and so is theoretically flawed; on the other hand, concentration and market shares can give a hint of effect of merger. (Note F&S final condition!) This could be a useful first step. Rule of thumb that has been used: US: HHI < no need for further investigation 1000 < HHI < maximum “safe” change in HHI due to merger = 100 HHI > maximum “safe” change in HHI due to merger = 50 EC: HHI < no need for further investigation 1000 < HHI < maximum “safe” change in HHI due to merger = 250 2000 < HHI maximum “safe” change in HHI due to merger = 150 ie: 10 equally sized firms or more  no problem 5 equally sized firms or fewer  very tough view 8 firm industry where two firms merge  safe (HHI inc. about 200) in EC only 6 firm industry where two firms merge  not safe anywhere.

Diversion Ratios Suppose the price of product i rises (all others held constant). Define: The diversion ratio of product i to product j: The proportion of this product’s loss in sales that moves to substitute product j is dij = (sales of i moving to j)/(total loss in sales to i). when firms producing i and j merge, the merged entity internalises the diversion effect of a change in price – so it is more willing to raise price. Hence, if the diversion ratio is large, the effect of the merger on price should also be large.

The larger the profit margin on product j, the larger the effect on the price of i
when the firms merge since by raising the price of i, the merged firm can divert sales to the higher margin product. If the two products have the same marginal cost, this effect can be captured by adjusting the diversion ratio by the price ratio: GUPPIij = dij(pj/pi) If costs differ, an alternative measure uses the gross margin (this will be derived in a few pages): GUPPIij = dij(mj)pj/pi In practice GUPPI > 10%  investigate further GUPPI < 5%  don’t investigate further Note that (1) GUPPI > 10% means something different when underlying demand shape is different (2) measured diversion ratios due to historic price changes may result from changes in preferences or other factors. On the other hand, they are quick and require little data and easy to apply for differentiated products.

While the number of bidders is clearly relevant in auction markets, the equivalent
of diversion ratios – the ranking of bids -- can be more informative since, by identifying the “runner up” in each auction, we can get an idea of the effect of a particular merger on the transaction price paid. eg. In a second bid auction, the second “highest” bid is the transaction price, so a merger between the top two firms could affect transaction price whereas a merger involving a much less competitive firm might affect price little. Market shares can potentially be used as a similar proxy over time, since they give us an idea of which firm(s) have been successful in the past and so the firms that are most active in affecting market price. Taking these together, we could for example investigate: Pi = a + bNi + cAi + dBi + gAiBi Where i is the auction market, N is the number of firms participating, A and B are dummy variables set to 1 if firm A or B participates in the bidding. g and b measure the effect that A’s and B’s bidding have on each other and the effect of changing the number of bidders per se.

Diversion Ratios and GUPPI’S: An Application to Wembley/O2 Merger
We discussed “GUPPI” measures the price effect (ie consumer harm) of a merger. We used the Wembley, O2 merger as an example, so the subscripts will be W for Wembley and O for O2. We define (one version of) the GUPPI as follows: GUPPIw,o = dw,omo[po/pw] = Value of W’s lost sales recovered by O2 divided by revenues lost by W when raise price. What does this try to measure? The upward pressure on prices due to the merger. Why should prices tend to rise with the merger? When any firm raises price, it loses some sales from the market entirely and loses some sales to competitors. eg. When VW raises price, it creates some people who use bicycles or motorbikes instead and also creates some people who buy a Peugeot instead. If Peugeot and VW were to merge, however, then some of the diverted sales would remain “within the company” and so the company is “less hurt” by the same price rise than pre- merger. Hence, there is an upward pressure on price caused by the merger.

Derivation of GUPPI Let Qw (Po,Pw) = demand function of Wembley (pre-merger) Qo (Po,Pw) = demand function of O2 (pre-merger) A Wembley price increase raises O2’s pre-merger sales, and the firm gets a profit margin on each of these sales. Hence, the “benefit” to the O2 of Wembley’s lost sales is: Where the marginal cost of O2 is co. And the revenues lost by Wembley when it raises its price are: 𝜕 𝑄 𝑤 𝜕 𝑃 𝑤 𝑃 𝑤 In other words, the revenue effect on Wembley is the product of the lost sales and the price on each of these sales.

The ratio of these two quantities is the GUPPI:
𝜕 𝑄 𝑤 𝜕 𝑃 𝑤 𝑃 𝑤 = 𝜕 𝑄 𝑜 𝜕 𝑃 𝑤 𝜕 𝑄 𝑤 𝜕 𝑃 𝑤 { 𝑃 𝑜 − 𝑐 𝑜 𝑃 𝑤 } { 𝑃 𝑜 𝑃 𝑜 } = 𝑑 𝑖𝑗 𝑃 𝑜 − 𝑐 𝑜 𝑃 𝑜 𝑃 𝑜 𝑃 𝑤 = 𝑑 𝑖𝑗 𝑚 𝑜 𝑃 𝑜 𝑃 𝑤 = diversion ratio (of total sales decrease of Wembley that are recovered by new partner) x (margin on sales) x (price ratio). This is what we defined the GUPPI as at the beginning of the presentation…

π P*w P**w Price Pre-merger optimum Post-merger optimum The GUPPI essentially measures the slope of the profit function at the pre-merger point. The larger is the slope, the farther to the right the post-merger price will lie. The problem is that the GUPPI doesn’t tell us exactly how far to the right the new price will lie. This is because the shape of the profit function matters…and the GUPPI only reflects the local shape. The merger may create a large change, though. In practice, linear demands often are used. In this case a 5-10% GUPPI will be enough to generate sufficient price rises that merger will be viewed as problematic (causing a 5% or greater rise in price.)

A full-fledged merger simulation (as we discussed earlier in term with fish and shampoo)
would give an idea of the precise shape of the profit function…but is costly. Hence, GUPPIs are used to get a first look at whether a full simulation model would be worth the cost. If the GUPPI is too high (5% or more) then probably not… Wembley specifics Ancillary Income: If O2 has ancillary activities (like restaurants and parking) then the profit margins at the O2 may be, effectively, higher than otherwise would be. This tends to raise the mo term in our expression for the GUPPI. If this term rises, then we should expect the post-merger price rises at Wembley to be *larger* than the basic GUPPI predicts. We could formalise this idea as follows: Pre-merger, Wembley maximises (WRT Pw) :( 𝑃 𝑤 − 𝑐 𝑤 ) 𝑞 𝑤 ( 𝑃 𝑤 , 𝑃 𝑜 ) Post-merger, Wembley maximises (WRT both P) :( 𝑃 𝑤 − 𝑐 𝑤 +∆ 𝜇 𝑜 ) 𝑞 𝑤 + ( 𝑃 𝑜 − 𝑐 𝑜 +∆ 𝜇 𝑜 ) Where Δμo = ancillary sales from services at the venue.

We can manipulate the first order condition with respect to Pw to get the modified
GUPPI that is appropriate to this case. The modified GUPPI behaves quite differently: To get the 5% “modified” GUPPI that is the “trigger” for a negative evaluation by competition authorities, and for an ancillary profit measure of £10k per event, for example, to get a 5% upward price pressure, we would need a “basic” GUPPI Of 11%. And for an ancillary profit of £40k per event, we would need a “basic” GUPPI of 39% to get a 5% upward price pressure. The intuition is that the ancillary revenues create an incentive for the firms to price the event low in order to pull customers in and then profit from the ancillary services. Hence, the change in business model projected for Wembley to ancillary service revenue from solely event revenue will tend to create a downward pressure on event prices. Factoring this into the upward price calculation makes a big difference to how much we predict the O2-Wembley merger will affect ticket prices for customers.

Statistical Methods Check past relation between price and concentration using panel data: Pit = ai + bHHIit + cXit + errorit … run for large number of markets, I, (countries/states) and time periods, t. and variables usually measured in logs and X is set of controls (eg country size) From this, we can infer the price effect of a proposed merger once we know HHI and change in HHI due to the merger. As this is based on historical data, specific information for this merger, such as entry or cost savings will not be taken into account.

Market Definition HHI/CR requires some definition of the market – other methods (diversion ratios) don’t. SNIP test usually determines this. Say Coke wants to merge with Innocent Smoothies: Start with narrowest market (Coca Cola). Would it be profitable for Coke to raise its price 5% for a sustained period – if it were the only competitor in the relevant market? If so, then stop. Coke’s merger probably won’t affect price (since Coke is a market on its own). If not, increase definition (Any cola) because the price rise clearly would divert a lot of sales to “substitute” products. Would it be profitable for these firms, acting as a monopolist, to raise price 5% for a sustained period? If so, then stop. Coke’s merger won’t affect price since colas form a separate market. If not, increase definition (all sodas)… (all beverages)… Then compute market shares for appropriate definition. V. big markets  small merger effects; V. small markets  small merger effects.

Cointegration of prices often used to indicate similar markets (salmon case)
Cross price elasticity or diversion ratios also used. Consumer surveys used. Or…diversion ratio can be used in order to avoid having to define a market in a first step. The diversion ratio allows diversion to be measured and taken as an indication of market definition. Since market definition is divisive, it can be better to skirt around this issue.

Summary Mergers can confer an externality on non-merging firms This externality can reduce the benefits of merger, despite market power gains overall for the market. Efficiencies can counteract the market power effect The extent to which efficiencies are passed through to consumers affects this gain and depends on the elasticity of (residual) demand which, in turn, depends on concentration. Concentration ratios by themselves are not well theoretically justified. Neither is HHI, as we need to compare equilibrium shares and prices rather than use pre-merger shares. This is harder and takes more time, so non-equilibrium analysis often done first to narrow down the number of merger cases viewed as “problematic” When we do this, the link between HHI and price/welfare is less clear as merger can allow for rationalisation of product even if it doesn’t create synergies. Synergies make the argument for HHI even weaker. Indeed, if not too many firms merge, any profitable merger may raise (total) welfare! Market Definition a first step to any HHI/CR analysis, although diversion ratios can “short circuit” this step.

References Farrell, J, and C. Shapiro (1990) “Horizontal Mergers: An Equilibrium Analysis”, American Economic Review 80(1),