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The Role of a Labor and Employment Expert

Although wage and hour litigation is rooted in statutory and regulatory requirements, economic and statistical analysis frequently determines the financial consequences of the alleged violations. Labor and employment experts assist counsel by translating complex employment records into objective, data-driven analyses that quantify potential damages under the legal assumptions applicable to the case.

Their work often begins well before expert reports are prepared. During the early stages of litigation, experts help legal teams estimate potential exposure, identify the records needed to evaluate claims, and assess whether existing data appears sufficient to support a reliable damages methodology. This early involvement frequently improves discovery planning by identifying missing payroll fields, inconsistencies among databases, or operational records that may become important later in the case.

As discovery progresses, experts review payroll files, timekeeping records, scheduling information, human resources databases, and other employment records to determine whether the available information accurately reflects employee work activity and compensation. This process often involves reconciling data from multiple systems, validating record consistency, and identifying anomalies that could affect damages calculations.

Once the relevant data has been assembled and verified, economists and statisticians might develop analytical models tailored to the facts of the case. These models may estimate unpaid overtime, evaluate alleged off-the-clock work, analyze employee classifications, or calculate other forms of compensation associated with wage and hour claims. Because litigation frequently involves competing factual and legal assumptions, experts might prepare multiple damages scenarios that allow attorneys to evaluate financial exposure under alternative outcomes.

Beyond performing calculations, experienced experts serve as strategic advisors throughout the litigation process. They assist with deposition preparation, evaluate opposing expert reports, identify methodological strengths and weaknesses, and explain complex statistical or economic concepts in a manner that judges, juries, mediators, and arbitrators can readily understand.

Understanding the Data Behind Wage and Hour Claims

The quality of any damages analysis depends upon the quality of the underlying data. While payroll records typically provide the foundation for a wage and hour analysis, they often represent only one component of the broader evidentiary record. Reliable damages models often require integrating information from several sources to develop a comprehensive understanding of employee work activity and compensation.

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Payroll systems document wages, overtime payments, bonuses, commissions, shift differentials, and other forms of compensation that may affect damages calculations. Timekeeping systems complement these records by documenting clock-in and clock-out times, meal periods, scheduling practices, and recorded work hours. Human resources databases provide additional context regarding employee classifications, job titles, employment dates, reporting structures, and organizational changes that may influence the scope of the analysis.

In many cases, operational business records also become important sources of evidence. Computer login records, security badge data, production reports, GPS information, call center activity, or point-of-sale transactions may provide objective information regarding employee work patterns when traditional payroll records do not fully capture the activities at issue. These records can be particularly valuable in matters involving allegations of off-the-clock work or disputes regarding uncompensated time.

Before performing any damages calculations, labor and employment experts devote significant effort to validating the available information. Large employers frequently maintain employment records across multiple payroll vendors, timekeeping platforms, and human resources systems. Employee identifiers may change over time, compensation codes may differ between systems, and duplicate or incomplete records may exist. Reconciling these datasets is an essential step in developing analyses that accurately reflect workforce activity throughout the damages period.

Although much of this work occurs behind the scenes, careful data validation forms the foundation of every reliable expert opinion. Courts increasingly expect damages analyses to rest upon transparent methodologies supported by accurate and well-organized data rather than assumptions regarding the completeness of employment records.

Economic Analysis of Wage and Hour Claims

Every wage and hour matter presents unique factual circumstances, requiring experts to tailor their methodologies to the available data. Rather than applying standardized formulas, economists and statisticians develop analytical approaches that reflect the employer’s compensation practices, workforce structure, and payroll systems while remaining grounded in accepted economic and statistical principles.

Overtime claims provide a useful example of this process. Determining unpaid overtime frequently requires more than identifying hours worked beyond a statutory threshold. Experts must evaluate how an employer calculated employees’ regular rates of pay, determine whether bonuses or incentive compensation affected overtime obligations, and assess whether payroll systems consistently applied applicable compensation policies. Employees working multiple positions or receiving different forms of compensation often require individualized analyses before aggregate damages can be estimated.

Employee misclassification cases present a different set of analytical challenges. Assuming liability is established, experts estimate the compensation employees would have received under the alternative classification advanced by counsel. These analyses often involve reconstructing work schedules, evaluating historical payroll practices, and accounting for changes in compensation structures over time. For employers operating across multiple locations or business units, experts may also evaluate whether damages methodologies should differ among employee groups based on variations in job duties, compensation arrangements, or operational practices.

Off-the-clock work claims similarly may require careful examination of both payroll records and operational evidence. Because employees may allege that work occurred outside recorded hours, experts frequently evaluate computer activity, electronic communications, security badge records, scheduling information, or other business data to determine whether objective evidence supports the alleged work patterns. Integrating multiple data sources allows experts to develop analyses that are more comprehensive and reliable than those based solely on payroll information or anecdotal testimony.

Meal and rest break claims, time rounding practices, travel time, and other wage and hour issues present their own analytical considerations. Although the specific methodology varies depending on the facts of each case, the underlying objective remains the same: developing a transparent, well-supported analysis that accurately measures the financial consequences of the alleged employment practices under the assumptions relevant to the litigation.

Statistical Methods and Representative Evidence

As wage and hour litigation has become more data intensive, statistical analysis has assumed an increasingly important role in employment damages evaluations. Individual claims may involve relatively straightforward calculations, but class and collective actions often require experts to analyze millions of payroll and timekeeping records covering large employee populations. In these matters, economists and statisticians combine economic analysis with statistical techniques to evaluate patterns within the available data and develop damages methodologies that are both reliable and transparent.

One commonly used approach involves representative evidence. When complete records are unavailable or reviewing every employee record is impractical, experts may evaluate whether a representative sample can provide reliable insight into broader employment practices. Developing an appropriate sampling methodology requires careful consideration of workforce composition, job classifications, geographic locations, departments, compensation structures, and other factors that may influence employee experiences. The objective is to ensure that any conclusions drawn from the sample reasonably reflect the larger population being evaluated.

Statistical methods may also be used to estimate damages under alternative factual assumptions or evaluate the sensitivity of damages models to changes in key inputs. Rather than presenting a single damages figure without context, experts often develop multiple scenarios that illustrate how differing assumptions affect estimated exposure. These analyses provide legal teams with a more comprehensive understanding of litigation risk while demonstrating the robustness of the underlying methodology.

Equally important is the process of data validation. Before any statistical analysis is performed, experts reconcile payroll records across multiple systems, identify duplicate observations, evaluate missing data, and verify that compensation and timekeeping records are internally consistent. These quality-control procedures help ensure that damages estimates are based on reliable information and reduce the likelihood that data irregularities will influence the final analysis.

Regardless of the specific methodology employed, effective expert analyses emphasize transparency. Clearly documenting assumptions, explaining analytical choices, and identifying any limitations within the available data allows legal teams, opposing experts, and the court to understand how conclusions were reached and evaluate the reliability of the resulting opinions.

Wage and Hour Analysis in Class and Collective Actions

Class and collective actions introduce additional complexity because experts must evaluate damages across broad groups of employees while recognizing that individual work experiences may vary. Unlike individual employment disputes, these matters often require methodologies capable of analyzing workforce-wide compensation practices using common evidence.

Labor and employment experts begin by organizing and integrating payroll, timekeeping, and human resources data across the proposed class. This process frequently involves reconciling records generated by multiple payroll systems, facilities, or business units to develop a consistent analytical framework. Once the data has been validated, experts evaluate compensation practices, identify potentially affected employee populations, and estimate aggregate damages under the assumptions relevant to the litigation.

Economic or statistical analyses may also inform issues related to class certification. Although certification is ultimately a legal determination, experts often assist legal teams in evaluating whether damages can be measured using common methodologies across the proposed class or whether substantial individualized differences may require additional analysis. Understanding the degree of variation within the workforce can help counsel assess litigation strategy, evaluate settlement opportunities, and anticipate challenges that may arise during expert discovery.

Because employment class actions often involve substantial financial exposure, damages models must be sufficiently flexible to accommodate evolving legal rulings, newly produced records, and alternative assumptions. Experienced experts develop analytical frameworks that can be updated efficiently as litigation progresses while maintaining consistency in methodology and documentation.

Common Challenges in Employment Damages Analysis

Even when employment records are extensive, wage and hour analyses rarely proceed without challenges. Differences among payroll systems, evolving compensation practices, incomplete records, and disputed factual assumptions all influence how damages are evaluated.

Incomplete or inconsistent data is among the most common obstacles. Employers frequently change payroll providers, implement new workforce management systems, or modify compensation policies during the relevant damages period. As a result, employment information may exist across several databases that use different employee identifiers, compensation codes, or reporting structures. Before damages can be calculated, experts must reconcile these records and confirm that they accurately reflect employee compensation and work activity.

Another challenge involves reconstructing work patterns when complete timekeeping records are unavailable. In off-the-clock work cases or disputes involving uncompensated activities, experts often supplement payroll information with operational business records, electronic activity logs, or other objective evidence to estimate work performed outside recorded hours. Evaluating the reliability of these alternative data sources requires both technical expertise and an understanding of the employer’s operations.

Experts must also navigate competing factual assumptions presented by the parties. Plaintiffs and defendants may disagree regarding the number of uncompensated hours worked, the composition of the affected employee population, or the appropriate methodology for calculating damages. Rather than relying on a single estimate, experts frequently prepare alternative damages models that reflect different liability scenarios. This approach provides attorneys with a clearer understanding of potential financial outcomes while maintaining analytical objectivity.

What Attorneys Should Look for in a Wage and Hour Expert

Selecting the right expert involves more than identifying someone with experience calculating damages. The most effective labor and employment experts combine technical expertise with practical litigation experience, allowing them to address both the analytical and strategic demands of complex employment disputes.

Attorneys should look for experts who have substantial experience working with payroll systems, timekeeping records, and large employment databases. An expert with an experienced team can save a lot of money and time with respect to processing data. Modern wage and hour litigation often requires integrating information from multiple sources, identifying data quality issues, and developing analytical models capable of handling millions of employment records.

Experience with statistical analysis, database management, and economic modeling can significantly improve both the efficiency and reliability of the resulting damages analysis.

Equally important is an expert’s ability to communicate complex concepts clearly. Judges, juries, mediators, and arbitrators rarely have technical backgrounds in economics or statistics. Experts who can explain sophisticated methodologies in straightforward language often provide greater value throughout litigation, particularly during depositions, expert testimony, and settlement discussions.

Legal teams should also consider whether an expert approaches each engagement with independence and methodological rigor. Courts place considerable weight on analyses that are transparent, well documented, and supported by accepted analytical principles. Experts who carefully explain their assumptions, acknowledge limitations within the available data, and evaluate competing methodologies are generally better positioned to provide opinions that withstand scrutiny during litigation.

Finally, involving an expert early in the case often provides meaningful advantages. Early collaboration can improve discovery planning, identify critical data sources, evaluate preliminary exposure, and help counsel develop litigation strategies informed by objective economic analysis rather than incomplete financial information.

Conclusión

Wage and hour litigation has evolved into one of the most analytically demanding areas of employment law. Although the legal issues determine whether liability exists, the financial outcome of many cases depends on the ability to organize complex employment data, apply reliable economic methodologies, and quantify damages using objective evidence.

Labor and employment experts play an essential role in this process. By combining expertise in economics, statistics, database management, and employment compensation practices, they help legal teams transform payroll records and workforce data into defensible damages analyses that support informed decision-making throughout litigation. From evaluating payroll systems and validating employment records to developing damages models and presenting expert testimony, these professionals provide the analytical foundation necessary to assess financial exposure with confidence.

As wage and hour disputes continue to increase in both size and complexity, rigorous economic analysis will remain an essential component of effective advocacy. Attorneys who engage experienced labor and employment experts early in the litigation process are often better positioned to evaluate competing damages theories, identify strengths and weaknesses in the available evidence, and develop analytical frameworks capable of withstanding scrutiny from opposing experts and the court.

Why Expert Evidence Plays a Central Role in International Arbitration

International arbitration routinely involves disputes that require specialized economic, financial, technical, or industry knowledge. Unlike many domestic court proceedings, arbitrators are often selected because of their legal expertise rather than their familiarity with the technical issues underlying a dispute. Expert witnesses can bridge that knowledge gap by providing independent and objective analyses that assist tribunals in evaluating complex facts and evidence.

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Complex Commercial Disputes Require Specialized Knowledge

Today’s international arbitration landscape encompasses a wide variety of disputes across industries and jurisdictions. Common matters include:

Cross-border mergers and acquisitions
Construction and infrastructure projects
Energy and natural resources
Joint ventures and shareholder disputes
Intellectual property licensing
International distribution agreements
Investment treaty arbitration
Competition and antitrust matters
Financial services and securities disputes

Each of these disputes may involve complicated economic questions, large amounts of data, detailed accounting analyses, sophisticated valuation models, and/or highly technical industry practices. Arbitrators rely on experienced experts to explain these issues objectively and translate large volumes of data into understandable conclusions.

For example, determining damages in an international arbitration matter may require estimating future lost profits, evaluating discounted cash flow models, analyzing market competition, reconstructing historical financial performance, or assessing industry benchmarks across multiple jurisdictions. These analyses demand specialized expertise that in many cases only an experienced arbitration expert can provide. Given the vast range of topics that fall under the international arbitration umbrella, it is important for legal teams to vet an expert’s experience and skills to ensure they are the right fit.

Common Areas Where Experts Are Used

Expert testimony appears in nearly every stage of significant international arbitration proceedings. Depending on the nature of the dispute, experts may address:

Daños económicos

Economic experts may evaluate lost profits, overcharges, price effects, unjust enrichment, business interruption, and other measures of economic harm using accepted analytical methodologies.

Valoración de empresas

Business valuation experts often determine the value of companies, assets, intellectual property, minority interests, or investment opportunities using valuation approaches appropriate to the facts of the case.

Accounting and Financial Analysis

Accounting experts may interpret financial records, analyze transactions, identify accounting irregularities, calculate losses, and evaluate financial reporting practices.

Competition and Market Analysis

In competition-related disputes, economic experts may define a market, assess market power and competitive effects, pricing behavior, barriers to entry, market shares, and the industry structure.

Industry and Technical Expertise

Construction engineers, energy specialists, mining experts, intellectual property professionals, and other technical experts often explain industry-specific standards, engineering principles, operational practices, and/or scientific issues that may influence liability or damages.

Regardless of the discipline, the objective remains consistent: provide specialized knowledge that assists the tribunal in evaluating disputed issues through reliable, objective analysis.

What Arbitrators Expect from Expert Witnesses

Although arbitration rules differ across institutions and jurisdictions, experienced arbitrators consistently emphasize several characteristics that distinguish persuasive expert testimony from less effective opinions. Understanding these expectations helps counsel identify experts who can contribute meaningfully to the tribunal’s decision-making process.

Independence Above Advocacy

Perhaps the single most important characteristic of an effective expert witness is independence.

While experts are typically retained by one party, their ultimate responsibility is not to advocate for that party’s legal position. Rather, their role is to assist the tribunal by offering objective opinions based on specialized knowledge and accepted methodologies. Providing an analysis closely tied to the facts and data of the case is important.

Tribunals are generally quick to recognize reports that appear designed primarily to support a client’s litigation strategy rather than provide an impartial evaluation of the evidence. Experts who ignore unfavorable facts, cherry pick data, or stretch methodologies beyond accepted practice may significantly undermine their own credibility.

By contrast, experts who acknowledge limitations, explain uncertainties, and fairly address competing viewpoints often enhance the persuasive value of their testimony. Demonstrating intellectual honesty frequently carries more weight than attempting to eliminate every weakness in an analysis.

Experienced counsel understand that credibility is earned through transparency rather than advocacy.

Clear and Defensible Methodology

Even the most accomplished expert cannot persuade a tribunal without a sound analytical foundation.

Expert opinions should be supported by methodologies that are:

Appropriate for the issues presented
Consistent with accepted professional standards
Based on reliable and sufficient data
Transparent and reproducible
Clearly explained throughout the report

For example, damages calculations should identify the factual assumptions underlying each component of the analysis, explain why specific valuation techniques were selected, and demonstrate how conclusions follow logically from the available evidence.

For example, in a valuation analysis, selecting a discount rate can be a point of contention. That decision must be well supported.

Where assumptions materially affect results, experts frequently perform sensitivity analyses or evaluate alternative scenarios. Rather than weakening an opinion, this transparency often strengthens credibility by demonstrating that conclusions remain robust under reasonable variations in assumptions.

Conversely, unsupported estimates, unexplained adjustments, or opaque calculations invite scrutiny during cross-examination and may diminish the overall persuasive value of the report.

Communication Matters as Much as Technical Expertise

The strongest analyses provide little value if arbitrators cannot easily understand them. That is why it is crucial for an expert to be able to describe advanced calculations or methodologies in an accessible way.

International arbitration frequently involves complex financial models, statistical analyses, or technical concepts that must be communicated to audiences with varying degrees of subject matter expertise. Effective experts recognize this challenge and tailor their presentations accordingly.

Successful expert reports generally:

Use plain language whenever possible
Define technical terminology
Organize analyses logically
Incorporate charts and visual summaries
Connect analytical findings directly to the disputed issues

The same principles apply during testimony. Experts who answer questions directly, remain composed under cross-examination, and explain complicated concepts without unnecessary jargon tend to be more persuasive than those who rely on overly technical language or evasive responses.

Ultimately, the tribunal’s confidence depends not only on what an expert concludes, but also on how effectively those conclusions are communicated.

Expert evidence has become indispensable to international arbitration precisely because the disputes themselves have grown more technical, more data-intensive, and more economically complex. The most effective experts are not those with the most impressive credentials alone, but those who combine genuine expertise with independence, methodological rigor, and the ability to make difficult concepts accessible to a tribunal. For counsel, this reframes the task of retaining an expert: the goal is not simply to find a recognized name in the field, but to identify someone who can maintain objectivity under pressure, anticipate methodological challenges, and explain their reasoning persuasively from the report stage through cross-examination. Handled well, expert testimony does more than support a party’s case. It helps the tribunal reach a sound decision on the issues that matter most, and that, ultimately, is where its persuasive power lies.

Background: Emerging Fire Truck Antitrust Litigation

Multiple antitrust class-action cases against fire truck manufacturers have been consolidated in the U.S. District Court for the Eastern District of Wisconsin. The case is named In Re: Fire Apparatus Antitrust Litigation. A “Fire Apparatus” is “[a] vehicle designed to be used under emergency conditions to transport personnel and equipment or to support the suppression of fires or mitigation of other hazardous situations.”[1] Fire trucks are one type of fire apparatus. For simplicity, this article uses “fire trucks” to refer to fire apparatus generally.

Fire truck manufacturers are alleged to have engaged in coordinated pricing and output restrictions, resulting in inflated pricing and persistent supply backlogs. Plaintiffs contend this behavior coincided with elevated revenues and profit margins for defendants REV Group, Oshkosh Corporation, and Rosenbauer America (“Defendants”).

Also named as a Defendant is the Fire Apparatus Manufacturers’ Association (“FAMA”). FAMA is a trade organization whose membership includes Defendant manufacturers. FAMA is alleged to have hosted regular meetings which Defendants attended, and facilitated their exchange of competitively sensitive, nonpublic information and economic data.

Plaintiffs further assert that Defendants’ conduct led to constrained supply and inflated prices, with the result being that fire truck purchasers, such as municipalities and fire departments, allegedly paid supracompetitive prices dating back to at least as early as 2016.

From an economic perspective, these allegations raise questions about whether observed market structure and outcomes (in particular, rising prices and extended lead times) are consistent with competitive conditions or are indicative of coordinated conduct within a highly concentrated industry. This article offers economic insights in each of these areas.

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Market Structure: Concentration and Barriers to Entry

When assessing market dynamics, economists typically begin by examining the structure of the market. Market concentration and barriers to entry are two foundational considerations, as they directly affect the ability and incentives of firms to exercise market power. Economic theory suggests that having a small number of firms makes coordinated behavior easier to accomplish and more likely to succeed, especially when firms can use information-sharing to monitor each other’s actions and respond accordingly.

Barriers to entry, which can include regulatory hurdles, high capital requirements, and technical expertise, can reinforce these market dynamics by limiting the ability for a new competitor to enter the market and discipline prices. In that regard, it is important to consider not only whether new competitors could enter the market at all, but also whether entrants’ success was stifled by the incumbent firms’ conduct.

While these factors alone do not necessarily imply anticompetitive conduct, they provide an important context for evaluating observed pricing and output patterns.

High Market Concentration

According to an April 15, 2025 United States Senate letter from Elizabeth Warren and Jim Banks to Edward Kelly (General President, International Association of Fire Fighters), “REV Group controls the largest share of the fire truck manufacturing market, at approximately 33 percent,” while “independent companies make up only 20 percent of the market” as of 2023.^[2] This indicates that leading firms including REV Group, Oshkosh Corporation, and Rosenbauer America have a combined market share of roughly 80 percent of the market.

From an economic perspective, high levels of concentration may create conditions in which firms face reduced competitive pressure (due to the limited number of credible competitors) and therefore are more sensitive to the behavior of rivals.

How to Count the Number of Firms and Measure Concentration

Cases involving alleged collusion also raise questions as to how to measure concentration and what counts as a “firm.” Consolidation (and thus increased concentration) can occur even without the elimination of existing brand names. From a superficial perspective, there may appear to be the same number of brands as before, even as industry ownership is “rolled up” under a small number of owners.

From an economics perspective, it is not just the number of brands or corporate entities that matters when evaluating the potential for anticompetitive conduct. Rather, what matters is control over those brands or entities. Multiple brands or subsidiaries, if they are controlled by the same entity, are properly treated as a single “firm” from an economics perspective.

Consolidation Trends

Over the past twenty years, there has been a reduction in the number of independent competitors, largely due to private equity acquisitions and roll-ups.[3] This has contributed to a consolidation of companies into a smaller number of larger, vertically integrated firms.

REV Group was acquired by private equity company American Industrial Partners (“AIP”) in 2006.[4] Since then, REV Group/AIP has acquired more fire apparatus companies, including E-ONE (2008)[5], KME (2016)[6], Ferrara (2017)[7], and Spartan (including Smeal, Ladder Tower, and UST) (2020).[8]

REV’s acquisition of Spartan is particularly noteworthy, as REV viewed it as an opportunity to “increase[] the Company’s market share in several key product categories” through vertical integration with an “upstream” producer of fire truck cabs and chassis.[9]

Oshkosh, which owns the Pierce brand, has also acquired numerous fire apparatus companies. In 2021, Pierce acquired Boise Mobile Equipment, a premier provider of wildland firefighting vehicles and products.[10] In 2022, Oshkosh acquired Maxi-Metal, Inc., a “leading innovator of mission-critical vehicles and essential equipment” that serves fire and emergency professionals.[11] Aside from these third-party manufacturers, Oshkosh (through subsidiaries and dealers) also acquired related brands such as Schuhmacher Fire Equipment (2018)[12], Superior Equipment (2019)[13], Minuteman Fire and Rescue (2019)[14], Emergency Vehicle Specialists (2023)[15], Churchville Fire Equipment (2023)[16], and Halt Fire Inc. (2025)[17].

Rosenbauer also acquired fire apparatus companies, including the remaining 25 percent of General Safety Equipment Corp in 2022, which provided Rosenbauer full control of the company.[18] In 2023, Rosenbauer announced a partnership with IKON Fire, LLC for fire apparatus sales and service in Colorado and Wyoming.[19]

The above transactions reflect a sustained pattern of consolidation among leading fire apparatus manufacturers and their affiliated subsidiaries and dealers. As a result, the industry has become increasingly concentrated with a small number of firms exerting ever-greater control over manufacturing, distribution, service, and sales.

Barriers to Entry

New firms attempting to manufacture fire trucks face significant challenges in entering and competing effectively. These barriers to entry include high upfront capital investment costs, economies of scale and scope, specialized manufacturing processes, long production cycles, regulatory compliance, and long-established relationships with municipal buyers.

As noted above, the presence or absence of barriers to entry matters because it determines whether incumbent firms will face meaningful competitive pressure from new entrants. If there are high barriers to entry, incumbent firms would likely face limited competitive pressure from new entrants.

Alleged Anticompetitive Conduct: Economic Theories of Harm

The anticompetitive conduct alleged in these cases can be described as (1) information exchange, such as the sharing of confidential and competitively sensitive information and economic data among supposed rivals; (2) coordinated suppression of supply; and (3) coordinated efforts to fix, raise, maintain, or stabilize prices at elevated levels.[20]

1. Information Exchange as a Coordination Mechanism

Exchanging competitively sensitive information and economic data through industry associations has become an increasingly hot topic in the world of antitrust and is currently alleged to have occurred across a range of industries including the one at issue here. While information sharing can serve procompetitive purposes, it may raise concerns when it involves confidential or competitively sensitive information and/or economic data. For example, exchanging pricing, cost, production, or other strategic information can facilitate coordination across competitors and reduce uncertainty in ways that make collusion easier.

REV Group (E-ONE, KME, Ferrara, and Spartan), Oshkosh (Pierce), and Rosenbauer are all members of FAMA. The cases allege that FAMA enabled manufacturers to share competitively sensitive information resulting in supply suppression and artificially inflated prices.[21] An important requirement for successful collusion is the ability of participants to monitor compliance with the collusive agreement. FAMA provided statistics and reports—containing very detailed information on trucks, parts, and more—that allegedly gave Defendants access to competitively sensitive information that enabled them to monitor compliance.[22]

2. Output Restriction and Supply Constraints

The cases allege an intentional scheme to increase the backlog of unfulfilled orders. This backlog is alleged to have stemmed from Defendants’ suppression of supply. Instead of expanding their output in response to increasing demand, Defendants are alleged to have prevented output expansion and thus diverted the excess demand into their backlog. The backlog at each of the major suppliers has grown substantially since 2020.

As shown in Figure 1 below, REV Group’s backlog increased from $708 million in 2018 to $3.7 billion in 2023, an increase of 409 percent.

As shown in Figure 2 below, Oshkosh saw similar increases in their backlog, which rose from $970 million in 2019 to $6.6 billion in 2025, a 580 percent increase.

Rosenbauer’s president Mark Fusco confirmed that Rosenbauer also experienced an increase in backlog in 2022, stating that the company had “the strongest order backlog in company history.”[23]

3. Coordinated Efforts to Fix, Raise, Maintain, or Stabilize Prices at Elevated Levels

These cases are still in their early stages, and presumably Defendants will be asked to produce data and documents which might help answer the question of whether there were coordinated efforts to fix, raise, maintain, or stabilize prices at elevated levels.

In addition to Defendants’ own documents and data relevant to the presence or absence of coordinated efforts, economists can turn to a combination of public data and economic theory. For example, standard economic theory suggests that the competitive response to this sustained increase in demand would be an increase in output and possibly entry by new competitors. However, this was not the case.

The industry has experienced record-high backlogs and orders since 2020. Yet industry shipments of fire apparatus decreased between 2020 and 2022, falling below the 2011-2019 average.[24] See Figure 3 below. Basic economic theory would suggest that an increase in demand combined with flat or reduced output would lead to higher equilibrium prices. The cases allege that this is exactly what has played out in the market, with prolonged delivery times triggering massive price increases.[25]

Source: FAMA Releases Fire Apparatus Industry Update, Fire Apparatus Manufacturers Association (June 17, 2025), https://www.fama.org/fama-releases-fire-apparatus-industry-update/.

Are Price Effects Justified by Normal Competitive Behavior?

Price increases are not necessarily anticompetitive, as they may reflect increases in cost or quality improvements. Thus, an important question to ask is whether the observed price increases are, in fact, warranted by natural competitive behavior.

However, this is not to say that a cost increase or product improvement will automatically invalidate claims of anticompetitive price inflation. In fact, cost increases have been used in the past as excuses for price increases that were determined to have been anticompetitive.[26]

Economic Indicators of Potential Collusion

Economists can help assess alleged collusion and other anticompetitive conduct by analyzing industry characteristics, pricing behavior, market shares, and concentration metrics. While none of these are dispositive by themselves, economists can opine on whether observed market outcomes are consistent with collusion.

Parallel Pricing Behavior

Parallel pricing refers to a pattern in which competing firms adjust their prices in similar ways over time. This can arise with firms independently responding to natural market conditions, but it also can indicate coordinated conduct. If the parallel pricing behavior cannot be explained by competitive dynamics (e.g., increases in cost) then this may suggest that the parallel pricing is due to coordinated conduct. To address this issue, economists will typically construct an econometric model that predicts but-for prices which can then be compared to the actual prices in the market.

Stable Market Shares

Market shares provide a measure of a firm’s relative size and competitive position within a market. Economists can use market shares to assess market concentration and competitive effects. If prices unexpectedly rise for some competitors but market shares remain relatively stable over time, it may suggest that there is limited competition among rivals.

Stable or Elevated Margins

Margins refer to the difference between a product’s price and cost and are usually a strong predictor of a firm’s overall profitability. In a competitive market, economists expect margins to fluctuate as firms respond to changes in cost, demand, and competitive pressures from rivals.[27] Margins that are persistently stable and/or elevated—especially in the face of changing market conditions—may suggest limited competition, which can be consistent with coordination among firms.

Persistent Supply Delays

Persistent supply delays refer to continuous or recurring disruptions in the production and delivery of goods that extend beyond what would be expected under normal market conditions. While, broadly speaking, supply delays are not necessarily uncommon, those that seemingly occur under stable market conditions and are persistent in nature may indicate reduced competitive pressure to meet market demand. In certain instances, this can suggest firms limiting output or failing to compete aggressively on output/delivery.

Distinguishing Coordination from Competitive Outcomes

Market outcomes must always be carefully evaluated to determine whether they are the result of competition or coordinated conduct. Parallel pricing, stable market shares, stable and elevated margins, and persistent supply delays can theoretically arise in competitive markets. Of course, coordinated anticompetitive conduct could also contribute to these patterns, particularly when they are persistent, closely aligned across firms, and unexplained by market fundamentals. Given this complexity, economists must assess the totality of the evidence—including firm behavior, market conditions, market outcomes, and timing—to distinguish between competitive dynamics and coordination.

Alternative Explanations of Market Outcomes

Historically, fire truck manufacturers could estimate labor and material costs with a reasonable degree of confidence. However, more recently there have been various factors impacting labor and material costs including inflation, the Pandemic, and tariffs.[28]

Rising Costs

1. Material Costs

One of the primary material costs for fire truck manufacturers is aluminum.[29] As shown in Figure 4 below, the price of U.S. Midwest Aluminum fluctuated between $0.75 and $1.28 per pound between January 2010 and December 2019. From 2020 to March 2022, the average price per pound rose significantly to a high of $2.00, but it has since fallen to an average of $1.27 in 2023 and 2024.

Steel is another prominent material input for fire truck manufacturers.[30] As shown in Figure 5 below, the adjusted closing price of U.S. Midwest Domestic Hot-Rolled Coil Steel fluctuated between $391 and $920 per ton between January 2010 and December 2019. From January 2020 to September 2021, the price shot up to a high of $1,900 per ton. Since then, the price has fallen to an average of $898 per ton from 2022 to 2024.

Looking at two input costs alone does not tell the whole story. However, both aluminum and steel prices did increase substantially in 2021 and 2022, partly due to the pandemic shock followed by a surge in economic activity.[31] Since that time, material costs affecting fire truck manufacturers have decreased and are exhibiting a consistent trend that is above the 2010-2020 average but well off the highs experienced in 2021 and 2022. Econometric analysis enables an economist to account for the expected effects of these cost fluctuations on Defendants’ prices absent coordination.

1. Labor Costs

Labor is another major cost affecting fire truck manufacturers.[32] This is because fire trucks are highly specialized vehicles, in some cases custom built, and their production is heavily reliant on skilled workers such as welders, electricians, and mechanics.[33] As shown in Figure 6 below, unit labor costs for the manufacturing sector as a whole have risen consistently in recent years. The increasing unit labor costs indicate that wages are rising faster than productivity.

Increasing Demand

According to FAMA, orders for new mainline fire trucks reached 5,946 per year from 2021 to 2023. This compares to average orders of 4,169 per year during the prior decade.[34]

Despite the increasing labor and materials costs discussed above, fire truck manufacturers have seen record profits,[35] suggesting that increases in cost do not fully explain the increase in prices. This raises economic questions about whether fire truck manufacturers are using their market power to increase prices to supracompetitive levels. Providing a complete answer to this question may require additional, detailed data from the fire truck manufacturers themselves.

Economic Tests and Frameworks

Economists have a unique set of tools to assess how markets function, how prices are determined, and how resources are allocated. These tools help simplify complex real-world situations into economic models that can be analyzed and understood. In practice, some common tests and analytical frameworks an economist can use include:

But-for analysis: Estimates what prices would have been in the absence of a specific event or course of conduct.
Benchmarking against comparable industries: Compares pricing behavior, margins, etc. across similar markets to identify unusual patterns.
Capacity utilization analysis: Examines the degree to which producers are using their production capabilities, to understand how supply constraints or excess capacity are influencing prices.
Event studies around pricing changes: Analyzes how prices respond to specific events over time to identify causal relationships and broader market reactions.

Methods such as these enable economists to analyze claims of alleged anticompetitive conduct, including in the Fire Apparatus Antitrust Litigation. This can involve testing hypotheses, evaluating market behavior, and drawing reliable conclusions about pricing behavior and market outcomes.

Damages and Impact on Municipal Buyers

Many of the claims against the fire truck manufacturers are brought by municipalities that purchase fire trucks from Defendants. These municipalities presumably expect competitive pricing to help manage limited public budgets and ensure efficient allocation of taxpayer resources. However, if prices were artificially inflated due to the alleged anticompetitive conduct, this would result in municipal buyers paying more than they should have, yielding harm to municipalities in the form of overcharges.

Overcharge Estimation

Overcharges refer to the amounts that purchasers paid in excess of the amounts that would normally correspond to existing supply and demand factors. In terms of fire trucks, the overcharge is what municipalities paid in excess of the prices that would have prevailed in a but-for world absent the alleged misconduct.

Estimating overcharges requires constructing a reliable benchmark to predict what the pricing would have been absent the challenged conduct. Economists have several approaches at their disposal, including creating a but-for pricing model, comparing the affected period to an unaffected “yardstick” period, or benchmarking against similar industries or products. Which approach is best suited for the allegations against the fire truck manufacturers depends on various factors that cannot be accurately assessed without access to the production of documents and data.

Budgetary and Public Safety Implications

Overcharges might not be the only economic harm at issue in cases against fire truck manufacturers. Aside from claims that buyers paid more than they should have, buyers were also forced to delay purchases and extend the life of aging equipment given the stark rise in backlogs. This could have led to a broader economic cost in the form of reduced service quality and increased risk exposure that ultimately should be considered.

Key Economic Questions Going Forward

With cases and allegations stacking up against fire truck manufacturers, there will be several key economic questions going forward such as:

Can observed pricing patterns be explained by cost and demand fundamentals alone?
What impact did information-sharing through FAMA statistics and reporting have?
What is the appropriate competitive benchmark?

Conclusion: Why Economic Analysis Will Be Central

Most cases involving complicated economic questions, vast amounts of data, and complex market dynamics benefit from involving an experienced economist early in the process. Economic analysis provides a structured and rigorous framework for gathering and evaluating evidence and quantifying overcharges.

In these cases against fire truck manufacturers, where pricing behavior, supply backlogs, and the sharing of competitively sensitive information are central allegations, economic analysis is particularly important. These factors require careful, data-driven analysis to distinguish between oligopolistic and coordinated anticompetitive conduct.

By relying on an experienced economist to apply established methodologies, legal teams can expect well-supported analyses demonstrating impact of the challenged conduct on purchasers and the extent of any overcharges, as well as clear and objective conclusions grounded in the facts and economic evidence.

Why Market Efficiency Matters in Securities Cases

The importance of market efficiency in securities litigation traces back to the Supreme Court’s decision in Basic Inc. v. Levinson. In that case, the Court recognized that in an efficient market, the price of a security reflects publicly available information. As a result, investors who rely on the integrity of that price can be presumed to have relied on any material misstatements embedded within it.

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This presumption fundamentally changes the dynamics of class certification. Without it, plaintiffs would need to show that each investor actually relied on the alleged misrepresentation. That is a task that is typically incompatible with classwide treatment. With it, reliance can be established through common proof.

But the presumption is not automatic. Courts require plaintiffs to demonstrate that the market for the security was efficient. And even when efficiency is established, defendants may seek to rebut the presumption by showing that the alleged misstatements did not actually affect the price (a concept known as price impact).

Taken together, these issues place finance and securities experts at the center of securities class actions. Their analysis often determines whether a case proceeds on a classwide basis or not at all.

The Finance and Securities Expert’s Role

Finance and securities experts in securities litigation are tasked with translating financial theory into empirical evidence that courts can evaluate. That is usually not as simple as checking boxes or citing academic literature. It requires a careful examination of how the market for a particular security actually functioned during the relevant period.

At a practical level, this often means analyzing trading patterns, information flow, and price action. It also means selecting and implementing appropriate statistical tools such as event studies that test whether the market responded to new information in a timely and reliable way.

Experienced experts approach these questions holistically. They consider not just individual indicators of efficiency, but how those indicators fit together, and whether the empirical evidence supports a coherent narrative about how the market operated.

Understanding Market Efficiency

Market efficiency is often discussed in theoretical terms, but in litigation it has a more practical meaning. Courts are generally concerned with whether the market for a security quickly and reliably incorporates new, public information into its price. If a security does incorporate new information into its price, it could be an indicator that the market is efficient.

Finance and security experts often describe efficiency in three forms:

Weak-form efficiency, where prices reflect historical trading data
Semi-strong efficiency, where prices reflect all publicly available information
Strong-form efficiency, where prices reflect all information, public and private

For purposes of securities litigation, the focus is almost always on semi-strong efficiency. The question is whether publicly available information such as earnings announcements, press releases, or analyst reports is quickly incorporated into the stock price.

Importantly, efficiency does not require perfection.

Prices need not adjust instantaneously, nor must they always reflect the “correct” value of the security.

Instead, courts look for evidence that the market generally responds to new information in a consistent and economically meaningful way.

Core Indicators of Market Efficiency

Courts and experts often evaluate market efficiency using a set of commonly referenced factors. While these factors are sometimes presented as a checklist, in practice they are better understood as pieces of a broader evidentiary picture heavily supported by data.

Trading Volume and Liquidity

High trading volume is one of the most frequently cited indicators of efficiency. Active trading suggests that a large number of market participants are buying and selling the security, which facilitates the rapid incorporation of information into price.

Metrics such as average weekly trading volume or turnover ratios can provide insight into how actively a security is traded. Higher levels of liquidity are generally associated with more efficient markets, as they allow new information to be reflected in price without significant delays.

Analyst Coverage

Analyst coverage plays a key role in the dissemination and interpretation of information. When a security is followed by multiple analysts, new information is more likely to be scrutinized, interpreted, and communicated to the market.

This process helps ensure that relevant information is incorporated into the stock price. Conversely, limited analyst coverage may indicate that information is not being processed and incorporated as efficiently.

Market Makers and Institutional Participation

The presence of market makers and institutional investors can also support a finding of efficiency. Market makers facilitate trading by providing liquidity, while institutional investors such as mutual funds and hedge funds often engage in sophisticated analysis and trading strategies.

Together, these participants contribute to the process of price discovery, helping ensure that new information is reflected in market prices.

Bid-Ask Spreads

Bid-ask spreads provide a measure of transaction costs and liquidity. Narrow spreads generally indicate that the security can be traded easily and at low cost, which is consistent with efficient markets.

Wider spreads, on the other hand, may suggest lower liquidity and less efficient price formation.

Exchange Listing and Market Structure

Listing on major exchanges such as the New York Stock Exchange or NASDAQ is often cited as evidence of efficiency. These exchanges impose listing requirements and provide infrastructure that supports active trading and information dissemination.

However, courts typically treat exchange listing as one factor among many. It is not, by itself, sufficient to establish efficiency.

Event Studies: The Core Empirical Tool

While structural factors provide a useful context, courts place significant weight on direct empirical evidence of how a security’s price responds to new information. Think of this as relying on data to support your claim. A primary tool for this is an event study analysis.

An event study examines whether a security experiences abnormal returns. For example, price movements that differ from what would be expected based on overall market or industry trends.

The basic approach involves:

Identifying relevant event dates, such as earnings announcements or major disclosures
Estimating a model of expected returns based on market or industry benchmarks
Comparing actual returns to expected returns to determine whether the difference is statistically significant

If the security consistently exhibits statistically significant price reactions to new information, that indicates that the market is incorporating information efficiently.

Courts often view event studies as one of the most persuasive forms of evidence on efficiency. However, their effectiveness depends on the implementation. Choices about the model, the benchmark, and the selection of events can all influence the results. It is important for a finance and securities expert to run sensitivities on their model to ensure it is robust.

From Market Efficiency to Reliance

The connection between market efficiency and reliance is central to securities class actions. Under the fraud-on-the-market framework, an efficient market allows courts to presume that investors relied on the integrity of the market price.

This presumption simplifies the analysis of reliance, transforming what would otherwise be an individualized inquiry into a common one. But it also places significant weight on the efficiency determination itself.

If the market is not efficient, the rationale for the presumption breaks down. Investors may not be relying on a price that reflects all public information, and individualized issues may predominate.

For this reason, efficiency is often heavily contested at the class certification stage. Putting forth a credible analysis at this stage can heavily determine if the case continues.

Price Impact: A Critical Companion to Efficiency

Even when market efficiency is established, the analysis does not end there. Courts have made clear that defendants may rebut the presumption of reliance by showing that the alleged misstatements did not actually affect the security’s price.

This principle was reinforced in Halliburton Co. v. Erica P. John Fund, Inc., where the Supreme Court held that evidence of lack of price impact can be used at the class certification stage.

Price impact refers to whether the alleged misrepresentation, or its correction, had a measurable effect on the stock price. In practice, this often involves analyzing price movements on the dates of alleged misstatements and corrective disclosures.

Efficiency creates the conditions under which price impact can be observed, but it does not guarantee that price impact occurred. A market can be efficient, yet a particular statement may have no measurable effect on price.

How Experts Evaluate Price Impact

Finance and securities experts typically use event studies to assess price impact, much as they do for market efficiency. The focus, however, shifts to specific dates tied to the alleged conduct.

Experts may analyze:

Dates of alleged misstatements
Dates of corrective disclosures
Other events that could have affected the price

The goal is to determine whether the security experienced statistically significant abnormal returns on those dates, and whether those returns can be attributed to the information at issue.

This analysis can become complex, particularly when multiple pieces of information are released at the same time. Disentangling the effects of different disclosures requires careful judgment and, in some cases, additional analysis.

Experts may also consider different theories of price impact, including:

Price inflation, where misstatements artificially increase the price
Price maintenance, where misstatements prevent the price from declining

Each theory has implications for how the analysis is conducted and how the results are interpreted.

Common Challenges in Efficiency and Price Impact Analyses

In practice, analyses of market efficiency and price impact often face a range of challenges.

Some securities trade infrequently or have limited analyst coverage, making it more difficult to demonstrate efficiency. In other cases, the empirical evidence may be mixed, with some events showing significant price reactions and others not.

Confounding information is another common issue. When multiple disclosures occur on the same day, isolating the effect of a particular statement can be difficult. Courts are attentive to these issues and often expect experts to address them directly.

Another recurring challenge is the tendency to rely too heavily on checklists. While structural factors are useful, courts increasingly emphasize direct evidence of price responsiveness. A robust analysis typically combines both.

What Courts Look For

Courts evaluating expert testimony on market efficiency and price impact focus on several key considerations.

First, they look for a clear and coherent methodology. The analysis should be grounded in accepted economic principles and applied in a way that is consistent with the facts of the case.

Second, they consider the fit between the analysis and the legal issues. The expert’s work should address the specific questions before the court, not just provide a general discussion of efficiency.

Third, they evaluate the reliability of the data and the transparency of the analysis. Experts are expected to explain their methods, document their assumptions, and address potential limitations.

Finally, courts often place significant weight on event study evidence. Demonstrating that the market consistently responds to new information can be particularly persuasive.

What Legal Teams Should Look for in a Finance and Security Expert

For legal teams, selecting and working with a finance and securities expert involves more than identifying someone with strong technical credentials.

Experience in securities litigation is critical, particularly at the class certification stage where the legal standards are well developed and heavily contested. Experts who understand how courts evaluate efficiency and price impact are better positioned to provide analysis that is both rigorous and relevant.

Communication is equally important. The most sophisticated analysis will have limited impact if it is not presented clearly. Experts must be able to explain their methods and conclusions in a way that judges (and if necessary, juries) can understand.

Strategic thinking also plays a role. Effective experts do not treat efficiency and price impact as isolated issues. They consider how those analyses fit into the broader case strategy and how they may be challenged.

Conclusión

Market efficiency is not a technical detail. It is a foundational issue that shapes how securities cases are litigated and resolved.

A well-executed analysis does more than check the necessary boxes. It provides a clear, evidence-based explanation of how the market for a security functioned, how it responded to new information, and whether the alleged conduct affected its price.

For legal teams, the takeaway is straightforward. Engaging finance and securities experts early can make a meaningful difference in how these critical issues are resolved.

Economic Analysis as a Framework for IP-Driven Market Behavior

In intellectual property disputes, economic analysis typically begins with understanding the relevant market and how products that use the asserted intellectual property compete within that market.

This may involve evaluating how consumers perceive products, whether certain technologies or features meaningfully differentiate them, and how firms position competing offerings. In some cases, the central question may be whether products serve as economic substitutes.

To ground this analysis, experts can examine:

Observed purchasing patterns across competing products
Pricing relationships between products with and without specific features
Product characteristics tied to the asserted intellectual property
Competitive positioning within the industry

This evidence, along with other information, can help establish whether and how intellectual property-related features are associated with competitive outcomes.

Constructing a Counterfactual in an IP Context

A component of economic analysis in intellectual property disputes is the construction of a counterfactual scenario, often referred to as the “but-for” framework. This approach evaluates how outcomes may differ under alternative conditions.

In the IP context, this may involve considering how the market would function if a particular feature, design, or technology were absent, or if alternative products were used instead. The goal is to develop a structured benchmark that allows for meaningful comparison.

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In practice, constructing this framework may involve:

Examining historical periods before or after the introduction of a feature
Identifying comparable products or technologies
Examining relationships between price, demand, and product characteristics

This approach can help isolate the potential role of intellectual property-related factors from broader market influences.

Evaluating Causation in IP Disputes

Causation may be complex in intellectual property disputes because multiple factors can influence observed outcomes simultaneously. Changes in sales, pricing, or market share may be driven by innovation, marketing, distribution, or broader industry trends.

Economic analysis can address this by testing competing explanations and evaluating which are most consistent with the data. Rather than assuming a single cause, the analysis considers if there are other possible drivers.

Some common factors evaluated include:

The role of the asserted intellectual property
Competing innovations or product improvements
Changes in consumer preferences
Industry-wide or macroeconomic trends

This process can help ensure that conclusions remain grounded in evidence and help avoid over-attribution to any single element.

Understanding Value Contribution of Intellectual Property

Intellectual property may not be the sole driver of product value. Some products incorporate a combination of features, technologies, branding, and distribution strategies that collectively influence performance in the market.

Economic analysis can identify the incremental contribution of specific elements. This may involve evaluating:

Whether the feature or technology influences consumer demand
Its role in product differentiation
Whether it is associated with pricing differences relative to alternatives

This may be especially important in disputes involving complex or multi-component products, where isolating the role of a single element requires careful consideration.

Financial Analysis in an IP Context

Financial analysis translates economic relationships into measurable outcomes. In intellectual property disputes, this may involve examining how products that incorporate certain features perform relative to alternatives.

Some approaches include:

Comparing revenue and margin patterns across products
Evaluating pricing differences between product variants
Assessing changes in financial performance over time

In some cases, evaluating how different scenarios could influence expected performance can be helpful. These analyses are grounded in the economic framework and help quantify observed relationships.

Attribution in Multi-Component Products

Many intellectual property disputes involve products that incorporate multiple components, some of which may be tied to the asserted intellectual property. This can create a challenge in evaluating how much influence any single element may have.

Economic analysis could address this through attribution, which may involve:

Comparing products with and without specific features
Analyzing consumer preferences for particular attributes
Evaluating pricing differences across products

Because components often interact, attribution requires careful judgment and may involve more than one analytical approaches to ensure consistency.

Hypothetical Negotiation in IP Analysis

In some circumstances, economic analysis may consider how parties might behave under a hypothetical negotiation framework. This approach focuses on the economic incentives of the parties and the range of outcomes that could emerge under different conditions.

Within an intellectual property context, this may involve, among other considerations, evaluating:

The potential value associated with access to a feature or technology
The availability of alternatives
The relative bargaining positions of the parties

This framework can provide a structured way to assess one or more economically viable scenarios.

Data Considerations in IP Disputes

The reliability of economic and financial analysis depends in part on the quality and structure of the underlying data. In intellectual property disputes, this may include detailed information on sales, pricing, product characteristics, and financial performance.

Key data considerations can include:

Completeness and consistency of datasets
Availability of feature-level or product-level detail
Transparency in assumptions and adjustments

Addressing these issues supports the credibility and reproducibility of the analysis.

Considering Alternative Explanations

One feature of rigorous economic analysis is the evaluation of alternative explanations. In intellectual property disputes, this can be important because market outcomes are rarely driven by a single factor.

Analysts may evaluate whether observed results are instead explained by:

Competing technologies or innovations
Brand strength or marketing strategies
Distribution or availability differences
Broader market trends

Evaluating these alternatives strengthens the reliability of the analysis and supports a more complete understanding of the market.

Conclusión

Economic and financial analysis provides a structured way to evaluate how intellectual property-related factors interact with market forces and influence observable outcomes.

While these analyses do not determine legal conclusions, they may play an important role in interpreting complex evidence and clarifying how products compete, how value is created, and how different factors may influence financial performance. By grounding analysis in data, testing alternative explanations, and aligning with real-world conditions, economic experts contribute to a more informed understanding of intellectual property disputes.

Framing the Claim, Certainty vs. Probability

At the core of any loss of profits claim lies the issue of reasonable certainty, where the Claimant demonstrates that future revenues would have materialized, but for the harmful act.

However, in many cases, the alleged harm is not purely economic. Reputational or moral damage often affects the likelihood of generating revenues, rather than eliminating a defined income stream.

This distinction is not merely conceptual; it has been reflected in arbitral outcomes. Tribunals have repeatedly required specific and independent evidence of intangible harm and have refused to infer it automatically from a breach. For example, in cases such as Lemire v. Ukraine (ICSID, 2011) and Metal Tech v. Uzbekistan
(ICSID, 2013), claims for moral or reputational damage were rejected where evidentiary thresholds were not met.

Where the alleged harm operates on probability, Discounted Cash Flow (DCF) approaches could possibly overstate certainty, leaving claims vulnerable to challenges related to speculation and causation, particularly in the selection of discount rates.

A careful initial framing, distinguishing between and probabilistic impact, can help ensure methodological alignment and credibility.

Loss of Profits[1] vs. Loss of Opportunity[2]

Where future revenues cannot be established with sufficient certainty, a loss of opportunity framework may provide a more robust and defensible basis for quantification.

This may be relevant where:

The causal chain is indirect or multi step, for example reputational harm affecting market access.
The business lacks a reliable operating history.
Market conditions are volatile or disrupted.

From a practical perspective, adopting a probabilistic approach:

Anchors the valuation in underlying economic reality
Mitigates exposure to challenges based on excessive speculation.
Anchors the valuation with the underlying economic reality.
Supports outcomes that are proportionate, robust, and potentially more readily assessable by the Tribunal.

This approach is reflected in Tecmed v. Mexico (ICSID, 2003), where the Tribunal acknowledged that State conduct damaged the Claimant’s reputation and ability to operate, but compensation was effectively captured through loss of value and lost profits, not a standalone reputational award. The Tribunal therefore accepted a counterfactual framework as the basis for determining quantum, including the economic consequences associated with reputational harm.

This approach is increasingly consistent with arbitral expectations of prudence and analytical discipline.

Managing Double Recovery Risk

The coexistence of economic and intangible harm may create a risk of double counting, which Tribunals scrutinize closely.

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This can arise where:

Reputational harm is claimed separately, while;
its economic consequences are already embedded within a loss of profits model.

A structured approach can mitigate this risk by:

Defining the harmful event.
Identifying and separating the channels of impact.
To the extent possible, ensuring each effect is allocated to only one category of damages. However, where an effect is not fully captured within a single category, any remaining portion may be allocated to another appropriate category, provided there is no double counting.

A disciplined allocation enhances both transparency and defensibility, reducing the likelihood of downward adjustments by the Tribunal.

Integrating Interdisciplinary Evidence

Intangible harm may require input from specialists outside the economic field, including communications, ESG, psychological or market experts.

The role of the quantum expert is to translate these findings into credible economic terms, not to substitute or replicate them.

In practice, this entails:

A clear delineation of expert roles.
Reliance on objective, verifiable inputs.
Transparent integration of external findings into the valuation framework.

Where this is done effectively, claimed harm is anchored in evidence, causally linked to the alleged conduct, and translated into measurable economic effects or probability-weighted outcome, strengthening the overall analysis and supporting Tribunal confidence in the methodology.

Evidentiary Thresholds for Intangible Damages

Although claims for reputational and moral damages are frequently advanced, arbitral practice demonstrates a consistent pattern, they are admissible in principle but rarely granted in practice.

The jurisprudence shows that awards may be limited to exceptional circumstances, often involving serious misconduct or demonstrable psychological or reputational harm. For instance, in Desert Line Projects v. Yemen (ICSID, 2008), damages were awarded in light of threats, coercion, and reputational harm. Whereas in Smurfit Kappa v. Venezuela (ICSID, 2024), damages were only granted on a symbolic basis.

Conversely, in more ordinary commercial disputes, such claims could be rejected.

Key limiting factors may include:

Lack of specific and independent evidence.
Overlap with economic loss, leading to exclusion.
Absence of exceptional circumstances.

Where awarded, such damages may be modest in quantum, reflecting a cautious and proportionate approach.

For Claimants, this underscores the importance of robust substantiation and careful delimitation.

Practical Implications for Counsel and Clients

In light of these developments, several practical considerations emerge:

Frame the claim early and correctly, distinguishing between certainty and probability. Early quantification reduces dispute escalation by replacing assumptions with structured economic evidence.

Select methodologies that reflect the practical nature of the harm, rather than defaulting to standard models.
Address double recovery risks proactively.
Integrate interdisciplinary inputs while maintaining economic rigor and independence.
Approach intangible damages as exceptional claims with heightened evidentiary support.

A well-structured and transparent approach not only strengthens the claim but also enhances its persuasiveness and resilience under scrutiny.

Conclusión

The interaction between loss of profits and intangible harm is reshaping the way damages are assessed in arbitration. As these issues become more complex, engaging an expert with direct experience in assessing both financial and intangible harms is increasingly helpful.

Success increasingly depends on the ability to combine;

Conceptual clarity,
Methodological discipline, and
Evidentiary rigor.

In a landscape where Tribunals are placing greater emphasis on coherence and proportionality, a carefully designed quantum analysis is not simply supportive, it may be determinative of the outcome.

Why Market Definition Matters in Antitrust Litigation

Market definition provides the framework for assessing market power and competitive effects in an antitrust case. Without clearly defined markets, courts likely wouldn’t be able to meaningfully evaluate whether a firm possesses the ability to anticompetitively raise prices, reduce output, or otherwise harm competition. This makes antitrust market definition a pivotal and prominent issue that can shape the trajectory of an antitrust case.

Courts rely on market definition to determine whether alleged conduct could plausibly harm competition. In monopolization cases under Section 2 of the Sherman Act, for example, defining the relevant market is essential to evaluating whether a defendant possesses monopoly power.¹ Similarly, in merger reviews conducted by the Federal Trade Commission (FTC) or the Department of Justice (DOJ), market definition establishes the competitive landscape against which concentration and competitive effects are measured.²

Economic experts can play a central role in helping to translate real-world market behavior into defensible market boundaries. This analysis bridges the gap between abstract legal standards and the practical realities of how firms compete, how customers make purchasing decisions, and how prices respond to competitive forces.

The Concept of the Relevant Market in Antitrust Analysis

The relevant market in antitrust analysis consists of two components: the product market and the geographic market. Together, these define the arena of competition within which competitive effects are evaluated. The Supreme Court established foundational principles for this analysis in Brown Shoe Co. v. United States (1962), and these principles continue to guide modern case law.³

Product Market Definition

Product markets are defined by identifying products or services that consumers view as reasonable substitutes. The central inquiry focuses on demand-side substitution: would buyers switch to alternative products in response to a price increase? If so, those alternatives may belong in the same market.

Economists examine several factors when defining product markets:

- Cross-elasticity of demand between products
- Functional interchangeability from the customer’s perspective
- Industry recognition of distinct product categories
- Pricing patterns such as correlations and customer preferences
- Unique production facilities or distribution channels

The goal is to identify the competitive constraints that limit firms’ pricing behavior. A firm cannot profitably raise prices if customers would simply switch to readily available substitutes. This focus on competitive alternatives, rather than superficial product similarity, reflects the basic economic principles underlying market definition.

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Geographic Market Definition

A geographic market reflects the area (geographically) in which sellers compete and where buyers can turn for alternative products. The analysis examines where customers actually purchase products and whether sellers in different locations effectively constrain each other’s pricing.

Experts assess several factors when determining geographic scope, including:

- Transportation costs relative to product value
- Regulatory barriers that limit cross-border competition
- Customer purchasing patterns and willingness to travel
- Shipping constraints and delivery logistics
- Historical patterns of customer switching between suppliers

Geographic scope is determined by practical, economic constraints rather than formal boundaries. A relevant geographic market might be local, regional, national, or international depending on the specific industry and customer behavior at issue.

Economic Principles Underlying Market Definition

Market definition is deeply rooted in microeconomic theory about substitution and competition. The market definition process starts from the premise that firms are constrained by actual competitive alternatives. If a firm attempts to raise prices above competitive levels, economic theory tells us, buyers will turn to substitutes, and the firm (who attempted to raise price) will lose sales.

In addition to product similarity, economists focus on competitive alternatives. Two products that might appear to be physically similar may not compete in the same market if they serve different customer needs, have different price points, or are purchased through different channels. Conversely, products that seem different may belong in the same market if customers treat them as substitutes or consider them interchangeable.

An analysis of market definition aims to identify the smallest set of products and locations that meaningfully constrain pricing behavior.

This approach ensures that market definition captures the relevant competitive dynamics without including products or areas that do not actually discipline a firm’s pricing behavior.

Key economic concepts applied in market definition include:

The SSNIP Test

How the SSNIP Test Works

The SSNIP (Small but Significant and Non-Transitory Increase in Price) test provides the conceptual framework courts (and competition regulators/agencies) use for defining markets.⁴ The test asks whether a hypothetical monopolist controlling a candidate set of products could profitably impose a small but significant non-transitory increase in price (typically five percent) without losing sufficient sales to alternatives.⁵

Said differently, the test evaluates whether enough customers would switch to alternative products (or suppliers in other geographies) in response to a small but significant price increase such that the price increase would become unprofitable. This would indicate that those alternative products (or geographies) should be included in the same relevant market and the market must be expanded to include those alternatives. The test then repeats with the broader candidate market and continues in an iterative fashion until a market is identified where price increases would be profitable because customers lack adequate substitutes.⁶

The logic is straightforward: a relevant market is one in which a firm would have sustainable pricing power.

Practical Application of the SSNIP Framework

Economists can apply the SSNIP test using data on prices, margins, distribution channels, etc. When detailed transactions data exist, an economist may estimate demand elasticities and calculate whether a 5% price increase would be profitable after accounting for lost sales. This can provide a rigorous and data-driven approach in support for defining a market.

Depending on the available data, the SSNIP test may be implemented quantitatively or qualitatively. Using data, as described above, can be challenging and complex but empirically solveable. However, in some matters, particularly those involving nascent industries or rapidly evolving markets, economic research may rely more heavily on qualitative evidence such as customer interviews, internal business documents, and industry studies. Neither should be considered superior and must be viewed alongside the facts of the case.

It is important to note that courts view the SSNIP framework as a conceptual tool rather than a mechanical formula. As decades of antitrust litigation have demonstrated, judges appreciate analysis grounded in the SSNIP methodology but do not require precise numerical implementation in all cases. The framework provides discipline and structure while allowing flexibility based on available evidence.

Evidence Economists Use to Define Markets

Pricing and Transactions Data

Transactions data (data indicating price paid, quantity purchased, location of sale, date/time, etc.) provides insight into how prices vary across products, categories, customers, and/or locations. Economists often use transactions data to understand pricing patterns, customer segments, and competitive dynamics that help to inform market definition.

Key data elements can include:

- Historical prices across product variants
- Volume and revenue by customer type and geography
- Margin information to assess profitability of price changes
- Price movements over time in response to competitive events

Economists may analyze whether price movements are constrained by competitive alternatives. If prices for two products move together over time (i.e., exhibit correlation) or if price increases for one product lead to sales losses to another, this might suggest the products compete in the same market. Pricing evidence helps assess substitution patterns in practice rather than in theory.

Customer and Supplier Substitution Evidence

Customer switching behavior in response to price changes or supply disruptions is another area economic experts might turn to. Documentary evidence from companies—including strategic plans, competitive analyses, and customer correspondence—often reveals how firms perceive their competitive constraints and which alternatives they monitor. This type of information can be complementary to econometric analyses discussed below.

Supplier responses, such as entry or repositioning, inform supply-side substitution. While the primary focus may be on demand-side substitution, supply-side considerations may be relevant where suppliers can reposition quickly and credibly. The ability of firms to expand or reposition makes it easier for customers to substitute among products or across geographies. Of course, the opposite is also true: if firms lack willingness to alter supply availability, then this weakens customers’ ability to substitute.

Documentary evidence may be used to corroborate economic findings. When a company’s own internal documents identify specific competitors and competitive threats, this provides powerful support for a defined market.

Econometric and Quantitative Analysis

Regression analysis is another tool economists can use to estimate demand elasticities and measure how customers respond to price changes. For example, if the demand for product A (the regression “dependent” variable) increases when product B becomes more expensive (product B’s price is a regression “control” variable), then A and B are substitutes. These techniques can allow an economist to isolate the effect of price on quantity demanded while controlling for other factors like seasonality, economic conditions, and/or product characteristics.

Economic models help test whether products or regions belong in the same market by examining evidence such as:

- Price correlation across products and locations
- Diversion ratios measuring where lost sales flow
- Critical loss calculations assessing profitability of price increases
- Natural experiments from historical pricing events

These analyses support market definition by linking data to economic theory. However, it is worth noting that the extent to which quantitative methods can be deployed depends on data quality and availability—factors that vary significantly across cases from our own experience.

Market Definition and Competitive Effects Analysis

Market definition can inform whether a firm possesses market power. Once markets are defined, economists can calculate market shares along with concentration metrics to assess the competitive landscape. These metrics serve as proxies for the ability to raise prices or exclude competition.

Defined markets provide the context for evaluating pricing behavior, output, and competitive constraints. In reality, the relationship between market definition and competitive effects is iterative—evidence about competitive effects can inform market definition, and market definition shapes how competitive effects are assessed.

An analysis of competitive effects relies on market definition to assess whether conduct harmed competition. Key aspects of this relationship can include:

Market share can provide an initial indicator of market power
Concentration changes (measured by the Herfindahl-Hirschman Index) might signal merger competitive implications⁷
Barriers to entry can help determine whether new competition can discipline incumbent behavior
Buyer power may constrain seller pricing even in concentrated markets

Courts have increasingly recognized that direct evidence of competitive effects can sometimes reduce the emphasis on precise market definition.⁸ When clear evidence demonstrates anticompetitive harm, the substantive issue of competitive impact may take priority over definitional debates.

Market Definition Across Different Antitrust Contexts

Horizontal Conduct and Mergers

In cases or reviews of horizontal competitors, market definition assesses the competitive overlap of the firms. Mergers between firms selling substitute products can raise concerns about reduced competition and potential for price increases. Market definition identifies which products and geographic areas are relevant to evaluating such concerns.

Economists can evaluate whether consolidation or coordination reduces competition within the defined market. Under the Clayton Act, agencies assess whether mergers may substantially lessen competition, and market definition provides the framework for this analysis.⁹ High post-merger market shares, combined with significant increases in concentration, can create presumptions of anticompetitive effects.¹⁰

Vertical and Single-Firm Conduct

Market definition helps evaluate foreclosure and exclusionary effects in cases involving vertical competitors. When a firm controls an essential input or distribution channel, a market definition analysis can examine whether that control can be leveraged to harm competition in related markets

Economists may analyze whether conduct limits access to critical inputs or customers. Vertical restraints, exclusive dealing arrangements, and tying practices all require market definition to assess their competitive significance. A firm with modest market share in a broad market may still harm competition if proper market definition reveals dominance in a narrower segment or adjacent market.

Common Challenges in Market Definition

Market definition presents several challenges that complicate an antitrust analysis:

Data limitations may constrain the ability to provide a quantitative assessment. In such cases, economists can rely more heavily on qualitative evidence (such as produced documents) and industry knowledge.

Rapidly evolving industries might complicate substitution analysis. Technology markets, in particular, present challenges when products and competitive dynamics change rapidly.

A common dispute between economists is whether markets are defined too narrowly or too broadly. Narrow market definitions tend to produce higher market shares which could heighten antitrust scrutiny, while broad definitions can do the opposite.

Additional challenges may include:

Two-sided platform markets where demand on one side depends on participation on the other
Bundled products that may or may not compete with unbundled alternatives
Global supply chains that blur geographic market boundaries
Innovation markets where future competition is uncertain

The Economic Expert’s Role in Presenting Market Definition Evidence

Experts often translate complex market data and analysis into clear explanations relied on by courts. Judges and juries typically lack specialized training in economics, so an effective economic expert must convey sophisticated concepts in accessible terms without sacrificing analytical rigor.

Strong expert testimony explains the assumptions, data, and reasoning underlying market definition. A credible expert opinion often:

Begins with clear articulation of the proposed market, including how it is related to and will help evaluate the alleged anticompetitive conduct
Explains the methodology used and why it is appropriate given the facts of the case or the available data
Presents supporting evidence in logical sequence, e.g., designing and implementing the market definition analyses and tests followed by next estimating market shares and market concentration.
Addresses alternative market definitions and explains why they are less appropriate
Connects the market definition to the competitive effects analysis

Courts expect transparency and consistency between market definition and competitive effects analysis. An expert who defines a narrow market to establish a high market share but then relies on broad competitive conditions to explain firm behavior may face credibility challenges. Sound expert analysis maintains internal consistency throughout.

Conclusion: Market Definition as a Foundation of Antitrust Analysis

Market definition is a critical step in antitrust litigation that shapes how courts evaluate competitive harm. Even as analytical tools have evolved, determining the relevant market has remained central to antitrust cases and it likely will continue to play a pivotal role in the years to come.

Economic experts apply accepted economic tools to define markets grounded in data and real-world behavior. The SSNIP test provides a conceptual discipline, while evidence from transactional data, customer behavior, and produced documents ensures that market boundaries reflect actual competition rather than theoretical abstractions.

Sound market definition supports a credible competitive effects analysis. When markets are properly defined, market shares and concentration metrics provide meaningful information about competitive conditions. When markets are poorly defined—whether too narrow or too broad—the resulting analysis can mislead courts and produce incorrect outcomes. For this reason, engaging a qualified economic expert early in an antitrust matter provides essential benefits for navigating these complex issues.

In complex commercial disputes, measuring damages requires more than a mechanical calculation of lost profits or overcharges. It also requires constructing a framework for analyzing how economic events would have evolved for the relevant parties absent the alleged conduct. Framing an appropriate counterfactual (or “but-for”) state of the world can often be a complex task, especially in cases where multiple factors in addition to alleged misconduct may affect the economic activity under investigation. The purpose of this step is to tie the damages calculation directly to the conduct at issue while minimizing potential confounding effects of other variables.

In this post, I explain how economic experts build credible counterfactual models, including the core steps, the kinds of data and methodologies that are used, and common challenges that arise in that process. By understanding how these models or scenarios are developed and defended, legal counsel and other decision-makers can better evaluate the strength and defensibility of damages claims.

Why “But-For” Analysis Takes Center Stage in Modeling Damages in Litigation

In civil litigation, the quantification of damages often becomes the focal point of a case. Even where liability appears contested, the financial impact of the conduct at issue carries tremendous weight when it comes to negotiation dynamics, trial strategy, and the ultimate resolution of the dispute. With so much riding on a proper quantification of damages, a damages expert’s task requires more than a simple tally of losses. It requires isolating what harm, if any, is economically attributable to the alleged misconduct.

This is where the concept of the “but-for world” takes center stage.

A but-for world is a structured counterfactual scenario that models what economic performance would have looked like had the alleged misconduct not occurred.

It provides a baseline for comparison with actual outcomes, allowing the economic effects of the conduct to be isolated and measured.

Constructing the but-for world is not an exercise in speculation. Rather, it should be grounded in the facts and circumstances and consistent with economic principles. In that regard, the process may require careful consideration of factors such as historical performance, industry context, competitive dynamics, and macroeconomic conditions.

EXAMPLE: Suppose a class of consumers claims it incurred harm in the form of overcharges due to delayed generic entry of a drug. Constructing a proper but-for world scenario should consider factors such as accounting for the drug’s pre-existing decline in sales (historical performance), typical price erosion following generic entry (industry context), the likely number and timing of other generic entrants (competitive dynamics), and changes in prescription demand driven by insurance or economic conditions (macroeconomic factors).

Because damages claims can involve substantial financial stakes, methodological transparency and defensibility are paramount. A but-for model must be capable of withstanding scrutiny of data sources, assumptions, and analytical choices. Understanding how these counterfactuals are constructed provides essential context for evaluating damages claims.

Core Steps in Constructing a But-For Model

While no two disputes are identical, most but-for world analyses (whether they involve a subject individual or business), follow the process described below:

Step 1: Establish the Baseline Scenario

The baseline scenario models the subject’s historical performance to identify normal operating patterns. Baseline scenario analysis may examine factors such as:

- Revenue, cost, and profit margin trends
- Operating capacity and utilization
- Customer mix and competitive position
- Contract terms
- Earnings capacity & earnings growth trends
- Broader industry and economic conditions

The goal is to identify normal operating characteristics and patterns of the business. Using a sufficiently long historical period helps account for short-term volatility and identify relevant trends.

Step 2: Identify the Alleged Misconduct

The expert must clearly identify the conduct at issue and the timing of its effects. Importantly, this step is informed by pleadings and the factual record, and not by economic speculation or unsupported assumptions. Key factors to consider include:

- When did the alleged misconduct begin? When did it end?
- Which business functions did the alleged misconduct plausibly affect?
- Was the impact of the alleged misconduct temporary? Did it have lingering effects after the conduct ended?

Without a clear temporal and conceptual definition of the conduct at issue, constructing a coherent counterfactual becomes difficult.

Step 3: Isolate Affected Economic Variables

Not all financial metrics are influenced by alleged misconduct. The expert must determine which variables are economically relevant and connected to the alleged misconduct. For example:

- A supply disruption caused by exclusionary conduct may increase input costs or constrain output.
- Predatory pricing may suppress a rival’s profit margins, ability to expand capacity, deter market participation, and discourage new entry.
- A wrongful termination or breach of employment contract may affect earnings trajectory, bonuses, and career progression.
- False or misleading statements about a competitor may reduce sales, customer retention, or brand value.
- A breach of contract involving key inputs may result in higher production costs and reduced profit margins.

Identifying relevant economic variables helps prevent overbroad or unsupported damages claims.

Step 4: Develop the But-For Projection

With the baseline established, the alleged conduct clearly defined, and the relevant economic variables identified, the economic expert can develop a projection of how economic circumstances would have prevailed absent the challenged conduct. Although projection methods vary depending on facts of the case and the availability of economic data, common approaches include:

- Trend extrapolation with adjustments for market changes.

EXAMPLE: A regional retailer alleges a competitor’s false advertising campaign caused a sharp drop in sales in 2024. The expert extrapolates the retailer’s 2018–2023 revenue trend but adjusts for sales shocks caused by the COVID-19 pandemic and local population growth to estimate what sales would have been absent the misconduct.

- Application of comparable company benchmarks.

EXAMPLE: A medical device startup claims it was excluded from a hospital network due to anticompetitive conduct. The expert compares the company’s expected growth and profit margins to those of similarly situated startups (same stage, product type, and regulatory status) that were not excluded, using those firms’ performance as a benchmark for the but-for world.

- Application of industry growth rates.

EXAMPLE: A franchisee alleges wrongful termination of a licensing agreement. The expert projects but-for revenues by applying published industry growth rates for that franchise segment, but adjusts them for the franchisee’s historical performance and local market saturation.

- Modeling based on contract terms.

EXAMPLE: A supplier claims breach of a long-term supply agreement. The contract specifies pricing tiers, minimum purchase volumes, and escalation clauses. The expert models but-for profits directly from the contract terms and incorporates the supplier’s expected order volumes and cost structure into the calculation.

- Econometric regression analysis.

EXAMPLE: A class of direct purchasers of a critical construction input alleges that manufacturers of the at-issue product engaged in the conspiracy to fix its price. The expert estimates a regression model of the product price as a function of manufacturing costs, demand, and market conditions using data from unaffected regions or time periods. The model predicts prices absent collusion, and the difference from actual prices forms the basis for overcharges.

Each assumption the expert makes should have a valid basis and the expert must be prepared to explain why his or her projection methodology is reasonable given the available evidence.

Step 5: Compare Actual and But-For Outcomes

The final step involves calculating the difference between actual performance and the projected but-for performance over the relevant damages period. Projections of future performance (e.g., earnings or profit levels) are typically discounted to the present value prior to differencing. This difference represents measured economic impact that is specifically attributable to the alleged misconduct.

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Key Data Sources for But-For World Analysis

Having a solid data foundation can greatly enhance the strength of a but-for world analysis. For this reason, economists prefer to access more data over less and will look to draw from multiple internal and external sources when available. Categories of data that experts typically use to analyze the but-for world include:

Internal Financial Records

Internal financial records and transactional data form the foundation of many but-for damages analyses. Core documentation typically includes income statements, balance sheets, cash flow statements, budgets and forecasts prepared in the ordinary course of business, detailed sales and customer data, and cost accounting records. These materials provide insight into historical performance, cost structure, and operational trends that inform projection modeling.

Industry and Market Data

Industry and market data provide essential context for evaluating company performance within a broader economic framework. External benchmarks may include public filings of comparable firms, economic data published in industry research reports, trade association data, and market pricing surveys. These sources help experts assess how similarly situated businesses performed during the relevant period and whether broader market forces influenced results. Incorporating this external data ensures that but-for projections reflect real-world economic conditions rather than relying solely on internal company assumptions.

Government Agency Data

Government economic statistics provide an independent benchmark for assessing macroeconomic and industry conditions. Sources such as the U.S. Bureau of Labor Statistics, Bureau of Economic Analysis, and U.S. Census Bureau offer data on employment, prices, output, and industry structure. Where necessary, additional information may be obtained through Freedom of Information Act (FOIA) requests.

Economic Journals and Academic Literature

Peer-reviewed economic literature provides both theoretical and empirically grounded support for methodologies and assumptions used in damages analysis. These sources often provide useful data and statistics that can help anchor key assumptions and model inputs the but-for analysis in established empirical evidence. Incorporating this literature helps ensure that but-for projections are consistent with accepted economic principles.

Challenges in Constructing But-For Worlds

Constructing a credible but-for world can be analytically demanding, particularly when data and market conditions are less than ideal. Historical records may be incomplete, inconsistently maintained, or affected by accounting changes and system migrations that complicate comparisons across time periods. At the same time, market volatility (including technological disruption, regulatory shifts, or sudden competitive changes) can increase projection uncertainty and make it inappropriate to assume stable trends. In these circumstances, experts must work carefully within data limitations, clearly disclose constraints, and ensure that models are appropriately tailored to the available evidence.

Closing Remarks

Constructing a credible but-for world is often a central component for estimating economic damages. By carefully establishing a baseline, identifying the alleged misconduct, isolating affected economic variables, and applying appropriate projection methodologies, economic experts can develop a structured and defensible framework for measuring harm. This process ensures that damages are tied specifically to the conduct at issue rather than broader market forces.

Given the complexity and judgment involved at each stage of this process, engaging an experienced economic expert early in the process is critical. The selection of data, the framing of assumptions, and the choice of methodology can materially influence the outcome of a damages analysis. An expert with practical experience in economic modeling is better positioned to navigate these decisions, anticipate challenges, and develop analyses that withstand scrutiny from opposing experts.

At the same time, but-for analysis is inherently fact-specific and often subject to data limitations, competing interpretations, and evolving market conditions. As a result, transparency in assumptions, consistency in methodology, and grounding in reliable data are essential to producing analyses that are both credible and defensible. When executed properly, a well-constructed but-for model provides courts and decision-makers with a clear, economically grounded basis for evaluating damages and assessing the true impact of alleged misconduct.

A PAGA notice initiates a formal process under California law in which an employer is alleged to have committed one or more Labor Code violations. Historically, such notices have often preceded significant litigation exposure.

Recent legislative changes between 2024 and 2026 have modified certain aspects of this process, including providing employers with opportunities to address alleged violations and potentially reduce associated penalties. This article provides an overview of PAGA notices and summarizes key changes in the law.

What is a PAGA letter?

A PAGA letter is a formal notice alleging that an employer violated one or more California Labor Code. The name stands for the Private Attorneys General Act.

A business might get this letter from an employee’s lawyer or the state. Once it arrives, the business usually has 33 days to respond or fix the issues.[1]

The “Private Attorney General” Concept

It is helpful to consider the concept of a “private attorney general.” PAGA establishes a framework in which employees may bring representative actions to recover civil penalties on behalf of the State of California for alleged Labor Code violations. In doing so, it creates mechanisms through which such claims may be pursued, including allowing an individual employee to seek penalties on a representative basis for a broader group of employees.

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Damages vs. PAGA Penalties

There are distinctions between damages and PAGA penalties:

Damages: This is the money a business owes the employee for the actual violation. For example, if someone misses a meal break, they may owe them one hour of pay plus interest.
PAGA Penalties: These are extra fines paid on top of damages. They generally can be pursued for each violative employee pay period.

A Brief History of PAGA

California created PAGA in 2004. Since then, the process has followed a standard path:[2]

Notice: The employee must tell both the employer and the California Labor and Workforce Development Agency (LWDA) they plan to sue.
State Review: The state has 60 days to investigate.
Green Light: If the state does not investigate or respond, the employee’s lawyer can move forward with the lawsuit themselves.

Over the years, filings have trended upward. Since July 2016, these notices are filed online, making them much easier for the state to track. Counts of filings for full years in 2015 and 2016 were not located, so these appear missing.

Key Updates Prior to 2024

Below is my understanding of important case decisions and passing of laws, both in California and on a federal level:

2011 – AT&T Mobility LLC v. Concepcion, 563 U.S. 333: clarified that arbitration is binding, which made PAGA an alternative to class actions in California.
2014 – Iskanian v. CLS Transportation Los Angeles, LLC: clarified that arbitration agreements do not apply to PAGA lawsuits.
2015 – AB 1506: Introduced cure provisions & 33-day window to fix certain wage statement violations
2016 – SB 836: Increased LWDA oversight. Specifically, notice review period extended from 30 to 60 days, requirement to file PAGA notices online, and required LWDA be able to review proposed settlements at same time as the judge.
2018 – Huff v. Securitas: Allowed employee to sue for all violations at a company. This included those they didn’t experience, if they were impacted by at least one.
2022 – Viking River Cruises, Inc. v. Moriana: The U.S. Supreme Court ruled that if an employee signs an arbitration agreement, the employer can force the primary employee’s lawsuit into arbitration.
2023 – Adolph v. Uber – California Supreme Court ruled that even if an individual’s claim is in arbitration, they still have standing. While the primary plaintiff’s lawsuit was in arbitration the group lawsuit stayed on hold.

The Big Changes: 2024 to 2026

In 2024, the state reformed the law to reward businesses that are proactive in addressing wage and hour issues.[3]

Reasonable Steps Clarified (2026)

While the 2024 reform limited PAGA penalties for employers that took “reasonable steps,” it was not initially clear what this entailed. The 2026 reform clarified this.[4] Employers are expected to be able to document that they:

Conduct periodic wage and hour audits (at least annually)
Have proof that policies reflect current law and were received by employees
Documented training for frontline managers
Plan to make “employees whole” for violations. This includes correcting underpayments with interest and taking steps to ensure it doesn’t happen again

Understanding the “33-Day Clock” (2024)

The 2024 reform rewards speed. How an employer handles the first month may have a significant impact on PAGA penalties owed.

Small Employers (Under 100 staff): The employer has 33 days to send a “cure proposal” to the state. If the state accepts the plan to fix all issues, the entire lawsuit may be limited or blocked.[5]
Large Employers (100+ staff): The employer can fix pay stub errors within 33 days to stop those specific claims. For larger issues, they can request an Early Evaluation Conference (EEC). This pauses the case for 70 days. During this time, a neutral party reviews the adequacy of the proposed “cure” and helps both sides reach a settlement that reflects the new statutory limits.[6]

The 60-Day “Reasonable Steps” Window (2024)[7]

Penalties are capped at 30% if an employer shows that it took “all reasonable steps” to follow the law within 60 days of the PAGA notice.

If the employer was already doing regular audits before the letter arrived, that cap drops to 15%. For example, if the employer finds a payroll error during a routine audit and pay the employees back before a lawyer gets involved, their PAGA fine may be reduced by 85%.

New 2026 Regulations[8]

In February 2026, the LWDA proposed a set of rules to clarify the 2024 reform. These rules are expected to be finalized soon, as a public hearing was held April 9:[9]

Details Meaning of “Reasonable Steps”: Defines documents and audits needed to prove reasonable steps were taken, which caps penalties under the 2024 PAGA reform. This is discussed above.
Standard Forms: Plaintiffs must use a specific form with job and location details. No more vague “boilerplate” letters only listing the code sections.
Vexatious Filers: The state now tracks high-frequency lawyers (those filing 200+ cases a year) and subjects them to stricter screening.
Settlement Oversight: The LWDA now has 45 days to review any settlement to make sure it is fair. Previously, LWDA received the proposed settlement at the same time as the court.
Overlapping PAGA Suits Notice: In situations with multiple overlapping PAGA lawsuits against an employer, requires a waiting period of 21 days where other plaintiffs can submit their objections to the LWDA.
Prohibits Adding New Theories: Prohibits adding new theories as part of a proposed settlement agreement.

Practical Considerations

The 33-day response window is a key feature of the PAGA process and can require prompt attention. From a data and analytics perspective, the following considerations may be helpful:

Proactive review: Periodic audits of time and pay practices can help identify and address potential issues in advance. In some cases, documenting these efforts may also be relevant in assessing potential penalties.
Timely evaluation: Once a notice is received, early engagement with data and records can be important. Evaluating workforce-wide information within a limited timeframe can be complex and may benefit from a structured approach.

Developing a clear and well-supported estimate of any amounts owed can help inform next steps and support a more efficient resolution process.

Introducción

In many class cases, class certification can hinge on whether the alleged conduct had a common impact across the proposed class. This is sometimes referred to as classwide impact. While courts may routinely accept that defendants engaged in common conduct, what they often scrutinize much more closely is whether that conduct produced injury that can be shown with common proof on a classwide basis.

That is where economic analysis becomes crucial. A well-developed common impact framework does more than support certification. It can shape how the entire case is understood. Conversely, a weak or misaligned analysis can derail certification even when the underlying allegations might appear strong.

For legal teams, the challenge is not just presenting an economic model, but ensuring that the model aligns with the theory of harm, the available data, and the legal standard under Rule 23 of the Federal Rules of Civil Procedure. The most effective economic experts approach common impact as a structured, step-by-step exercise that integrates economic theory, evidence produced in the case, facts of the industry, and empirical testing.

This article walks through that framework and highlights what courts may find persuasive and what could end up risking rejection.

What “Common Impact” Really Means in Practice

At a high level, common impact asks a straightforward question: can plaintiffs show that all or nearly all members of the proposed class were injured by the alleged conduct using common evidence?

In practice, that question is anything but simple and is one of the most contested points in any class case.

Courts distinguish between common conduct and common injury. A defendant may have engaged in a uniform policy or agreement, but if that conduct affected customers differently or not at all for some, you will risk not satisfying the requirement under Rule 23(b)(3).

This distinction is where many certification efforts break down. Plaintiffs may point to internal documents, industry structure, or anecdotal examples suggesting harm. But courts increasingly expect a rigorous analysis indicating the alleged harm operated through a mechanism capable of affecting the class in a consistent way.

At the same time, courts may not require perfect uniformity. Variation across class members is expected in markets. The key issue is whether that variation reflects noise around a common effect, or whether it demonstrates that impact must be assessed individually.

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The Economist’s Role: Bridging Theory and Evidence

Economic experts sit at the important intersection of theory and proof. Their role is not just to work with data and run regressions, but to connect the alleged conduct to measurable outcomes in a way that can be tested across the class.

That process typically begins with understanding the legal facts of the case, while not rendering any legal opinions. If plaintiffs allege price-fixing, the economist might want to articulate how that conduct would be expected to raise prices. If the claim involves exclusionary conduct, the economist might want to explain how competition was reduced and how that reduction in competition affected pricing, output, and/or quality.

Much of the task of an economist is also empirical in nature. For example, does the data show evidence of the identified effects across the proposed class?

This is where experienced experts tend to differentiate themselves from those that are less experienced. The strongest analyses are not built around a single model introduced late in the case. They are developed iteratively, with the theory of harm, the structure of the market, and the available data informing each other from the outset. It is not uncommon for a model to start off in one place and end up in a completely different place at the end as more and more evidence is produced.

The following steps provide a general foundation for an Economist on a class case.

Step 1: Defining a Coherent Theory of Harm

Everything in a common impact analysis flows from the legal theory of harm. If that theory is vague, internally inconsistent, or not supported by evidence produced in the case, there is generally no amount of statistical work that can change that..

A coherent theory of harm answers three basic questions:

- What conduct is alleged?
- Through what mechanism does that conduct cause harm?
- Who is affected, and how?

In price-fixing cases, the theory is often relatively straightforward: coordinated or collusive behavior tends to lead to higher prices than would have prevailed in a competitive (or but-for) market. But even in a seemingly clear example like that, details matter. Does the alleged conduct affect all products and customers equally? Are there contractual features that could dampen or amplify the economic effects?

In monopolization or exclusion cases, the mechanism can be more complex. The analysis may depend on how rivals were foreclosed, how that foreclosure affected competitive dynamics such as entry and success of rivals, and how those changes translated into outcomes for customers.

Courts pay close attention to whether the theory of harm is grounded in the facts of the industry. Produced internal documents, pricing practices, market structure, and market shares all play an important role. When the theory shifts over time or fails to account for key features of the market, it creates gaps that can undermine the entire analysis.

Step 2: Market Definition and Industry Context

Market definition falls more under the liability umbrella, but it plays an equally important role in common impact. It also happens to be a highly contested issue between experts similar to the class issue we have discussed.

A properly defined market helps establish who was exposed to the alleged conduct. If the proposed class includes customers who operated in meaningfully different markets, that can complicate the argument for common impact.

For example, customers with long-term fixed-price contracts may be affected differently than those purchasing on the spot market. Similarly, geographic differences can matter if competitive conditions vary across regions.

Economic experts typically examine substitutability, market entry, pricing behavior, and broader competitive dynamics to assess whether the proposed market is consistent with a common mechanism of harm. While this can contain a theoretical component in nature, it directly informs how the empirical analysis should be structured.

Step 3: Building a Reliable Data Foundation

Even the most well-conceived model will fail if the underlying data is not reliable.

Common impact analyses often rely on very large, transaction-level datasets with millions or billions of observations. These transactional datasets generally include pricing, quantities, rebates, product characteristics, customer attributes, costs, among other things. In practice, assembling and preparing these datasets is one of the most time-consuming and critical parts of the process. Hiring a team with data experts who have experience handling large volumes of data can be very beneficial for the case broadly.

Data rarely arrives in a clean, ready to use format. It’s not uncommon for it to come from multiple systems, reflect changes or edits over time, or contain inconsistencies that need to be resolved. Decisions about how to clean, normalize, and structure the data can materially affect the results.

Courts have become increasingly attentive to these issues and should be at the forefront of every expert’s work. Experts are expected to explain how the data was prepared and why those choices are appropriate. Additionally, experts are required to provide backup files which include the data, programs, and supporting files that contributed to the experts opinions. Transparency matters. So does consistency.

Step 4: Testing for Common Impact Using Econometrics

With a clear theory of harm and a complete dataset, the next step is to test whether the alleged conduct produced a common effect.

Regression analysis is often the most appropriate and most common tool for this purpose. While the specific econometric model depends on the facts of the case and the question being answered, the general goal is to estimate what prices (or other outcomes) would have prevailed in the absence of the alleged conduct and compare that benchmark to observed outcomes.

Different approaches may be used, including before-and-after comparisons, comparisons existing benchmark markets, or difference-in-differences frameworks. What matters most is not the label attached to the model, but whether it is consistent with the theory of harm and the structure of the data supports such a method.

Courts look for a clear connection between the model and the alleged mechanism of harm. They also evaluate whether the model is capable of detecting classwide effects, rather than simply producing an average that may mask meaningful variation across class members.

Robustness checks play an important role here and are something every economist should do. Testing alternative specifications, examining subsets of the data, and evaluating the sensitivity of results to key assumptions all help establish the reliability of the findings.

Robustness checks also help experts and their teams prepare for criticisms that are forthcoming by opposing experts.

Step 5: Addressing Variation Across Class Members

No real-world market is perfectly uniform, and courts do not expect it to be. The presence of variation does not defeat common impact. With that being the case, the question becomes, what does that variation represent?

If most class members experienced a positive effect consistent with the theory of harm, and the variation reflects differences in magnitude rather than direction, courts are more likely to find that common issues predominate.

On the other hand, if a meaningful portion of the class appears uninjured, or if the model suggests that some members may have benefited, that raises more serious concerns.

Economists use a range of tools to evaluate these sorts of issues. Looking at distributions can show how estimated effects vary across observations. Subgroup analyses can examine whether results differ systematically across customer types or product categories.

The goal is not to eliminate variation, but to understand it. When variation is acknowledged and addressed directly, it tends to strengthen the credibility of the analysis. When it is ignored or obscured, it becomes a focal point for challenge.

Step 6: Aligning Impact with Damages

Courts often emphasize that the method used to establish impact should align with the method used to calculate damages. This does not mean the two analyses must be identical, but they should be grounded in the same underlying theory.

If the impact analysis relies on one mechanism of harm and the damages model relies on another, that disconnect can be problematic and should be considered by the expert. Similarly, if damages require highly individualized calculations, that may undercut the argument that common issues predominate.

A well-integrated approach ensures that the same framework used to demonstrate common impact can also support a classwide measure of damages.

Step 7: Presenting the Analysis to the Court

Even the most rigorous analysis must be communicated effectively. This is true in the economic reports experts prepare, but more importantly in a court room where you will surely have an audience that is not familiar with economic concepts.

Courts evaluating expert testimony under the Daubert standard focus on both reliability and fit. That includes the methods used, the assumptions made, and how well the analysis addresses the issues in the case.

Clarity is critical. Judges (and jurys) are not looking for unnecessary complexity; they are looking for a clear explanation of how the analysis works and what it shows.Experts who can explain a complicated analysis to a lay audience generally have much better success.

Visuals or demonstratives can be helpful, particularly when presenting distributions of estimated effects or comparing observed and benchmark outcomes. But they need to be used carefully, with explanations that make their relevance clear.

Equally important is transparency. Explaining the limitations of the analysis does not weaken it. In many cases, it enhances credibility by showing that the expert has considered potential weaknesses and addressed them directly.

Common Pitfalls in Common Impact Analyses

The following issues arise repeatedly in class certification disputes:

A theory of harm that is not clearly defined or does not match the evidence
Models that rely on averages without examining variation across class members
Failure to account for differences in contracts, products, or customer types
Data preparation choices that are not documented or explained
Analyses developed too late in the process, leading to misalignment with the case strategy

These pitfalls are often avoidable with early expert involvement and a disciplined approach to the analysis. Interacting with the expert regularly also helps as it aligns those focused on the legal issues with the expert who is working with the data and developing the model. Without consistent interaction, you risk a misunderstanding which could make or break a case.

What Legal Teams Should Look for in an Economic Expert

From a practical standpoint, legal teams evaluating experts should focus on more than technical credentials.

Experience matters, particularly in class certification settings where the legal standards are well developed and heavily litigated. So does the ability to work collaboratively, translating economic concepts into arguments that resonate with the court.

Strong experts tend to share a few important characteristics:

They engage early and help shape the analytical framework from the outset
They are comfortable working with complex, imperfect datasets
They communicate clearly and frequently, both in writing and in testimony
They anticipate challenges and address them proactively
They bring up issues with the data or model early and often with counsel

Perhaps most importantly, they understand that the goal is not just to produce an analysis, but to support a persuasive, defensible narrative about how the alleged conduct affected the class.

Conclusión

Common impact is not a box to check. It is a central question that can determine the trajectory and success of a case.

A well-executed analysis brings together theory, data, and empirical testing in a way that aligns with the legal standard and withstands scrutiny. Done correctly, it provides a clear and coherent answer to the question courts care about most: whether injury can be shown with common proof.

For legal teams, the takeaway is clear: involving economic experts early helps ensure the analysis reflects both the case facts and underlying data realities which can potentially shape how the case is ultimately resolved.