Income inequality makes a lot of things we care about worse, according to a new book, The Spirit Level: Why Greater Equality Makes Societies Stronger, by Richard Wilkinson and Kate Pickett. Looking across 20 or so rich nations and across the 50 American states, Wilkinson and Pickett find that countries and states with greater income inequality tend to have lower life expectancy, higher infant mortality, more mental illness, more obesity, higher rates of teen births, more murder, less trust, and less upward mobility.
The following plot of life expectancy by income inequality shows a pattern that appears again and again in The Spirit Level.
“The problems in rich countries,” Wilkinson and Pickett conclude, “are not caused by the society not being rich enough (or even by being too rich) but by the scale of material differences between people within each society being too big. What matters is where we stand in relation to others in our own society” (p. 25).
The book has received a good bit of attention. It’s been reviewed in a number of major newspapers and been the focus of events at progressive think tanks in London and Washington, DC. It’s easy to see why. Many progressives worry about inequality. Here is a book, referencing hundreds of social scientific studies and making extensive use of quantitative data, which says, in effect, that many of our social problems can be significantly eased by reducing income inequality.
Is it correct? I was initially skeptical, and after reading the book I remain so.
What’s the causal link?
It wouldn’t be surprising to find that inequality in the income distribution contributes to inequality in health, education, and so on. And there’s plenty of evidence that it does. Wilkinson and Pickett make a different claim: income inequality worsens the average level of health, education, safety, trust, and other good things. How does it do that?
Wilkinson and Pickett say high inequality increases status competition, which in turn increases stress and anxiety, which leads to social dysfunction.
“Greater inequality seems to heighten people’s social evaluation anxieties by increasing the importance of social status…. If inequalities are bigger, so that some people seem to count for almost everything and others for practically nothing, where each one of us is placed becomes more important. Greater inequality is likely to be accompanied by increased status competition and increased status anxiety.” (pp. 43-44)
Here’s how they see stress as the link between income inequality and a key health outcome, lower average life expectancy:
“One of the most important recent developments in our understanding of the factors exerting a major influence on health in rich countries has been the recognition of the importance of psychological stress…. The most powerful sources of stress affecting health seem to fall into three intensely social categories: low social status, lack of friends, and stress in early life…. Much the most plausible interpretation of why these keep cropping up as markers for stress in modern societies is that they all affect — or reflect — the extent to which we do or do not feel at ease and confident with each other. Insecurities which can come from a stressful early life have some similarities with the insecurities which can come from low social status, and each can exacerbate the effects of the other.” (p. 39)
“So how do the stresses of adverse experiences in early life, of low social status, and lack of social support make us unwell? … The psyche affects the neural system and in turn the immune system — when we’re stressed or depressed or feeling hostile, we are far more likely to develop a host of bodily ills, including heart disease, infections and more rapid ageing. Stress disrupts our body’s balance, interferes with what biologists call ‘homeostasis’ — the state we’re in when everything is running smoothly and all our physiological processes are normal.” (p. 85)
Here’s the hypothesized link with obesity:
“People with a long history of stress seem to respond to food in different ways from people who are not stressed. Their bodies respond by depositing fat particularly round the middle, in the abdomen, rather than lower down on hips and thighs…. The body’s stress reaction causes another problem. Not only does it make us put on weight in the worst places, it can also increase our food intake and change our food choices, a pattern known as stress-eating or eating for comfort.” (p. 95)
And educational achievement:
“New developments in neurology provide biological explanations for how our learning is affected by our feelings. We learn best in stimulating environments when we feel sure we can succeed. When we feel happy or confident our brains benefit from the release of dopamine, the reward chemical, which also helps with memory, attention, and problem solving. We also benefit from serotonin which improves mood, and from adrenaline which helps us to perform at our best. When we feel threatened, helpless and stressed, our bodies are flooded by the hormone cortisol which inhibits our thinking and memory. So inequalities of the kind we have been describing in this chapter, in society and in our schools, have a direct and demonstrable effect on our brains, on our learning and educational achievement.” (p. 115)
Other mechanisms are discussed at various points in the book, including oppositional culture, perceived expectations of inferiority, and humiliation. But stress is the key.
An important question here, which Wilkinson and Pickett don’t address, concerns the tightness of the link between the degree of income inequality in a society and the degree of status competition. The United States has the most unequal income distribution among rich countries, but I’m not certain this results in it having more status competition than other countries. Some European nations with less income inequality have a long history of class divisions. American culture is relatively informal, and Americans tend to be optimistic about the possibility of upward mobility. As a result, perceptions of status divisions may be less pronounced in the U.S. than in some other nations. The same is true for the American states. The states with the highest income inequality include Alabama, Arkansas, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, and Wyoming. Is status competition greatest in these states? I’m not sure.
How strong is the effect?
Wilkinson and Pickett are convinced that the effect of income inequality on social well-being is real, and perhaps it is. But if so, how strong is the effect? Social scientists frequently discover statistically significant effects that turn out to be trivially small in magnitude.
Look again at the chart above, which shows life expectancy by income inequality across affluent nations. If you follow the regression (“best-fit”) line, you’ll see it suggests that going from very high income inequality to very low income inequality will increase life expectancy by approximately two years (from about 77.5 to 79.5). The same is true across the 50 U.S. states. Is that a large impact?
One way to think about this is to consider how much life expectancy has changed in these countries over time. Let’s compare 1980 to 2006. I got data for these two years from the OECD for 21 of the 23 countries included in Wilkinson and Pickett’s graph. In 1980 the average life expectancy in these countries was 71 years. By 2006 it had jumped to 78 years. This increase is not simply a function of the poorer countries making huge leaps. In the three richest countries — Norway, the United States, and Switzerland — life expectancy rose by five or six years. The smallest rise, in the Netherlands, was four years.
If Wilkinson and Pickett’s estimate of the impact of income inequality is correct, reducing inequality in the United States to Sweden’s level would improve life expectancy by two years. Yet in the past generation life expectancy in the U.S. increased by more than twice that amount. By this gauge, inequality’s effect isn’t an especially large one.
Are the correlations true?
The point-in-time associations in Wilkinson and Pickett’s graphs are their key piece of evidence. Are they accurate? In studies such as this, there almost always is reason to worry about data and measurement choices. I’ll mention just one here. Wilkinson and Pickett measure income inequality for countries using data from the United Nations’ Human Development Report. It’s not a bad choice, but a more reliable source when comparing across nations is the Luxembourg Income Study (LIS). The LIS has data for fewer countries, but if an association is genuine it ought to hold for a subset of the countries examined by Wilkinson and Pickett.
The following chart plots life expectancy by income inequality as of 2005, using LIS data for inequality. There is no association.
Actually, this isn’t so much because of the difference in data source; it’s mainly a function of the particular countries that drop out when switching to the LIS data. The association in Wilkinson and Pickett’s chart rests heavily on the position of Japan, Singapore, and Portugal, none of which are in the LIS database. A small number of countries, often the United States and Japan, exert a good bit of influence on the patterns in a number (though not all) of Wilkinson and Pickett’s scatterplots. This is worrisome.
Are cross-sectional point-in-time associations the appropriate empirical test?
Patterns of association across countries or states at a single point in time may be very useful evidence. Or they might not. With this kind of evidence, we worry about other ways in which countries differ from one another that could be the true drivers of the observed association.
To supplement cross-sectional snapshots, we can, where data availability permits, look at what happens over time. Wilkinson and Pickett presumably would think this a good idea. In the book’s final chapter they note that the level of income inequality has changed in a number of these countries over the last few decades. And in the conclusion to an article that summarizes the book, they say “Standards of health and social well-being in rich societies may now depend more on reducing income differences than on economic growth without redistribution.” If income inequality is reduced, they’re suggesting, life expectancy and other social outcomes should improve; if inequality rises, outcomes are likely to worsen.
Yet The Spirit Level includes virtually no analysis or discussion of over-time developments. There is one over-time chart in the chapter on trust, a brief discussion in the chapter on crime, and a few references to other studies in a summary chapter. But as best I can tell, that’s all.
This is an important omission, because researchers who have examined over-time relationships between income inequality and average levels of health have tended to find no support for the hypothesized link (Jennifer Mellor and Jeffrey Milyo; Jason Beckfield; Andrew Leigh, Christopher Jencks, and Tim Smeeding). Here’s one way to see this. The following chart plots life expectancy on the vertical axis and income inequality on the horizontal. Each country is shown at two points in time, around 1980 and around 2005. For each country, a line connects the two data points. In most of the countries income inequality has increased and yet so has life expectancy. That’s not what Wilkinson and Pickett’s argument and findings would lead us to expect. Moreover, in the two countries where inequality was already low and then decreased, the Netherlands and Denmark, life expectancy rose the least.
I haven’t looked carefully at over-time data for the other outcomes Wilkinson and Pickett examine. But a few trends in the United States seem problematic for their argument. Average educational achievement has improved over the past generation even while income inequality soared. Violent crime began increasing in the mid-1960s, well before the rise in inequality, and it has dropped considerably since the early 1990s. Trends such as these don’t necessarily mean inequality has had no effect, but at the very least they call into question its magnitude.
Interestingly, Wilkinson and Pickett report that anxiety, the mechanism through which they believe income inequality causes social dysfunction, has been increasing steadily in the United States and other rich nations over the past half-century. But as they note, that isn’t due to rising income inequality: “That possibility can be discounted because the rises in anxiety and depression seem to start well before the increases in inequality which in many countries took place during the last quarter of the twentieth century. (It is possible, however, that the trends between the 1970s and 1990s may have been aggravated by increased inequality.)” (p. 35). This leaves us with an important unanswered question: Why would income inequality be a key determinant of stress across countries at a point in time, as Wilkinson and Pickett posit, but not within countries over time?
In sum, longitudinal developments offer further grounds for skepticism about the effect of income inequality on average levels of health, education, safety, and other social goods.
What to do
Improving social outcomes is certainly a worthwhile aim. What’s the best way to do it? According to Wilkinson and Pickett,
“Attempts to deal with health and social problems through the provision of specialized services have proved expensive and, at best, only partially effective…. The evidence presented in this book suggests that greater equality can address a wide range of problems across whole societies.”
I wish it were that simple. I share Wilkinson and Pickett’s conviction that it would be good for America and some other affluent nations to reduce income inequality, but this book hasn’t convinced me that doing so would help us to make much headway in improving health, safety, education, and trust. To achieve those gains, my sense is that our best course of action is greater commitment to specialized programs and services, coupled with poverty reduction.
Then again, I’m not certain that Wilkinson and Pickett are wrong. I’ve focused here mostly on the effect of inequality on life expectancy, because that is the social outcome for which the hypothesized causal link (stress) seems most plausible and because it has received the most attention in prior research. I’m skeptical that income inequality has much of an impact on average life expectancy. But perhaps life expectancy will turn out to be the exception to the rule.
It seems unlikely that changes in inequality are going to be reflected rapidly in changes in mortality and other indicators, as your critique (and the typical panel analysis) proposes. After all, mortality is the product of many decades of life experience.
Seems to me that two years of life is significant. My understanding is the discovery of Penicillin did not add 2 years. Attributing it to ‘stress’ seems difficult if not impossible to statistically analyze.
I take the liberty of cross-posting what I put in the comments thread under the post “Inequality as a Social Cancer?” at Economist’s View 19 Jan.
Aha! No wonder I thought of Michael Marmot (Prof. of Epidemiology and Public Health, University College, London) when reading this post. I suspect that the R.Wilkinson who co-authored the book is the same R.Wilkinson who co-authored the WHO publication “Social Determinants of Health: The Solid Facts” with Prof. Marmot
and also co-authored the book “Social Determinants of Health” with Marmot.
Prof. Marmot is well-known for his thesis that social inequality plays a large part in determining health outcomes. He wrote about his research in his book “The Status Syndrome: How Social Standing Affects Our Health and Longevity” (plus several other publications), and also appeared in the PBS TV documentary “Unnatural Causes: Is Inequality Making Us Sick?”
From “Social Determinants of Health: The Solid Facts”:
“Poor social and economic circumstances affect health throughout life. People further down the social ladder usually run at least twice the risk of serious illness and premature death as those near the top. Nor are the effects confined to the poor: the social gradient in health runs right across society, so that even among middle-class office workers, lower ranking staff suffer much more disease and earlier death than higher ranking staff (Fig. 1)”.
(end of cross-post)
As I understand Marmot’s thesis, “poor social and economic circumstances” are multidimensional, not limited to money income.
Nice post – my take was quite similar (http://andrewleigh.com/?p=2400).
And while I’d like JQ’s long lags theory to hold up, the analysis that I’ve done with top incomes suggests that when you start doing 10-20 year lags (with country & year fixed effects), the coefficients imply that inequality is good for your health.
A policy of “poverty reduction” though, would in itself be a attempt to reduce inequality, since poverty in the developed world is a relative concept.
I concede that Wilkinson and Pickett’s argument that high income inequality leads directly to weak health outcomes is not air tight. However, I think you minimize too quickly the very plausible link between high societal inequality and bad population health. The point we need to consider is what kind of inequality are we talking about. Even a brief reflection should make us realize that some forms of inequality will tend to have a strong effect on individual and population health and well-being, while others probably do not. Consider two brothers, otherwise similar, one of whom has a much nicer car, or a greater range of available TV channels available to him than his poorer sibling. Does anyone believe that the one brother’s nicer car or superior TV channel options would markedly improve his health over that of his less advantaged brother? Surely not. But change the comparison to one brother living in a low crime neighborhood and the other in a high crime one; or consider the impact if one brother has access to quality healthcare through insurance and the other lacks health insurance. In such cases, the material and economic differences between the two brothers could plausibly lead to very different health and mortality outcomes. If we apply this train of thought to society as a whole, what we can conclude is that there are a number of basic needs for a flourishing life (educational opportunities, quality healthcare, physical security, freedom from poverty, among others) which when lacking for part of the population will very probably increase poor health. Those societies that come closest to meeting these needs for their entire populations, not just for the most prosperous, will tend to have the best health results. (In practice it is societies most influenced by social democratic political traditions that tend to perform the best on this measure.) So inequality matters very much, but not primarily in the ways measured in income figures. Rather it matters most in the degree to which a society is willing and able to meet on a minimal level the entire population’s basic needs for a flourishing life. That the U.S. does not do well by this standard, and correspondingly has dismal population health compared to other wealthy nations is obvious from international health data.
I’m unconvinced that even a 20-year lag is enough. I suspect that the big adverse effects of inequality are sustained in the first couple of decades of life. OTOH, life expectancy is dominated by what happens after about age 55.
Comments on Andrew Leigh’s post at his blog are closed, so I’ll put my reactions to Dalton Conley’s article here. Andrew Leigh linked to the article in his blog post.
Dalton Conley, in the linked American Prospect article, says “A few years ago, there seemed to have emerged a cottage industry on the deleterious effects of economic inequality on health”. He proceeds to argue that links between inequality and health are always found to be mediated by other factors. He says: “Other studies have shown that U.S. states with more inequality are less likely to be healthy. But what really makes the difference between states are policy differences — like minimum wages, welfare rules, ease of divorce, and speed limits — which suggests that, like countries, whatever states do to produce equality also produces population health; equality itself does not produce better health”.
This looks like a distinction without a difference. If those policy differences both produce more equality and better health, then go ahead and implement them. You will have better health and more equality, and, if Mr Conley is right (in the later part of his article), you’ll also have more honest politics.
Frankly, if studies linking inequality and poor health are a “cottage industry”, articles like Mr Conley’s look like a “palace industry”, aimed at maintaining the status quo with quibbles. The approving millionaire reader can then go, after finishing reading what to him/her is a feel-good piece, to the exclusive dating service advertised on the same page of American Prospect, where an outfit called Elite Meeting – Romance For the Successful and Attractive promises access to its “membership of successful and attractive singles”. What a life!
Well, blink and you miss it! The ad. for “successful and attractive singles” dating has now been replaced by an ad. for stopping health care reform!
This is a very interesting post. I suspect there are a range of things going on and your second chart is a better representation of reality than the first chart from Wilkinson and Pickett.
One problem with the first chart is that Japan is not a very equal society and indeed never was. There was an article in the Review of Income and Wealth from the late 1980s which showed that the view that Japan was a really equal place was based on surveys that excluded single person households but also excluded the self employed including farmers i.e. getting on for 40% of the population. Moreover, income inequality in Japan has risen from whatever it really was, in part due to the ageing of the population and also because of the casualisation of the younger workforce. So we should move Japan from the left hand side towards the right hand side of the chart. It has high life expectancy, but it is not a low inequality society – and my understanding is that the same is true for South Korea and Taiwan.
But also why is life expectancy in Denmark so much lower than in Sweden despite the similar levels of inequality ? Well my understanding is that people in Denmark smoke a lot more than people in Sweden.
I’m not to sure of your analysis. If you think of income inequality as a proxy for a broad distribution of income levels as opposed to a narrow distribution, it seems to make more sense. As the distribution broadens, you get a lot more people without access to proper medical care and life extending benefits of modern society. Since income curves tend to be power curves, a broad curve means you have lot of people down at the bottom, while a narrower curve means that everyone sort of bunches up near the middle.
As mentioned above, and also concluded by the authors themselves – the connection between life-expectancy and inequality is one of the weaker correlations presented in the book. One explanation offered is that income inequalities in a society vary over the lifespan of an individual, and is therefore not expected to strictly correlate with the current level of inequality. This is also the reason for why your graph is difficult to interpret. The large increase of life-expectancy in US might very well be connected with the postwar era of relative equality.
In the edition of The Spirit Level I have, the discussion about the causes for the correlation, the social stress, is quite elaborate. Firstly, the authors conclude that “stress” is a poor description of the phenomenon, since stress is a widely used term, but decide to stick with it in lack of better terminology. Second, that this kind of social stress has direct and measurable physiological effects has long been known in social medicine (lately, but not exclusively reported in for example “If your shoes are raggedy you get talked about”: Symbolic and material dimensions of adolescent social status and health. Sweet E. Soc Sci Med. 2010 Mar 16. [Epub ahead of print]). There are obvious medical explanations for a variety of physiological and psychological problems seen in the wake of inequality. So, social hierarchies, and especially a low standing in a social hierarchy, cause well known effects on medical conditions (observed in both human and different animal populations in different experiments and studies) and ultimately health. We have an effect as show by Pickett and Wilkinson (and not only them, they refer to 170 different studies in my copy of the book). As a medical scientist, cause and effect, the causal correlation, is beyond question. What we can debate is the importance of this effect.
As I pointed out, that the poorest 20% in a society will suffer a bad health from inequality is a prediction made by medical research long time ago, and not in any way controversial. The much more interesting conclusion reached by Pickett and Wilkinson is the one where they claim that social stress is problematic for the rest of the society, also for the richest 20%. There are great implications of this conclusion and I hope we will see more research on this subject.
I am a medical scientist and the more I read how economists discuss The Spirit Level, the more I doubt you are even qualified to understand basic medical reasoning. As I have learned, conclusions in economics can be disregarded and accepted as a matter of taste. This is not the case in medical research. You can not, with maintained credibility, ignore conclusions based on large amounts of published data without offering an alternative explanation that fit the entire set of data better, or atleast as well. (then you can ofcourse claim that the data is invalid for some reason, but since it is the same data as all other makroeconomists use, I havent seen any attempts to this). Posts like the above puts the ability of economists to analyze medical and especially epidemiological research in to question. Not surprising, maybe, since extensive training is required in order to become an epidemiologist. However, I think economists in general would benefit from being more humble in the evaluation of the kind of research presented by Pickett and Wilkinson, since after all, epidemiology, as opposed to economics, have proven a powerful instrument to improve wellbeing in society. I think that in order to offer scientific criticism of the conclusion in The Spirit Level, it is instrumental that the original peer-reviewed papers referred to within can be read and understood. (in addition to the book, I may add). So, but failing to offer an alternative, testable hypothesis to the explanation offered in The Spirit Level, you are demoting your role in the discussion to mere producers of opinions.
On another note, I think it is very welcome if the discussion about The Spirit Level increase the criteria of what can be regarded as causal evidence. I look forward to seeing future (and past) scientific conclusions in the field of economics being analyzed according to these new criteria for causality imposed on the conclusion of The Spirit Level.
I think you’re right, and you’re not alone.
A theory of everything that explains nothing
One of the problems seems to be that they are comparing homogenous scandanavian countries with ethnically diverse countries (Milton Friedman mentioned the problem with these comparisons). Racial groups have different propensities for heart disease, diabeties, alcoholism. In terms of crime groups have different testosterone levels and MAO-A variants are distributed differently. Not to mention cultural and religious differences.
For instance, Hong Kong & Singapore have some of the highest levels of income inequality but are nearly the best in the world for having low infant mortality rates and low crime.
obviously the scientists discuss the comparisons in lenght, both in the book and in the bulk of scientific articles the conclusions in the book is based on. The conclusions do not rest on a bunch of graphs. They are used to illustrate a point in a popular science book that has been made scientifically (published in peer-reviewed journals of a spectra of diciplines).
This you would have seen if you had read the book. Which neither you nor anyone else “considering the evidence” actually has. Is this how you reason? That since Freidman pointed out that there are problems with comparisons, corrected and controlled studies of scientists (with much more accumulated knowledge than Freidman) can not be taken into account? Friedman is, FYI, not a God.
In order to have an opinion of the quality of science, I advice you to first read and understand it. I understand from this blog that a number of people havent come that far in the discussion.
(When it comes to Hong kong there are numerous indeptht discussions of how this citys population is made up by the upper crusts of both the chinese and the brittish societies. Since it has been concluded that it is our socioeconomic staus as children that will influence our health and behaviour for the rest of our lives http://goo.gl/gT3r , it is of no surprise that the inequalities of Hong Kong have little negative impact on its population. Similar conclusions can be made for Singapor)
Many of the commentators are conflating two distinct issues: inequality and poverty. It is difficult to imagine that a society with high income equality but no poverty would have bad health outcomes, just as it seems unlikely that a country with little inequality but lots of poverty would have good health outcomes.
This distinction is important because there is no policy option that reduces inequality while keeping total wealth fixed. There is generally a trade-off between equality and economic efficiency.
To Nymnchen I would respond that the quality of statistical reasoning employed in the medical profession is sometimes very low indeed (see for example the literature on publication bias). Indeed, medical professionals know a great deal about medicine, but not necessarily about statistics.
The authors of the book are not of the medical profession. They are epidemiologists. Epidemiologists eat and breath statistics. I would say these people aquire more statistic for breakfast than a member of “the medical profession” aquires during his/her lifetime. Most of the litterature supporting the hypothesis is produced by others than people “employed in the medical profession”. Which you would have known if you had bothered to read the book.
Still, to in such a manner disregard the competence in the medical profession to identify and characterize the reasons behind lack of health, that is arrogant, ignorant and it greatly discredits your credibility. What you should be aware of before further embarrassing yourself is that most respectable universities have departments of statistical experts, mathematicians, biostatisticians and engineers (certainly no economists), devoted to assis in the analysis of data and designing the studies.
The article in Pediatrics that I linked to, indeed produced by a professor of physiology, describes the mechanism of how inequality affects biology at a physiological level. And for your information, epigenetics is not a result of a glitch of statistical methods.
(Berkeley is equipped with excellent facilities and expertise for statistical analysis, at the service of the scientific “members of the medical profession”, by the way)
If you would have read the book, you would also have been updated on the extended discussion of the differences and importance of relative poverty vs absolute poverty.
There is the only way to remove social inequality.
Noone argues that it should be removed. According to this metastudy, it should just rather be pushed under 0,3 http://goo.gl/d8o4
We in the nordic countries managed that perfectly well without any kind of communism and with a very high degree of personal freedom, inventiveness and entrepreneurship (as a result maybe)
With regard to the US being an outlier: yes, and so is Japan.
Specifically in hte proposed mechanism by which inequality produces these bad health outcomes: status.
For Japan has a low income inequality and yet is, compared to most other societies being mentioned, hyper-sensitive to status.
So from the income part, we’d expect Japan to be on the “good” end of all of the hypotheses….which it pretty much is (although Wilkinson unaccountably drops Japan when comparing inequality and working hours). But if we take the suggested mechansim through which it all works, Japan should be at the “wrong” end. Which it isn’t.
Which leads to the suggestion that there’s something screwy about the mechanism at least.
The in depth analysis by Slate and others have shown that the assumed causes of income inequality, namely tax and trade policy, have less of an effect than things like education and technology. Technology has allowed talented individuals to exercise greater control over resources than ever before. For example since 1980 most of the income going to the top earners came from salaries wherein before it came from investments. While tax policy did play a role one must realize that in the pre-information age there was only a limited amount an owner could do to add value to his holdings. Therefore more persons were required to make large organizations function which spread the wealth created by the organization and also lead to the stereotype of the aristocratic landlord living a life of idleness while his money worked for him. Today those with great wealth are very active in maintaining and managing either their organizations or their money. They use their talent and skills to directly add value at a scale that was impossible before. Technology has allows individuals to capture more of the wealth that their enterprise generates.
For a more down to earth example consider professional sports. Back in the day professional sports players earned high yet “reasonable” salaries. As new technologies increased the revenues of the sports the highly talented players came to demand a larger share of the pie. Today top tier players in any major sport earn astronomical salaries while lower tier athletes struggle or make nothing at all. This is supremely unequal, yet nobody is clamoring for super-stars to take “fair” salaries. They have the talent, they should earn whatever that talent can get them.
That the best argument this piece can come up with to illustrate the damage of high income inequality is “stress” shows that this problem may be a tad overrated. While it is sensible policy to ensure that wealth does not beget wealth w/o regard to talent (ie the estate tax), in a world where single individuals can create outsized value is greater inequality really a problem?
What people need is equal opportunity to rise according to their talents and in America I don’t really see any move by those with wealth to shut out deserving individuals so that their otherwise undeserving offspring can maintain power like some feudal lord.
Let’s not forget about differences in the economic performance of whites, blacks, and latinos. Low-performing minorities increase the inequality and lower various metrics in health. Of course, high-performing minorities also increase inequality, but they don’t have a negative effect on health. We have a lot more information about this topic than what is being presented. Let’s look at that information, if you have any integrity.