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.

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.

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.