Category: Labor markets

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.