Mitt Romney in a recent Fortune magazine interview: “I indicated as I announced my tax plan that the key principles included the following. First, that high-income people would continue to pay the same share of the tax burden that they do today.”
That’s odd. Sensible debates about tax fairness and tax policy focus on what rate each group should pay, not on what each group’s share of total tax payments (the “tax burden”) should be.
High-income people’s share of tax payments is determined by their average tax rate, their share of total pretax income, and the average tax rate among all taxpayers.
Policy makers have a lot of control over tax rates. They have some, but far less, influence on the share of pretax income that goes to each group. Hence they have limited ability to control the share of total tax payments paid by a particular group.
In the past several decades federal tax rates on the top 1% of Americans have been lowered (Reagan), raised (Bush I and Clinton), then lowered again (Bush II). If all else stayed the same, that would have reduced the top 1%’s share of total tax payments. But this effect has been dwarfed by the large rise in the top 1%’s share of pretax income, which causes their share of total tax payments to increase. Here’s what the numbers looked like in 1979 and 2007, two years at comparable points in the business cycle (data are from the CBO).
The top 1%’s share of pretax income doubled, from 8.9% to 18.7%. Although the average tax rate they paid fell, their share of total tax payments increased, from 14.2% to 26.2%, because their income share jumped so much.
Consider what the Romney approach would have implied for tax rates paid by the top 1% during the 1979-2007 period. In 1979 their average federal tax rate was 35%; in 2007 it was 28%. Suppose policy makers had promised to keep the top 1%’s share of total tax payments at its 1979 level of 14%. Given the sharp rise in the top 1%’s income share, the average federal tax rate paid by the top 1% would have needed to fall to just 15%.
What does this mean going forward? In pledging to maintain the tax share of the richest Americans at its current level, Mitt Romney is in effect promising that if that group’s pretax income share continues to rise as it has in the past three decades, he will slash their tax rates.
Mark Thoma adds: “He is also promising that if the income share falls, he’ll raise tax rates for upper income households. Anyone think he’d really do that?”
Eduardo Porter, writing in the New York Times, says we need policies to help adjust to, not fight against, economic globalization.
In the Financial Times, Jared Bernstein argues that our chief tax problem is lack of revenues, not lack of progressivity.
From the mid-1940s through the mid-1970s, inflation-adjusted wages for Americans in the middle and below rose in sync with the economy. Since then, the median wage has barely budged. Steve Landsburg suggests that worry about this is misplaced, because what looks like wage stagnation actually is an artifact of a compositional shift in our labor force: “There’s been a great influx of lower income groups — women and nonwhites — into the workforce. This creates the illusion that nobody’s progressing when in fact everybody’s progressing.”
It’s true that employment of women and nonwhites has increased relative to that of white males. But that didn’t begin in the late 1970s. It’s been going on for a long time. Here is the trend in the white male share of total employment since the early 1950s:
A compositional shift in employment isn’t what distinguishes the era of wage stagnation from the earlier period of rising wages.
Three decades ago, 15% of American adults were obese. Today 35% are. Obesity has increased in many other rich nations too. Why?
Although we burn fewer calories now than in the past, reduced physical activity likely played only a minor role in obesity’s rise. Instead, the main cause was a sharp increase in the number of calories we consume. Why did that happen? The most common story focuses changes in the supply of food. Tasty, high-calorie food became cheaper and more easily accessible in larger quantities, so we began eating more of it.
In the past several years some researchers have advanced an alternative hypothesis that blames rising income inequality and/or economic insecurity (see here, here, here, here). These are said to increase stress, which in turn prompts overeating. How well does this square with the evidence?
OVER TIME IN THE UNITED STATES
Begin with the over-time trend in the United States. The obesity rate was flat in the 1960s and 1970s and then shot up in the 1980s. The timing fits for income inequality, which has increased significantly since the 1970s. Economic insecurity, too, has risen during this period, though I’m not sure its increase has been large enough to have produced the massive jump in obesity that occurred.
Note that for the over-time story to work, we need to assume little or no time lag. There was a large rise in obesity during the 1980s. Income inequality and economic insecurity began to rise in the late 1970s at the earliest. If it takes a long time for them to have an impact on obesity, they probably can’t have caused the 1980s obesity increase.
Given that for both hypotheses the key mechanism is stress, we might ask whether stress has increased, and whether the timing fits with the rise in income inequality, economic insecurity, and obesity. None of the research I’ve seen looks into this, but some cite a paper published a decade ago that finds evidence of a rise in anxiety in the U.S. Curiously, though, that study concluded that anxiety rose steadily from the 1950s through the early 1990s. This doesn’t match up well at all with the over-time trends in income inequality, economic insecurity, or obesity.
ACROSS THE RICH COUNTRIES
The chief empirical evidence cited in support of the income inequality and economic insecurity hypotheses is the pattern across affluent countries. However, there’s a problem with the country-level obesity data. In most of these nations the only available data are from interviewees’ self-reports of their height and weight, which are likely to underestimate the true obesity rate. If the degree of bias is similar in all countries, this wouldn’t pose much of a problem for an analysis of cross-country differences. But we don’t know whether the bias is similar across countries or not.
The following chart shows the data we have for the late 2000s. For a few countries — the U.S., Australia, Canada, Ireland, and Finland — there are obesity estimates both from self-reports and from actual measurements of people’s height and weight. The latter are likely to be quite accurate. In each of these five countries the obesity rate based on self-reports is lower. But in the U.S., Canada, and Ireland it’s quite a bit lower, whereas in Finland it’s somewhat lower and in Australia it’s only slightly lower.
This leads me to worry a good bit about the degree of bias for many of the countries. It’s certain that that the U.S. has the highest obesity rate and that Japan has the lowest. But apart from those two nations it’s difficult to be confident. In almost all of the other countries, the obesity rate according to the self-reported data is within a fairly narrow band, between 10% and 16%. Maybe these countries’ true obesity rates line up in the same way they appear in the chart. But maybe not. Bottom line: we should be very cautious in drawing inferences from the cross-country data.
Okay, with that caveat, what does the cross-country evidence suggest? Let’s start with the simple cross-section. (I’ll come to over-time patterns in a moment.) The next chart shows the association between obesity and income inequality as of the mid-to-late 2000s. I’ve used obesity rates based on self-reports for most of the countries and the true rate minus a few percentage points for the others. As the solid line indicates, the association is positive; nations with higher income inequality tend to have higher obesity rates.
But the positive association is driven entirely by the group of six English-speaking nations in the upper-right portion of the chart: Australia, Canada, Ireland, New Zealand, the United Kingdom, and the United States. If we exclude them, the association disappears entirely (dashed line). That’s not due to lack of variation in income inequality among the remaining nations. The Nordic countries are well over to the left with low inequality, while Portugal, Spain, Italy, and Japan are well over to the right. But there is no relationship between income inequality and obesity among these 14 non-English-speaking countries.
Maybe there’s something about the English-speaking nations, other than high income inequality, that has resulted in high obesity. Here is where the economic insecurity hypothesis comes in. In a recent paper in the journal Economics and Human Biology, Avner Offer, Rachel Pechey, and Stanley Ulijaszek write “Among affluent countries, those with market-liberal welfare regimes (which are also English-speaking) tend to have the highest prevalence of obesity. The impact of cheap, accessible high-energy food is often invoked in explanation. An alternative approach is that overeating is a response to stress, … that market-liberal countries have an environment of greater economic insecurity, and that this is the source of the stress that drives higher levels of obesity.” Offer and his colleagues conclude that economic insecurity is a good predictor of the cross-country variation in obesity, much better than income inequality.
I suspect it’s true that the English-speaking countries tend to have more economic insecurity than other rich nations. But I have limited faith in the insecurity measures Offer and his coauthors use in their analyses. To be economically secure is to have sufficient resources to cover one’s expenses. Economic insecurity is a product of low income, of significant income decline coupled with lack of private or public insurance and lack of assets, or of inadequate insurance to head off large unexpected expenses. At the moment I don’t think we have an especially valid and reliable measure of economic insecurity for cross-country analysis.
What do the over-time patterns in obesity tell us? They’re shown in the following chart, with data based on measured height and weight shown in solid lines and data based on self-reports shown in dashed lines. Note the similarity between the trend for the U.S. and the trends for Australia, New Zealand, and the U.K. The pace of increase since the 1970s has been about the same in all four of these countries. This suggests that there is indeed something different not just about the United States but about the English-speaking nations as a group.
And yet, the differing data sources should give us pause. The data for the other two English-speaking countries, Canada and Ireland, are from self-reports, and their over-time trends look very much like those of the non-English-speaking nations with self-report data. Maybe the apparent difference between the English-speaking countries and other rich countries (apart from Japan) in the pace of obesity’s rise is simply a function of data source. Unfortunately, we can’t be sure.
If the English-speaking countries do in fact stand apart in their obesity rates or trends, there is an alternative hypothesis that ought to be considered. Rather than being driven by income inequality or economic insecurity, it might owe to these countries’ weak regulation of food and restaurants and to their lack of a well-entrenched healthy eating culture. Large-portion restaurants, particularly fast-food ones, may have proliferated more rapidly in the English-speaking nations. Junk food may have become available in grocery and convenience stores sooner and in larger quantities. And the shift away from home cooking and limited snacking may have occurred more quickly and decisively. This strikes me as more plausible than the suggestion that Americans and their counterparts in other English-speaking nations suddenly began eating more due to heightened stress. It’s also consistent with my own anecdotal impressions, though I haven’t seen any hard data.
Offer and colleagues include a measure of the price of a McDonald’s Big Mac relative to per capita GDP. This is likely to capture only part of what I’m referring to, and in their analysis it doesn’t account for much of the cross-country variation. A better measure, though still only a partial one, might be something like the number of restaurants per capita. One study finds that within the United States this correlates strongly with the prevalence of obesity over time.
ACROSS THE STATES
To my knowledge there are no state-level studies of the impact of economic insecurity on obesity, perhaps because we lack good state-level data on economic insecurity. Income inequality has received more attention, and some researchers have concluded that there is a positive association between inequality and obesity across the states (e.g. chapter 7 here).
Obesity data for the U.S. states are available from 1995 to 2010. The data are from self-reports, so here too we should be wary. But we can hope that the degree of bias is similar in each state.
Here is the cross-sectional pattern as of the late 2000s. The predicted positive association is there (solid line). But it is driven by eight southern states in the upper-right portion of the chart: Alabama, Arkansas, Kentucky, Louisiana, Mississippi, Oklahoma, Tennessee, and West Virginia. (Four other deep-south states — Georgia, North Carolina, South Carolina, and Texas — are close by.) Without these states there is no correlation (dashed line). It’s not difficult to think of plausible alternative causes of these states’ high obesity rates, most notably diet.
Indeed, since the states differ in a slew of ways that might affect obesity — from food preferences to education to affluence to physical activity — our best bet is to compare changes over time. If income inequality is an important determinant of obesity, we would expect states in which income inequality has increased most rapidly to have experienced the fastest rise in obesity. Have they? As the next chart shows, the answer is no.
(Two technical details: First, do we need to allow a longer time lag for the effect to show up? Perhaps, but if so the case for inequality as a major contributor to the rise in obesity is, as I suggested earlier, much less compelling. Second, is there a positive association between the level of income inequality in the mid-1990s and subsequent changes in obesity? The answer again is no.)
Now, it’s possible that analyzing the period from the mid-1990s through the late 2000s isn’t very informative. It could be that the strong causal effects are visible only in the 1980s, when the obesity rise began, and patterns since then don’t shed much light. Unfortunately, there’s no way to know, because we don’t have 1980s obesity data for many of the states. What can be said is that given the available data, the case for income inequality as a key determinant looks weak.
ACROSS INDIVIDUALS IN THE U.S.
Another piece of evidence sometimes cited as supporting the economic insecurity hypothesis is the social gradient in obesity in the United States — the fact that obesity rates have tended to be highest among the poor, those who are least secure economically.
Of course, there are reasons other than stress why poor people might be more vulnerable to obesity, such as less education, less ability to afford healthy food, and less access to such food. Here too, then, it’s helpful to examine changes over time rather than just levels. One potentially useful piece of information is changes in obesity among women after the mid-1990s welfare reform. That reform placed strict time limits on receipt of cash assistance for women with low income. If there is any change in recent decades that ought to have heightened stress among low-income women, welfare reform is it. According to the economic insecurity hypothesis, obesity rates in the period after the mid-1990s should have risen more rapidly among low-income women than among other women.
But that isn’t what happened, as the next chart shows. Obesity rates actually increased a bit more rapidly among middle-income and high-income women than among those with low incomes.
WHAT SHOULD WE DO?
About a third of American adults are obese. Obesity tends to have adverse financial and mental and physical health consequences for these individuals, and it’s estimated to cost the country about 1% of GDP in medical expenses each year. It’s a significant social and economic problem.
What’s the best strategy for reducing obesity? Some scholars have come to believe that reducing income inequality and/or economic insecurity is a key part of the cure. I’m not persuaded that the evidence supports this view. Though there’s a lot of uncertainty due to data limitations, my best guess is that inequality and insecurity have played a minor role, if any, in obesity’s rise.
Since the 1970s the financial system in the United States, and in some other rich nations, has been oriented around equity markets. Many firms are publicly owned, with stock ownership widely dispersed. Shareholders care first and foremost about appreciation in the stock price, and they believe short-run profit performance is the best indicator of likely appreciation.
Recent reports highlight some significant cracks in this system (The Economist, Felix Salmon, James Surowiecki, Andreas Utermann): fewer firms are now publicly traded, with more choosing to remain private or become partnerships; more firms that go public insist on a dual stock structure that limits shareholder voting rights; and financial advisers are paying more attention to dividends rather than simply share price.
I see two interesting questions going forward: (1) Will this amount to a significant shift over the next decade or two, or will these changes turn out to be marginal? (2) If the shift is large and sustained, will it help to remedy some of the drawbacks of the equity-market-centered system, such as short-termism, excessive speculation and risk-taking by financial institutions, and oversized compensation for those at the top of the corporate hierarchy? Will it have significant costs, such as smaller retirement nest-eggs and weakened oversight of firms’ conduct?
The Weight of the Nation is a four-part series on obesity in America by HBO Films and the Institute of Medicine, with assistance from the Centers for Disease Control (CDC) and the National Institutes of Health (NIH). It’s been showing on HBO and can be viewed online. Each of the four parts is well done and informative.
Obesity is defined as having a body mass index (BMI) of 30 or more. For a person 6 feet tall, that means a weight of more than 220 pounds. For someone 5’6″, the threshold is 185 pounds. People who are obese tend to earn less and are more likely to be depressed. They are at greater risk of diabetes, heart disease, stroke, and some types of cancer, and they tend to die younger. The CDC estimates the direct and indirect medical care costs of obesity to be $150 billion a year, about 1% of our GDP.
The chart below, which appears several times in The Weight of the Nation, shows the trend in obesity among American adults since 1960, the first year for which we have good data. The data are from the National Health and Nutrition Examination Survey (NHANES). They are collected from actual measurements of people’s height and weight, rather than from phone interviews, so they’re quite reliable. After holding constant at about 15% in the 1960s and 1970s, the adult obesity rate shot up beginning in the 1980s, reaching 35% in the mid-2000s.
What caused the surge in obesity? The standard explanation is too much eating and too little physical activity, and The Weight of the Nation sticks with this story. But it shouldn’t, because the evidence suggests one of these two hypothesized culprits has been far more important than the other.
Here is the trend in eating, measured as average calories in the food supply (adjusted for loss and spoilage) according to data from the Department of Agriculture. This chart too is from The Weight of the Nation. The timing of change matches that for obesity; the level is flat through the 1970s and then rises sharply beginning in the 1980s. An alternative series, measuring energy consumption per capita, goes back to 1950 (see figure 6, chart F here); it too shows little or no change until 1980, and then a sharp jump. The rise in food consumption correlates closely with the rise in obesity.
That isn’t true of physical activity. We’re less active now than we were half a century ago, but the timing of the decline in activity doesn’t match up with the shift in obesity.
We don’t have good historical data for a comprehensive measure of activity, such as calories expended, so we have to look instead at individual components. We can begin with the most-often-cited culprit: television. Here too The Weight of the Nation presents data, shown below, with the suggestion that TV watching is a significant cause of rising obesity. But the trend doesn’t support that inference. Time spent watching television has increased steadily since 1950. There was no sudden rise in the 1980s.
What about video games, the internet, and smartphones? The internet and smartphones arrived on the scene too late to account for the rise in obesity in the 1980s and most of the 1990s. The timing doesn’t work for video games either; they’re played mostly by the young, beginning in the 1980s, but obesity rates rose sharply in the 1980s and 1990s among adults of all ages, even among the elderly (see table 2 here).
More Americans now have sedentary jobs and drive to work. Yet as David Cutler, Edward Glaeser, and Jesse Shapiro noted in a paper published nearly a decade ago, these shifts have been going on for a long time, with no acceleration in the 1980s.
“Between 1910 and 1970, the share of people employed in jobs that are highly active like farm workers and laborers fell from 68 to 49 percent. Since then, the change has been more modest. Between 1980 and 1990, the share of the population in highly active jobs declined by a mere 3 percentage points, from 45 to 42 percent. Occupation changes are not a major cause of the recent increase in obesity.
“Changes in transportation to work are another possible source of reduced energy expenditure — driving a car instead of walking or using public transportation. Over the longer time period, cars have replaced walking and public transportation as a means of commuting. But this change had largely run its course by 1980. In 1980, 84 percent of people drove to work, 6 percent walked, and 6 percent used public transportation. In 2000, 87 percent drove to work, 3 percent walked, and 5 percent used public transportation. Changes of this minor magnitude are much too small to explain the trend in obesity.”
Another reason to doubt the importance of declining physical activity is that the elderly probably have become more active over time, rather than less, and yet we observe a rise in obesity among the elderly too, similar in timing and magnitude to that of younger adults (again see table 2 here).
This doesn’t mean physical activity plays no role in determining which persons become obese. And it doesn’t mean an increase in activity won’t help reduce obesity’s prevalence. But it does suggest that a strategy focused on increasing activity — and The Weight of the Nation leans in this direction — may not get us as far as we’d like. To make serious progress in reducing obesity, we need to significantly reduce the number of calories many of us consume.
Lecture slides for my “The Good Society” course this spring are posted here. The topics:
- What should we seek?
- Rising incomes and living standards
- Economic security
- Economic and social policy
- Economic growth and employment
- What do Americans want?
- Can we generate more tax revenue?
- Is progress possible?
Since the 1970s, income growth for middle-class American households has become decoupled from growth of the economy. The chart below offers one way to see this. It shows trends in GDP per capita and median family income, with each series displayed as an index set to equal 1 in the initial year. From the late 1940s through the mid-to-late 1970s, the two moved in lockstep. After that, GDP per capita continued its steady upward march (through 2007), but median income rose much less rapidly.
This is disappointing, but seemingly not surprising. After all, income inequality increased sharply during these years. The share of income going to the top 1% of households jumped from 8% in 1979 to 17% in 2007. With a larger and larger portion of economic growth going to those at the top, a divorce between growth of the economy and growth of middle-class incomes is exactly what we would expect to see.
One objection is that the price deflator typically used to adjust GDP per capita for inflation differs from the deflator used for median family income. I’ve addressed that here by using the same deflator for both.
A second concern has to do with GDP per capita as an indicator of economic advance. Since the 1970s a larger portion of GDP has gone to replace old capital equipment and therefore can’t go to household income. Also, the number of persons has increased less rapidly than the number of households, so a per capita (per person) measure of GDP could mislead.
A third worry is that the income measure used to calculate median family income is too thin. If a growing portion of GDP has gone to employer benefits, that would help middle-class households, but it wouldn’t show up in these income data.
To address these second and third concerns, we can turn to a more encompassing measure of household income. The data are from the Congressional Budget Office (CBO). The measure includes all sources of cash income. It adds in-kind income (employer-paid health insurance premiums, food stamps, Medicare and Medicaid benefits), employee contributions to 401(k) retirement plans, and employer-paid payroll taxes. Tax payments are subtracted.
We can use average household income in these data as a substitute for GDP per capita. The CBO data set doesn’t tell us the median income, but it provides something quite similar: the average income of households in the middle quintile of the distribution (from the 40th percentile to the 60th). The following chart adds these two series. The story is virtually identical.
Decoupling is real and sizable.
Since the 1970s, the incomes of Americans in the lower half have risen very slowly. That’s not because economic growth has been slow. Instead, as this chart shows, it’s because growth of incomes has lagged well behind growth of the economy.
This isn’t good. In a growing economy, the benefits of growth should accrue not just to those in the upper half (or in the upper 5% or 1% or 0.1%), but to everyone. The income gains needn’t be spread perfectly equally, but those in the bottom half ought to get more than a crumble.
Yet is the story conveyed by this graph misleading? The income data are from the Current Population Survey. Each year a representative sample of American adults is asked what their income was in the previous year. But each year the sample consists of a new group; the survey doesn’t track the same people as they move through the life course. If we interpret the above chart as showing what happens to typical American households over the life course, we’ll conclude that they see very little increase in income as they age. That’s not correct. In any given year, some of the people with below-median income are young. Their wages and income are low because they are in the early stage of the work career and/or because they’re single. Over time many of them will in fact experience a significant income rise. They’ll get pay increases; or they’ll partner with someone who also has earnings; or both. The chart above misses this income growth over the life course (absolute intragenerational income mobility).
The following chart offers one way to see this. The lower line shows median income among families with a “head” age 25 to 34. (As in the first chart, I use families instead of households in order to be able to go back farther in time; data for households aren’t available prior to 1967.) The top line shows median income among the same cohort of families twenty years later, when their heads are age 45 to 54.
To clarify, consider the year 1979. The lower line tells us that in 1979 the median income of families with a 25-to-34-year-old head was about $54,000 (in 2010 dollars). The data point for 1979 in the top line tells us the median income of that same group of families twenty years later, in 1999. They’re now 45 to 54 years old, which is the peak earning stage for most people. The median income in this group is now about $85,000.
In each year the gap between the two lines is roughly $30,000. This tells us that the incomes of middle-class Americans tend to increase substantially as they move from the early years of the work career to the peak years.
Should this reduce our concern about the over-time pattern shown in the first chart above? No, it shouldn’t. Look again at the second chart. Between the mid-1940s and the mid-1970s, the median income of families in early adulthood (the lower line) rose steadily. Median income for these young families was around $25,000 in the mid-1940s. By the mid-1970s it had doubled to $50,000. Americans during this period experienced income gains over the life course, but they also tended to have higher incomes than their predecessors, both in their early work years and in their peak years. That’s because the economy was growing at a healthy clip and the economic growth was trickling down to Americans in the middle. (Though I don’t show it here, the same was true below the median.) After the mid-1970s, this steady gain disappeared. From the mid-1970s to 2007 the median income of families with a 25-to-34-year-old head was essentially flat. Each cohort continued to achieve income gains during the life course. (Actually, we don’t yet know about those who started out in the 1990s and 2000s, as they’re just now beginning to reach age 45 to 54. The question marks in the second chart show what their incomes will be if the historical trajectory holds true.) But the improvement across cohorts that had characterized the period from World War II through the 1970s — each cohort starting higher and ending higher than earlier ones — disappeared.
So yes, for many Americans income rises during the life course. And yes, this is hidden by charts such as the first one here. But that shouldn’t lessen concern about the decoupling between economic growth and household income growth that has occurred over the past generation. We should want healthy income growth not just within cohorts (over the life course) but also across them.
Yes. As best we can tell, America’s tax system is slightly progressive and the tax systems of most other affluent nations are slightly regressive. Details from Peter Whiteford, Lucy Barnes, me, and more from me.
Alan Krueger, Chair of President Obama’s Council of Economic Advisers, gave a talk a few weeks ago on inequality. Krueger described the sharp increase in income inequality in the United States since the 1970s and discussed some undesirable consequences it may have. One of those consequences is reduced intergenerational mobility (relative intergenerational income mobility, to be more precise). Krueger provided a graph showing that nations with greater income inequality tend to have a stronger correlation between the earnings of parents and their children (less mobility). This has sparked a wide-ranging discussion about the link between income inequality and mobility (Winship, Corak, Winship, Corak, Cowen, Yglesias, Wolfers, Smith, Winship, Quiggin, Cowen, Quiggin, Bernstein).
Here’s what the pattern looks like according to Miles Corak, the source of Krueger’s data (enlarged version here). The vertical axis in the chart is immobility; lower means more mobility. The horizontal axis is income inequality a few decades earlier.
Nations with lower income inequality tend to have more intergenerational mobility, and the association is quite strong. There are concerns about the data. But suppose the data are accurate, and suitable for testing this link. What does the association depicted in this chart tell us about the magnitude of inequality’s impact? How much would reducing income inequality in the United States help?
For most, the aim isn’t high intergenerational mobility per se; it’s low inequality of opportunity. Mobility serves as an indicator (not perfect, but not bad) of equality of opportunity.
Money ought to be good for children’s opportunity. Kids growing up in households with higher incomes are more likely to have good health care, low stress, learning-centered preschools, good elementary and secondary schools, extracurricular activities that promote cognitive skills and earnings-enhancing noncognitive traits, and access to a strong university. It would be surprising, therefore, if inequality of parents’ incomes did not contribute to inequality of opportunity among their children.
But how large is the effect? After all, money isn’t the only thing that matters; a good bit of our abilities and motivations when we reach adulthood stem from nonmonetary influences such as genetics, in-utero developments, our parents’ habits and behaviors, and peers. Also, there are diminishing returns to money; beyond a certain point, more parental income probably helps only a little, if at all.
Yet the graph suggests a large impact. Apart from data concerns, is there any reason to question this? I think so. First, let’s set aside the low- and middle-income countries (Argentina, Brazil, Chile, China, Pakistan, Peru, Singapore). Mobility processes in these countries may or may not be comparable to those in the rich nations. Next, notice that inhabiting the lower-left corner of the chart are the four Nordic nations: Denmark, Finland, Norway, and Sweden. These countries have been providing affordable high-quality early education to a substantial portion of children age 1 to 5 for roughly a generation. James Heckman and Gøsta Esping-Andersen, among others, have argued that early education is perhaps the single most valuable thing a society can do to equalize opportunity. These countries also feature late tracking in elementary and secondary schools and heavy subsidies to ensure college is affordable for all. These public services, rather than low income inequality, might be the chief reason the Nordic countries have such high intergenerational mobility.
What would that imply for the cross-country association between income inequality and intergenerational mobility? As the following chart shows, if we leave out the Nordic nations the association is still there, but the countries are widely dispersed around the line, suggesting weaker grounds for confidence that the association is a strong one. (For the statistically inclined, the r-squared is .47 with the Nordics included and .16 without them.)
Is it possible, then, for a country to have high income inequality but also low inequality of opportunity? John Quiggin is skeptical. He suggests the UK experience has debunked this “third way” notion. I’m not so sure. Imagine a rich nation with America’s income inequality and Nordic public services: affordable high-quality early education, K-12 schooling with late tracking and equal funding, and widespread access to good-quality universities. And perhaps also comprehensive prenatal care. Would its opportunity (mobility) structure look more like America’s or more like Sweden’s?
But, some will respond, you can’t get those services if income inequality is high. The rich will block the heavy taxation needed to fund them. Maybe. But income inequality has been rising in Sweden. In fact, in the late 1990s and mid 2000s the top 1%’s share of income (including capital gains) in Sweden was about the same as in the 1970s United States (see figure 7 in this paper by Atkinson, Piketty, and Saez). So far this hasn’t undermined Swedish taxation, though it’s probably too soon to draw any firm conclusions.
Suppose income inequality continues to rise in Sweden but its public services hold up. Will Sweden’s intergenerational mobility a few decades from now look like ours does today? I’d predict no. I suspect opportunity-enhancing programs can overcome a good bit of the harm done by income inequality.
That’s not to say we shouldn’t also try to reduce income inequality. I think we should. The point is that if we want to reduce inequality of opportunity, reducing income inequality isn’t the only way, and perhaps not even the best way, to do it.
Lecture slides for my “Social Issues in America” course this fall are posted here. The topics:
- Should we legalize marijuana?
- Are humans causing dangerous climate change?
- Should same-sex marriage be legal?
- Is rising income inequality a serious problem?
- Are Americans overtaxed?
- Should we promote gender equality?
- Why are some of us red and others blue?
- Is party polarization bad?
- What drives government policy?
- Is big business ruining America?
- What should we eat?
- Are American universities failing?
- Free trade or fair trade?
- What should we do about immigration?
- When should we intervene abroad?