Census Data Are Weird

For those of you with better things to do than scroll through Paul Krugman’s twitter feed, I have news: last Tuesday the Census Bureau released its annual report on Income and Poverty, and people are stoked.

Here’s the upshot: Median household income increased 5.4% from last year after nine years of general decline. It’s now only 1.6% lower than it was in 2007, the year before the recession, and 2.4% lower than its historic peak in 1999.

While Asian households didn’t see a significant increase, black, white, and Hispanic households did. Median household incomes increased in all regions of the country and, for the first time since the recession, real income gains are distributed beyond the top earners.

Sounds like great news! It might well be, but before you celebrate there are some things to note about these statistics. The following isn’t a refutation of the conclusion that the economy is improving. Rather, it’s an indictment of the statistics that lead us to such conclusions. Here are three things to consider:

  • Household income data aren’t all they’re cracked up to be

All statistics have limits, but median household income is particularly misleading in the wrong hands. For years now, economists and politicians have cited median household income data to paint grim pictures of the American economic landscape. While the story is nicer this year, the logic behind the choice to measure households, rather than individuals, is still suspect.

A positive or negative change in median household income doesn’t imply a similar change in individuals. That’s because the characteristics of households vary across time and population.

Average household size has decreased from 3.6 to 2.5 people since 1940. Demographic shifts can also affect household incomes, because average household sizes differ between races.

Another limitation of household income data is that individuals aren’t equally distributed among households of different income levels. There are far more individuals–let alone workers–in the top quintile of income-earning households than the bottom. People who have vested interests in portraying an economically lopsided America tend to cite household data for this reason, without noting this.

Households expand and contract as more people are able to afford their own places. This can strangely cause median household income to rise while people are making less money. For example, if I were demoted and had to move in with my mom because I was now making half as much money, the median household income would increase as our two households merged, despite less aggregate income for the individuals involved.

The same works in reverse. When I started making enough money, I moved out of my mom’s house. Even though our combined income was greater, median household income fell.

Speaking of which…

  • Millennials are living at home longer and in greater numbers than previous generations

Fully 32% of 18-34 year-old Americans live with their parents, making it the most common living arrangement for that group. There are a couple of reasons for this: higher unemployment among young adults; an accompanying delay in or aversion to marriage; and a changing ethnic makeup of America, among others.

While Millennials are more likely to live with mom and dad, we’ve also become the largest generation in the workforce. A larger part of the workforce consolidating in fewer households could explain part of the rise in household income.

This probably isn’t too big of a factor, but since we’re measuring households it’s worth mentioning that about a third of people ages 18-34 are living with mom and dad.

  • “Low-income households” and poor people aren’t necessarily the same

This is a big one. Part of the elation about the Census data comes from the fact that lower-earning households have seen more of a bump in income than they have in recent years.

The problem is income isn’t the same as wealth. It’s closer to a derivative of wealth, like a stillframe is to a film. It’s a simplistic method of gauging standard of living, hobbled by the fact that it doesn’t consider government transfers of money, assets, or liabilities. Economists would probably argue that consumption data are more informative indicators of standard of living.

A wealthy elderly couple and a part-time minimum-wage earner might both be in the lowest income quintile in a given year. That doesn’t mean their standards of living are similar.

Rising incomes of the lowest earners might indicate lots of things: for example, that people are being forced back into the labor market after retiring. As I’ve noted here before, most poor households have no income earners, according to data from the Federal Reserve Board of San Francisco. Unless the rate of employment among the poor grew at the same time, there could be reason to believe that the increase in low-earning households is due to something other than increased income of “the poor.”

Another common assumption is that the households’ positions within income brackets are stagnant, as if we lived in a world without job churn. The households in the bottom 10% of income earners this year aren’t necessarily the same ones that were there in 2008.

We’re used to seeing data based on groups of income earners, not individuals. That’s how the Census reports. However, studying individuals tells a more relevant story.

The United States Treasury tracked individuals’ tax returns from 1990 to 2005. They found that over half of people in the bottom quintile as of 1990 had moved to a higher quintile by 2005.

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The Census statistics measure exactly what they measure: nothing more. That doesn’t mean that information is useless, it just means we shouldn’t lose our heads over it. Extrapolating a verdict about America’s economic health from median household income data exposes us to opportunities to make mistakes based on a deceptively simplistic figure.

*

Don’t mistake my skepticism of stats for pessimism about the American economy. Where long-term trends in the American economy are concerned, optimism is never a bad idea.

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