Version 0.4 of my notebooks for cleaning up and working with Current Population Survey public use microdata is available on GitHub. Several new variables were added, including the COVID-19 supplement questions, and several bugs were fixed. If you want to work with many months of CPS data in python, the code from these notebooks will likely be helpful. If you run the files locally and have trouble, please send me an email and I’ll try to help.
I’m still looking for a way to host the actual data files from this project. Each annual file is about 75mb after compression. Any suggestions are welcome.
As always, please contact me (email@example.com) if you find any errors or have any questions.
Unlike comparable countries, the US federal government does not require businesses to provide paid maternity or paternity leave to new parents. Luckily for some US parents, a handful of states have recently implemented state-level family leave laws that seek to bring their local jurisdiction into the developed world. This blog post looks at how families of infants rearrange their lives to provide care and shows that the handful of state laws have an effect large enough to be seen in nation-wide data.
Newborns require a lot of care and this care work is critical for the newborn and for society. Yet without federal protections for new parents, only 21 percent of workers have access to paid family leave as of March 2020. Further, there are substantial racial disparities in who has access; Black and Latino parents are less likely to have the already rare jobs that come with paid family benefits. Most new parents therefore face a dilemma: caring for their child during the critical first few months means giving up income.
As families with a new child temporarily rearrange their lives to care for the child, they go about it in a number of ways. Some parents (or other relatives) take weeks or months off from their job (paid or unpaid) with the expectation of returning, some work reduced hours, some leave their job completely with no expectation of returning, while others keep working. Next, I use survey data to approximate these groups and test the effect of having an infant on the number of hours people spend at their jobs during the reference week of the survey. Specifically, I look at two groups of adults ages 18 to 54: the first group lives with a related infant (under age 1), while the youngest related child in the second group is five years old.
Survey data confirm that care required by infants constrains how many hours their adult family members spend at work (chart 1). In 2000, 35 percent of the adult family members of infants did not work at all during the survey week, compared to 23.5 percent of adults in families where the youngest child is five years old. Comparable data for 2020 show the same overall pattern, with 36.2 percent of infants’ family not at work, compared to 28.4 for families where the youngest kid is five. The next section looks at whether those not at work expect to go back to a job.
Some infants’ family members who were not working in the survey reference week are employed but absent from their job, whether paid or not. In 2000, 3.4 percent of infants’ adult family report being on maternity or paternity leave, and an additional two percent report being absent for other reasons such as taking personal leave (chart 2). Among families where the youngest child is five years old, maternity or paternity leave (for example for adoption) is much more rare, while rates of other absences are about the same.
Importantly, however, the vast majority of those who report working zero hours during the reference week do not actually have a job. In 2000, 22.8 percent of adult family members of infants did not have a job and reported their main activity as family or home responsibilities, compared to 13.5 percent among families where the youngest child is age five. An additional 3.8 percent of family members of infants reported not being employed for another reason, such as school, a disability, or having trouble finding work, compared to 5.3 percent of families where the youngest child is five.
In the latest data, covering September to November 2020, infants’ family members are less likely to be non-employed caregivers (19.6 percent of the group, compared to 22.8 percent in 2000) and more likely to be on maternity or paternity leave (5.5 percent of the group, compared to 3.4 percent in 2000)1. This seems to be an encouraging development coming from the state paid family leave laws.
Digging into the causes for the increase in maternity/paternity leave, a few US states have enacted paid family leave laws, starting with California in 2002. In some form or another, by the middle of 2020, five states and the District of Columbia have these laws in place (the others are New Jersey, Rhode Island, New York, and Washington state). Three more states (Massachusetts, Connecticut, and Oregon) have passed laws but have not yet begun paying benefits.
We can see the early result of state paid family leave laws after separating the adult family of infants by whether or not they live in a state that has implemented paid family leave as of September 2020 (chart 3). In 2000, incidence of paid family leave was nearly equal between the two groups of states; neither group had paid family leave laws at the time. In 2020, among states that implemented laws, incidence of paid family leave is nearly five times higher than it was in 2000. Unpaid leave has fallen among states with paid leave laws, but still exists as there are gaps and limits in the various state systems.
In general, use of maternity and paternity leave has grown since 2000, but much of this change has come from various state efforts to make life easier for new parents. Critically, surveys of both employees and employers show the laws are a success. In California, the first state to implement paid family leave, surveys of employers show higher productivity, higher employee morale, and, in some cases, even cost savings for businesses. A federal law guaranteeing paid family leave is long overdue and would resolve the income dilemma faced by new parents with massive care responsibilities.
1 It’s worth noting that the 5.5 percent figure is not measuring the share of new parents taking maternity or paternity leave, but instead measures adult family members of infants under age 1 who report maternity or paternity leave as the reason they were absent from work in the reference week. In other words, if the source data captured only new parents with infants less than 12 weeks old, the share on family leave would be much higher, perhaps 3 or 4 times the 5.5 percent rate listed for all adult family members of infants.
The resources available to people ages 65 and older depend on several factors. For those working full-time, earnings from work can often cover expenses. For those with little or no earnings, income depends on private assets, pensions, Social Security, and welfare and public assistance, and is not always enough to avoid poverty. Despite gaps in the program, Social Security is by far the most important poverty reduction tool in the US. Social Security reduces the age 65 and older poverty rate by more than 30 percentage points.
The US Social Security Administration (SSA) Income of the Aged Chartbook, 2014 contains several charts and tables that aid in thinking about resources available to people ages 65 and older. In this blog post, I discuss two of my favorite charts from the SSA publication, update the charts for 2019, and create new versions that emphasize the importance of Social Security for disadvantaged groups.
Shares of aggregate income
The SSA chartbook includes a chart (page 17) showing how different income sources contribute to total income for both low- and high-income “aged units”. SSA “aged units” are married couples where at least one partner is age 65 or older and unmarried people ages 65 and older. Aged units are ranked by total income and divided into five equal groups, called quintiles. In 2014, the lowest quintile aged units have total income below $13,500, while the highest quintile aged units have total income above $72,129.
The SSA chart on shares of aggregate income, copied below, shows the importance of Social Security to low-income people ages 65 and older. In 2014, Social Security benefits are 80.7 percent of total income for those in the lowest income quintile, meaning Social Security benefits are more than four of every five dollars received by the group. Cash public assistance and welfare, including Supplemental Security Income, comprise an additional 9.5 percent of total income for the lowest quintile. Those in the highest income quintile also receive Social Security benefits, and the dollar amounts of their individual benefits are often higher than the dollar amounts received by the low-income group. However, the high-income group has high income because of access to other sources of income, such as earnings and pensions.
Using the latest data from the same source, I’ve recreated and updated the above SSA chart for 2019. The story is mostly the same in 2019 as it was in 2014, with a couple differences1. The 2019 quintile limits are higher, meaning overall income has increased; the lowest quintile now captures the fifth of aged units with total income below $15,000 a year, while the highest quintile covers the one-fifth with total income above $89,627. Also, cash public assistance represents a smaller share of income for the lowest quintile in 2019, and asset income provides a larger share of income for the highest quintile. In 2019, Social Security comprises 81.6 percent of total income for the lowest income quintile, compared to 80.7 percent in 2014.
Shares of aggregate income in disadvantaged groups
Total income received by people ages 65 and over, and the sources of this income, both depend heavily on race and ethnicity. Two additional charts showing the shares of aggregate income for Black and Hispanic aged units2 illustrate this point.
Compared to the overall US, the income of Black aged units is much lower at all points of the income distribution; one in five has total income below $10,434 in 2019, and four in five have total income below $54,670. Additionally, Black aged units in the lowest income quintile depend more on cash public assistance, a patchwork of income- and asset-tested welfare programs, including Supplemental Security Income, that fill some of the gaps in Social Security. Among the lowest income quintile of Black aged units, Social Security provides 70 percent of total income.
Additionally, relative to the overall US highest quintile group, the highest quintile of Black aged units have less total income and much less asset income, and depend more heavily on Social Security, earnings, and pensions. Less asset income among Black families is a result of the massive US racial wealth gap. The Federal Reserve reports that the typical White family above age 55 has $260,000 more wealth than the typical Black family in the same age group.
Aged units of Hispanic or Latino origin also have lower income when compared to aged units of any ethnicity. In 2019, one in five Hispanic aged units has total income below $10,128, while four in five have total income below $54,507. Hispanic aged units are relatively less likely to receive Social Security benefits (see chartbook page 11) and depend particularly heavily on income from working. Still, Social Security is nearly 70 percent of income for the lowest quintile of Hispanic or Latino aged units.
Among people ages 65 and older with low income, Social Security provides the vast majority of resources. Yet for many, including the bottom fifth of Black and Hispanic aged units, income is below the US poverty threshold and comes from a patchwork of complicated sources. One way to resolve this is to set the minimum Social Security Old Age benefit to the poverty threshold. Doing so would simplify many older peoples’ lives, increase their income, and eliminate the need for Supplemental Security Income and other public assistance programs.
Poverty among those ages 65 and older
A 2014 SSA chart shows the poverty rate for subgroups of older people (page 28 and copied below). The chart uses the official poverty measure developed by the SSA in the mid-1960s. The official poverty measure compares pre-tax cash income to a threshold that was initially set to three times a minimal food budget in 1963 and that is adjusted for inflation and by family size. In 2014, ten percent of people ages 65 and older are officially in poverty in the US. An additional 5.2 percent of the age group are considered “near poor” because their total income is between the poverty threshold and 125 percent of the poverty threshold. Poverty rates vary dramatically by group; almost one in five Black people ages 65 and older is in poverty in 2014, with an additional 8.5 percent nearly in poverty.
From 2014 to 2019, poverty fell in the US as more people found jobs and earnings increased. Recreating the above SSA chart for 2019 shows that the poverty rate has fallen among all groups but remains very high, particularly for disadvantaged groups. In 2019, 8.9 percent of people ages 65 and older are in poverty by the official poverty measure, and an additional 4.4 percent are near poverty. The poverty rate of Black people ages 65 and older is 18 percent in 2019, a decrease of only 1.2 percentage points since 2014, despite the unemployment rate for Blacks or African Americans ages 65 and older falling from 7.9 percent in 2014 to 4.6 percent in 2019. Among Hispanics or Latinos ages 65 or older, 17.1 percent are in poverty with an additional eight percent near poverty.
A different measure of poverty
The way poverty is measured in the 2014 SSA chartbook does not take into account some aspects of poverty that disproportionately affect older people in the US. The Supplemental Poverty Measure (SPM) was created in 2009 as a more complete measure of poverty. The SPM identifies whether the cash and non-cash resources that someone has available can meet a poverty threshold that adjusts for inflation and family size as well as additional characteristics such as geography. The SPM also accounts for various expenses, including medical expenses. Medical expenses increase the age 65 and older poverty rate by four percentage points.
The next chart uses the SPM poverty rate instead of the official poverty rate seen in the previous chart. Additionally, the next chart shows the share of each group that is removed from poverty by Social Security, meaning not in poverty specifically because of receiving Social Security benefits. For people ages 65 and older, the SPM poverty rate (12.8 percent) is higher than the official poverty rate (8.9 percent), primarily because the SPM accounts for medical expenses. Among those ages 65 and older in disadvantaged groups, the SPM poverty rate is particularly high. The SPM poverty rate is 21 percent for Black people ages 65 and older and 24.4 percent for people in the age group with Hispanic or Latino origin.
While old-age poverty is higher than it should be, the importance of Social Security for reducing old-age poverty cannot be overstated. In 2019, despite a booming economy, an additional 31.1 percent of people ages 65 and older would be in poverty if they did not receive Social Security benefits. That is, the SPM poverty rate would be 43.9 percent for those ages 65 and older but instead is 12.8 percent because of Social Security benefits.
Further, more than a third of women ages 65 and older are taken out of poverty by Social Security; the poverty rate for women in the age group is 14 percent instead of 47.5 percent. Perhaps most astoundingly, despite the relatively good economic conditions, more than half of Black and Hispanic people ages 65 and older would be in poverty in 2019 without Social Security benefits. Nearly a third, 32.6 percent, of Black people ages 65 and older are taken out of poverty by Social Security. The figure is slightly less, 29.8 percent, for those of Hispanic of Latino origin.
1 The 2014 and 2019 income categories are not strictly comparable due to a redesign of the survey to better capture pension income. See my calculations
2 The race and ethnicity of a married couple aged unit is defined by the 2014 SSA chartbook as the race and ethnicity of the husband. In the 2019 data, same sex married couples are included, so for these couples I use the race of the older partner or the race of the partner appearing first in the survey if both are the same age.
Despite the ongoing pandemic, the US Bureau of Labor Statistics report that a typical full-time worker earns the equivalent of more than $52,000 a year. This post discusses earnings from wages and salaries and presents two broader measures that are designed to include people with little or no earnings.
As a starting point for thinking about a person’s earnings: survey data show that wages tend to increase with age. The typical older worker has more work experience and is paid more than the typical younger worker. Among full-time wage and salary workers, earnings increase steadily from $25,000 per year at age 16 to more than $60,000 per year around age 45, then plateau and remain near their peak until the social security retirement age (see chart 1).
Measuring the earnings of full-time workers, however, does not tell us about people who are either working part-time, unemployed, or work-limited in another way. Typical earnings are much lower if we include the earnings of all people in the survey rather than just those who are currently working full-time. The median wage falls from $52,500 for current full-time workers to $15,290 for anyone in the survey aged 16 or older. Broken down by age, the broader measure shows earnings are zero for a typical 16 year-old, around $30,000 for the typical 25 year-old, and peak at around $42,000 for a typical person in their mid 40s (see chart 2). Median earnings past retirement age are zero.
By including people working part-time as well as people with zero earnings, the second chart reverses a major result from the first chart. Specifically, during the pandemic many people lost jobs or became part-time and therefore are removed from the 2020 measurement of full-time workers’ wages. Since jobs lost during the pandemic were more-often below the 2019 median wage, removing these jobs from a wage measurement makes the new median wage of the remaining jobs higher. In other words, the chart 1 result showing that the wage of the typical full-time worker is higher in 2020 than it was in 2019 is because the group of people being measured has changed and the typical worker is a different person. Measuring the same group of people in both 2019 and 2020 shows that earnings have instead fallen substantially during the pandemic. The reduction in earnings is confirmed by data on total wage and salary income.
Importantly, despite far worse economic conditions in 2020 than in 2019, chart 2 shows that several features of the relationship between earnings and age persist across both years. As one persistent feature, in both 2019 and 2020 the typical person who has reached retirement age has stopped working and has zero earnings. The US does a reasonably good job of providing welfare payments to people who reach retirement age, through Social Security, which facilitates retirement.
A second persistent feature is that children have no earnings in either year. With some exceptions, including newspaper delivery and family businesses, wage labor from children under the age 16 is uncommon and it is not measured in the survey. Also, many teenagers above the age of 15 are not working because of school.
Lastly, some portion of working-age adults are work-limited at any given point in time. The work-limited include people with an injury, disability, or illness, as well as students, and people with additional responsibilities at home such as caregivers and new parents. US rules around welfare of children and persons with disabilities are more strict and payments are meager, if available at all, relative to the help retirees receive from Social Security. One consequence of a work-focused welfare system is that many who become work-limited are expected to rely on the earnings of their family members to get by.
Living with family is the way many people, including children, receive resources. Living together allows people to pool their income, share costs, and use resources like a car or a kitchen more efficiently. Economists sometimes calculate a concept called “equivalized” family earnings by adjusting the total earnings of a family for the size of the family (see footnote of chart 3 for details). The result is a per person measure of family wage and salary earnings that accounts for the efficiency of the size of a person’s family. Typical equivalized family earnings are $21,620 per person per year in 2020.
By age, median equivalized family earnings are around $32,000 for newborns, $40,000 for 20-year olds, more than $50,000 for 50-year olds, and zero for those age 70 or older (see chart 3). The drop in family earnings starting at age 60 is from the combination of retirement and from people in these age groups being less likely to live with someone else who works.
Interestingly, the decrease in median earnings from 2019 to 2020 is less severe in the family earnings measure from chart 3 than in the personal earnings measure from chart 2. The resilience of equivalized family earnings to the recession is due in part to more people moving in with family. In 2020, a larger share of people utilize the resource efficiency of living with others, which is captured by an equivalized measure such as family earnings but not by the personal earnings measure.
Families with No Earnings
While the above sections focus on the typical person, measured as the median or middle member of the group, the effects of the COVID-19 recession have fallen more heavily on people nearer to the bottom of the wage distribution, an effect already evidenced in chart 1. One way to see how job losses hurt families is to look at the share of people whose family have no earnings. During a recession, the share without earnings is larger because there are fewer jobs. In 2020, 37.8 percent of people have no family earnings in the survey week, compared to 35.4 percent in 2019. By age, around 15 percent of newborns have no family earnings, compared to less than 10 percent of 45 year-olds and more than half of 70-year olds (see chart 4).
Chart 4 can help to illustrate the relationship between poverty, age, and welfare. By definition, families without earnings will be in poverty unless they receive sufficient income from welfare or from private assets. Because the elderly are far less likely to have family earnings from work, the age group relies heavily on other sources of income to avoid poverty. For elderly people without much private wealth, Social Security payments facilitate independent living and result in much less poverty for elderly people and their families. That is, social insurance makes up for a lack of family earnings and reduces elderly poverty to the same rate or lower as the overall population. Othercountriesgofurther than the US and apply this same technique to other groups of people who do not have earnings, such as children. Including people who do not have earnings when measuring earnings can be useful for thinking about how the US should treat someone when they are work-limited.