A Better Read on the Economy

There’s an entire genre of “things are better than you think” books, stretching back at least a couple decades. In these sunny tomes, academics push back against pessimistic claims that, for example, middle-class incomes are stagnant, the poor are getting poorer, and inequality is exploding thanks to the gains of the evil top 1 percent. Think It’s Getting Better All the Time from Stephen Moore and Julian L. Simon; Myths of Rich and Poor from W. Michael Cox and Richard Alm; Factfulness from Hans Rosling; Enlightenment Now from Steven Pinker; and The American Dream Is Not Dead from Michael Strain.

Joining them is The Myth of American Inequality from former senator Phil Gramm and coauthors Robert Ekelund and John Early, all three of them economists. The U.S. government is getting key concepts all wrong, they say, including income, inflation, poverty, and inequality. They detail how some often-cited metrics are calculated—and how various corrections change the numbers.

It turns out things are better than you think!

Kidding aside, this is an impressive, clearly written book that can introduce everyday readers to the sausage-making process behind the numbers they see cited in the media. It also leaves room for disagreement about the authors’ corrections to the official estimates, as well as their policy recommendations.

The book’s core is a series of chapters taking on numerous concepts the government tries to measure.

Income? They’re counting only cash income—leaving out in-kind transfers like food stamps and employer benefits, as well as failing to subtract taxes. Inflation? They’re overestimating it, which means they assume more of our gains are eaten up by rising prices than is really the case. Both of these problems, meanwhile, affect the measurement of poverty, which depends on whether a family’s income exceeds a threshold that is adjusted for inflation over time. Inequality also hinges on what is counted as income, and to make matters worse, international comparisons are sullied by the Census Bureau’s failure to conform to the reporting rules other countries follow. These aren’t wild conspiracy theories; they’re backed up with careful explanations and citations, and for the most part already well known to people who follow these academic debates.

Even more interesting is the authors’ attempt to present a fresh picture of American households’ finances—both in terms of the current income distribution and in terms of trends over time—by accounting for problems like these.

Ranking households by their earned income (including employer-paid benefits and investment income), there’s a 60-to-1 disparity between the top 20 percent and the bottom 20 percent. The official Census Bureau numbers, including all cash income, put the disparity at about 17 to 1. But add in all transfers and subtract taxes, and the gap shrinks to 4 to 1.

Government transfers to the lowest-earning quintile are enormous, totaling about $45,000 per household—about $19,000 from old-age entitlements, $2,500 from disability, $10,000 from Medicaid and the Children’s Health Insurance Program, and $1,500 from food stamps, plus $13,000 from other programs. The mix is different for elderly and non-elderly households, but the authors report very similar total results when the elderly are excluded, with bottom-quintile non-elderly households also receiving about $45,000 in total.

Indeed, by Gramm et al.’s calculations, the bottom 60 percent of households have been made startlingly equal. The bottom 20 percent end up with roughly $50,000 after taxes and transfers, versus $54,000 for the second quintile and $66,000 for the middle one. If one further adjusts for household size, the lowest income quintile slightly beats the second-lowest, which works more but sees less government largesse and has more mouths to feed.

Regarding poverty, the official rate has stayed within a narrow range of about 10 percent to 15 percent for decades. But when the authors add in government benefits the official measure fails to count, the rate is more like 3 percent, and it falls even lower if the inflation adjustment is improved as well. Gramm et al. also cite work from Bruce D. Meyer and James X. Sullivan that reached similar numbers by measuring poverty based on consumption rather than income.

Has inequality been rising over time? Yes, in terms of earned income, for a number of reasons. Lower-skilled men have been working less, higher-skilled women have been working more (and marrying similarly high-earning men), the returns to education have increased, etc. But growing redistribution has counterbalanced these trends—and, simultaneously, encouraged declining earnings at the bottom, by promising benefits to people who don’t work.

Things are better than you think, but they could be better still, as the authors urge policymakers to enact a suite of reforms to improve opportunity. These include broader use of work requirements for government aid, which will probably be the most contentious aspect of the book among the left. A central thrust of the authors’ empirical analysis, after all, is that counting anti-poverty spending as income makes things look a lot better—and then they turn around and recommend cutting anti-poverty spending, because it’s unfair for people to have similar incomes despite large differences in work effort.

Such reforms could increase work, as shown by the 1996 welfare reform, and there is also a strong moral case that taxpayers shouldn’t support people who refuse to help themselves. At the same time, given the results presented in this book, even a reformed safety net will likely need to achieve substantial redistribution to keep poverty (and inequality, for those worried about it) suppressed.

Gramm and his coauthors are correct in their central claim: Official government statistics measure things in odd and inaccurate ways, and on balance this tends to make things look worse than they are. Those who follow academic work on these topics (and read the other books in this genre) have known this for years.

But it’s also worth flagging that, however clear it is that the official numbers are skewed, “unskewing” the data is at least as much art as science, with numerous debates about which adjustments to make. Gramm et al. explain what they do clearly and provide additional documentation for those who want to dig in, but readers should think about the consequences of each decision.

Take, for instance, the authors’ finding of an eerie income equality among the bottom 60 percent after adjusting for taxes, transfers, and household size, to the point that the bottom quintile makes slightly more than the next group up. A lower-income group has higher income than a higher-income group—a “blockbuster” finding.

This is possible because the authors rank households according to their earned income, then recalculate each group’s income with the adjustments. If a single elderly man has little to no earned income, but more than $50,000 in Social Security and Medicare benefits, he’s placed in the very bottom tier of society, and then the adjustments help to make that bottom tier look well-off. But one can argue for redoing the rankings themselves with the adjustments too, in which case that man wouldn’t be assigned to the bottom tier to begin with, and it would be mathematically impossible for a lower quintile to have higher income than a higher one. This case is easiest to make with the household-size adjustment, which reflects basic economic realities rather than policy, and old-age benefits, which differ in kind from other government transfers.

Other subjective decisions abound. For instance, how does one place a value on public health care benefits, which are an enormous proportion of government spending on both the elderly and the poor and thus can dramatically change the numbers? The authors value health benefits at the amount the government pays for medical services. They present this as a conservative choice because the government underpays for these services, forcing providers to charge higher rates to the privately insured, and because their measure does not include the programs’ administrative costs. If the government paid $2,000 for someone’s medical care, that person received $2,000 in government benefits. Fair enough.

On the other hand, you can’t eat Medicaid. Unlike, say, food stamps, this spending does not function anything like cash for the folks on these programs. It doesn’t necessarily improve their well-being in a dollar-for-dollar fashion, and the benefits are something of a lottery—invaluable for those who fall severely ill, helpful for those who avoid out-of-pocket costs or get routine care they’d otherwise skip, and just some peace of mind otherwise. It’s a judgment call whether and how to account for these issues. In a 2016 report, for instance, Scott Winship decided to value medical benefits at one-quarter of their “market value” as determined by the Census Bureau. (See the discussion of the issue in Appendix 1 here.)

Correcting the poverty rate is also fraught with difficulties. In measuring trends over time, the rate should obviously consider government benefits and properly account for inflation. But what standard of living should the poverty line represent? If we start at the onset of the War on Poverty, with roughly a fifth of Americans officially considered poor, and just track improvement from there, we can say that the war is over and we won: Hardly anyone is poor by mid-1960s standards anymore.

But as standards of living rise in general, should our sense of what it means to be poor change as well? Critics noted that the aforementioned Meyer/Sullivan consumption measures, which suggest a poverty rate of around 3 percent in the late 2010s, were “anchored” to the official poverty rate in 1980. As a result, the late-2010s poverty thresholds were just $13,000 to $18,000 for a family of four (with the exact number varying across measures). Anchoring to 2015 (as Meyer and Sullivan also did in their reports) instead raises the poverty rate to about 12 percent and the thresholds by more than $5,000 each. The Supplemental Poverty Measure, the Census Bureau’s own attempt to create a poverty metric that actually makes sense, has similarly classified around a 10th of Americans as poor in recent years.

There are any number of ways to fix the official numbers, and Gramm et al.’s approach is just one of them. But they have done a stellar job of critiquing the statistics at the heart of so many economic debates and providing a thought-provoking alternative.

The Myth of American Inequality: How Government Biases Policy Debate
by Phil Gramm, Robert Ekelund, and John Early
Rowman & Littlefield, 255 pp., $29.95

Robert VerBruggen is a fellow at the Manhattan Institute.