Cash aid without conditions was considered a radical idea before the pandemic. But early results from a program in Stockton, Calif., showed promise. Then interest exploded after it became clear how much COVID stimulus checks and emergency rental payments had helped people. The U.S. Census Bureau found that an expanded child tax credit cut child poverty in half. That is, until the expansion ended and child poverty spiked.
Around the country, from big cities to rural counties, there’ve been more than 150 basic income pilots, and counting. Supporters say it works because people can spend the money on whatever they need most…
The pandemic also spurred cash aid because cities got their own pot of COVID relief money. Many are using that to fund guaranteed income pilots. Philanthropic donations are another major funding source, including from groups that have long organized direct cash payments to combat poverty in developing nations.
The pilots target low- to moderate-income people, from a few hundred to a few thousand households, and generally pay them $500 or $1,000 a month for a year or two.
Here is one way to think about such programs: the United States often focuses on helping people or social actors reach their top potential. Whether in education or in innovation, why not enable the top performers to be even better performers? But, another way to operate is to help raise the floor in areas like income so fewer people struggle. These programs seek to provide monies so that people with less income have more opportunities.
Given the outcomes of these programs plus some of the outcomes of the COVID-19 aid, my guess is that we will see more of this with hopefully positive outcomes for people and communities.
The biggest point of contention between the two camps revolves around “unreported income,” more commonly known as tax evasion. Tax returns are the best data source available for studying income distributions, but they’re incomplete—most obviously because people don’t report all of the income that they’re supposed to. This information gap requires inequality researchers to make some educated guesses about how unreported income is distributed, which is to say, about who is evading the most taxes. Piketty, Saez, and Zucman assume that it’s the people who already report a lot of income: Think of the well-paid corporate executive who also stashes millions of dollars in an offshore account. Auten and Splinter, by contrast, assume that those who evade the most taxes are people who report little or no income: Think plumbers or housekeepers who get paid in cash. They believe, in other words, that members of the 99 percent are a lot richer than they look…
To take the true measure of inequality, economists need a way to account for all the income and expenses that don’t show up on people’s tax returns. The method that Piketty, Saez, and Zucman pioneered, and that Auten and Splinter follow, was to take the gross domestic product—a measure of all of the spending in the national economy every year—and figure out who exactly is receiving how much of it. (Technically, they use something called gross national income, which is a close cousin of GDP.) The benefit of this approach is that nothing gets left out. The drawback is that, well, nothing gets left out. GDP measures the total production of an entire economy, so it includes all sorts of expenditures that don’t seem like income at all.
Much of the difference between the authors’ estimates of inequality hinges on how they treat government spending on things that benefit the public at large, such as education, infrastructure, and national defense. Because this spending is part of gross national income, it must be allocated to someone in order for the math to work out. Piketty, Saez, and Zucman take the view that this stuff really shouldn’t be considered income, so they allocate it in a way that doesn’t change the overall distribution. Auten and Splinter, however, argue that at least some of this money should count as income. Citing research indicating that education spending tends to disproportionately benefit lower- and middle-income kids, they decide to allocate the money in a way that increases the bottom 99 percent’s share of income—by a lot. Austin Clemens, a senior fellow at the Washington Center for Equitable Growth, calculates that in Auten and Splinter’s data set, a full 20 percent of income for those in the bottom half of the distribution “comes in the form of tanks, roads, and chalkboards.”…
The deeper you get into how GDP is actually calculated and allocated, the more you feel as though you’ve fallen through a wormhole into an alternate dimension. Let’s say you own a house. Government statisticians imagine that you are renting out that house to yourself, calculate how much money you would reasonably be charging, and then count that as a form of income that you are, in essence, paying yourself. This “imputed rent” accounts for about 9 percent of all GDP, or more than $2 trillion. Or suppose you have a checking account at a major bank. Statisticians will calculate the difference between what the bank pays you in interest on that account (usually close to nothing) and what you could have earned by investing that same money in safe government bonds. That difference is then considered the “full value” of the benefits you are receiving from the bank—above and beyond what it actually charges you for its services—and is therefore considered additional income for you, the depositor. All of these choices have some theoretical justification, but they have very little to do with how normal people think about their financial situation.
These are common issues working with all sorts of variables that matter in life: trying to collect good data, operationalization, missing data, judgment calls, and then difficulty in interpreting the results. In this case, it affects public perceptions of income inequality and big questions about the state of society.
Is this just an arcane academic debate? Since academics tend to want their work to matter for society and policy, this particular discussion matters a lot. Every day, economic news is reported. People have their own experiences. Humans like to compare their own experiences to those of others now and in the past. People search for certainty and patterns. The question of inequality is a recurrent one for numerous reasons and having good data and interpretations of that data matters for perceptions and actions.
The way that academics tend to deal with this is to continue to measure and interpret. Others will see this debate and find new ways to conceptualize the variable and collect data. New studies will come out. Scholars of this area will read, discuss, and write about this issue. There will be disagreement. Conditions in the world will change. And hopefully academics will get better at measuring and interpreting the concept of income.
I interviewed nine real-estate experts to help me understand why the numbers vary so much and, I hoped, help me figure out the right one to use for myself. They confirmed that, yes, the mortgage-affordability numbers are all different, and though some lenders use them to approve mortgages, they are basically guesstimates. “To some extent, they’re plucked out of the air,” Robert Van Order, an economics professor at George Washington University, told me. “A lot of these numbers are pretty arbitrary,” added Edward Seiler, the associate vice president of housing economics at the Mortgage Bankers Association. “It’s just based on people staring at data and thinking, What are the tipping points that force people into delinquency?” If the percentages don’t seem ironclad, it’s because they aren’t.
If these numbers are at the upper end of what people should spend, what do people actually spend?
Despite hearing the 30 percent figure from many of the experts I talked with, I was surprised to learn that most current homeowners actually spend much less on their housing. So do most renters. The median homeowner with a mortgage spends 16 percent of their gross income on their house payment, including taxes and insurance. That number is higher—24 percent—for low-income households, but it’s still less than 30 percent. Renters spend an average of 26 percent of their income on housing. In other words, if you take the mortgage calculators at their word and spend 28 percent, you’re paying much more for a house than the average American does.
Medians can disguise a lot of variability. In certain housing markets or in certain economic conditions or certain personal circumstances, the top end percent might be very helpful. In other situations, it may not matter as much.
Even with the variation in recommendations, it appears they roughly fall into a range of 25-35% of income. Would it be better then to suggest to people that they should aim to spend at most a quarter to one-third of their income on housing? This does not have the convenience of a single number but the range could fit a broader set of conditions and circumstances.
The calculator takes your household income and adjusts it for the size of your household. The income is revised upward for households that are below average in size and downward for those of above average size. This way, each household’s income is made equivalent to the income of a three-person household (the whole number nearest to the average size of a U.S. household, which was 2.5 in 2018)…
Your size-adjusted household income and the cost of living in your area are the factors we use to determine your income tier. Middle-income households – those with an income that is two-thirds to double the U.S. median household income – had incomes ranging from about $48,500 to $145,500 in 2018. Lower-income households had incomes less than $48,500 and upper-income households had incomes greater than $145,500 (all figures computed for three-person households, adjusted for the cost of living in a metropolitan area, and expressed in 2018 dollars).
The following example illustrates how cost-of-living adjustment for a given area was calculated: Jackson, Tennessee, is a relatively inexpensive area, with a price level in 2018 that was 19.0% less than the national average. The San Francisco-Oakland-Hayward metropolitan area in California is one of the most expensive areas, with a price level that was 31.6% higher than the national average. Thus, to step over the national middle-class threshold of $48,500, a household in Jackson needs an income of only about $39,300, or 19.0% less than the national standard. But a household in the San Francisco area needs a reported income of about $63,800, or 31.6% more than the U.S. norm, to join the middle class.
Key here is the idea that incomes go further in some places and have less purchasing power elsewhere. By itself, income may not be that great of a measure for determining social class. Including location helps get at local variations in class.
Of course, there are other factors that go into assessing social class. This includes education, wealth, social networks, and more.
(Note: this calculator is based on 2018 data so there could be some important changes here in 2023.)
Wyoming’s Teton County, home to Jackson Hole, has the nation’s highest per-capita income from assets, according to a study by the Economic Innovation Group. The analysis found a sharp increase in geographic concentration of asset ownership over the past decades…
It’s soared in places like New York City and the San Francisco Bay Area. Meanwhile, across Appalachia, the Deep South and much of the Midwest, it stagnated, representing a negligible source of income…
Nationwide, the county with the lowest asset income per capita is in South Dakota, home to the Pine Ridge Indian Reservation. At $2,800 per person, it’s one-third of the national average. Among the largest U.S. counties, the ones with the five lowest incomes from assets per capita are all mostly Hispanic or Black.
Only a minority of Americans holds assets beyond homes, cars and retirement savings. About 15% of households own stocks and 13% hold business equity or other residential property, according to Fed data.
First, the emphasis here on asset income is helpful compared to the more common analysis of incomes. While income may be related to assets, assets gets more at wealth or how income is converted into more long-lasting economic resources.
Second, that assets are concentrated in particular locations is not surprising but with the relatively limited number of Americans who have certain assets, this concentration is even more notable. The truly wealthy Americans have assets and utilize them in certain places, like New York City, San Francisco/Silicon Valley, and Jackson Hole, Wyoming.
With this said, how much does increasing incomes reduce the gap in wealth and assets? Or, how might efforts at local and national levels affect this gap both locally and nationally? The most exclusive locations are going to be difficult for many Americans to afford at any point, regardless of their income. While much sociological research has studied the concentration of poverty, wealth also concentrates with positive feedback loops for those who can participate.
Researchers found that when wives are the bigger breadwinners, husbands report making an average of 2.9 percent more than what’s in their tax filings. Meanwhile, women who make more than their husbands report earning 1.5 percent less than their actual income…
So why does this phenomenon happen? Researchers say they suspect societal expectations about the roles each person plays in a marriage could be a main factor.
“When married couples . . . violate the norm that husbands outearn their wives, the survey respondents reporting the couples’ earnings appear to minimize the violation by inflating the earnings of the lower-earning husbands and deflating the earnings of the higher-earning wives,” researchers wrote in their findings.
If the misreporting is due to gender norms, might we expect this to go away as more women earn more money? Already, “In about one out of four couples surveyed, wives made more money than their husbands.” Give this a few decades and this misreporting might disappear.
On the other hand, social norms can be last a long time even after society has changed quite a bit from when the social norm arose. If the misreporting continues or even increases, it would be interesting to see how the Census and other surveyors adjust their figures.
“When you look nationwide at the share of households that had roommates or lived with parents, it did start to increase in the years just before the housing bust,” said Aaron Terrazas, senior economist with Zillow. “But it really took off during the financial crisis” that began in 2007, often referred to as the Great Recession.
Since 2005, the doubling up has increased at the same rate among employed and unemployed adults, regardless of age, Zillow found. The share of 20-somethings living in doubled-up households climbed faster than any other age bracket, but people in their 50s came in second.
The median individual income of an employed adult in a doubled-up household is $30,000, compared with the $45,000 earned by those living alone.
“I think there are both demographic and economic forces driving this doubling up — living with parents or living with roommates,” Terrazas said. “In the near term, I don’t see those forces turning around.”
I suspect more Americans would want to live alone – for reasons that sociologist Eric Klinenberg describes in Going Solo– but resources can hold them back. I wonder if the same trend is present on college campuses: those students with more resources live in solo rooms or can live in nicer settings off campus while others may not be able to access those residences.
More broadly, this gets at what Americans think about privacy and intimacy, personal space, and what home should be like. Are roommates really only an option until you find something better (a family or relationship of your own choosing, living by yourself because you can afford it)? Does this help explain why Americans have such big dwellings compared to much of the world (they need space to get away from others who live in the same residence)?
A millionaire is a person with a net worth of $1 million or more. Net worth is the value of everything a person owns, minus all debts…
Such an individual could have a negative net worth, yet they drive a Range Rover and live in a McMansion. Meanwhile, the millionaire next door lives in a three-bedroom house and drives a Hyundai…
Although it’s a common misconception that millionaires spend their money on luxury vacations, clothing, houses, and cars, what I’ve learned in growing my own net worth — and speaking with other millionaires — is that after a certain point, money stops mattering as much as it once did.
This seems to line up with the accepted wisdom that many American millionaires are relatively frugal and made their way to that wealth through saving and hard work.
But, if millionaires are not buying all those McMansions, who is? The flip argument expressed above that there are plenty of people living a millionaire lifestyle or above their means does not apply in all cases either.
Part of the trick here might be disconnecting income from wealth. Having $1 million plus in wealth does not necessarily mean you have the kind of assets to put down a sizable down payment or make sizable payments on a large house. (Think of the people who have paid off their mortgages and have a lot in retirement and savings accounts – this is not always easy to access.) Some people might be willing to buy homes based on whether they can afford the monthly payments – does it roughly fall within 30-35% of my monthly take-home pay – while others would be unwilling to splurge on a McMansion.
To be honest, I have not seen a convincing article or set of data regarding McMansion owners. I would guess a good number are in the top 20% of earners in the United States but probably a good portion are also living paycheck to paycheck.
Instead, analysts said, the decline in both marriage and partnerships is likely a result of the declining ability of men to earn a salary large enough to sustain a family.
“All signs point to the growing fragility of the male wage earner,” said Cheryl Russell, a demographer and editorial director at the New Strategist Press. “The demographic segments most likely to be living without a partner are the ones in which men are struggling the most — young adults, the less educated, Hispanics, and blacks.”
Russell pointed to data that shows marriage rates increase for younger Americans in connection with salaries. Fewer than half of men between the ages of 30 and 34 who earn less than $40,000 a year are married. More than half of those who make more than $40,000 a year are married, including two-thirds of those who make between $75,000 and $100,000 a year…
The Pew data underscores the economic marriage gap: Adults who do not live with partners are more than twice as likely to live in poverty than those who have partners.
“Our surveys show us that one of the things that’s holding unmarried adults back from getting married is that they feel they’re not financially stable enough,” Parker said.
While there are likely additional reasons for this (one example: the development of the idea that marriage is about two economically stable people coming together), marriage in American is increasingly tied to social class.
Regionally, economic growth was uneven.
The median household income in the Midwest grew just 0.9 percent from last year, which is not a statistically significant amount. In the South, by contrast, the median income grew 3.9 percent; in the West, it grew 3.3 percent. “The Midwest is the place where we should have the greatest worry in part because we didn’t see any significant growth,” said Mary Coleman, the senior vice president of Economic Mobility Pathways, a national nonprofit that tries to move people out of poverty. Median household income was also stagnant in rural areas, growing 13 percent, to $45,830. In contrast, it jumped significantly inside cities, by 5.4 percent, to $54,834, showing that cities are continuing to pull away from the rest of the country in terms of economic success…
African Americans and Hispanics experienced significant gains in income, but still trail far behind whites and Asians.
All ethnic groups saw incomes rise between 2015 and 2016, the second such annual increase in a row. The median income of black families jumped 5.7 percent between 2015 and 2016, to $39,490. Hispanic residents also saw a growth incomes, by 4.3 percent, to $47,675. Asians had the highest median household income in 2016, at $81,431. Whites saw a less significant increase than African Americans and Hispanics, of 1.6 percent, but their earning are still far higher, at $61,858.
The poverty rate for black residents also decreased last year, falling to 22 percent, from 24.1 percent the previous year. The poverty rate of Hispanics decreased to 19.4 percent, from 21.4 percent in 2015. In comparison, 8.8 of whites, or 17.3 million people, were in poverty in 2016, which was not a statistically significant change from the previous year, and 10.1 percent of Asians, or 1.9 million people were in poverty, which was also similar to 2015…
Income inequality isn’t disappearing anytime soon.
Despite the improvements in poverty and income across ethnic groups, the American economy is still characterized by significant income inequality; while the poor are finally finding more stable footing following the recession, the rich have been doing well for quite some time now. The average household income of the the top 20 percent of Americans grew $13,749 from a decade ago, while the average household income of the bottom 20 percent of Americans fell $571 over the same time period. The top 20 percent of earners made 51.5 percent of all income in the U.S. last year, while the bottom 20 percent made just 3.5 percent. Around 13 percent of households made more than $150,000 last year; a decade ago, by comparison, 8.5 percent did. While that’s something to cheer, without a solid middle class, it’s not indicative of an economy that is healthy and stable more broadly.
Both of these figures – the poverty rate and median household incomes – are important indicators of American social and economic life. Thus, that both are trending in the right direction is good.
Yet, we also have the impulse these days to (1) dig deeper into the data and (2) also highlight how these trends may not last, particularly in the era of Trump. The trends noted above (and there are others also discussed in the article) can be viewed as troubling as the gains made by some either were not shared by others or do not erase large gaps between groups. Our understandings of these income and poverty figures can change over time as measurements change and perceptions of what is important changes. For example, the median household income going up could suggest that more Americans have more income or we may now care less about absolute incomes and pay more attention to relative incomes (and particularly the gap between those at the top and bottom).
In other words, interpreting data is influenced by a variety of social forces. Numbers do not interpret themselves and our lenses consistently change. Two reasonable people could disagree on whether the latest data is good for America or suggests there are enduring issues that still need to be addressed.
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