You’ve heard the talking points: The economy is better than it’s ever been. Unemployment — that holy grail of economic indicators — is at an all-time low. The American economy is creating jobs. The stock market is riding high (despite occasional blips with each new coronavirus variant!). Indeed, the White House communications coordinator said, “Every economic indicator shows an economy that is growing, that is stronger, that is creating jobs, that is putting more money in people’s pockets.”
And yet poll after poll shows that Americans are uneasy about the economy. For example, a recent CNBC poll showed that fears of inflation have become the number one worry for Americans, worse than COVID or climate change. Indeed, the Consumer Price Index rose to a level unseen in America since I was born.
The debate over whether or not we’re experiencing the “Greatest Economy Ever” or one of the worst in several decades raises an important note about how we measure the economy — frankly, population-wide statistics more generally — in the first place.
Before we cut in, let me put some of my priors on the table: First, I’m not an economist. But as an epidemiologist, I do know a thing or two about measuring populations, and perhaps more importantly, about how the way we measure them can obscure aspects of the collective experience of the things we are measuring. Second, I want this to be the “Greatest Economy Ever;” I worry about the way concerns over the economy may be exploited by the party out of power to make the economy even worse for the people that our economic indicators overlook in the first place.
Metrics are created for the express purpose of enabling us to quickly summarize a population’s experience of a certain thing. A great metric is easy to collect, captures an experience that is meaningful, and responsive to changes within that experience. But there are inherent problems. Metrics are, by definition, worse predictors of a collective experience when there is a lot of variation in the experience. The more variable the experiences, the harder it is for a single metric to capture it, after all. And while a metric may be responsive over the short term, it's usually less effective at tracking changes in the very structure of the phenomenon we’re measuring.
When it comes to our economy, the overwhelming story over the past several decades has been rising American inequality. Wages among lower-income workers have largely stagnated even as a greater proportion of the returns of economic productivity have accrued to the wealthiest. The top 1% of earners saw their real annual wages increase by 157% between 1979 and 2019. Meanwhile, real annual wages increased by a mere 22% among the bottom 90%. The advent of mass inequality in America exacerbates both of the fundamental flaws in topline economic metrics that I explained earlier: they obscure variability (even as inequality means that variability is increasing) and they do not account for structural changes in the system we’re measuring.
Take unemployment for example. Wage stagnation among the bottom 90% of the economy fundamentally changes the economic meaning of being employed. The median employee commands less from the economy than they used to. It also obscures the changing experience of “employment” itself, which increasingly means an insecure gig job that doesn’t come with benefits. Gig jobs skyrocketed between 1978 and 2010.
One phenomenon economists have struggled to explain over the past several months is the “Great Resignation.” After all, why would someone willingly give up a job they have for no job? Well, perhaps it’s because the nature of a job itself has changed so dramatically. Consider the fact that resignations have been concentrated in low-income, insecure sectors of the economy, such as hospitality. One interpretation of the Great Resignation is as a backlash to the gigification and earning stagnation of these sectors. People are deciding that the measly paychecks they’re offered aren’t worth the insecurity or poor treatment they have to put up with to get them. It turns out that “a job’s a job” simply isn’t true, particularly over the sweep of time.
Another metric economists pay attention to is the median family income. If you lined up every family by income, the middle family would earn the median family income. In the United States, it sits just under $70,000 per year for a family of four. It’s meant to capture how much the economy delivers to a middle-class household. But it obscures the profound poverty in which so many families live. Consider a thought experiment. Imagine everyone below that median lost their jobs and all other sources of income. How would it change our median family income? It wouldn’t move it a dime. Perhaps taking an arithmetic mean (a true average, rather than the median, or middle family) would more heavily weight the incomes of the lowest earners, right? Sure. But then consider how inequality at the top obscures the metric, as well: the top 1% of earners in America contribute a full 20% of the country’s income.
Another problem with economic metrics is that they generally lag behind our experiences. But economic comfort isn’t quite a matter of anything that happened in the past; it’s a matter of what we think will happen in the future. To get a picture of that, we tend to extrapolate from current trends. While pundits and politicians often pay attention to where a metric is right now, most people pay attention to how a metric is trending. When Americans are hit monthly with a warning that inflation is increasing, threatening to take ever bigger bites out of their paychecks, it’s no wonder they’re worried. This is particularly true among the lowest-income Americans, whom economic indicators have always underrepresented.
Rather than try to assuage anxieties about the economy with claims that economic metrics are as good as they’ve ever been, the Administration should take seriously the fears that Americans have about the economy. Because there’s a pernicious feature to economic anxieties — they create economic futures. Fears over inflation create behaviors that drive inflation. Rather than tout the “Greatest Economy Ever,” perhaps it would be better to ask what the metrics are obscuring — and have been obscuring for millions of Americans. One thing remains clear, though. Passing the President’s Build Back Better agenda, including universal child care, home- and community-based care, paid family leave, and childhood tax credits would do wonders for the people our metrics tend most often to overlook.
Because while the economic metrics may not be that bad, they are indeed bad metrics.