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The Return of the FedEx Indicator?

On September 16, 2022 an article in the Wall Street Journal had the headline: “Economic Worries, Weak FedEx Results Push Stocks Lower.” Another article in the Wall Street Journal noted that: “The company’s downbeat forecasts, announced Thursday, intensified investors’ macroeconomic worries.”

Why would the news that FedEx had lower revenues than expected during the preceding weeks cause a decline in stock market indexes like the Dow Jones Industrial Average and the S&P 500? As the article explained: “Delivery companies [such as FedEx and its rival UPS) are the proverbial canary in the coal mine for the economy.” In other words, investors were using FedEx’s decline in revenue as a leading indicator of the business cycle. A leading indicator is an economic data series—in this case FedEx’s revenue—that starts to decline before real GDP and employment in the months before a recession and starts to increase before real GDP and employment in the months before a recession reaches a trough and turns into an expansion.

So, investors were afraid that FedEx’s falling revenue was a signal that the U.S. economy would soon enter a recession. And, in fact, FedEx CEO Raj Subramaniam was quoted as believing that the global economy would fall into a recession. As firms’ profits decline during a recession so, typically, do the prices of the firms’ stock. (As we discuss in Macroeconomics, Chapter 6, Section 6.2 and in Economics, Chapter 8, Section 8.2, stock prices reflect investors’ expectations of the future profitability of the firms issuing the stock.)

Monitoring fluctuations in FedEx’s revenue for indications of the future course of the economy is nothing new. When Alan Greenspan was chair of the Federal Reserve from 1987 to 2006, he spoke regularly with Fred Smith, the founder of FedEx and at the time CEO of the firm. Greenspan believed that changes in the number of packages FedEx shipped gave a good indication of the overall state of the economy. FedEx plays such a large role in moving packages around the country that most economists agree that there is a close relationship between fluctuations in FedEx’s business and fluctuations in GDP. Some Wall Street analysts refer to this relationship as the “FedEx Indicator” of how the economy is doing.

In September 2022, the FedEx indicator was blinking red. But the U.S. economy is complex and fluctuations in any indicator can sometimes provide an inaccurate forecast of when a recession will begin or end. And, in fact, some investment analysts believed that problems at FedEx may have been due as much to mistakes the firms’ managers had made as to general problems in the economy. As one analyst put it: “We believe a meaningful portion of FedEx’s missteps here are company-specific.”

At this point, Fed Chair Jerome Powell and the other members of the Federal Open Market Committee are still hoping that they can bring the economy in for a soft landing—bringing inflation down closer to the Fed’s 2 percent target, without bringing on a recession—despite some signals, like those being given by the FedEx indicator, that the probability of the United States entering a recession was increasing.

Sources: Will Feuer, “FedEx Stock Tumbles More Than 20% After Warning on Economic Trends,” Wall Street Journal, September 16, 2022; Alex Frangos and Hannah Miao, “ FedExt Stock Hit by Profit Warning; Rivals Also Drop Amid Recession Fears,” Wall Street Journal, September 16, 2022; Richard Clough, “FedEx has Biggest Drop in Over 40 Years After Pulling Forecast,” bloomberg.com, September 16, 2022; and David Gaffen, “The FedEx Indicator,” Wall Street Journal, February 20, 2007.

Should the Fed Be Looking at the Median CPI?

For years, all the products for sale in Dollar Tree stores had a price of $1.00 or less. But as inflation increased, the company had to raise its maxium prices to $1.25. (Thanks to Lena Buonanno for sending us the photo.)

There are multiple ways to measure inflation. Economists and policymakers use different measures of inflation depending on the use they intend to put the measure of inflation to. For example, as we discuss in Macroeconomics, Chapter 9, Section 9.4 (Economics, Chapter 19, Section 19.4), the Bureau of Labor Statistics (BLS) constructs the consumer price index (CPI) as measure of the cost of living of a typical urban household. So the BLS intends the percentage change in the CPI to measure inflation in the cost of living as experienced by the roughly 93 percent of the population that lives in an urban household. (We are referring here to what the BLS labels CPI–U. As we discuss in this blog post, the BLS also compiles a CPI for urban wage earners and clerical workers (or CPI–W).)

As we discuss in an Apply the Concept in Chapter 15, Section 15.5, because the Fed is charged by Congress with ensuring stability in the general price level, the Fed is interested in a broader measure of inflation than the CPI. So its preferred measure of inflation is the personal consumption expenditures (PCE) price index, which the Bureau of Economic Analysis (BEA) issues monthly. The PCE price index is a measure of the price level similar to the GDP deflator, except it includes only the prices of goods and services from the consumption category of GDP. Because the PCE price index includes more goods and services than the CPI, it is suits the Fed’s need for a broader measure of inflation. The Fed uses changes in the PCE to evaluate whether it’s meeting its target of a 2 percent annual inflation rate.

In using either the percentage change in the CPI or the percentage change in the PCE, we are looking at what inflation has been over the previous year. But economists and policymakers are also looking for indications of what inflation may be in the future. Prices of food and energy are particularly volatile, so the BLS issues data on the CPI excluding food and energy prices and the BEA does the same with respect to the PCE. These two measures help avoid the problem that, for example, a period of high gasoline prices might lead the inflation rate to temporarily increase. Note that inflation caclulated by excluding the prices of food and energy is called core inflation.

During the surge in inflation that began in the spring of 2021 and continued into the fall of 2022, some economists noted that supply chain problems and other effects of the pandemic on labor and product markets caused the prices of some goods and services to spike. For example, a shortage of computer chips led to a reduction in the supply of new cars and sharp increases in car prices. As with temporary spikes in prices of energy and food, spikes resulting from supply chain problems and other effects of the pandemic might lead the CPI and PCE—even excluding food and energy prices—to give a misleading measure of the underlying rate of inflation in the economy.

To correct for this problem, some economists have been more attention to the measure of inflation calculated using the median CPI, which is compiled monthly by economists at the Federal Reserve Bank of Cleveland. The median CPI is calculated by ranking the price changes of every good or service in the index from the largest price change to the smallest price change, and then choosing the price change in the middle. The idea is to eliminate the effect on measured inflation of any short-lived events that cause the prices of some goods and services to be particularly high or particularly low. Economists at the Cleveland Fed have conducted research that shows that, in their words, “the median CPI provides a better signal of the underlying inflation trend than either the all-items CPI or the CPI excluding food and energy. The median CPI is even better at forecasting PCE inflation in the near and longer term than the core PCE price index.”

The following figure shows the three measures of inflation using the CPI for each month since January 2019. The red line shows the unadjusted CPI, the green line shows the CPI excluding food and energy prices, and the blue line shows median CPI. To focus on the inflation rate in a particular month, in this figure we calculate inflation as the percentage change in the index at an annual rate. That is, we calculate the annual inflation rate assuming that the inflation rate in that month continued for a year.

Note that for most of the period since early 2021, during which the inflation rate accelerated, median inflation was well below inflation measured by changes in the unadjusted CPI. That difference reflects some of the distortions in measuring inflation arising from the effects of the pandemic.

But the last two values—for July and August 2022—tell a different story. In those months, inflation measured by changes in the CPI excluding food and energy prices or by changes in median CPI were well above inflation measured by changes in the unadjusted CPI. In August 2022, the unadjusted CPI shows a low rate of inflation—1.4 percent—whereas the CPI excluding food and energy prices shows an inflation rate of 7.0 percent and the median CPI shows an inflation rate of 9.2 percent.

We should always be cautious when interpreting any economic data for a period as short as two months. But data for inflation measured by the change in median CPI may be sending a signal that the slowdown in inflation that many economists and policymakers had been predicting would occur in the summer of 2022 isn’t actually occurring. We’ll have to await the release of future data to draw a firmer conclusion.

Sources: Michael S. Derby, “Inflation Data Scrambles Fed Rate Outlook Again,” Wall Street Journal, September 14, 2022; Federal Reserve Bank of Cleveland, “Median CPI,” clevelandfed.org; and Federal Reserve Bank of St. Louis.

Podcasts Back for Fall 2022! – 9/9/22 Podcast – Authors Glenn Hubbard & Tony O’Brien discuss inflation, the Fed’s Response, cryptocurrency, and also briefly touch on labor markets.

Solved Problem: How Can Total Employment and the Unemployment Rate Both Increase?

Supports: Macroeconomics, Chapter 9, Section 9.1, Economics Chapter 19, Section 19.1, and Essentials of Economics, Chapter 13, Section 13.1.

As it does on the first Friday of each month, on September 2, 2022, the U.S. Bureau of Labor Statistics (BLS) released its “Employment Situation” report for August 2022. According to the household survey data in the report, total employment in the U.S. economy increased in August by 442,000 compared with July. The unemployment rate rose from 3.5 percent in July to 3.7 percent in August. According to the establishment survey, the total number of workers on payrolls increased in August by 315,000 compared with July.

How are the data in the household survey collected? How are the data in the establishment survey collected?
Why are the estimated increases in employment from July to August 2022 in the two surveys different?
Briefly explain how it is possible for the household survey to report in a given month that both total employment and the unemployment rate increased.

Solving the Problem

Step 1: Review the chapter material. This problem is about how the BLS reports data on employment and unemployment, so you may want to review Chapter 9, Section 9.1, “Measuring the Unemployment Rate, the Labor Force Participation Rate, and the Employment–Population Ratio.”

Step 2: Answer part a. by explaining how the data from the two surveys are collected. As discussed in Section 9.1, the data in the household survey is from interviews with a sample of 60,000 households, chosen to represent the U.S. population. The data in the establishment survey—sometimes called the payroll survey in media stories—is from a sample of 300,000 establishments (factories, stores, and offices).

Step 3: Answer part b. by explaining why the estimated increase in employment is different in the two surveys. First note that the BLS intends the surveys to estimate two different measures of employment. The household survey includes people working at jobs of all types, including people who are self-employed or who are unpaid family workers, whereas the establishment survey includes only people who appear on a non-agricultural firm’s payroll, so the self-employed, farm workers, and unpaid family workers aren’t counted. Second, the data are collected from surveys and so—like all estimates that rely on surveys—will have some measurement error. That is, the actual increase in employment—either total employment in the household survey or payroll employment in the establishment survey—is likely to be larger or smaller than the reported estimates. The estimates in the establishment survey are revised in later months as the BLS receives additional data on payroll employment. In contrast, the estimates in household survey are ordinarily not revised because they are based only on a survey conducted once per month.

Step 4: Answer part c. by explaining how in a given month the household survey may report an increase in both employment and the unemployment rate. The BLS’s estimate of the unemployment is calculated from responses to the household survey. (The establishment survey doesn’t report an estimate of the unemployment rate.) The unemployment rate equals the total number of people unemployed divided by the labor force, multiplied by 100. The labor force equals the sum of the employed and the unemployed. If the number of people employed increases—thereby increasing the denominator in the unemployment rate equation—while the number of people unemployed remains the same or falls, as a matter of arithmetic the unemployment rate will have to fall.

The BLS reported that the unemployment rate in August 2022 rose even though total employment increased. That outcome is possible only if the number of people who are unemployed also increased, resulting in a proportionally larger increase in the numerator in the unemployment equation relative to the denominator. In fact, the BLS estimated that the number of people unemployed increased by 344,000 from July to August 2022. Employment and unemployment both increasing during a month happens fairly often during an economic expansion as some people who had been out of the labor force—and, therefore, not counted by the BLS as being unemployed—begin to search for work during the month but don’t find jobs.

Source: U.S. Bureau of Labor Statistics, “The Employment Situation—August 2022,” bls.gov, September 2, 2022.

Why Might Good News for the Job Market Be Bad News for the Stock Market?

On Tuesday, August 30, 2022, the U.S. Bureau of Labor Statistics (BLS) released its Job Openings and Labor Turnover Survey (JOLTS) report for July 2022. The report indicated that the U.S. labor market remained very strong, even though, according to the Bureau of Economic Analysis (BEA), real gross domestic product (GDP) had declined during the first half of 2022. (In this blog post, we discuss the possibility that during this period the real GDP data may have been a misleading indicator of the actual state of the economy.)

As the following figure shows, the rate of job openings remained very high, even in comparison with the strong labor market of 2019 and early 2020 before the Covid-19 pandemic began disrupting the U.S. economy. The BLS defines a job opening as a full-time or part-time job that a firm is advertising and that will start within 30 days. The rate of job openings is the number of job openings divided by the number of job openings plus the number of employed workers, multiplied by 100.

In the following figure, we compare the total number of job openings to the total number of people unemployed. The figure shows that in July 2022 there were almost two jobs available for each person who was unemployed.

Typically, a strong job market with high rates of job openings indicates that firms are expanding and that they expect their profits to be increasing. As we discuss in Macroeconomics, Chapter 6, Section 6.2 (Microeconomics and Economics, Chapter 8, Section 8.2) the price of a stock is determined by investors’ expectations of the future profitability of the firm issuing the stock. So, we might have expected that on the day the BLS released the July JOLTS report containing good news about the labor market, the stock market indexes like the Dow Jones Industrial Average, the S&P 500, and the Nasdaq Composite Index would rise. In fact, though the indexes fell, with the Dow Jones Industrial Average declining a substantial 300 points. As a column in the Wall Street Journal put it: “A surprisingly tight U.S. labor market is rotten news for stock investors.” Why did good news about the labor market could cause stock prices to decline? The answer is found in investors’ expectations of the effect the news would have on monetary policy.

In August 2022, Fed Chair Jerome Powell and the other members of the Federal Reserve Open Market Committee (FOMC) were in the process of tightening monetary policy to reduce the very high inflation rates the U.S. economy was experiencing. In July 2022, inflation as measured by the percentage change in the consumer price index (CPI) was 8.5 percent. Inflation as measured by the percentage change in the personal consumption expenditures (PCE) price index—which is the measure of inflation that the Fed uses when evaluating whether it is hitting its target of 2 percent annual inflation—was 6.3 percent. (For a discussion of the Fed’s choice of inflation measure, see the Apply the Concept “Should the Fed Worry about the Prices of Food and Gasoline,” in Macroeconomics, chapter 15, Section 15.5 and in Economics, Chapter 25, Section 25.5.)

To slow inflation, the FOMC was increasing its target for the federal funds rate—the interest rate that banks charge each other on overnight loans—which in turn was leading to increases in other interest rates, such as the interest rate on residential mortgage loans. Higher interest rates would slow increases in aggregate demand, thereby slowing price increases. How high would the FOMC increase its target for the federal funds rate? Fed Chair Powell had made clear that the FOMC would monitor economic data for indications that economic activity was slowing. Members of the FOMC were concerned that unless the inflation rate was brought down quickly, the U.S. economy might enter a wage-price spiral in which high inflation rates would lead workers to push for higher wages, which, in turn, would increase firms’ labor costs, leading them to raise prices further, in response to which workers would push for even higher wages, and so on. (We discuss the concept of a wage-price spiral in this earlier blog post.)

In this context, investors interpretated data showing unexpected strength in the economy—particularly in the labor market—as making it likely that the FOMC would need to make larger increases in its target for the federal fund rate. The higher interest rates go, the more likely that the U.S. economy will enter an economic recession. During recessions, as production, income, and employment decline, firms typically experience lower profits or even suffer losses. So, a good JOLTS report could send stock prices falling because news that the labor market was stronger than expected increased the likelihood that the FOMC’s actions would push the economy into a recession, reducing profits. Or as the Wall Street Journal column quoted earlier put it:

“So Tuesday’s [JOLTS] report was good news for workers, but not such good news for stock investors. It made another 0.75-percentage-point rate increase [in the target for the federal funds rate] from the Fed when policy makers meet next month seem increasingly likely, while also strengthening the case that the Fed will keep raising rates well into next year. Stocks sold off sharply following the report’s release.”

Sources: U.S. Bureau of Labor Statistics, “Job Openings and Labor Turnover–July 2022,” bls.gov, August 30, 2022; Justin Lahart, “Why Stocks Got Jolted,” Wall Street Journal, August 30, 2022; Jerome H. Powell, “Monetary Policy and Price Stability,” speech at “Reassessing Constraints on the Economy and Policy,” an economic policy symposium sponsored by the Federal Reserve Bank of Kansas City, Jackson Hole, Wyoming, August 26, 2022; and Federal Reserve Bank of St. Louis.

Solved Problem: Evaluating the Disney World Pricing Strategy

Supports: Microeconomics, Chapter 6, Section 6.3 and Chapter 10, Section 10.3, Economics Chapter 6, Section 6.3 and Chapter 10, Section 10.3, and Essentials of Economics, Chapter 7, Section 7.4 and Section 7.7.

In August 2022, an article in the Wall Street Journal discussed the Disney Company increasing the prices it charges for admission to its Disneyland and Walt Disney World theme parks. As a result of the price increases, “For the quarter that ended July 2 [2022], the business unit that includes the theme parks … posted record revenue of $5.42 billion and record operating income of $1.65 billion.” The increase in revenue occurred even though “attendance at Disney’s U.S. parks fell by 17% compared with the previous year….”

The article also contains the following observations about Disney’s ticket price increases:

“Disney’s theme-park pricing is determined by ‘pure supply and demand,’ said a company spokeswoman.”
“[T]he changes driving the increases in revenue and profit have drawn the ire of what Disney calls ‘legacy fans,’ or longtime parks loyalists.”

Briefly explain what must be true of the demand for tickets to Disney’s theme parks if its revenue from ticket sales increased even though 17 percent fewer tickets were sold. [For the sake of simplicity, ignore any other sources of revenue Disney earns from its theme parks apart from ticket sales.]
In Chapter 10, Section 10.3 the textbook discusses social influences on decision making, in particular, the business implications of fairness. Briefly discuss whether the analysis in that section is relevant as Disney determines the prices for tickets to its theme parks.

Solving the Problem

Step 1: Review the chapter material. This problem is about the effects of price increases on firms’ revenues and on whether firms should pay attention the possibility that consumers might be concerned about fairness when making their consumption decisions, so you may want to review Chapter 6, Section 6.3, “The Relationship between Price Elasticity of Demand and Total Revenue” and Chapter 10, Section 10.3, “Social Influences on Decision Making,” particularly the topic “Business Implications of Fairness.”

Step 2: Answer part a. by explaining what must be true of the demand for tickets to Disney’s theme parks if revenue from ticket sales increased even though Disney sold fewer tickets. Assuming that the demand curve for tickets to Disney’s theme parks is unchanged, a decline in the quantity of tickets sold will result in a move up along the demand curve for tickets, raising the price of tickets. Only if the demand curve for theme park tickets is price inelastic will the revenue Disney receives from ticket sales increase when the price of tickets increases. Revenue increases in this situation because with an inelastic demand curve, the percentage increase in price is greater than the percentage decrease in quantity demanded.

Step 3: Answer part b. by explaining whether the textbook’s discussion of the business implications of fairness is relevant as Disney as determines ticket prices. Section 10.3 may be relevant to Disney’s decisions because the section discusses that firms sometimes take consumer perceptions of fairness into account when deciding what prices to charge. Note that ordinarily economists assume that the utility consumers receive from a good or service depends only on the attributes of the good or service and is not affected by the price of the good or service. Of course, in making decisions on which goods and services to buy with their available income, consumers take price into account. But consumers take price into account by comparing the marginal utilities of products realtive to their prices, with the marginal utilities assumed not to be affected by the prices.

In other words, a consumer considering buying a ticket to Disney World will compare the marginal utility of visiting Disney World relative to the price of the ticket to the marginal utility of other goods and services relative to their prices. The consumer’s marginal utility from spending a day in Disney World will not be affected by whether he or she considers the price of the ticket to be unfairly high.

The textbook gives examples, though, of cases where a business may fail to charge the price that would maximize short-run profit because the business believes consumers would see the price as unfair, which might cause them to be unwilling to buy the product in the future. For instance, restaurants frequently don’t increase their prices during a particularly busy night, even though doing so would increase the profit they earn on that night. They are afraid that if they do so, some customers will consider the restaurants to have acted unfairly and will stop eating in the restaurants. Similarly, the National Football League doesn’t charge a price that would cause the quantity of Super Bowl tickets demanded to be equal to the fixed supply of seats available at the game because it believes that football fans would consider it unfair to do so.

The Wall Street Journal article quotes a Disney spokeswomen as saying that the company sets the price of tickets according to demand and supply. That statement seems to indicate that Disney is charging the price that will maximize the short-run profit the company earns from selling theme park tickets. But the article also indicates that many of Disney’s long-time ticket buyers are apparently upset at the higher prices Disney has been charging. If these buyers consider Disney’s prices to be unfair, they may in the future stop buying tickets.

In other words, it’s possible that Disney might find itself in a situation in which it has increased its profit in the short run at the expense of its profit in the long run. The managers at Disney might consider sacrificing some profit in the long run to increase profit in the short run an acceptable trade-off, particularly because it’s difficult for the company to know whether in fact many of its customers will in the future stop buying admission tickets because they believe current ticket prices to be unfairly high.

Sources: Robbie Whelan and Jacob Passy, “Disney’s New Pricing Magic: More Profit From Fewer Park Visitors,” Wall Street Journal, August 27, 2022.

Is the U.S. Economy in a Recession? Real GDP versus Real GDI

The Bureau of Economic Analysis (BEA) publishes data on gross domestic product (GDP) each quarter. Economists and media reports typically focus on changes in real GDP as the best measure of the overall state of the U.S. economy. But, as we discuss in Macroeconomics, Chapter 8, Section 8.4 (Economics, Chapter 18, Section 18.4), the BEA also publishes quarterly data on gross domestic income (GDI). As we discuss in Chapter 8, Section 8.1 when discussing the circular-flow diagram, the value of every final good and services produced in the economy (GDP) should equal the value of all the income in the economy resulting from that production (GDI). The BEA has designed the two measures to be identical by including in GDI some non-income items, such as sales taxes and depreciation. But as we discuss in the Apply the Concept, “Should We Pay More Attention to Gross Domestic Income?” GDP and GDI are compiled by the BEA from different data sources and can sometimes significantly diverge.

A large divergence between the two measures occurred in the first half of 2022. During this period real GDP declined—as shown by the blue line in the following figure—after which some stories in the media indicated that the U.S. economy was in a recession. But real GDI—as shown by the red line in the figure—increased during the same two quarters. So, was the U.S. economy still in the expansion that began in the third quarter of 2020, rather than in a recession? Or, as an article in the Wall Street Journal put it: “A Different Take on the U.S. Economy: Maybe It Isn’t Really Shrinking.”

In fact, most economists do not follow the popular definition of a recession as being two consecutive quarters of declining real GDP. Instead, as we discuss in Chapter 10, Section 10.3, economists typically follow the definition of a recession used by the National Bureau of Economic Research: “A recession is a significant decline in activity spread across the economy, lasting more than a few months, visible in industrial production, employment, real income, and wholesale-retail trade.”

During the first half of 2022, most measures of economic activity were expanding, rather than contracting. For example, the first of the following figures shows payroll employment increasing in each month in the first half of 2022. The second figure shows industrial production also increasing during most months in the first half of 2022, apart from a very slight decline from April to May after which it continued to increase.

Taken together, these data indicate that the U.S. economy was likely not in a recession during the first half of 2022. The BEA revises the data on real GDP and real GDI over time as various government agencies gather more information on the different production and income measures included in the series. Jeremy Nalewaik of the Federal Reserve Board of Governors has analyzed the BEA’s adjustments to its initial estimates of real GDP and real GDI. He has found that when there are significant differences between the two series, the BEA revisions usually result in the GDP values being revised to be closer to the GDI values. Put another way, the initial GDI estimates may be more accurate than the initial GDP estimates.

If that generalization holds true in 2022, then the BEA may eventually revise its estimates of GDP upward, which would show that the U.S. economy was not in a recession in the first of half of 2022 because economic activity was increasing rather than decreasing.

Sources: Jon Hilsenrath, “A Different Take on the U.S. Economy: Maybe It Isn’t Really Shrinking,” Wall Street Journal, August 28, 2022; Reade Pickert, “Key US Growth Measures Diverge, Complicating Recession Debate,” bloomberg.com, August 25, 2022; Jeremy L. Nalewaik, “The Income- and Expenditure-Side Estimates of U.S. Output Growth,” Brookings Papers on Economic Activity, Spring 2010, pp. 71-127; and Federal Reserve Bank of St. Louis.

How Should We Measure Inflation?

In the textbook, we discuss several measures of inflation. In Macroeconomics, Chapter 8, Section 8.4 (Economics, Chapter 18, Section 18.4) we discuss the GDP deflator as a measure of the price level and the percentage change in the GDP deflator as a measure of inflation. In Chapter 9, Section 9.4, we discuss the consumer price index (CPI) as a measure of the price level and the percentage change in the CPI as the most widely used measure of inflation.

In Chapter 15, Section 15.5 we examine the reasons that the Federal Reserve often looks at the core inflation rate—the inflation rate excluding the prices of food and energy—as a better measure of the underlying rate of inflation. Finally, in that section we note that the Fed uses the percentage change in the personal consumption expenditures (PCE) price index to assess of whether it’s achieving its goal of a 2 percent inflation rate.

In this blog post, we’ll discuss two other aspects of measuring inflation that we don’t cover in the textbook. First, the Bureau of Labor Statistics (BLS) publishes two versions of the CPI: (1) The familiar CPI for all urban consumers (or CPI–U), which includes prices of goods and services purchased by households in urban areas, and (2) the less familiar CPI for urban wage earners and clerical workers (or CPI–W), which includes the same prices included in the CPI–U. The two versions of the CPI give slightly different measures of the inflation rate—despite including the same prices—because each version applies different weights to the prices when constructing the index.

As we explain in Chapter 9, Section 9.4, the weights in the CPI–U (the only version of the CPI we discuss in the chapter) are determined by a survey of 36,000 households nationwide on their spending habits. The more the households surveyed spend on a good or service, the larger the weight the price of the good or service receives in the CPI–U. To calculate the weights in the CPI–W the BLS uses only expenditures by households in which at least half of the household’s income comes from a clerical or wage occupation and in which at least one member of the household has worked 37 or more weeks during the previous year. The BLS estimates that the sample of households used in calculating the CPI–U includes about 93 percent of the population of the United States, while the households included in the CPI–W include only about 29 percent of the population.

Because the percentage of the population covered by the CPI–U is so much larger than the percentage of the population covered by the CPI–W, it’s not surprising that most media coverage of inflation focuses on the CPI–U. As the following figure shows, the measures of inflation from the two versions of the CPI aren’t greatly different, although inflation as measured by the CPI–W—the red line—tends to be higher during economic expansions and lower during economic recessions than inflation measured by the CPI–U—the blue line.

One important use of the CPI–W is in calculating cost-of-living adjustments (COLAs) applied to Social Security payments retired and disabled people receive. Each year, the federal government’s Social Security Administration (SSA) calculates the average for the CPI–W during June, July, and August in the current year and in the previous year and then measures the inflation rate as the percentage increase between the two averages. The SSA then increases Social Security payments by that inflation rate. Because the increase in CPI–W is often—although not always—larger than the increase in CPI–U, using CPI–W to calculate Social Security COLAs increases the payments recipients of Social Security receive.

A second aspect of measuring inflation that we don’t mention in the textbook was the subject of discussion following the release of the July 2022 CPI data. In June 2022, the value for the CPI–U was 295.3. In July 2022, the value for the CPI–U was also 295.3. So, was there no inflation during July—an inflation rate of 0 percent? You can certainly make that argument, but typically, as we note in the textbook (for instance, see our display of the inflation rate in Chapter 10, Figure 10.7) we measure the inflation rate in a particular month as the percentage change in the CPI from the same month in the previous year. Using that approach to measuring inflation, the inflation rate in July 2022 was the percentage change in the CPI from its value in July 2021, or 8.5 percent. Note that you could calculate an annual inflation rate using the increase in the CPI from one month to the next by compounding that rate over 12 months. In this case, because the CPI was unchanged from June to July 2022, the inflation rate calculated as a compound annual rate would be 0 percent.

During periods of moderate inflation rates—which includes most of the decades prior to 2021—the difference between inflation calculated in these two ways was typically much smaller. Focusing on just the change in the CPI for one month has the advantage that you are using only the most recent data. But if the CPI in that month turns out to be untypical of what is happening to inflation over a longer period, then focusing on that month can be misleading. Note also that inflation rate calculated as the compound annual change in the CPI each month results in very large fluctuations in the inflation rate, as shown in the following figure.

Sources: Anne Tergesen, “Social Security Benefits Are Heading for the Biggest Increase in 40 Years,” Wall Street Journal, August 10, 2022; Neil Irwin, “Inflation Drops to Zero in July Due to Falling Gas Prices,” axios.com, August 10, 2022; “Consumer Price Index Frequently Asked Questions,” bls.gov, March 23, 2022; Stephen B. Reed and Kenneth J. Stewart, “Why Does BLS Provide Both the CPI–W and CPI–U?” U.S. Bureau of Labor Statistics, Beyond the Numbers, Vol. 3, No. 5, February 2014; “Latest Cost of Living Adjustment,” ssa.gov; and Federal Reserve Bank of St. Louis.

Antitrust Policy and Monopsony Power

As we discuss in Microeconomics and Economics, Chapter 15, Section 15.6, the U.S. Department of Justice’s Antitrust Division and the Federal Trade Commission have merger guidelines that they typically follow when deciding whether to oppose a merger between two firms in the same industry—these mergers are called horizontal mergers. The guidelines are focused on the effect a potential merger would have on market price of the industry’s output. We know that if the price in a market increases, holding everything else constant, consumer surplus will decline and the deadweight loss in the market will increase. But, as we note in Chapter 15, if a merger increases the efficiency of the merged firms, the result can be a decrease in costs that will lower the price, increase consumer surplus, and reduce the deadweight loss.

The merger guidelines focus on the effect of two firms combining on the merged firms’ market power in the output market. For example, if two book publishers merge, what will be the effect on the price of books? But what if the newly merged firm gains increased market power in input markets and uses that power to force its suppliers to accept lower prices? For example, if two book publishers merge will they be able to use their market power to reduce the royalties they pay to writers? The federal antitrust authorities have traditionally considered market power in the output market—sometimes called monopoly power—but rarely considered market power in the input market—sometimes called monopsony power.

In Chapter 16, Section 16.6, we note that a pure monopsony is the sole buyer of an input, a rare situation that might occur in, for example, a small town in which a lumber mill is the sole employer. A monopoly in an output market in which a single firm is the sole seller of a good is also rare, but many firms have some monopoly power because they have the ability to charge a price higher than marginal cost. Similarly, although monopsonies in input markets are rare, some firms may have monopsony power because they have the ability to pay less than the competitive equilibrium price for an input. For example, as we noted in Chapter 14, Section 14.4, Walmart is large enough in the market for some products, such as detergent and toothpaste, that it is able to insist that suppliers give it discounts below what would otherwise be the competitive price.

Monopsony power was the key issue involved in November 2021 when the Justice Department filed an antitrust lawsuit to keep the book publisher Penguin Random House from buying Simon & Schuster, another one of the five largest publishers. The merged firm would account for 31 percent of books published in the U.S. market. The lawsuit alleged that buying Simon & Schuster would allow “Penguin Random House, which is already the largest book publisher in the world, to exert outsized influence over which books are published in the United States and how much authors are paid for their work.”

We’ve seen that when two large firms propose a merger, they often argue that the merger will allow efficiency gains large enough to result in lower prices despite the merged firm having increased monopoly power. In August 2022, during the antitrust trial over the Penguin–Simon & Schuster merger, Markus Dohle, the CEO of Penguin made a similar argument, but this time in respect to an input market—payments to book authors. He argued that because Penguin had a much better distribution network, sales of Simon & Schuster books would increase, which would lead to increased payments to authors. Authors would be made better off by the merger even though the newly merged firm would have greater monopsony power. Penguin’s attorneys also argued that the market for book publishing was larger than the Justice Department believed. They argued that the relevant book market included not just the five largest publishers but also included Amazon and many medium and small publishers “all capable of competing for [the right to publish] future titles from established and emerging authors.” The CEO of Hachette Book Group, another large book publisher, disagreed, arguing at the trial that the merger between Penguin and Simon & Schuster would result in lower payments to authors.

The antitrust lawsuit against Penguin and Simon & Schuster was an example of the more aggressive antitrust policy being pursued by the Biden administration. (We discussed the Biden administration’s approach to antitrust policy in this earlier blog post.) An article in the New York Times quoted a lawyer for a legal firm that specializes in antitrust cases as arguing that the lawsuit against Penguin and Simon & Schuster was unusual in that the lawsuit “declines to even allege the historically key antitrust harm—increased prices.” The outcome of the Justice Department’s lawsuit against Penguin and Simon & Schuster may provide insight into whether federal courts will look favorably on the Biden administration’s more aggressive approach to antitrust policy.

Sources: Jan Wolfe, “Penguin Random House CEO Defends Publishing Merger at Antitrust Trial,” Wall Street Journal, August 4, 2022; David McCabe, “Justice Dept. and Penguin Random House’s Sparring over Merger Has Begun,” New York Times, August 1, 2022; Eduardo Porter, “A New Legal Tactic to Protect Workers’ Pay,” New York Times, April 14, 2022; Janet H. Cho and Karishma Vanjani, “Justice Department Seeks to Block Penguin Random House Buy of Viacom’s Simon & Schuster,” barrons.com, November 2, 2021; United States Department of Justice, “Justice Department Sues to Block Penguin Random House’s Acquisition of Rival Publisher Simon & Schuster,” justice.gov, November 2, 2021;

The Economics of Sneaker Reselling

Buying athletic shoes and reselling them for a higher price has become a popular way for some people to make money. The mostly young entrepreneurs involved in this business are often called sneakerheads. Note that economists call buying a product at a low price and reselling it at a high price arbitrage. The profits received from engaging in arbitrage are called arbitrage profits. One estimate puts the total value of sneakers being resold at $2 billion per year.

Why would anybody buy sneakers from a sneakerhead that they could buy at a lower price online or from a retail store? Most people wouldn’t, which is why most sneakerheads resell only shoes that shoe manufacturers like Nike or Adidas produce in limited quantities—typically fewer than 50,000 pairs. To obtain the shoes, shoe resellers use two main strategies: (1) waiting in line at retail stores on the day that a new limited quantity shoe will be introduced, or (2) buying shoes online using a software application called a bot. A bot speeds up a buyer’s checkout process for an online sale. Typical customers buying at an online shoe site take a few minutes to choose a size, fill in their addresses, and provide their credit card information. But a few minutes is enough time for shoe resellers using bots to buy all of the newly-released shoes available on the site.

In addition to reselling shoes on their own sites, many sneakerheads use dedicated resale sites like StockX and GOAT. These sites have greatly increased the liquidity of sneakers, or the ease with which sneakers can be resold. In effect, limited-edition sneakers have become an asset like stocks, bonds, or gold because they can be bought and sold in the secondary market that exists on the online resale sites. (We discuss the concepts of primary and secondary markets for assets in Macroeconomics, Chapter 6, Section 6.2 and in Microeconomics and Economics, Chapter 8, Section 8.2.)

An article in the New York Times gives an example of the problems that bots can cause for retail shoe stores. Bodega, a shoe store in Boston, offered the limited-edition New Balance 997S sneaker on its online site. Ten minutes later, the shoe was sold out. One of the store’s owner was quoted as saying: “We got destroyed by bots. It was making it impossible for our average customers to even have a shot at the shoes.” Although the store had a policy of allowing customers to buy a maximum of three pairs of shoes, shoe resellers were able to get around the policy by having shoes shipped to their friends’ addresses or by having a group of people coordinate their purchases. An article on bloomberg.com described how one reseller along with 15 of his friends used bots to buy 600 pairs of Adidas’s Yeezy sneakers from an online site on the morning the sneakers were released. Adidas has a rule that each customer can buy only one pair of its limited-edition shoes, but the company has trouble enforcing the rule.

Shopify and other firms have developed software that retailers can use to make it difficult for resellers to use bots on the retailers’ sites. But the developers of bot software have often been able to modify the bots to get around the defenses used by the anti-bot software.

In contrast with owners of retail stores, Nike, Adidas, New Balance, and the other shoe manufacturers have a more mixed reaction to sneakerheads using bots scooping up most pairs of limited-edition shoes shortly after the shoes are released. Like the owners of retail stores, the shoe manufacturers know that they risk upsetting the typical customer if the customer can only buy hot new shoe releases from resellers at prices well above the original retail price. But an active resale market increases the demand for shoes, just as individual investors increased their demand for individual stocks when it became possible to easily buy and sell stocks online using sites like TD Ameritrade, E*Trade, and Fidelity. So manufacturers benefit from knowing that most of their limited-edition shoes will sell out. One industry analyst singled out “The durability of Nike’s … ability to fuel the sneaker resale ecosystem ….” as a particular strength of the company. In addition, manufacturers may believe that the publicity about limited edition shoes rapidly selling out may spill over to increased demand for other shoes the manufacturers sell. (In Microeconomics and Economics, Chapter 10, Section 10.3 we note that some consumers may receive utility from buying goods that are widely seen as popular and fashionable.)

In the long run, is it possible for sneakerheads to make a profit reselling shoes? It seems unlikely for the reasons we discuss in Microeconomics and Economics, Chapter 12, Section 12.5. The barriers to entry in reselling sneakers are very low. Anyone can list shoes for sale on StockX or one of the other resale sites. Waiting in line in front of a retail store on the day a new shoe is released is something that anyone who is willing to accept the opportunity cost of the time lost can do. Similarly, bots that can be used to scoop up newly released shoes from online sites are widely available for sale. So, we would expect that in the long run entry into sneaker reselling will compete away any economic profit that sneakerheads were earning.

In fact, by the summer of 2022, prices on reselling sites were falling. In just the month of June, the average price of sneakers listed on StockX declined by 20 percent. Resellers who had stockpiled shoes waiting for prices to increase were instead selling them because they feared that prices would go even lower. And new limited-edition shoes were taking longer to sell out. According to an article in the Wall Street Journal, “A pair of Air Jordans released on July 13 [2022] that might have once vanished in minutes took days to sell out from Nike Inc.’s virtual shelves.” One reseller quoted in the Wall Street Journal article indicated that entry was the reason that prices were falling: “You don’t want prices to go down, but they’re going down anyways, just because of how many people are selling in general.”

Although a seemingly unusual market, sneaker reselling is subject to the same rules of competition that we see in other markets.

Sources: Inti Pacheco, “Flipping Air Jordans Is No Longer a Slam Dunk,” Wall Street Journal, July 23, 2022; Shoshy Ciment, “Sneaker Reselling Side Hustle: Your Guide to Making Thousands Flipping Hyped Pairs of Dunks, Jordans, and Yeezys,” businessinsider.com, May 3, 2022; Teresa Rivas, “A Strong Sneaker-Resale Market Is Another Boon for Nike,” barrons.com, May 24, 2022; Curtis Bunn, “Sneakers Are So Hot, Resellers Are Making a Living Off of Coveted Models,” nbcnews.com, October 23, 2021; Daisuke Wakabayashi, “The Fight for Sneakers,” New York Times, October 15, 2021; and Joshua Hunt, “Sneakerheads Have Turned Jordans and Yeezys Into a Bona Fide Asset Class,” bloomberg.com, February 15, 2021.