Tag: Income inequality over time

How Well Have Low-Wage Workers Done over the Years?

Image of servers in a restaurant generated by ChatGTP-4o.

How should you track over time the real wagees of low-wage workers? If you are interested in income mobility, you would want to track the experience over the course of their working lives of individuals who began their careers in low-wage occupations. Doing so would allow you to measure how well (or poorly) the U.S. economy succeeds in providing individuals with opportunities to improve their incomes over time.

You might also be interested in how the real wages of people who earn low wages has changed over time. In this case, rather than tracing the wages over time of individuals who earn low wages when they first enter the labor market, you would look at the real wages of people who earn low wages at any given time. The simplest way to do that analysis would be using data on the average nominal wage earned by, say, the lowest 20 percent of wage earners, and deflate the average nominal wage by a price index to determine the average real wage of these workers. How the average real wage of low-wage workers varies over time provides some insight into the changing standard of living of low-wage workers.

In a recent Substack post, Ernie Tedeschi, Director of Economics at the Budget Lab research center at Yale University, has carried out a careful analysis of movements over time in the average real wage of low-wage workers. Tedeschi points out a complicating factor in this analysis: “The population has gotten older over time and more educated. The workforce looks different too, with more workers in services and fewer in manufacturing. Shifting populations means that comparisons of workers aren’t apples-to-apples over time.”

To correct for these confounding factors, Tedeschi constructs a low-wage index that makes it possible to examine the real wage of low-wage workers, holding constant the composition of low-wage workers with respect to “sex, age, race, college education, and broad industry and occupation” at the values of these characteristics in 2023. Using this approach, makes it possible to separate changes in wages of workers with given characteristics from changes in wages that occur because the average characteristics of workers has changed. For example, on average, workers who are older or who have more years of education will be more productive and, therefore, on average will earn higher wages than will workers who are younger or have fewer years of education.

The following figure from Tedeschi’sSubstack post shows movements in his low-wage index during each quarter from the first quarter of 1979 to the first quarter of 2024, with “low wage” defined as workers at the 25th precentile of the distribution of wages. (That is, 24 percent of workers receive lower wages and 75 percent of workers receive higher wages than do these workers.) The index shows that a low-wage worker in 2024 has a much higher real wage than a low-wage worker in 1979, but the increase in the average real wage occurs mainly during two periods: 1997–2007 and 2014–2024. (Tedeschi uses the person consumption expenditures (PCE) price index to convert nominal wages to real wages.)

A more complete discussion of Tedeschi’s methods and results can be found in his blog post.

Measuring Changes in Income Inequality

As we discuss in Chapter 17, there are several complications in accurately measuring changes in the distribution of income over time. First, people will not typically remain in the same place in the income distribution their whole lives. Instead, their incomes are likely to fluctuate, moving them up and down the income distribution. So comparing the distribution of income for the whole population at two points in time can give a misleading idea of how the incomes of particular individuals changed. Measuring income mobility can be difficult, however, because it entails tracking the incomes of individuals over time. Doing that requires specialized studies rather than relying on the more readily available government data we can use to track changes in the incomes of the whole population. 

Second, we are more interested in the income people have available to spend rather than the income they earn. Because people pay taxes on the incomes they receive and because many people receive transfer payments from the government, including unemployment insurance payments and Social Security payments, the income distribution is more equal if we measure it after taking into account the taxes people pay and the transfer payments they receive.

Finally, people earn income from a variety of sources in addition to wages and salaries, including dividends they receive from owning stock, capital gains they earn from selling a financial or other asset, and income they earn from owning a business such as a restaurant or dry cleaners. The income people at the top of the income distribution earn from owning a business can be particularly hard to measure because it depends on how the income is reported to the Internal Revenue Service, which depends in turn on changes in laws affecting how businesses are organized and how they pay taxes. Dealing with these measurement issues is particular important in determining how much the share of income earned by the top 1% of the income distribution has changed over time—an issue that has been the subject of much political debate.

Wojciech Kopczuk of Columbia University and Eric Zwick of the University of Chicago address these measurement issues in a new article in the Journal of Economic Perspectives. Even skimming the article makes clear just how difficult the measurement issues are. Click HERE to read the article.

Note that the article is part of a symposium on income and wealth inequality that appears in that issue of the journal. The other articles in the symposium are also worth reading. Articles that appear in the Journal of Economic Perspectives are frequently (but not always!) nontechnical summaries of research that can be read without knowledge of economics beyond the principles course.