Certain death? Black-White death dispersions

New research report, after rumination.

Knowing the exact moment of death is a common fantasy. How would it change your life? Here’s a concrete example: when I got a usually-incurable form of cancer, and the oncologist told me the median survival for my condition was 10 to 20 years, I treated myself to the notion that at least I wasn’t going to the dentist anymore (6 years later, with no detectable cancer, I’m almost ready to give up another precious hour to dentistry).

I assume most people don’t want to die at a young age, but is that because it makes life shorter or because it makes them think about death sooner? When a child discovers a fear of death, isn’t it tempting to say, “don’t worry: you’re not going to die for a long, long time”? The reasonable certainty of long life changes a lot about how we think and interact (one of the many reasons you can’t understand modernity without knowing some basic demography). I wrote in that cancer post, “Nothing aggravates the modern identity like incalculable risk.” I don’t know that’s literally true, but I’m sure there’s some connection between incalculability and aggravation.

Consider people who have to decide whether to get tested for the genetic mutation that causes Huntington’s disease. It’s incurable and strikes in what should be “mid”-life. Among people with a family history of Huntington’s disease, Amy Harmon reported in the New York Times, the younger generation increasingly wants to know:

More informed about the genetics of the disease than any previous generation, they are convinced that they would rather know how many healthy years they have left than wake up one day to find the illness upon them.

The subject of Harmon’s story set to calculating (among other things) whether she’d finish paying off her student loans before her first symptoms appeared.

The personal is demographic

So what is the difference between two populations, one of which has a greater variance in age at death than the other? (In practice, greater variance usually means more early deaths, and the risk of a super long life probably isn’t as disturbing as fear of early death.) Researchers call the prevalence of early death — as distinct from a lower average age at death — “life disparity,” and it probably has a corrosive effect on social life:

Reducing early-life disparities helps people plan their less-uncertain lifetimes. A higher likelihood of surviving to old age makes savings more worthwhile, raises the value of individual and public investments in education and training, and increases the prevalence of long-term relationships. Hence, healthy longevity is a prime driver of a country’s wealth and well-being. While some degree of income inequality might create incentives to work harder, premature deaths bring little benefit and impose major costs. (source)

That’s why reducing life disparity may be as important socially as increasing life expectancy (the two are highly, but not perfectly, correlated).

New research

Consider a new paper in Demography by Glenn Firebaugh and colleagues, “Why Lifespans Are More Variable Among Blacks Than Among Whites in the United States.”

I previously reported on the greater life disparity and lower life expectancy among Blacks than among Whites. Here is Firebaugh et al’s representation of the pattern (the distribution of 100,000 deaths for each group):

bwdeaths

Black deaths are earlier, on average, but also more dispersed. The innovation of the paper is that they decompose the difference in dispersion according to the causes of death and the timing of death for each cause. The difference in death timing results from some combination of three patterns. Here’s their figure explaining that (to which I added colors and descriptions, as practice for teaching myself to use an illustration program — click to enlarge):

bw death disparities

The overall difference in death timing can result from the same causes of death, with different variance in timing for each around the same mean (spread); different causes of death, but with the same age pattern of death for each cause (allocation); and the same causes of death, but different average age at death for each (timing). Above I said greater variability in life expectancy usually means more early deaths, but with specific causes that’s not necessarily the case. For example, one group might have most of its accidental deaths at young ages, while another has them more spread over the life course.

Overall, the spread effect matters most. They conclude that even if Blacks and Whites died from the same causes, 87% of the difference in death timing would persist because of the greater variance in age at death for every major cause. There are differences in causes, but those mostly offset. Especially dramatic are greater variance in the timing of heart disease (especially for women), cancer, and asthma (presumably more early deaths), The offsetting causes are higher Black rates of homicide (for men) and HIV/AIDS deaths, versus high rates of suicide and accidental deaths among White men (especially drug overdoses).

The higher variance in causes of death seems consistent with problems of disease prevention and disparities in treatment access and quality. (I’m not expert on this stuff, so please don’t take it exclusively from me — read the paywalled paper or check with the authors if you want to pursue this.)

Are these differences in death timing enough to create differences in social life and outlook, or health-related behavior, between these two groups? I don’t know, but it’s worth considering.

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Divorce, animated

Next up the in The Story Behind the Numbers series of animations for my book: Divorce (Chapter 10, “Divorce, Remarriage, and Blended Families). Using the demographic characteristics associated with divorce, from my paper here, the artists at Kiss Me I’m Polish set the story in charming abstract creatureville:

Here’s the relevant table from the paper. Positive coefficients mean the variable is associated with increased odds of divorce, negative is the reverse:

divtables

Meanwhile, I have written several posts about the planned cuts to the American Community Survey, which include the questions necessary to conduct this analysis: marital events (did you get divorced in the last year) and marital history (how many times have you been married, and when was the last time).

Here’s the information on how to register your opinion on these cuts:

The information about the planned cuts to the American Community Survey is here: https://www.federalregister.gov/articles/2014/10/31/2014-25912/proposed-information-collection-comment-request-the-american-community-survey-content-review-results:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

Comments will be accepted until December 30, 2014.

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So you want to know the Asian divorce rate (save the ACS marital events edition)

One of the most popular posts ever on this blog is about Asian incomes, and especially the variation in average incomes across Asian national-origin groups and cities. Turns out the diverse Asian groups have different divorce rates as well. Why not? It would be nuts to assume the immigrants and their descendants from everywhere from Bangladesh to Japan had common family practices and behavior.

We can figure this out with the American Community Survey (see below; data from which is provided by IPUMS.org). The ACS is big enough to measure divorce rates for Asian subgroups if you pool together a few years — for this I use the 2008-2012 file. For reliability, here I am just showing those groups that had a sample of at least 1,000 married people. And I’m including as separate groups those that selected more than one “race” – Japanese-White, Korean-White, and Filipino-White (you’ll see why I separated them out). Note these are multiple-race individuals, not couples in which the two spouses reported different races.

The national refined divorce rate — divorces per 1,000 people — fell from 20 to 18 at the start of the recession in 2008, before rebounding back up to 19 by 2012. So compare these numbers with about 19 as the national average divorce rate (click to enlarge).

asian divorce rates 08-12.xlsx

Look at that spread! Now won’t you feel a little foolish for even asking what the “Asian” divorce rate is? I leave the interpretation to the relevant experts (media note: but I’ll be happy to speculate if it will help you get your story past the editor).

A further wrinkle: gender. Unfortunately, because the ACS is a household survey, if someone is divorced, the person they divorced is usually not living in the same household, which means we don’t know who they divorced (or even the other spouse’s gender!). Naturally, men and women in the same ethnic group can have different divorce rates to the extent that they marry outside their own group (or get gay divorced at different rates).

So here are the divorce rates for the same groups, but separately by gender. Groups above the line have higher divorce rates for men (Pakistanis, Cambodians), those below the line have higher divorce rates for women (Korean, Vietnamese, Korean-White). Click to enlarge:
asiandivorcegenderBy now you’ve realized what a wonderful treasure-trove of data this is for understanding the incredibly expanding family complexity that pulses all around us. Or, as they say, “Pretty nice data you got there. I’d hate to see something happen to it.” Read on.

Speak up

Last week I reported “millennial” generation divorce rates for 25 metropolitan areas. That’s something you can only get from the very large American Community Survey (because we have no national registry of marital events).

In addition to local areas, however, the vast size of the ACS lets us drill down into very small groups in the population — like small Asian subgroups. For another example, remember the big ruckus over same-sex marriage (you know, homogamy)? I for one would love to have good national data on same-sex marriage patterns when the equality-deniers finally lope back into their caves and the dust settles.

But now the feds are proposing to scrap the marital events (did you get married, divorced, or widowed last year?) and marital history (how many times have you been married, and when was the last time?) questions from the ACS just to save a few million dollars. I hope you’ll help demographic science convince them not to. (In the previous post I listed a bunch of divorce facts we only know because of the ACS questions.)

The information about the planned cuts to the American Community Survey is here: https://www.federalregister.gov/articles/2014/10/31/2014-25912/proposed-information-collection-comment-request-the-american-community-survey-content-review-results:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

Comments will be accepted until December 30.

* Contrary to popular belief, there is no “Asian” category on the Census/ACS form. People are identified as Asian if they pick any of the Asian national origins listed on the “race” question. It’s all pretty American-exceptional. Here is the question, from this form:

acs2010raceq

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Policy, politics, and promoting education versus marriage

Here are three ideas I disagree with:

1. Most people aren’t smart enough to make going to college worth it.

Maybe the best-known purveyor of this idea is Charles Murray, who argued in his 2008 book Real Education (offshore bootlegged copy here) that the “consensus intellectual benchmark” for understanding real college-level material is an IQ of 115, which by definition is only 16% of the population — but probably only 10% are really, truly smart enough (and efforts to improve education at lower levels to prepare more people for college are futile, so don’t even think about spending more on education, because so many people are “born lazy“).

2. We’ve done so much for poor people, it’s time for them to do something for themselves.

This is clearly related to idea #1, insofar as the government spends billions of dollars educating people for college — and subsidizing the colleges they attend — who could instead just work hard and enjoy life in a job requiring less education. But it extends to all kinds of social welfare and anti-poverty programs, as illustrated by the exasperated people in the policy establishment from Brookings to Heritage.

3. Poor women should get married before they have children.

This idea is pervasive, as I’ve discussed many times under the single mothers tag, in response to people blaming single mothers for rising inequality, poverty, low upward mobility, and crime.

One response

Here I offer one response to these three ideas combined. It is possible to increase access to college education, which would increase stability and opportunity for poor people and their children.

In demography, there is a long-running debate over whether there is a biological limit to human longevity, and whether and how fast we may be approaching it. Regardless of the ultimate answer, so far it’s clear that projections based on an inevitable tapering off of increases in life expectancy have repeatedly proved wrong (here’s a review and a recent paper). The same might be said of college education. Here is the trend in 25-34 year-old U.S. civilians with at least a BA degree, from Census numbers:

college completion trends.xlsx

There was more talk about hitting the limits of college access 10 years ago, but even then it was increasing rapidly among women. Yes, we can and should improve college education. But I see nothing here to suggest a ceiling approaching. Still, people keep assuming that expanding education isn’t feasible.

For example, while Murray holds forth on the intelligence limitations among the poor, his colleague Brad Wilcox argues for a cultural press on those with less than a college degree:

They can go down the road of not having marriage as the keystone to their family formation, family life, or we can hold the line, if you will, and try to figure out creative strategies for strengthening marriage in this particular middle demographic in the United States.

In addition to upscaling their deficient values, however, couldn’t we also move them out of the less-than-college category altogether? Not so fast, says Wilcox in a recent interview:

On the education front, the U.S. spends a ton of money and devotes unparalleled attention to college. But the reality is that only one-third of adults, even today, will get a college degree, a B.A. or B.S. We can do a lot better in both funding and focusing on vocational education and apprenticeship training.

Really, America, be reasonable: Our “ton of money” is “unparalleled.” Don’t set your sights too high. Who do you think you are, anyway, Poland (college graduation rate: 53%), Ireland (46%), or Portugal (41%)? From OECD numbers:

college graduation rates OECD.xls

I know expanding college access (the real kind, not the for-profit kind) suggests expanding a broken financial aid system, and the economic returns aren’t guaranteed, but for my purposes it’s not just about getting a better job. People who go to college — and those who know they are going to go to college before they do — usually delay having children, not because some moralizing think tank tells them it’s wrong, but because they’re trying to rationally sequence their lives. Of course, married couples have relatively low poverty rates, but even for parents who aren’t married, higher education sure helps. From the American Community Survey via IPUMS.org:

H8.xlsx

Trying to get more poor people to get married is both offensive and useless. But increasing access to higher education is both uplifting and useful. The choice between early birth with low education and later birth with higher education is not hard to make, but unless it’s feasible — with a readily apparent, practical, path toward completion — there is no choice to make.

The increase in college education has already helped keep child poverty levels from rising as marriage rates have fallen. Among women old enough to have finished college (ages 22-44) the percentage of babies born to mothers with college degrees (married or not) has increased from 23% in 1990 to 35% in 2010. From the Current Population Survey via IPUMS.org:

H8.xlsx

Promoting marriage among the poor is a moralizing salve for the self-esteem — and anti-tax self-interest — of pious elites, with zero proven success in helping anybody poor. Promoting access to higher education is good policy and good politics.

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Top 25 cities for Millennial divorce (save the American Community Survey marital history and events questions edition)

First some news, then the urgent story behind the news.

All marriages and divorces are local. Whether and when people marry is dependent on who they meet and the conditions under which their relationships develop — social, economic, and even political. And divorce depends on local factors as well, such as the likelihood or feasibility of meeting alternative partners, the costs and consequences of divorce, and the norms and laws regulating divorce. (The same is true for forming and ending non-marital relationships, but those are harder to measure and their dynamics are different).

The Millennial Divorce Capital

So, I know the question you’re dying to have answered is: Where do Millennials get divorced? This question is so compelling that I’ve suspended my normal objection to arbitrary generational definitions, and let Mellennials be defined as anyone born in 1980 or later — so this is the divorce rate among people roughly ages 15 to 31 in the 2009-2011 American Community Survey.

Measuring divorce is complicated, because you’ve got a lot of choices. Here are two simple ways: The number of divorces among Millennials occurring in the previous year per 1,000 Millennials in the population (the crude Millennial divorce rate), and the number of those divorces per 100 married Millennials (the refined Millennial divorce rate). Think of the crude rate as the chance of meeting a Millennial who just got divorced walking down the street, and the refined rate as the chance that one of your married friends just got divorced. I’ve ranked them by the refined rate for this table, which we can use to crown Portland, Oregon the Millennial Divorce Capital of the United States (it’s #1 on both measures).

div acs metro demo.xlsx

This is just the 25 largest Millennial population centers, for which we have the most reliable estimates of divorce rates. Nationally, 6.2 out of every 1,000 living Millennials reported getting divorced in the previous 12 months.

It’s complicated

The differences in the two rates I show can be very important. For example, if I expanded the list to the top 50, you would see that the city in which you are most likely to bump into a divorced Millennial at random (spilling your non-caffeinated beverage) is Salt Lake City, where an astonishing 9.7 out of every 1,000 Millennials got divorced in the past year. That’s not because they love divorce, however, it’s because they love marriage. An amazing 34% of Salt Lake City Millennials in 2009-2011 had already been married, compared to just 23% in Divorce Capital Portland.

On the other hand, it’s not just that more married people means more people available for divorce. It’s also the case that early marriage increases the risk of divorce. And more than that, places where early marriage is common have higher rates, even for people who get married at older ages. In this figure I show an adjusted divorce rate (technically, the predicted chance of divorcing in year 5 given marrying at age 23) by the average age at first marriage in each metro area: Divorce is less common in the late-marriage cities*:

div acs metro demo ageat

(Note that, to produce this figure, you need a survey that asks millions of people how many times they’ve been married, the year they most recently got married, and whether they got divorced in the past year. You don’t just type this into a Google search box.)

But wait, I’m afraid it’s more complicated than that. And here I’m moving toward the urgent story behind the news.

People move around. Divorce may occur in a split second, but what demographers call “relationship dissolution” unfolds over time. People move after they divorce, they divorce after they move, and they may even get divorced in places other than where they live. The ACS data I’m using here help sort this out. This divorce incidence measure is based on a survey question, not a legal record. As with all the other questions on the survey (age, race, income, education, etc.), we more or less have to trust the answers people give (some implausible answers are edited out by the Census Bureau). If we really want to understand how and where divorce (or marriage) happens, we need to be creative and careful, and use the best data. And this is the best data.

Here’s a simple illustration. This figure shows the percentage of two groups of Millennials in each state who arrived in the past year: Those who are married, and those who just got divorced. For example, in Oregon, home of the Millennial Divorce Capital, 17% of the divorced Millennials lived in a different state last year. So either moving to Oregon led to their divorce, or their divorce led to an interstate migration. In contrast, only 7% of Oregon’s married Millennial population just got there (click to enlarge):

aca-state-divorce-movers

The red line is the diagonal, so states above the line — most states — have more divorced arrivals than married arrivals (I excluded a few states with few cases in the data). There are, naturally, a lot of fascinating ways you might approach these questions. Which brings me to the urgent news.

Save the American Community Survey marital events and history data

I know from experience that some of you are thinking things like, “Break it down by race!”, “What about gay couples?”, and “What about hypergamy?” If you want those answers, get out your wallets. This information doesn’t just happen, it’s garnered through a massive federal data collection, without which our ability to know ourselves and our society would be severely compromised. And that’s what might be about to happen.

The data I just showed came from the American Community Survey (ACS), the large Census Bureau survey that replaced the “long form” of the decennial census in the 2000s. (The data are wonderfully prepared and distributed by the good people at IPUMS.org.) Unlike a simple national random survey — which is a major undertaking in itself — the ACS uses a sophisticated rotating geographic design that samples from all around the country to gather the information we need for all levels of geographic detail – down to the neighborhood.

Filling out this survey, in 3.5 million households, is estimated to take about 2.3 million hours of the American people’s time and cost a fortune. Now the federal government is reviewing the different parts of the survey looking for unnecessary parts, and they have identified 7 questions that could be cut, including the ones I’ve been using here: marital events (did you get married, divorce, or widowed in the last year), marital history (how many times have you been married, when did you get married most recently), and a couple others. So I’m trying to convince you to submit a public comment urging them not to make the cuts.

Why do we need this?

Believe it or not, there is no national count of marriages and divorces. That’s right, your government cannot tell you how many legal marriages and divorces there are. They used to collect this from every state, but now they don’t. States collect this information, but it’s not standardized, and it’s not collected together. And, even if it were, we wouldn’t be able to analyze it with all the detail I’ve used here — using marriage duration, age at marriage, and other important factors. So, even at the national level, this is all we have.

However, just for national marriage and divorce statistics, we wouldn’t need the ACS. We could use a smaller survey, like the Current Population Survey or others. If they wanted to work out one of those alternatives before canceling these questions, that would be OK for national statistics.

However, for smaller populations — state and local populations, minority groups, gay and lesbian couples — there is no alternative. If we lose these questions on the ACS, we lose the ability to do all that. Unfortunately, there is no legal or legislative mandate to collect this information down to the local level, which is why it’s on the chopping block. It’s just super interesting and important, not legally required. So we need to communicate that up the chain of command and hope they listen.

To help motivate and inform you toward that end, here’s a list of what we would not know about divorce without the ACS marital events and history questions, and then the information for contacting the federal government with your comment. These are just from my blog, I haven’t done an exhaustive search. The point is not that I’ve done so much, but that there is so much of vital importance that we can learn from this data.

  • The refined divorce rate in 2012 was 19 per 1,000 married people.
  • The overall projected divorce rate for couples marrying in 2012 is about 50%. This requires using marriage, divorce, and widowhood incidence to calculate competing risks. You need all the ACS questions for that.
  • We lost about 150,000 divorces during and after the recession. Then divorce rebounded to catch up to its (declining) trend. That’s the result of my analysis published in Population Research and Policy Review, which relied on a model using all the ACS individual data in all 50 states.
  • People with disabilities are much more likely to get divorced than people without. The magnitude of the difference depends on the type of disability.
  • Divorce rates in first marriages are more than three-times as high for Black women as for Asian women in the U.S.
  • The 2008-09 refined divorce rate by state was correlated with Google searches for “colt 45 automatic” at .86 (on a scale of -1 to 1).
  • The 2011 crude divorce rate by state was correlated with Google searches for “vasectomy reversal” at .79.
  • The changing pattern of same-sex marriage across states and local areas. We don’t know this yet, but we should, and we’ll want to, and the ACS is the only way we’ll be able to.

Speak up

The information about the planned cuts to the American Community Survey is here: https://www.federalregister.gov/articles/2014/10/31/2014-25912/proposed-information-collection-comment-request-the-american-community-survey-content-review-results:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

Comments will be accepted until December 30.

* Here’s the mixed-effect multilevel regression testing the relationship between average age at marriage (meanagemarr) and odds of divorcing, controlling for age at marriage and duration of marriage, for 262,269 married people in 283 metro areas:

acs-metro-div-reg

If you want to see serious research into the effects of age at marriage, local age at marriage, and religion, on divorce, this paper by Glass and Levchak is the right place to start.

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Repeated misinterpretation is not causation

The other day I criticized Brad Wilcox and Bob Lerman for claiming that increasing marriage would reduce inequality. In that post I passed up the chance to reinforce a lesson about misleading claims regarding selection and unobserved factors by members of the right-wing family social science community.

Photo by Jonathan Tellier from Flickr Creative Commons.

Which comes first, social advantages or marriage?
Photo by Jonathan Tellier from Flickr Creative Commons.

Passages like the following have become standard for Wilcox when he makes overblown claims regarding the benefits of marriage. Here is the latest:

Notwithstanding this report’s extensive data analysis, we do not claim that the associations we find among family structure while growing up, marriage as an adult, and economic outcomes are definitively causal. … Even after netting out the effects of many observed differences among individuals, both marriage and economic well-being may be the result of some third factor, such as unobserved differences in personality or character … Moreover, most of the evidence in this report is descriptive and does not derive from a causal model. For all these reasons, this report cannot definitively assert that adolescent family structure and adult marital status have a causal impact on individual and family economic well-being. …  Nevertheless, the evidence is widespread and consistent enough to suggest strong, causal positive roles for being raised in an intact family and for current marriage on a range of important economic outcomes for the average American.

So this is the criteria for evaluating whether selection and omitted variables are a problem — whether the “evidence is widespread and consistent enough”? No. The volume of evidence is irrelevant; what matters is what it means. If people with various kinds of advantages and privileges are more likely to get and stay married, then research that fails to take that into account will always show married people doing better than people who aren’t married. The evidence will be “widespread and consistent,” and that does not mean it means marriage is the cause of their advantages.

I think that repeating this over and over, having been corrected on it many times, qualifies as demagoguery, or the practice of a demagogue, as the OED defines it:

…a political agitator who appeals to the passions and prejudices of the mob in order to obtain power or further his own interests; an unprincipled or factious popular orator.

It’s appealing to passions and prejudices, and taking advantage of the credulity of the friendly media — and abusing their status as professional researchers, in Wilcox’s case with academic tenure — in the service of their own ideological and material interests.

I made this argument in a previous post, which demonstrated widespread and consistent evidence for an assertion that is probably not true because of obvious selection bias: Cars improve child health. There is no end to the ways you can demonstrate this pattern (and I controlled for income, to show how far that gets you), but the ubiquity of the evidence does not correspond with the veracity of the claim that the relationship is causal.

Real research addendum

If, unlike Wilcox and Lerman, you want to consider this set of issues seriously, I must say I don’t mean to imply that there is no causal effect of marriage on anything. But real research that rigorously takes selection into account usually finds the remaining (probable) effects of marriage are small, if still theoretically important. With earnings, for example, a substantial part of men’s marriage effect is due to selection — that is, men who are either already earning more or who are headed for higher earnings are more likely to get married. For example, this recent study by Christopher Dougherty finds that men’s earnings start rising on average more than five years before marriage. You could attribute this to the cultural power of marriage if you think it shows men getting their act together and earning more because they want or plan to get married, but there’s no evidence for that over the interpretation that marriage is a windfall that follows from other advantages – such as physical or mental traits or health, or social advantages such as rich networks of job and relationship connections (none of which is measured directly in the kinds of data we have for these purposes). Alexandra Killewald and Margaret Gough report a similar pattern, although it’s not the focus of their paper. Killewald, in another good piece, does a lot of selection checking for the positive effect of married fatherhood on men’s earnings, before coming down on the side of  a causal story. But her effect, although important, is not anywhere near large enough to lift poor people out of poverty or substantially reduce income inequality in the unlikely event that marriage increased among low-income parents. That’s a different discussion. As I argued the other day, even if marriage is good for married people, those who aren’t married are very unlikely to get the same benefit from marrying that we observe among the married population. They’re different people with different (mostly fewer) assets to capitalize on in marriage.

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Turns out marriage and income inequality go pretty well together

Diatribe first, then critique.

Brad Wilcox and Bob Lerman have a new report arguing, among other things:

Had marriage rates not declined substantially among parents, many more families would have attained middle-class incomes, and the inequality across families would have increased at a slower rate.

It’s well established that falling marriage rates are contributing to family income inequality. However, increasing inequality is not an inevitable result of low marriage rates. In general, among rich countries, higher marriage rates are associated with higher levels of income inequality. The USA is a clear outlier here:

marriage-inequality2

It’s possible marriage increases income inequality in general. It’s also possible that people don’t get married as much when they’re not worried about inequality. Regardless, this shows high marriage rates are quite compatible with high inequality.

Falling marriage does contribute to rising inequality in the USA, because of how it’s manifesting: increasing selectivity in marriage, so that richer people are getting and staying married more; and increasing social class endogamy, so that there are more two-high-income families lording over more one-low-income families. And all of that is exacerbated by widening underlying inequality, with high-end incomes pulling away from low-end incomes, relatively unchecked by income redistribution.

One obvious solution is to take money away from married high-income people and give it to single low-income people. With all the benefits that married people get — many of them through no special effort of their own, but rather as a result of their social status at birth, race, health, good looks, legal perks, or lucky breaks – it seems reasonable to tax marriage, like a windfall profits tax, or an inheritance tax, or a progressive income tax. But, if you’re squeamish about taxing something “good” like marriage, then just taxing wealth a little more would accomplish much the same thing. This elegant solution would decrease inequality, increase well-being for poor people, and equalize life chances for children (who are the future, I believe). In other words, it’s out of the question.

A second, less-obvious (but more-often mentioned) solution is more marriage. Low-income single people could become high-income married people. Or, failing that (which they would) they could settle for becoming low-income married people. Besides the fact that efforts to promote marriage have been a complete failure, would this even make poor single people and their children better off?

The family science right-wing establishment says Yes. To the poor singles, they say: “See how well married people are doing? Get married and you’ll be like them (also: you won’t get raped so much, you sluts.)” To their rich donors and political allies, they say, “Make them earn their benefits by demonstrating their moral fiber and manning up.” The welfare reform attempted this, and successfully forced many single mothers into the labor force in the cause of character development  – but it failed in its goal of marrying them off.

So more marriage is the new agenda — and the family right has a plan that leads inexorably to success (for them): either by successfully raising marriage rates among the poor (extremely unlikely), or by justifying the continued denial of basic welfare to the poor and shoring up the political case against economic redistribution (extremely likely).

A few notes on the first part of their report

Question: Why should we think the unmarried people would get the same benefits from marriage that currently married people do? If marriage is becoming increasingly selective, then you can’t assume the benefits observed among actually married people would be reaped by those who have been left out (or opted out) of the increasingly stringent marriage selection process. They may not have the assets that lead to marriage benefits — skills of many kinds, wealth, social networks, and so on.

Wilcox and Lerman say family income would have risen more — and there would be less inequality — if more people were married, because married couple incomes rose faster than average. They show this:

willerfaminc

Setting aside the completely misleading use of an area chart, and the gruesome y-axis truncation, this shows that married-parent families have had faster than average income growth. One obvious reason for this is women’s rising labor force participation, at least into the 1990s. That has a big effect on income at the median, which is the line this is showing for each group (though the area form makes it look like it’s some kind of distribution). Rising income at the median would reduce income inequality. The fact that single-parent families are dragging down the average contributes to growing inequality and a stagnant overall median.

But the top is where most inequality is being generated. Looking at the top will help us see not just growing inequality, but also why getting poor people to get married won’t help them as much as Wilcox and Lerman think it would. Let’s add the 90th and 10th percentiles to the married parent income trends. My figure shows that the married parent family’s 90th percentile’s income has risen 39% since 1979, while the median has risen 14%. But the 10th percentile’s income has fallen 12%.

married couple ineq.xlsx

So, if poor single people finally get with it and start getting married, which married parents are they going to look like?

The chart shows dramatically increasing inequality among married-couple families. Pouring more married couples into the bottom of the distribution doesn’t seem likely to fix that. And, as Jordan Weissman pointed out, the family structure story has nothing to do with the huge rise in incomes in the top 1% and .1%, which are central to the inequality story.

Till now I’ve skirted some thorny technical issues to make a comparison comparable to Wilcox/Lerman’s data. But assessments of family income inequality are tricky. Marrying two low earners creates one family household with twice the income. That shows up as a rise in incomes per family, but what is the real gain? They get economies of scale, but most descriptions (like Wilcox/Lerman’s) don’t take that into account. And the children might increase their consumption from greater access to the second income, but that’s hidden within the family black box.

To see how changes in family income distributions affect children, it’s useful to use a family size adjustment. I like one in here that counts kids as seven-tenths of an adult, and scales the family income by .65. (So you just divide family income by this: [(adults+(.70*kids)).^65].) Now you can track children’s cash on hand much better. I also prefer to use household rather than family income and composition, because the Census definition of families is narrow. In the charts so far, for example, parents’ cohabiting partners’ income is not included.

So here is the inequality trend for children — using the Gini index for needs-adjusted household income (code here) — by parents’ marital status:

kid-gini-1980-2012.xlsx

This shows that the increase in family inequality has been much more dramatic for married-couple families than single-parent families. That’s those high-income couples pulling away from the middle and the bottom. On the other hand, inequality has been and remains higher for single-parent families. Note that the inequality for all children is not just the average of the two other lines, because it also includes the inequality between married-couple and single-parent families.

So moving people from single to married would have reduce inequality more in 1980 than now, but just on composition it might still help if it boosted cash per kid through access and efficiency. Whether that benefit would outweigh the costs is not clear. If people not married yet aren’t just like the people who are — they may have lower skills and resources of various kinds, for example — marriage might not facilitate those transfers. Plus, it’s only good if the people want to be married.

Anyway, point is, married-couple families are doing pretty well at increased income inequality all by themselves.

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