As noted in Chapter 2, several different forms of economic analysis may enter into a business interruption loss analysis. In the top‐down framework presented in that chapter, a broad‐based macroeconomic analysis is used to assess the overall economic environment. Following that, the focus is narrowed to the regional level if the business at issue is a regional one. The focus then gets progressively narrowed further, where the firm‐specific analysis is conducted. However, this chapter starts the process by developing the macroeconomic and regional economic tools that are necessary for a thorough business interruption loss analysis. The analytical process for macroeconomic analysis and regional analysis is similar, although some of the data used are different. The macroeconomic and regional economic analysis then sets the stage for industry analysis, covered in Chapter 4.

Economic Fluctuations and the Volume of Litigation

Many attorneys and professionals working in the litigation support field believe that the litigation business is somewhat insulated from economic fluctuations. New research has shown that this is not the case.¹ The extent to which the volume of lawsuits follows the business cycle depends on the type of case. As one would surmise, bankruptcy litigation exhibits clear variation. However, other types of lawsuits are also affected by the variation in the economy. Interestingly, specific types of lawsuits exhibit a countercyclical variation.

Macroeconomic Analysis

Macroeconomics is the study of the overall economy; microeconomics focuses on subunits of the overall economy, such as specific industries or firms. Within the field of macroeconomics, there is a subfield called business fluctuations that analyzes the various factors in the economy that cause it to grow and contract. These business fluctuations are referred to as business cycles. The term “cycles” is unfortunate since it implies a periodicity such as that of a sine curve. Exhibit 3.1 features the usual textbook presentation of a business cycle; it shows an expansion phase that reaches a peak followed by a downturn, usually referred to as a recession. However, the economy does not behave in such a predictable manner. Moreover, the economics profession has not been very successful in predicting the turning points of business cycles.

Definition of a Recession

When the economy turns down and exhibits negative growth, this is termed a recession. Exhibit 3.2 depicts the 1990–91, 2001, and 2008–09 recessions. As mentioned earlier, recessions are generally defined as periods when economic growth is negative.

A simple definition of a recession, one that is often used by the media, is a period when there are two consecutive quarters of negative growth. Recessions, however, are defined on a case‐by‐case basis by the Business Cycle Dating Committee of the National Bureau of Economic Research (NBER) using a variety of economic data to make this determination.² This is a group of six economists, ones who specialize in macroeconomics and business fluctuations, who essentially make a judgment call based on their review of a variety of economic data. They look at more than simply real gross domestic product (GDP) growth; they also consider factors such as employment, personal income, manufacturing, and industrial production.³

Table 3.1 shows the recessions that occurred in the U.S. economy between 1948 and 2009. The average duration of a recession is 10.4 months. The severity of recessions decreased in the U.S. economy of the twentieth century (until we got to the Great Recession). Exhibit 3.3 graphically depicts the various recessions over the period 1948 to 2009.

Measuring Economic Growth and Performance

Many different economic statistics are used to measure the performance of the overall economy and its subunits. The broadest measure of economic performance is gross domestic product (GDP). GDP is the market value of all newly produced goods and services in a country over a period of time, such as one year. When this value is not adjusted for inflation, it is called nominal GDP (see Exhibit 3.4). When it is adjusted for the effects of inflation, which causes the value to increase due to price inflation, rather than greater production, it is called real GDP (see Exhibit 3.4). Real GDP grows at a lower rate than nominal GDP. This is reflected in the flatter slope of Exhibit 3.4 (a) relative to Exhibit 3.4 (b). The Bureau of Economic Analysis of the U.S. Department of Commerce publishes both real and nominal GDP data.

GDP is subdivided into four broad components: personal consumption expenditures, investment, government expenditures, and net exports (defined as the difference between exports and imports). The relative contribution of each component is shown in Table 3.2. The real equivalents of the nominal data shown in Table 3.2 are shown in Table 3.3. However, within each broad component there are still more narrowly defined subcomponents. For example, within total personal consumption expenditures one finds expenditures on durables, nondurables, and services. Depending on the business of the plaintiff, one may want to know the overall economic performance as reflected by GDP and personal consumption expenditures (see Exhibit 3.5); however, if the plaintiff is a marketer of durables, the durable component of personal consumption expenditures may be more relevant. In addition, if the plaintiff is a retailer, one may want to also review the trend in retail sales in addition to these consumer expenditure data. By narrowing the focus of the broad macroeconomic aggregates to better fit the nature of the plaintiff ’s business, it is possible to obtain additional information on the state of the economy specific to the case in question.

Business Cycles and the Movement of GDP Components

When evaluating the components of GDP and seeing how they each vary with the business cycles, we see that they do not move uniformly with GDP. The most volatile of these components are investment, the durable component of consumption, and the net exports. These components are more volatile than GDP overall. For that to be the case some other components have to be less volatile. These are government expenditures and the nondurable component of consumption.

In industries that make durables, such as automobiles and aircraft, the sales of their products are quite procyclical. Other sectors, such as nondurables like food and clothing, are much less cyclical. We say they are mildly procyclical. When the economy declines their sales may weaken somewhat, but not to the extent of makers of products like automobiles. Thus, when an expert is measuring damages for a provider of products or services, it is important to be mindful of how cyclical the business is. Perhaps a decline in sales that a plaintiff is alleging was caused by a defendant was actually a decline that would be what was expected given the nature of the product relative to the business cycle.

Business Cycles and Economic Damages

One factor that can cause a firm to experience losses is an overall slowdown of activity in the economy. When the economy is in recession, many companies slow down and generate losses. Such economy‐induced declines need to be differentiated from ones caused by the actions of the defendant. The analysis can become more complicated when both events are occurring at the same time. That is, it may be more challenging for the economist to filter out the losses caused by an economic downturn that were coincident with the damaging actions of the defendant. In some cases, the economy may be solely responsible for the losses of the plaintiff. In other cases, an economic downturn may explain some but not all of the plaintiff’s losses. When the economy‐wide influences are not considered, the defendant may be wrongly blamed for the losses of the plaintiff. In order to understand this, we need to learn more about business cycles.

There are varying theories on the causes of business cycles. For example, one theory that is currently popular in the economics profession is the Real Business Cycle Theory.¹¹ This theory sees the causes of the employment and output variations that occur in business cycles in terms of variations in technology and supply shocks.¹² An example of an adverse supply shock is the increase in oil prices in the 1970s, which slowed the economy and contributed to the recessions of 1974–75 and 1980.

Though the role that supply shocks can play in causing a recession is well established, there is not one accepted theory that can convincingly explain all business cycles. Most economists agree that there is no single cause of all economic downturns; further, the cause of such declines in the performance of the economy can vary depending on the particular circumstances of the economic downturn in question. The forensic economist, however, is not as concerned about the cause of a recession as he or she is about the reality of recessions and their recurring yet unpredictable pattern. One way to assess this pattern is to consider certain trends that are common to the cyclical variation of the national economy. These are the frequency of recessions and the average duration of recessions and recoveries.

During the years 1945 to 2020, there were eleven recessions in the U.S. economy. The average duration of these recessions was 11.1 months, while the average duration of the recoveries that followed was 67 months (see Table 3.1). A recovery is defined as the number of months between the trough of the downturn and the peak of the following upturn. There is some evidence that, in general, recessions have been getting milder and recoveries may have been getting longer. However, some economists dispute that and contend that this may be a function of increasingly higher‐quality economic data covering the more recent postwar time period. ¹³But recoveries have started more slowly and have been weaker at first. This certainly was the case with the recovery from the Great Recession. However, the expansion built up good momentum. While they may have started slowly, especially the 1990s expansion, the U.S. economy has had two very impressive back‐to‐back expansions in the 1980s and the 1990s.

Basic Facts About Business Cycles for Experts to Be Mindful Of ¹⁴

1. Business Cycles Are Not Cyclical: The term “cycles” does not apply to actual business fluctuations. The reason is that “cycles” implies a regular periodic phenomenon and business fluctuations do not behave in such a regular or repetitive manner.
2. Business Cycles Are Not Symmetrical: This is another way that business fluctuations are not cyclical. The length of cycles can vary from one to another. One recession may be longer or deeper than another and the same applies to expansions.
3. Varying Nature of Business Cycles: Due to the fact that cycles vary over time and that each is different, it is hard to extrapolate reliable trends across many cycles. For example, after the 1990 and 2000–01 recessions, some concluded that recessions were becoming milder and shorter. This also led some to conclude that the government and central bank had mastered the art of managing such downturns. Then we had the Great Recession of 2008–09.
4. Varying Changes in GDP Components Across Expansions and Recessions: It is clear that different expansions and recessions have different causes. For example, investment‐related “shocks” may be more of a cause on one downturn than another. Thus, it is normal to expect the changes in the components of GDP to be different across different downturns. In addition, certain expansions may be spurred on by different changes in certain components, such as a stronger than normal level of consumer expenditures.
5. Business Cycles Tend to Be More Severe in Third World Countries: In general, poorer countries tend to be more vulnerable to deeper downturns. They also have weaker central banks and a lesser ability of the government to engage in countercyclical policies. The opposite would be the case for a nation such as China, which has been very active in trying to offset any perceived weakness in its economy.

Varying Responses to Business Cycles Across Industries

Not all industries respond similarly to the ups and downs of the economy. Some are more procyclical than others. It is hard to find firms that are truly countercyclical. However, some do gain when others, such as high‐priced companies, lose sales. Some of the research in this area has focused on variables such as employment because this is a data set that is available on a timely and frequent basis (such as monthly).¹⁵ Studies have examined the correlation between industry demand and employment.¹⁶

The results of research by the Bureau of Labor Statistics on these employment effects were very intuitive. Industries that were known to be cyclical, such as the furniture industry, had the closest to 1 correlation coefficients. Others, including various services industries, such as accounting, education, and even commercial sports, had the closest correlations to –1. (See Table 3.4.)

Using More Narrowly Defined Economic Aggregates

The expert should select specific economic aggregates that are closely related to the performance of the plaintiff’s business. For example, if the plaintiff is a retailer, the expert could look at the variation in consumption expenditures and retail sales (see Exhibits 3.6 and 3.7). If the retailer sells only consumer durables, such as appliances, then more defined aggregates, such as the consumer durable component of consumption expenditures, can be selected (see Exhibit 3.8). Depending on the nature of the plaintiff’s business, various economic aggregates can be selected to determine overall macroeconomic environment. The economist needs to examine the historical trends of the selected aggregates and the company’s sales to make sure that the hypothesized relationship between the overall level of economic activity, as reflected in the trends in the selected aggregates, is consistent with the variation in the plaintiff’s sales. That is, the expert needs to verify that when the economy was expanding, as evidenced by the variation of the selected aggregates, the plaintiff’s business was also expanding. If that covariation is not apparent, then a further investigation needs to be conducted to make sure that there is a satisfactory explanation for what caused the differences.

Quantifying the Strength of the Relationship Between Selected Economic Aggregates and Firm Performance

The closeness of the association among these economic aggregates and the revenues of the plaintiff can be quantitatively measured using the correlation analysis discussed earlier. This is important to consider because it bolsters the economic theory that the economist presents. For example, the expert can say that a retail firm’s revenues for the years 2017 and 2018 should have risen because the economy was expanding: national income, consumer expenditures, and retail sales were all rising. The expert can go on to elaborate that the economy was in the longest postwar expansion in U.S. history. It may be even more compelling, for example, to state that 48% of the variation in the sales of the plaintiff could be explained by variation in national retail sales. A correlation analysis allows such percentages to be derived through the computation of what is known as the coefficient of determination. As we have noted, this is the square of the correlation coefficient. It represents the proportion of the total variation in the dependent variable, such as the plaintiff’s sales, that is explained by variations in selected independent variables, such as the national retail sales depicted in Exhibit 3.4. This further establishes the importance of considering these specific economic aggregates.

Implementing Inflationary Adjustments

Damages experts need to understand the inflation process. When projecting a company’s revenues, some experts increase monetary values at the rate of inflation. If inflationary adjustments alone are the only factor taken into account, the resulting projection may be quite flawed. Nonetheless, inflationary changes in price can be a factor that is considered in the lost revenues projection process. Thus, it is important. Issues such as the overstatement of inflation statistics are well known to economists but may be less well known to noneconomists. For that reason, we will discuss these issues here.

When a person, such as a typical juror, considers an inflation adjustment, they may be thinking about the consumer price index. This is what most people think about when they hear in the media about inflation statistics.

Overstatements in Inflation Statistics

Economists have known for some time that the inflation statistics issued by the Bureau of Labor Statistics of the U.S. Department of Labor may overstate the true rate of inflation. These statistics are constructed using what is known as a Laspeyres index. This type of index compares the value of a variable in a specific year with that of a preselected base year. The formula for a Laspeyres index is shown in Equation 3.1.

(3.1)

where:

• pⁱ_t = the price of the ith product at time t
• qⁱ_t = the quantity of the ith product at time t

The Laspeyres index keeps the original quantity fixed at q₀. One of the criticisms of a Laspeyres index, such as the consumer price index, is that it does not take into account the substitution effect whereby consumers switch to less expensive substitutes when prices of certain goods rise. This is because it keeps the original market basket the same. In doing so, it fails to consider the substitution effect when consumers switch to alternative products that may offer lower prices.

Other alternatives to a Laspeyres index are available, such as the Paasche index, which, instead of keeping the starting quantity fixed, uses the ending period quantity shown in Equation 3.2.

(3.2)

The Paasche formula also presents its own problems. Instead of using the original quantity q₀, it uses an ending period quantity q_t. A compromise between the Laspeyres and the Paasche indices is the Fisher “Ideal” index, which is depicted in Equation 3.3.

(3.3)

A review of Equation 3.3 shows that the key difference between the Paasche index and the Laspeyres is that the Paasche uses ending period quantities (q_t+1) as opposed to beginning period quantities (q₀). Normally, the Paasche index results in lower values than the Laspeyres index. The Fisher Ideal (FI), shown in Equation 3.3, being the product of the two, will then also be lower than the Laspeyres index. In sum, a Laspeyres index, such as the consumer price index, is flawed in the sense that it overstates inflation while a Paasche index might understate it. These flaws in the Laspeyres index overstatements come from several sources.

One of the fundamental flaws of the CPI is that it does not fully capture the substitution effect as consumers switch from more expensive products to less costly ones. Another flaw of the CPI is that it does not take into account qualitative differences in products over time. Products such as computers improve substantially over time. For example, a computer bought today for $2,000 is likely of significantly greater quality than one sold five or six years earlier for the same price. Still another problem with using a basic Laspeyres index is that it will not capture the introduction of new products because such an index would be using the quantities at t₀. Lastly, another possible source of upward bias is what is called outlet bias. This derives from the fact that large discount chains such as Costco and Sam’s Club may offer certain products at lower prices than other retail outlets. Still another cause of concern is the availability of products on the Internet, such as at Amazon, which may offer low prices – ones that may also change more rapidly than the BLS can capture. Nonetheless, the BLS is aware of these issues and is trying to sample prices from the sources that the consumers indicate they used including outlets and online.

The Bureau of Labor Statistics, with its large number of research economists, is well aware of the problems with the CPI’s overstatement of inflation. As a result, the BLS has implemented various changes in how the index is computed.¹⁹ This includes trying to address the substitution effect through the use of a geometric mean formula, thus placing less weight on prices that have increased the most. The BLS has also tried to take into account qualitative changes in products – especially ones that may have made prior versions obsolete. Based upon these various changes, while the CPI may at one time have overestimated actual inflation by about 1%, most economists believe that overestimation is not less, although there is still debate about the extent of the current overestimation.²⁰

The fact that the CPI overstates actual inflation has been well known to economists for many years. For example, in the mid‐1990s a report issued by the Advisory Commission to Study the Consumer Price Index – headed by Michael Boskin, chairman of the Council of Economic Advisors – concluded that the consumer price index, which was approximately 3% in 1996 (the year of the report), might have been overstated by as much as 1.1% per year.²¹ This implies that the inflation rate in that year might be below 2%. The authors of the Boskin Report have admitted that many of the adjustments they made were subjective judgments on factors such as qualitative improvements. In making such judgments, they have, in effect, created more of a cost‐of‐living index than a true price index.

The Boskin Report concluded that the CPI may overestimate inflation by about 1%. A later study arrived at an average 0.9% overestimation.²² These studies and others led to changes in the way that the CPI is computed.

While any overstatements of inflation embedded in the CPI put forward by the Labor Department Bureau of Labor Statistics may make inflationary adjustments applied by damages experts somewhat “on the high side,” they are often more concerning when they are used by the central bank in gauging its monetary policy goals and actions. For this reason, policy makers often look to a somewhat more accurate price index. This is the Personal Consumption Index (PCE), prepared by the Bureau of Economic Analysis of the U.S. Department of Commerce.

While damages experts often focus on the CPI, in damages analysis commercial lawsuits it may be useful to consider other indices. The CPI is really designed to reflect the cost of living to consumers. From a commercial damages perspective this is very important, as consumption is 68% of the U.S. economy and so many products and services are marketed to consumers. Thus, it may at times be useful to consider indices such as the producer price index. This is the producer’s counterpart to the CPI. This index, sometimes also called the wholesale price index, reflects the change in selling prices that producers receive from selling their products.

Regional Economic Trends

The fact that there are unique regional differences within a national economy is a well‐established proposition within the field of regional economics – sometimes called urban economics.²³ However, while there are many practitioners in the field of regional economics, the published literature is limited.²⁴ Nonetheless, the field is an established one with reliable data sources.

When the economy expands, not all regions of the country participate equally in this expansion. For example, California entered the 1990–91 national recession after many other parts of the country. However, the recession in California and the Northeast lasted longer than it did in other regions of the country (e.g., the Midwest). While the economy entered a recession prior to September 11, 2001, the regional economic impact of this terrible event was particularly pronounced in New York City, especially lower Manhattan.

For companies whose markets are mainly regional, where firms derive most or all of their sales from a particular region, the difference between regional and national economic climates is important. The macroeconomic analysis needs to focus on the economic activity within a particular region.

Many of the data sources available on the national level are also available on a regional level. State governmental agencies as well as private sources supply a variety of regional data. Using such data, the economist can observe the trends in regional economic aggregates and investigate the relationship between the plaintiff’s sales and the variation in the regional aggregates. Regional aggregates, such as state retail sales (see Exhibits 3.7 and 3.8), should be included in the overall macroeconomic framework; this puts the variation in the plaintiff’s sales during the alleged loss period in the proper macroeconomic context. For example, if all of the national and regional aggregates were expanding during the loss period, and the plaintiff’s sales (which normally move with the variation in these aggregates) moved sharply in the opposite direction, then an explanation other than the level of economic demand needs to be explored. However, when dealing with a more regional business and when there is a significant difference between the performance of the regional and the national economy, there may be cause to place more weight on the regional economic data and less on the national data.

Quality and Timeliness of Regional Economic Data

As the geographic region narrows, the availability and quality of the economic data may decline. Some data, such as gross state product, are not readily available from the Commerce Department and may be several years behind their national counterparts. Lacking access to aggregates such as consumption expenditures, the economist may substitute other closely varying time series such as retail sales, which are available on a timelier basis. This substitution process must be handled on a case‐by‐case basis and is often influenced by factors such as the nature of the product at issue.

Certain regional economic data are readily available. These include employment data produced by the U.S. Department of Labor. Typically, employment data are the timeliest and are even available for certain industry subcategories. They also can be used as an indicator of the performance of certain other sectors for which timely data are not available. For example, construction employment data are available on a timely basis for specific regions, such as states. These data can be used in the analysis of the performance of the construction industry. Although employment is a variable that lags the business cycles, it may provide useful information on the trends in a given industry. For plaintiffs in an industry such as construction, these types of data series add information that the economist can consider when analyzing the alleged damages of a plaintiff.

International Economic Analysis

For some types of commercial damages analysis, the focus of the economic analysis may need to be widened, rather than narrowed, even beyond the national level. If the plaintiff derived its demand from an international source, then an international area may require scrutiny. For example, if a U.S. plaintiff derives its sales from a specific country or group of countries outside the United States, the performance of those economies may need to be analyzed. A review of the performance of different national economies can quickly reveal that not all countries grow at the same rate. For example, when the United States economy started to recover and grow after the 1990–91 recession, the Japanese economy, the international economic star during the 1980s, was stagnant and experienced the pains of a recession. The same occurred again in the 1990s and early 2000s as the Japanese economy repeatedly went in and out of recession. This is shown in Exhibit3.8. One can see from an examination of the respective growth rates of the U.S., British, and Japanese economies that growth rates are somewhat similar; however, there are important differences. For example, in 1990, the U.S. and British economies slowed and then entered a recession in 1991, while the Japanese economy exhibited strong growth in 1990 but began to slow in 1991 and 1992. Japan’s growth turned negative in 1998 while growth remained strong in the United States and England. What is clear is that if the conditions of one nation’s economy are relevant to the losses of a plaintiff, such as when a nation or company in another nation is responsible for a significant amount of the lost sales of the plaintiff, a separate economic analysis of that country’s economy is required.

Obviously, for companies that have lost sales that would have been generated in a currency other than U.S. dollars, a currency conversion may be necessary. For historical losses, the historical conversion rates need to be used to convert the foreign currency into dollars. These statistics are readily available from several sources. For projection of future losses, the value of the respective currencies needs to be taken into account.

The field of international economics is a separate subfield within economics. Economists who work in the field of international economics, and who publish in the field’s specific journals, may not work in other areas. It is common for economists in the field of international economics to specialize in the economies of a specific country or group of countries. In cases that involve international economics, it may be useful to bring in an international economics specialist whose concentration is the economies of the countries in question. However, given that litigation economics is a separate subfield of economics, it is likely that the international economist lacks experience in litigation and the techniques of measuring damages. Therefore, such a specialist is an expert who is brought on to the litigation support team and who works at the direction of the economist conducting the loss analysis. That economist will stipulate the method of measuring damages and the damages loss model. As part of that process, certain tasks may be delegated to the international economist, who will hand off his or her output to the primary litigation economist. Depending on the issues involved, it may be useful to have both an economist and an accountant use the interdisciplinary approach advocated in this book. It may also be wise to involve international counterparts, each of whom deals with relevant international economic and accounting issues. Obviously, the size of the case and the international orientation of the issues have to justify involving such a group of experts.

Globalization of Supply and Demand

For companies that source their products in markets outside the U.S. such as Asia, as well as companies that market their products and services to foreign countries, this is a very important factor that may have to be factored into a lost profits analysis to the extent that conditions significantly change. A great example of this occurred in 2018–19 when the U.S. imposed tariffs on Chinese imports and when the Chinese responded in kind with their own tariffs. U.S. importers of Chinese profits saw their costs rise and then had to try to recoup these cost increases through higher prices. Obviously, the extent to which they could do that was governed by the elasticity of demand for their products. Many firms had to absorb some of the cost increase and accept an eroding of their profit margins. In such instances applying a historical margin to this time period might result in a speculative loss.

China, the world’s second largest economy, is a major source of demand for many companies. When the Chinese economy weakened in 2018–19, sales of certain U.S. products slowed. In 2019, U.S. companies such as Caterpillar and Apple reported weaker earnings – primarily due to slow demand from China.²⁶

In addition, in China the government can be a greater or lesser impediment to foreign companies and sometimes these changing positions are hard to predict. This also makes using historical data a more precarious exercise and one in which a more detailed analysis is necessary.

The slowdown in China, and other parts of the world paled in comparison to the global slowdown that came about as a result of the coronavirus pandemic. This pandemic, which originated in Wuhan, China, quickly spread throughout the world due to its high contagiousness and the poor decisions made by various governmental officials. The economic effects were horrendous. Equity markets collapsed and central banks, which had already used up many of the expansionary tools, such as interest rate reductions, could do little to offset the collapse. The reason for this is expansionary monetary policy tends to often be a weak tool and works best under special conditions. One such condition would be pent‐up borrowing demand which might reasonably respond to lower rates. However, in a depressed economy there is less pent‐up loan demand.

At the time of this writing, the global economy is in the throes of this pandemic and only starting to experience its pernicious effects. Economies of some weaker nations, such as Italy and Greece, are being totally annihilated. Specific U.S. industries, such as airlines and cruise lines, are being brought to their knees.

The relevance of this to business interruption losses, is that losses that may have been projected prior to this calamity will have to be evaluated through the prism of what actually did occur in the economy ̶ not what might have occurred had this event never happened. But‐for projections made based upon pre‐Coronavirus days will have to be considered in light of dramatically changed economic conditions.

Summary

This chapter introduced the first step in the methodological due diligence process of measuring business interruption loss analysis. This first step is the analysis of the macroeconomy. In doing this analysis, the expert assembles a variety of macroeconomic aggregates, starting with gross domestic product, and then concentrates on the part of the macroeconomy that most directly relates to the business of the plaintiff. In doing this analysis, the expert analyzes the strength of the relationship between changes in the selected macroeconomic aggregates and the plaintiff’s revenues and profits. Statistical measures such as the correlation coefficient can be used to measure the association between the performance of the macroeconomy and the performance of the plaintiff.

One reason for doing the macroeconomic analysis is to determine the extent to which the performance of the economy was responsible for the losses of the plaintiff. Conversely, if the economy was doing well, past experience, as assessed by the aforementioned statistical analysis, may create an expectation that the plaintiff should have realized a certain level of revenue and profit growth, while instead it incurred losses. In this case, macroeconomic analysis is an important first step in the economic damages analysis. The term “first step” is important because the macroeconomic analysis is but one part of the overall loss estimation process. Further investigation may show that the role of the economy was not that significant compared to other factors.

After having done the broad‐based macroeconomic analysis, the focus may be narrowed to the regional level if the plaintiff was mainly a regional business or if the losses at issue are restricted to a specific region of the country. In this part of the analysis, regional economic aggregates are used in a similar manner as they were for the macroeconomic analysis. The regional aggregates may be state‐level data or more narrowly focused economic statistics. Unfortunately, the quantity and timeliness of regional economic data are not as good as they are on the macro level.

Sometimes the economic analysis may need to be broadened rather than narrowed. This is the case when the losses have an international element. In such an instance, the economist may need to conduct a macroeconomic analysis of other relevant economies. This may involve the expertise of international economists depending on the relevant issues.

The macroeconomic framework defines the overall economic environment within which the plaintiff and defendant were operating at the time of the alleged losses. It can be used to find other possible causes of the plaintiff’s losses, such as an economic downturn. It can also be used to create an expectation of gains instead of losses as the focus of the litigation, when the economy was doing well in the loss period and when the macroeconomic analysis has shown that the plaintiff has done well in such economic conditions. The macroeconomic analysis is an important first step in the overall damages process. Once it has been done, the next step is to do an analysis of the industry within which the plaintiff was operating.

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www.nber.org/cycles.

www.ny.frb.org.