Assessing Damages in Antitrust Actions


Competition law arguments are sometimes raised by parties in international arbitrations and need to be considered as part of broader disputes between the parties. In such cases, it may be necessary to estimate the damages resulting from competition law infringement.

For a firm that has suffered harm from a competition law infringement, the harm can be defined as the difference between the profits earned in the actual setting (in which the infringement took place), and profits that would have been earned absent the infringement; that is, in the counterfactual situation.[2] Usually, harm will have been suffered for several periods, either because the infringement lasted for several periods or because it produced effects after the end of the infringement period (for instance, in the case of exclusionary behaviour leading to entry deterrence). In that case, damages should be estimated for each period in which harm was suffered and then summed up, using an appropriate interest rate.[3]

In practice, carrying out a full assessment of profits in the counterfactual situation would be very demanding and is often not necessary. For instance, if the infringement affects only a claimant’s input costs and does not affect other costs, the prices the claimant receives from its clients or the quantities it sells, harm can be quantified by comparing the input costs in the actual and counterfactual situation, without the need to estimate the counterfactual price and quantities. This greatly simplifies the analysis but can lead to an over- or under-estimation of harm if the infringement had a direct or indirect effect on prices or quantities. Therefore, each quantification of harm must begin with a thorough qualitative analysis of the infringement and the market in question, to identify and understand the effects that need to be quantified.

Below, quantification of harm is discussed for two types of infringements that are most likely to lead to harm and therefore damage claims: hard-core cartels and exclusionary behaviour. As these two types of conduct give rise to different types of methodological issues, they are discussed separately.

Quantification of harm from cartels

The main direct effect of a successful cartel is raising the price for the goods or services sold by cartel members to their customers. If the claimant uses the cartelised goods as inputs, the cartel has – all else being equal – a direct negative effect on the claimant’s profits by increasing the price of these inputs and thereby the claimant’s costs. This price increase is known as an overcharge, which leads to overcharge harm.[4], [5]

The negative effect on the harmed party’s profit can be reduced if, in response to the increased cost, the purchaser who uses the cartelised goods as inputs increases the prices it charges its own customers. This is known as the pass-on effect. However, an increase of the purchaser’s own price will probably lower its sales (as some customers will reduce their purchases in response to a price increase), thereby decreasing its profits. This partly offsets the pass-on effect and is known as the volume effect.

These three main effects of a cartel on the claimant’s profits are illustrated in Figure 1. It is assumed that a cartel raises the claimant’s unit cost of production from c0 to c1, which in turn leads to an increase in the claimant’s own sales price from p0 to p1, resulting in a decrease in quantity sold from q0 to q1. The total harm is equal to the overcharge harm, minus the pass-on effect, plus the volume effect.

Figure 1: Illustration of the main elements of the harm from cartels

The following discussion focuses on how the three main potential effects of the cartel – the overcharge harm, the pass-on and the volume effects – can be estimated.

The overcharge harm

Estimating the harm from overcharge requires comparing the actual price paid by the purchaser during the cartel period with the counterfactual price it would have paid absent the cartel, and multiplying the difference between the two (i.e., the estimated per-unit overcharge) by the volume of goods purchased by the claimant (volume of commerce).[6] Volume of commerce can be expressed as the number of units purchased from cartelists or, more often, as the value of purchases. It is important to realise that the overcharge cannot be estimated based only on the actual or current prices; it is necessary to consider prices in the counterfactual situation as well.

Volume of commerce

Determining the volume of (affected) commerce may seem straightforward, but in reality it can be a time-consuming and demanding task. The claimant needs to be able to prove that it indeed made the purchases for which it is claiming damages. This will often require collecting the claimant’s invoice data on purchases made from the cartel members and analysing them carefully to determine which purchases were potentially affected by the cartel. This includes, among other things, identifying the period during which the affected purchases were made, the product types, geographical areas or channels of distribution. Failing to delineate the scope of affected purchases properly may result in an under- or over-estimation of the harm from overcharge. For instance, the cartelised product may often be sold in a bundle with other products or services, in which case one has to make sure that the price paid for these other products and services is excluded. On the other hand, the cartel may have affected prices even after it formally ended, for instance because prices are renegotiated infrequently and the price set during the cartel period applies until the next negotiation. In that case, limiting the volume of commerce to the purchases made during the formal cartel period will underestimate the harm.

The counterfactual price

Once the volume of commerce has been determined, the overcharge harm can be estimated by multiplying it by the estimated overcharge. While the actual price will often be known, both to the purchaser and the cartel member (at least if firms have stored the data on purchases made during the cartel period), the counterfactual price is unknown and will need to be estimated. In most cases, the counterfactual price will need to be estimated based on the data obtained from the claimant or on market data.

Besides using a theoretical model of oligopolistic competition, a number of useful (statistical) methods have been identified for estimating the ‘but for’ prices. Each of these methods has advantages and disadvantages and their application is highly dependent on the specifics of the case.

There are three main methods that are typically applied to estimate the counterfactual price: comparator-based methods, market simulations and financial analysis.

Comparator-based methods

Comparator-based methods use data on transactions of products or geographical markets unaffected by the cartel as a benchmark for the counterfactual. Common sources of comparison are (1) historical time series of prices of the cartelised good in the same geographical market (e.g., the ‘before, during and after’ method), (2) prices of the cartelised good in a different but similar geographical market not affected by the cartel or of a related product not included in the cartel (the yardstick method), or (3) combinations of the former (e.g., the difference-in-differences method).

The before, during and after method compares the prices in the cartelised market outside the cartel period with those during the cartel period and attributes the difference to the effects of the cartel. If data from before the cartel are not available, as may be the case with long-lasting cartels, then the prices during the cartel can be compared with those after the cartel (a during and after method), although it may be more difficult to separate the effects of the cartel from those of other market developments.

The yardstick method compares prices in affected markets with prices in other geographical or product markets that are similar but not affected by the cartel. The advantage of the cross-sectional yardstick comparison over the temporal comparison employed in the before, during and after method is that it does not suffer from uncertainty about the actual infringement period. It also implicitly controls for common time trends (such as seasonality) that explain price changes both in the infringed and in the comparator market. However, the conditions in the comparator market must be sufficiently similar (i.e., cost structure and patterns, demand characteristics) to get valid results, and, crucially, the cartel must not have had any effect on the comparator market. In particular, when cartelists have reached a broad global understanding to restrict competition, there might be substantial uncertainty as to the geographical scope of the infringement.

A more sophisticated variation of the comparator-based methods is the difference-in-differences approach, which compares the development of the price in the cartelised market over time (known as the treatment group) to the price in a non-cartelised market over time (known as the control group). It therefore combines elements of the temporal before, during and after method and the cross-sectional yardstick method. The overcharge estimate is calculated as (1) the difference in prices in the treatment group between the pre- or post-infringement and the cartel period, less (2) the difference in prices in the control group between the same two periods. For instance, if during the cartel period prices in the cartelised market increased by 15 per cent, while in a similar non-cartelised market they increased by 5 per cent, then a very simplified version of the difference-in-differences method would lead to a conclusion that the cartel increased prices by 10 per cent.

Depending on the quantity and quality of available data, comparator-based methods can be applied by comparing arithmetic averages of prices, or by conducting econometric analysis. While the econometric method requires more data and is more demanding with respect to the analyst’s time and skills than a simple comparison of averages, it also produces more reliable results, for two main reasons. First, econometric methods can be used to test whether the difference in prices between the cartelised and non-cartelised period or market is statistically significantly different from zero relative to a certain significance level (i.e., whether there is compelling evidence that it was not caused by random price variations). Second, econometric methods are able to control for other factors that could potentially influence prices, such as increased costs or demand. This helps to isolate the effects of the cartel and could lead to conclusions that are not obvious from a casual inspection of the data, such as that the cartel had no statistically significant effect even though prices in the cartel period increased, or that the cartel resulted in a price increase that is statistically significantly different from zero even though the price level during the cartel period was not higher than in the comparator period.

Market simulations

The second method used to estimate counterfactual prices is market simulations. Applying market simulations involves mathematical modelling of the affected market based on assumptions regarding the type of competition that would prevail in the market absent the cartel, and on estimates of demand and cost functions derived from market data. The prices predicted by the model are then compared with the actual prices to determine the impact of the cartel.

A disadvantage of simulation models is that they require many assumptions on how the market works, and the results can be sensitive to relatively minor changes in these assumptions. Experts are likely to challenge the appropriateness of the underlying theoretical model, in particular where the industry is dynamic and customers are active.

Financial analysis or cost-based methods

These methods use financial analysis to estimate the counterfactual. The financial performance of either the claimant or the respondent can give indications as to the effects of the cartel. As with the before, during and after approach, one can compare a firm’s profitability over time, under the assumption that the cartel will have had a clear and measurable effect on the financial performance of both the claimant and the respondent. To measure the financial performance, profitability measures such as the net present value, discounted cash flow or other business valuation methods can be used. Another option in this category is the cost-plus method, in which the counterfactual price is derived by estimating the cost of the cartelised product based, for instance, on data from a cartel member, and then adding a profit margin that would be expected to prevail in the absence of a cartel.

Although the advantage of this method is that cost data are often available in a company’s records, for a multi-product firm with a large common cost component it may be a challenge to identify the cost of producing only the cartelised product. In addition, it may not always be straightforward to determine what the competitive margin should be. For example, high-technology industries may be characterised by a low unit production cost, but a substantial margin to recover research and development costs would be expected, even in the absence of collusion.

Choosing the appropriate method

The choice of the most appropriate method depends largely on the availability of suitable data. For instance, if there are sufficient data on the prices before and after the cartel, and on the main cost and demand factors that may have affected prices, the before, during and after method is likely to be most appropriate. If a similar geographical or product market can be identified, difference-in-differences method can also be applied. Market simulation or financial methods will most often be applied if comparator analysis is not possible.

Even for the same cartel, the available data will often differ depending on who is performing the analysis. For instance, a cartel member is likely to have access to data on its own costs and will therefore be in a better position to relate price increases to cost movements. On the other hand, a purchaser may have data on purchases from other suppliers that were not cartel members and be able to compare the price charged by cartel members to those charged by other suppliers. Overall, the results of the analyses of respondents and claimants are likely to differ as both parties will rely on data for the part of the market that they observe.

The pass-on effect

The harm caused by the overcharge may be reduced if the customer of a cartel increases its own price in response to the increase in the price of the cartelised input. As this effect decreases the size of harm, it will typically be brought up by respondents in cartel damages cases. Depending on the jurisdiction, different rules regarding the burden of proof in demonstrating pass-on may apply. The European Commission’s Directive on antitrust damages actions states that it is the infringer who should be required to prove the passing on.[7] Courts in European jurisdictions differ in their approaches to the burden of proof regarding pass-on; it remains to be seen how the national case law will develop further in this respect.

The evidence for pass-on can be derived based on the analysis of the purchaser’s internal documents that contain information on the price-setting process. It can also be estimated using econometric methods, by examining a statistical relationship between the cartelised input price and the downstream price. Using this method requires the availability of sufficient data on both the cartelised input price and the prices charged by the claimant, as well as other factors that may have affected the movements of the downstream price.[8]

Economic theory is sometimes used to estimate pass-on based on a qualitative analysis of the characteristics of the market and the cartel. As an example, theory predicts that pass-on is likely to be stronger if the purchaser’s competitors were also affected by the cartel than if they were not (for instance, because they buy their inputs in markets that were not cartelised). However, although theory is a useful tool to structure thinking about pass-on and to provide guidance on what evidence to look for, it should not be used as sole evidence, but should be supported by factual evidence (e.g., in addition to a quantitative analysis it is informative to interview relevant key personnel and review actual sales procedures).

The volume effect

Even if the increase in input prices is passed on by the purchaser into its own sales prices, it does not imply yet that harm is reduced by the full amount of the pass-on. For instance, if the cartel raises the price by €10, and the purchaser subsequently increases its own price by €10, that does not reduce the harm to zero. An increase in the claimant’s price decreases its sales and profits as some of its customers reduce their purchases in response to a higher price. The size of the volume effect depends on the degree of pass-on, the sensitivity of the demand for the claimant’s products to the price increase (described as the price elasticity of demand), and the profit margin lost on each unit of missed sales. Therefore, estimating the volume effect requires information on these variables. Depending on the market in question, the price elasticity of demand can sometimes be found in public sources, while the profit margin should be available in the purchaser’s records. To estimate the loss of volume, counterfactual estimation methods described earlier can also be used. For instance, the purchaser’s own sales volumes before, during and after the cartel could be compared, accounting for other relevant factors by which they may have been affected.

Other effects

In individual cases, it may be necessary to take into account other effects that could either reduce or increase the harm. For example, an additional harm from a cartel can arise from what is known as an ‘umbrella effect’. This arises if an increased price charged by cartel members encourages firms that are not cartel members but active on the same market to increase their prices as well. Additional harm could also have been caused if the cartel led to a lower quality of cartelised products, although this effect may be difficult to quantify. However, harm may be reduced if other mitigating factors are present, for instance if the claimant also sells products that compete with the cartelised products and benefited from the umbrella effect.

Quantification of damages caused by exclusionary behaviour

A second example of antitrust infringements that can give rise to harm and, therefore, damage claims are those abuses of dominant position that are aimed at the exclusion of competitors from the market. Examples of this type of practice are refusals to deal, tying and bundling, predatory pricing and anticompetitive rebates. Similar harm can arise from some types of vertical restraints. An important difference from a hard-core cartel as discussed in the previous section is that a successful cartel harms customers, whereas it may benefit competitors who may be able to profit from the umbrella effect. By contrast, exclusionary practices directly harm competitors, whereas the harm to customers often only arises in the long run, and may not be noticeable at the time of the claim, as the abuse may not have lasted long enough to lead to the targeted competitor’s exit. Therefore, most of the claims regarding exclusionary behaviour are brought forward by competitors and not customers. Claims by customers could nevertheless arise, for instance if exclusion already led to the exit of a competitor from the market and the dominant firm raised its prices afterwards.

Exclusionary behaviour harms competitors. Unlike in the case of cartels, where the single most important effect is an increase of the price of the cartelised products, the mechanisms of harm caused by exclusionary behaviour are more diverse. Depending on the precise type of the infringement, its effect on competitors can be a reduction of their sales volumes, or of the price they receive, as well as an increase in their costs. Predatory pricing or tying may result in the competitor losing sales to the dominant firm, while a refusal to deal may force the claimants to use more expensive inputs and thereby increase their costs. In an extreme case, if a competitor is forced to leave the market or is prevented from entry, the actual profits are equal to zero and the harm is equal to the full profits that the competitor would have earned if it were (still) active in the market.

Estimating harm resulting from the reduction of sales because of exclusionary behaviour requires estimating the volume of lost sales, and the profit that would have been earned on these sales, for instance, by using the average profit margin. To estimate counterfactual sales in the absence of the infringement, similar methods can be used as for the estimation of the counterfactual price in the case of cartels, for instance a comparison of a claimant’s performance before, during and after the infringement, or a claimant’s performance in other (geographical) markets that are not subject to exclusionary behaviour.

An additional complication is introduced by the fact that the effects of exclusionary behaviour may reach far into the future, if the outcome is market exit or absence of entry without a possibility to enter or re-enter. Extending harm into the future makes it necessary not only to construct a counterfactual situation for the past, but also expected counterfactual and actual situations for the future. This introduces an additional element of uncertainty into the estimates.

Interest on antitrust damages

Making sure that the victim of an infringement is fully compensated for the suffered harm requires that the infringer also pays appropriate interest on the damages. This takes into account the opportunity cost of capital (i.e., the fact that absent the infringement, its victim would have been able to invest the money and earn a return on its investment). Interest may be calculated using some statutory interest rate, or it can be based on the claimant’s actual opportunity cost of capital. The latter is usually estimated as the weighted average cost of capital, which takes into account both the actual cost of debt and the cost of equity, which are then aggregated using weights based on the actual financing structure of the claimant.


Some arbitration cases may require the estimation of harm suffered from an infringement of competition law. If the victim of an infringement is a firm, the harm can be defined as the decrease in the claimant’s profits resulting from the infringement. To properly identify and understand the effects that need to be quantified, any quantification must begin with a thorough qualitative analysis of the infringement and the market in question. The key element of any quantification is the determination of the counterfactual (i.e., the state of the world and the claimant’s profits in a hypothetical situation without the infringement).

One type of infringement that commonly leads to harm and, therefore, damages claims is cartels. The most important harm from a cartel is a higher price paid by purchasers for the cartelised goods. The main element of harm is from overcharge. This can be estimated based on the volume of commerce (i.e., the volume or value of purchases affected by the cartel, and the overcharge) that is, the per-unit difference between the actual prices paid by the purchaser and the prices it would have paid in the absence of the cartel. To estimate the overcharge, one needs to determine the counterfactual price. When determining the volume of commerce, attention must be paid to proper identification of the precise scope of the cartel in terms of the affected goods, geographical territory, distribution channel and the duration. To estimate the counterfactual price, various empirical techniques can be used, which will often be based on comparisons of the cartelised market with some comparator (i.e., a market that is sufficiently similar but not affected by a cartel). The eventual harm can be lower than the harm from overcharge if the purchaser passed on all or some of the price increase to its own customers. Such a behaviour can in turn lead to the volume effect – an additional profit loss resulting from lower volumes sold.

Quantifying harm from exclusionary behaviour follows the same general principles but the focus is on the estimation of the counterfactual volumes or costs rather than the price. Additional complexity is added by the fact that harm from exclusionary behaviour extends into the future. Therefore, both the counterfactual and the actual situation must be forecast, which increases uncertainty about the actual extent of harm.

Case for ‘assessing damages in antitrust actions’

The claimant owns a factory that uses material A for production. There are only a few producers of A in the world. The manufacturers of A agreed to divide the markets geographically and not to compete between each other. As a result, when the claimant asked various manufacturers for an offer, it was always the manufacturer located in the same country that provided the best offer and who won the contract.

This cartel lasted from June 2009 to February 2014. The claimant suspects it paid too much for the material and wants to claim damages from the manufacturer. For this, it has to estimate the volume of commerce and the overcharge.

During the cartel period, the claimant purchased approximately 100 million tonnes of the material. The claimant also purchased material B from the manufacturer, but that material is produced by more manufacturers and was not a part of the cartel.

Volume of commerce

The claimant has gathered information on all purchases during the cartel period. The invoices specify the amount of material purchased and the total price. However, the invoices for the purchase of approximately 20 per cent volumes included purchases for material B, and only the total price was reported. Also, for approximately 10 per cent of the purchased volumes, pricing information was missing.

Based on the 70 per cent of purchases for which the information for the purchase of A was available, the expert estimated the average price per tonne of the material in each year. This was then applied to the volumes purchased in each year to arrive at the annual ‘volume of commerce’.


To estimate the price in the counterfactual, the expert used the data on purchases outside the cartel period. The claimant had data on purchases for the years 2008–2012 and 2014–2020. The expert compared the prices during the cartel period with the prices outside the cartel period. The price during the cartel period turned out to be 2 per cent lower, on average. However, during the same period, the costs of producing the material decreased, while the demand in 2009 was negatively affected by the economic crisis. To take this into account, the expert estimated, using an econometric model, how the price is affected by the changes in costs and by fluctuations in demand. It turned out that, absent the cartel, the price during the cartel should have been 9 per cent lower than outside the cartel period because of changes in cost and demand. As the actual price was only 2 per cent lower, the effect of the cartel was estimated to be 7 per cent. This was then applied to the annual volume of commerce to arrive at the annual damages.


Based on the analysis of the internal documents of the claimant that explained the price-setting process, it was estimated that approximately 40 per cent of the overcharge was passed on into the claimants’ own price. Therefore, the damages were reduced by 40 per cent. However, it is estimated that because of the higher price, the claimant additionally lost 5 per cent of sales volumes. The damages are increased by an amount equal to the lost volumes times the average margin.


As the damages were computed in 2020, the amount of harm suffered each year was uplifted to 2020, using the average weighted cost of capital.


[1] Ewa Mendys-Kamphorst is a senior adviser at CEG Europe.

[2] Unlike the actual scenario, which can typically be assessed by observation, the counterfactual necessarily is hypothetical and has to be deducted from evidence using economic logic and reasoning.

[3] As the present value of a euro received today is higher than the value of a euro received tomorrow, to sum up the harm from different years an appropriate discount rate must be used to make the amounts comparable.

[4] Potential dynamic effects, such as a potential loss of innovation or quality improvements, as well as a welfare ‘dead-weight loss’ for consumers, are generally ignored.

[5] In principle, other upstream suppliers of input goods and services to the claimants may also be harmed by the reduction in purchasing volumes, if their goods and services are complementary to those procured from the cartelists. For example, as a result of a cartel in LCD screens, merchants may not just buy fewer (and more expensive) LCD screens but also demand fewer desktop computers. Likewise, as cartel members restrict output this may also impact other input providers up-stream of the cartelists, as the cartelists demand for inputs is artificially reduced.

[6] If the volume of commerce is expressed in the value of purchases rather than in purchased volumes, then the overcharge should be expressed as a percentage of the actual price rather than as an absolute price difference.

[7] Directive 2014/104/EU of the European Parliament and of the Council of 26 November 2014 on certain rules governing actions for damages under national law for infringements of the competition law provisions of the Member States and of the European Union, recital 39.

[8] For a comprehensive literature review on pass-on, see, e.g., RBB Economics, 2014, Cost pass-through: theory, measurement, and potential policy implications. A report prepared for the Office of Fair Trading.

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