Category: Labor markets

The Effect on a Firm’s Costs of Using a Generative AI Program

Supports: Microeconomics, Chapter 11, Section 11.5; Economics, Chapter 11, Section 11.5; and Essentials of Economics, Chapter 8, Section 8.5

Photo from the Wall Street Journal.

Imani owns a firm that sells payroll services to companies in the Atlanta area. Her largest cost is for labor. She employs workers who use software to prepare payroll reports and to handle texts and calls from client firms. She decides to begin using a generative AI program, like ChatGPT, which is capable of quickly composing thorough answers to many questions and write computer code. She will use the program to write the additional computer code needed to adapt the payroll software to individual client’s needs and to respond to clients seeking advice on payroll questions. Once the AI program is in place, she will need only half as many workers. The number of additional workers she needs to hire for every 20 additional firms that buy her service will fall from 5 to 1. She will have to pay a flat monthly licensing fee for the AI program; the fee will not change with the number of firms she sells her services to. Imani determines that making these changes will reduce her total cost of providing services to her current 2,000 clients from $2,000,000 per month to $1,600,000 per month

In answering the following questions, assume that, apart from the number of workers, none of the other inputs—such as the size of her firm’s office, the number of computers, or other software—change as a result of her leasing the AI program.

a. Briefly explain whether each of the following statements about the cost situation at Imani’s firm after she begins using the AI program is correct or incorrect.

  1. Her firm’s average total cost, average variable cost, and average fixed cost curves will shift down, while her firm’s marginal cost curve will shift up.
  2. Her firm’s average total cost, average variable cost, average fixed cost and marginal cost curves will all shift up.
  3. Her firm’s average total cost, average variable cost, and marginal cost curves will shift down, while her average fixed cost curve will shift up.
  4. Her firm’s average total cost, average variable cost, average fixed cost, and marginal cost curves will all shift down.
  5. Her firm’s average fixed cost curve will shift up, but her other cost curves will be unchanged.

b. Draw a graph illustrating your answer to part a. Be sure to show the original average total cost, average variable cost, average fixed cost, and marginal cost curves. Also show the shifts—if any—in the curves after Imani begins using the AI program.

Solving the Problem

Step 1:  Review the chapter material. This problem requires you to understand definitions of costs, so you may want to review the sections “The Difference between Fixed Costs and Variable Costs,” “Marginal Costs,” and “Graphing Cost Curves”

Step 2:  Answer part (a) by explaining whether each of the five listed statements is correct or incorrect. The cost of the AI program is fixed because it doesn’t change with the quantity of her services that Imani sells. Her firm will have greater fixed costs after licensing the AI program but she will have lower variable costs because she is able to produce the same level of output with fewer workers. Her marginal cost will also decline because she needs to hire fewer workers as the quantity of services she sells increases. We know that the average total cost per month of providing her service to 2,000 clients has decreased because we are given the information that it changed from ($2,000,000/2,000) = $1,000 to ($1,600,000/2,000) = $800.

  1. This statement is incorrect because her average fixed cost curve will shift up as a result of her total fixed cost having increased by the amount of the AI program license and because her marginal cost curve will shift down, not up.
  2. This statement is incorrect because all of her cost curves, except for average fixed cost, will shift down, not up.
  3. This statement is correct because it describes the actual shifts in her cost curves. 
  4. This statement is incorrect because her average fixed cost curve will shift up, not down.
  5. This statement is incorrect because her rather than being unaffected, her average total cost, average variable cost, and marginal cost curves will shift down.

Step 3:  Answer part (b) by drawing the cost curves for Imani’s firm before and after she begins using the AI program. Your graph should look like the following, where the curves representing the firm’s costs before Imani begins leasing the AI program are in blue and the costs after leasing the program are in red. 

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

Photo from the New York Times.

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.

  1. How are the data in the household survey collected? How are the data in the establishment survey collected?
  2. Why are the estimated increases in employment from July to August 2022 in the two surveys different? 
  3. 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?

Photo from the New York Times.

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.

The Surprisingly Strong Employment Report for January 2022

Leisure and hospitality was one of the industries showing surprisingly strong job growth during January 2022. Photo from the New York Times.

The Bureau of Labor Statistics’ monthly report on the “Employment Situation” is generally considered the best source of information on the current state of the labor market. As we discuss in Macroeconomics, Chapter 9, Section 9.1 (and in Economics, Chapter 19, Section 19.1), economists, policymakers, and investors generally focus more on the establishment survey data on total payroll employment than on the household survey data on the unemployment rate. The initial data on employment from the establishment survey are subject to substantial revisions over time (we discuss this point further below). But the establishment survey has the advantage of being determined by data taken from actual payrolls rather than by unverified answers to survey questions, as is the case with the household survey data. 

The establishment survey data for January 2022 (released on February 4, 2022) showed a surprisingly large increase in employment of 467,000. The consensus forecast had been for a significantly smaller increase of 150,000, with many economists expecting that the data would show a decrease in employment. The establishment survey is collected for pay periods that include the 12th of the month. In January 2022, in many places in the United States that pay period coincided with the height of the wave of infections from the Omicron variant of Covid-19. And, in fact, according to the household survey, the number of people out of work because of illness was 3.6 million in January—the most during the Covid-19 pandemic. So it seemed likely that payroll employment would have declined in January. But despite the difficulties caused by the pandemic, payroll employment increased substantially, likely reflecting firms’ continuing high demand for workers—a demand reflected in the very high level of job openings.

The employment report includes the BLS’s annual data revisions, which are based on a comprehensive payroll count for a particular month in the previous year—in this case, March 2021. The revisions also incorporate changes to the BLS’s seasonal adjustment factors. Each month, the BLS adjusts the raw payroll employment data to reflect seasonal fluctuations such as occur during and after the end-of-year holiday period. For instance, the change from December 2020 to January 2021 in the raw employment data was −2,824,000, whereas the adjusted change was 467,000 (as noted earlier). Obviously this difference is very large and is attributable to the BLS’s seasonal adjustments removing the employment surge in December attributable to seasonal hiring by retail stores, delivery firms, and other businesses strongly affected by the holidays.

The changes to the seasonal adjustment factors made the revisions to the 2021 payroll employment numbers unusually large. For instance, the BLS initially reported that employment increased from June 2021 to July 2021 by 1,091,000, whereas the revision reduced the increase to 689,000. Table A below is reproduced from the BLS report; the figure below the table shows the changes in employment from the previous month as originally published and as revised in the January report. Overall, the BLS revisions now show that employment increased by 217,000 more from 2020 to 2021 than initially estimated. The BLS expressed the opinion that: “Going forward, the updated models should produce more reliable estimates of seasonal movements. [Because there are now] more monthly observations related to the historically large job losses and gains seen in the pandemic-driven recession and recovery, the models can better distinguish normal seasonal movements from underlying trends.”

Source: The BLS “Employment Situation” report can be found here.

Glenn’s New Book Was Published Today

Link to Yale University Press’s website.

Link to Amazon page.

Link to availability at local independent bookstores in your area.

How Do We Know When the Economy Is at Maximum Employment?

Photo from the Wall Street Journal

According to the Federal Reserve Act, the Fed must conduct monetary policy “so as to promote effectively the goals of maximum employment, stable prices, and moderate long-term interest rates.” Neither “maximum employment” nor “stable prices” are defined in the act.

The Fed has interpreted “stable prices” to mean a low rate of inflation. Since 2012, the Fed has had an explicit inflation target of 2 percent. When the Fed announced its new monetary policy strategy in August 2020, it modified its inflation target by stating that it would attempt to achieve an average inflation rate of 2 percent over time. As Fed Chair Jerome Powell stated: “Our approach can be described as a flexible form of average inflation targeting.” (Note that although the consumer price index (CPI) is the focus of many media stories on inflation, the Fed’s preferred measure of inflation is changes in the core personal consumption expenditures (PCE) price index. The PCE is a broader measure of the price level than is the CPI because it includes the prices of all the goods and services included in consumption category of GDP. “Core” means that the index excludes food and energy prices. For a further discussion see, Economics, Chapter 25, Section 15.5 and Macroeconomics, Chapter 15, Section 15.5.) 

There is more ambiguity about how to determine whether the economy is at maximum employment. For many years, a majority of members of the Federal Open Market Committee (FOMC) focused on the natural rate of unemployment (also called the non-accelerating rate of unemployment (NAIRU)) as the best gauge of when the U.S. economy had attained maximum employment. The lesson many economists and policymakers had taken from the experience of the Great Inflation that lasted from the late 1960s to the early 1980s was if the unemployment rate was persistently below the natural rate of unemployment, inflation would begin to accelerate. Because monetary policy affects the economy with a lag, many policymakers believed it was important for the Fed to react before inflation begins to significantly increase and a higher inflation rate becomes embedded in the economy.

At least until the end of 2018, speeches and other statements by some members of the FOMC indicated that they continued to believe that the Fed should pay close attention to the relationship between the natural rate of unemployment and the actual rate of unemployment. But by that time some members of the FOMC had concluded that their decision to begin raising the target for the federal funds rate in December 2015 and continuing raising it through December 2018 may have been a mistake because their forecasts of the natural rate of unemployment may have been too high. For instance, Atlanta Fed President Raphael Bostic noted in a speech that: “If estimates of the NAIRU are actually too conservative, as many would argue they have been … unemployment could have averaged one to two percentage points lower” than it actually did.

Accordingly, when the Fed announced its new monetary policy strategy in August 2020, it indicated that it would consider a wider range of data—such as the employment-population ratio—when determining whether the labor market had reached maximum employment. At the time, Fed Chair Powell noted that: “the maximum level of employment is not directly measurable and [it] changes over time for reasons unrelated to monetary policy. The significant shifts in estimates of the natural rate of unemployment over the past decade reinforce this point.”

As the economy recovered from the effects of the Covid-19 pandemic, the Fed faced particular difficulty in assessing the state of the labor market. Some labor market indicators appeared to show that the economy was close to maximum employment while other indicators showed that the labor market recovery was not complete. For instance, in December 2021, the unemployment rate was 3.9 percent, slightly below the average of the FOMC members estimates of the natural rate of unemployment, which was 4.0 percent. Similarly, as the first figure below shows, job vacancy rates were very high at the end of 2021. (The BLS calculates job vacancy rates, also called job opening rates, by dividing the number of unfilled job openings by the sum of total employment plus job openings.) As the second figure below shows, job quit rates were also unusually high, indicating that workers saw the job market as being tight enough that if they quit their current job they could find easily another job. (The BLS calculates job quit rates by dividing the number of people quitting jobs by total employment.) By those measures, the labor market seemed close to maximum employment.

But as the first figure below shows, total employment in December 2021 was still 3.5 million below its level of early 2020, just before the U.S. economy began to experience the effects of the pandemic. Some of the decline in employment can be accounted for by older workers retiring, but as the second figure below indicates, employment of prime-age workers (those between the ages of 25 and 54), had not recovered to pre-pandemic levels. 

How to reconcile these conflicting labor market indicators? In January 2022, Fed Chair Powell testified before the Senate Banking Committee as the Senate considered his nomination for a second four-year term as chair. In discussing the state of the economy he offered the opinion that: “We’re very rapidly approaching or at maximum employment.” He noted that inflation as measured by changes in the CPI had been running above 5 percent since June 2021: “If these high levels of inflation get entrenched in our economy, and in people’s thinking, then inevitably that will lead to much tighter monetary policy from us, and it could lead to a recession.” In that sense, “high inflation is a severe threat to the achievement of maximum employment.”

At the time of Powell’s testimony, the FOMC had already announced that it was moving to a less expansionary monetary policy by reducing its purchases of Treasury bonds and mortgage-backed securities and by increasing its target for the federal funds rate in the near future. He argued that these actions would help the Fed achieve its dual mandate by reducing the inflation rate, thereby heading off the need for larger increases in the federal funds rate that might trigger a recession. Avoiding a recession would help achieve the goal of maximum employment.

Powell’s remarks did not make explicit which labor market indicators the Fed would focus on in determining whether the goal of maximum employment had been obtained. It did make clear that the Fed’s new policy of average inflation targeting did not mean that the Fed would accept inflation rates as high as those of the second half of 2021 without raising its target for the federal funds rate. In that sense, the Fed’s monetary policy of 2022 seemed consistent with its decades-long commitment to heading off increases in inflation before they lead to a significant increase in the inflation rate expected by households, businesses, and investors. 

Note: For a discussion of the background to Fed policy, see Economics, Chapter 25, Section 25.5 and Chapter 27, Section 17.4, and Macroeconomics, Chapter 15, Section 15.5 and Chapter 17, Section 17.4.

Sources: Jeanna Smialek, “Jerome Powell Says the Fed is Prepared to Raise Rates to Tame Inflation,” New York Times, January 11, 2022; Nick Timiraos, “Fed’s Powell Says Economy No Longer Needs Aggressive Stimulus,” Wall Street Journal, January 11, 2022; and Federal Open Market Committee, “Meeting Calendars, Statements, and Minutes,” federalreserve.gov, January 5, 2022.

The Effect of the Covid-19 Pandemic on Income Inequality

During 2020, Congress and President Donald Trump responded to the Covid-19 pandemic with very aggressive fiscal policy initiatives. First, in March 2020, Congress enacted the Coronavirus Aid, Relief, and Economic Security (CARES) Act. The CARES Act increased the federal government’s expenditures by $1.9 trillion. Then, in December 2020, in response to the continuing effects of the pandemic, Congress and President Trump included an additional $915 billion in expenditures related to Covid-19 in the Consolidated Appropriations Act.  These two fiscal policy actions included payments directly to households and supplemental unemployment insurance payments. Higher income households were not eligible for the direct payments (often referred to as “stimulus payments”). Higher income households were also less likely to be unemployed and so were less likely to receive the supplemental unemployment insurance payments.

In Chapter 17, Section 17.4, we discuss the unequal distribution of income in the United States. Because the federal payments were targeted toward lower and middle income households, did the payments result in a decline in income inequality? Table 17.6 in Chapter 17, shows a common measure of the distribution of income: Households in the United States are divided into five income quintiles, from the 20 percent with the lowest incomes to the 20 percent with the highest incomes, along with the fraction of total income received by each of the five groups. The following table displays the distribution of income using this measure for 2019 and 2020. (We also include the data for the share of income received by the 5 percent of households with the highest incomes.) Note that the definition of income used in the table includes tax payments households make in that year in addition to payments—including the stimulus payments—received from the government. The income is also “equivalence adjusted,” which means that income is adjusted to account for how many adults and children are in a household.

YearLowest 20%Second 20%Middle 20%Fourth 20% Highest 20%Highest 5%
20194.7%10.4%15.7%22.6%46.6%19.9%
20205.1%10.9%16.0%22.8%45.2%18.9%
Percentage change in income share8.7%4.8%2.1%0.8%−3.0%−5.1%

The table shows that the distribution of income in the United States became somewhat more equal during 2020, with the share of income going to each of the first four quintiles increasing, while the income of the highest quintile declined.  The income share of the lowest quintile increased the most—by 8.7 percent—while the income share of the top 5 percent of households decreased by 5.1%. In that section of Chapter 17, we discuss the Gini coefficient, which is a measure of how unequal the distribution of income is. The Gini coefficient ranges between 0 and 1 with higher values indicating a more unequal distribution. Between 2019 and 2020, the Gini coefficient decline from 0.416 to 0.399, or by 4.1 percent, which measure the extent to which the income distribution became more equal. 

Will the reduction in income inequality the United States experienced during 2020 persist? It seems likely to, at least through 2021, given that in March 2021, Congress and President Joe Biden enacted the American Rescue Plan, which included payments to households of up to $1,400 per eligible household member. As with the payments to households made during 2020, high-income households were not eligible. Congress also extended supplemental unemployment insurance payments through early September 2021 in states that were willing to accept the payments. 

What about after federal stimulus payments to households end? (As of late 2021, it appeared unlikely that Congress and President Biden planned on enacting any further payments.) One indication that some of the reduction in inequality might be sustained comes from the sharp increases in the wages of many low-skilled workers. For instance, in October 2021, the wages (as measured by their average hourly earnings) of workers in the leisure and hospitality industry, which includes workers in restaurants and hotels, increased by nearly 12 percent over the previous year. For all workers in the private sector, wages increased by about 5 percent over the same period. Many of the workers in this industry have low incomes. So, the fact that their wages were increasing more than twice as fast as wages in the overall economy indicates that at least some low-income workers were closing the earnings gap with other workers.

Sources: Emily A. Shrider, Melissa Kollar, Frances Chen, and Jessica Semega, U.S. Census Bureau, Current Population Reports, P60-270, Income and Poverty in the United States: 2020, Washington, DC, U.S. Government Printing Office, September 2021, Table C-3; and U.S. Bureau of Labor Statistics.

How Do firms Evaluate New Hires? The Curious Case of NFL Quarterbacks

As we discuss in Chapter 16, the demand for labor depends on the marginal product of labor. In our basic model of a competitive labor market we assume that all workers have the same ability, skills, and training. Firms can hire as many workers as they would like at the market equilibrium wage. Because, by assumption, all workers have the same abilities, firms don’t have to worry about whether one person might be less able or willing to perform the assigned work than another person.

In reality, we know that most firms face more complicated hiring decisions. Even for a job, such as being a cashier in supermarket, that most people can be quickly trained to do, workers differ in how well they carry out their tasks and whether they can be relied on to regularly show up for work and to treat customers politely.

When hiring workers, firms face a problem of asymmetric information: Workers know more about whether they intend to work hard than firms know. Even for applicants who have a work history, a firm may have difficulty discovering how well or how poorly the applicant performed his or her duties in earlier jobs. In responding to inquiries from other firms about a job applicant, firms are rarely willing to do more than confirm that a person has worked at the firm because they are afraid that reporting anything negative about the person—even if true—might expose the firm to a law suit. In Section 16.5, we discuss the field of personnel economics, which includes the study of how firms design compensation policies that attempt to ensure that workers have an incentive to work hard.

When hiring someone entering the labor market, such as a new college graduate, firms have a particular problem in gauging the likely performance of a worker who may have no job history. In this case, there may not be a problem of asymmetric information because the worker may also be uncertain as to how well he or she will be able to perform the job, particularly if the worker has not previously held a full-time job in that field. When hiring new college graduates, firms may rely on an applicant’s college grades, the reputation of the applicant’s college, and the applicant’s scores on standardized test. Some firms have also developed their own tests to measure an applicant’s cognitive skills, knowledge relevant to the position applied for, and even psychological temperament. Some technology firms and investment banks ask applicants to complete demanding problems that may be unrelated to either technology or banking but can provide insight into whether the applicant has the cognitive ability and temperament to quickly complete complicated tasks.

Teams in the National Football League (NFL) face an interesting problem when hiring new players, particularly those playing the position of quarterback. College football players hoping to play professional football enter the NFL draft in which each of the 32 teams select players in eight rounds, with the selections being in reverse order of the teams’ records during the previous football season. There is often a substantial gap between an athlete’s ability to be successful playing college football and his ability to be successful in the NFL. As a result, many players who are stars in college are unable to succeed as professionals.

The position of quarterback is usually thought to be the most difficult to succeed at. Many highly-regarded college quarterbacks fail to do well in the NFL. Teams typically settle on one player as their starting quarterback who will play most of the time. But teams also have one or two backups. Sometimes the backups are older, former starters on other teams, but often they are players chosen in the draft of college players. It’s very difficult to judge how well a quarterback is likely to perform except by seeing him play in a game. Players who perform well in practice often don’t play well in games. As a result, a backup quarterback may be drafted and, if the starting quarterback on his team remains healthy and is effective, earn a nice salary from year to year without actually playing in many games. If a team’s starting quarterback is injured or is ineffective, the backup quarterback may play in several games during a season.

If the backup shows himself to be an effective player, the team may decide to retain him as the starter—with a substantial increase in salary. But given the difficulty of playing the position of quarterback, a more likely outcome is that the backup plays poorly and the team decides to draft another backup quarterback the following year.

The result is an odd situation: The more that a backup quarterback plays in games, often the less likely he is to keep his job. And the less that a backup quarterback plays, the more likely he is to keep his job. Or as one NFL head coach put it: “Backups who don’t play a lot tend to have long NFL careers, while those who are exposed [by actually] playing … have shorter careers.”

This outcome is an extreme example of the difficulty firms sometimes have in measuring how well new hires are likely to perform in their jobs.

Source for quote: Sportswriter David Lombardi on Twitter, quoting San Francisco 49ers’ head coach Kyle Shanahan, December 14, 2020.

Does Automation Lead to Permanent Job Losses?

This post on the Federal Reserve Bank of St. Louis’s Page One blog discusses how the belief that automation can lead to permanent job losses is an example of the “lump of labor” fallacy. Click HERE to read the article.

The post refers to the circular-flow diagram, which we discuss in Chapter 2 and in Chapter 18 in the textbook. We discuss the effects of automation and robots on the labor market in Chapter 16.