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 needs-adjusted household income — 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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Data snapshot: Married before

Among newlyweds in the United States, 30% have been married before. Here’s the breakdown by state (click to enlarge):

married-before-2012-marriages

 

Here’s a list of states and DC, from highest to lowest percent married before:

married-before-2012-marriages-table

And here is the Google search most highly correlated with this pattern: Kerrelyn Sparks (correlation = .83):

kerrelynsparks

The top 100 correlated searches is shot through with romance and fantasy novels: Lynsay Sands, romance series, Sherrilyn Kenyon, vampire book, fever series, Jeaniene Frost.

Coming soon: Crouching Tiger, Forbidden Vampire (and your next marriage?):

crouching

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9 uses of “the ways in which” that should be replaced by “how”

Searching through sociology for the ways in which is literally like shooting ducks in a barrel (easy).

Shooting Ducks in a Barrel

For this post I made sure to include some giants in the field, and major journals, to underscore the ways in which this problem is not limited to the over-wrought fringe.

The “how” rule is not universally applicable. In some cases “the ways” would be a better replacement. But in these 9 examples “how” is enough.

Reproducing Stories: Strategic Narratives of Teen Pregnancy and Motherhood

Within this narrative, there is no space for negotiating or even acknowledging the ways in which poverty, racism, and sexism affect the lives of young mothers.

Social Network Analysis: An Introduction

… her research showed the importance of ties across kin groups and households and the ways in which the strength of membership within families varied…

The New Institutionalism in Organizational Analysis

Whereas economists and political scientists offer functional explanations of the ways in which institutions represent efficient solutions to problems of governance, sociologists reject functional explanations and focus instead on the ways in which institutions complicate and constitute the paths by which solutions are sought.

The Transformation of Intimacy: Sexuality, Love, and Eroticism in Modern Societies

She found major differences between the ways in which the boys discussed sex (they did not often speak of love) in the course of her lengthy interviews with them and the responses of the girls.

Practicing Intersectionality in Sociological Research: A Critical Analysis of Inclusions, Interactions, and Institutions in the Study of Inequalities

A good example of this can be found in Hays’s (2003) discussion of the ways in which college students are prone to the drug use and sexual activity that are so strongly condemned among poor teens.

The Division of Labor in Society (Introduction)

The new introduction to this edition takes a different tack, focusing on the ways in which this work is of present-day sociological interest.

Video Game Culture, Contentious Masculinities, and Reproducing Racialized Social Class Divisions in Middle School*

Recent feminist theorizing on relations between gender and technology emphasizes the ways in which the two mutually shape each other.

Pattern Variables Revisited: A Response to Robert Dubin

The Editor’s invitation to comment on his paper has given me the opportunity to work out an overdue clarification of the ways in which Model II builds on and goes beyond, rather than replaces, Model I.

Gastronationalism: Food Traditions and Authenticity Politics in the European Union

I use Brubaker’s (1996:10) broad definition of nationalism — a set of idioms, practices, and possibilities available in cultural and political life, delimited by social or physical boundaries — to consider the ways in which a nation’s people are defined, or self-define, as a distinct group.

*This was one of eight pieces in the Summer 2014 issue of Signs that came up in my search. For a previous criticism of the writing in Signs, see this post.

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Pregnancy discrimination and the gender gap, involuntary job choice edition

From Rachel Swarns at the New York Times comes the story of a woman, Angelica Valencia, fired from her $8.70-an-hour produce packing job because her doctor said she couldn’t work overtime because she was three months into a risky pregnancy. There actually is a new law on her side, but her employer somehow didn’t get around to notifying her of her right to reasonable accommodation.

Before reading my comment on this, why not check out this new video from the chapter on gender in my book. The video accompanies a much more compelling version of this graphic, showing the gender composition of some occupations, calculated from the American Community Survey:

figures 4-6.xlsx

Count that gender gap

OK, Back to Angelica Valencia. I’m not an expert on pregnancy discrimination, but I want to use this to comment on how we look at the gender gap in pay. The Census Bureau reports on the gender gap this way:

In 2013, the median earnings of women who worked full time, year-round ($39,157) was 78 percent of that for men working full time, year-round ($50,033).

Critics complain that this doesn’t account for occupational choice, time out of the labor force, and so on. As Ruth Davis Konigsberg sneeringly put it in Time:

Women don’t make 77 cents to a man’s dollar. They make more like 93 cents, as long as they don’t major in art history.

And Hanna Rosin helpfully explained:

Women congregate in different professions than men do, and the largely male professions tend to be higher-paying.

So what does the story of Angelica Valencia pregnancy tell us (besides the pitfalls of majoring in art history)? Valencia may end up winning some back pay in a lawsuit. But let’s assume someone just like her didn’t, and ended up instead in a lower-paying job that doesn’t like overtime, such as at McDonald’s. If we insist on statistically controlling for occupation, hours, job tenure, and time out of the labor force in order to see the real wage gap, people like Valencia may not show up as underpaid women — if they’re paid the same as men in the same jobs, holding constant hours, job tenure, and time out of the labor force. So the very thing that makes Valencia earn less — being fired for getting pregnant — disappears from the wage gap analysis. Instead, the data shows that women take more time off work, work fewer hours, change jobs more often, and “choose” less lucrative occupation.

Sure, a lot of women chose to get pregnant (and a lot of men choose to become fathers). But getting fired and ending up in a lower paid job as a result is not part of that choice (and it doesn’t happen to fathers). The overall difference in pay between men and women, which reflects a complicated mix of factors, is a good indicator of inequality.

For background on the motherhood penalty in wage, you might start here or here (including the sources citing these).

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How (and how much) academics talk about inequality, in one chart

Reader advisory: When I say “in one chart,” I never really mean it.

Updated with new chart at the end.

Because someone asked, here is the article count from Web of Science (an academic journal database with emphasis on science), showing the frequency of articles (of all types) according to the inequality-related phrases in their titles. This is obviously not an exhaustive list of work on these subjects, but I did want to show all combinations of race, class, and gender (click to enlarge).

strat terms.xlsx

  • “Social inequality” now completely dominates, but it once was second to “social stratification.”
  • The most common of the three-word combinations is “race, class, and gender.”
  • “Gender, race, and class” has almost always been second.
  • “Gender, class, and race” made a run in the late 1990s, but has since faded.

I’ve written a little more about language and intersectional concerns here.

Update:

Don Tomaskovic-Devey sent along this figure, which shows newspaper articles using inequality related terms. The dotted line shows articles with rich, wealthy, top 1%, top one %, while the solid line shows income inequality. He suggests the dotted line may reflect an Occupy Wall Street effect, while the solid line shows the Thomas Piketty framing process:

lexisineq

 

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Video series debut: The Story Behind the Numbers

The wonderful animators at Kiss Me I’m Polish, who did the design and graphics for my book The Family, are producing short videos based on an infographic series in the text called The Story Behind the Numbers. These are less than 2 minutes long and use just a few numbers, intended to spur reflection and discussion in conjunction with the details in the book, with narration by me.

The first one is available now. From chapter 7, “Love and Romantic Relationships,” we have a one-minute animation called, “Race and ethnicity divides college students’ dating lives.” In the book I took numbers from Elizabeth Aura McClintock’s 2010 paper in Journal of Marriage and Family and reported on the relative frequency of within-race/ethnicity dating among students at Stanford University. It’s fascinating to me how strong the matching is in such an elite setting, where you might expect gradations of social status to matter less.

The graphic in the book represents the whole table of matches relative to the proportion of each group in the dating pool.

As the rest of series comes out I will link them from the Teaching page.

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Life expectancy update, disparity edition

The good news is that U.S. life expectancy is at a record high, 78.8 as of 2012.

What about life disparity — the inequality in life expectancy? With the economic crisis and rise in income inequality, it would be great to know. However, the National Center for Health Statistics hasn’t released detailed life tables with data more recent than 2008, so I can’t yet update the data for the analysis I did last year, so here it is reposted instead:

Life Expectancy, Life Disparity

Reposted from July 23, 2013

In 2008 the life expectancy at birth in the U.S. was 78.1. That means that if a group children born in 2008 lived every year of their lives exposed to the risks of death observed in 2008, their average lifespan would be 78.1 years. But those who made it to age 60 would live an average of 22.7 more years, for a total of 82.7. And those who live to age 99 would live an average of 2.4 more years, for an average of 101.4.

So “life expectancy” as commonly used is not a prediction of how long today’s babies will live — since we hope the future is better than living 2008 over and over — and it’s not a prediction of how long your elderly loved ones will live.

Life disparity

Life expectancy — for any age — is a measure of central tendency: the average number of years of life remaining. And so there is a dispersion around that mean. That dispersion is inequality. A very nice article in the open-access journal BMJ Open, by James Vaupel, Zhen Zhang and Alyson A van Raalte, describes the measure of life disparity. It’s complicated, but a neat tool.

Life disparity is the average number of years people are expected to live when they die. For example, in the U.S. in 2008 an infant who died on the first day of life died 78.1 years early. And a 78-year-old who died, counterintuitively, died 10 years early (since the life expectancy at 78 is 10). To understand what this measure means, consider that if everyone died at exactly 78.1 years of age, life expectancy would be unchanged but life disparity would be 0. On the other hand, the greatest life disparity would occur if all early occurred at age 0.

Life disparity and life expectancy usually go together. That’s because reducing early deaths has the biggest effect on both measures. Here is the cool figure from that paper:

The association between life disparity in a specific year and life expectancy in that year for males in 40 countries and regions, 1840–2009. The black triangle represents the USA in 2007; the USA had a male life expectancy 3.78 years lower than the international record in 2007 and a life disparity 2.8 years greater. The brown points denote years after 1950, the orange points 1900–1949 and the yellow points 1840–1900. The light blue triangles represent countries with the lowest life disparity but with a life expectancy below the international record in the specific year; the dark blue triangles indicate the life expectancy leaders in a given year, with life disparities greater than the most egalitarian country in that year. The black point at (0,0) marks countries with the lowest life disparity and the highest life expectancy. During the 170 years from 1840 to 2009, 89 holders of record life expectancy also enjoyed the lowest life disparity.

The association between life disparity in a specific year and life expectancy in that year for males in 40 countries and regions, 1840–2009. The black triangle represents the USA in 2007; the USA had a male life expectancy 3.78 years lower than the international record in 2007 and a life disparity 2.8 years greater. The brown points denote years after 1950, the orange points 1900–1949 and the yellow points 1840–1900. The light blue triangles represent countries with the lowest life disparity but with a life expectancy below the international record in the specific year; the dark blue triangles indicate the life expectancy leaders in a given year, with life disparities greater than the most egalitarian country in that year. The black point at (0,0) marks countries with the lowest life disparity and the highest life expectancy. During the 170 years from 1840 to 2009, 89 holders of record life expectancy also enjoyed the lowest life disparity.

Countries at the bottom left (0,0) have both the world’s highest life expectancy and the lowest life disparity in the world for that year, which occurred 89 times over 170 years. Countries below the diagonal have relatively low life disparity given their life expectancy; those above the diagonal (like the U.S.) have higher-than-expected life disparity for their level of life expectancy. In our case that reflects the fact that we do a pretty good job keeping old people alive, but let too many young people die.

U.S. improvement

The good news is that life expectancy is increasing in the U.S. (and most other places), and that the inequality between Blacks and Whites is getting smaller, as reported by the National Center for Health Statistics. That is, the Black-White inequality in average expectation of life at birth has shrunk.

The mixed news is that life disparity is much higher for Blacks than Whites — but that gap is falling as well. Here are those numbers for 1998 and 2008 (I did the life disparity calculations from this and this, and will happily share the spreadsheet). Click to enlarge:

expectancydisparity

So Black deaths are more dispersed than White deaths: 14 and 13 for males and females, compared with 12 and 11. For comparison, the Swedish female life disparity is 9. What does a higher disparity mean? Generally, a larger share of early deaths. That’s why the race gap in life expectancy at birth is greater than the race gap in life expectancy at older ages — average 65-year-old Whites and Blacks have more similar life expectancies than do infants.

Why is life disparity more interesting than life expectancy alone, and how does this help explain Black-White inequality in the U.S.? For one thing, high life disparity indicates either relatively unhealthy or dangerous living conditions at younger ages. So it’s partly a measure of the quality of life. Vaupel et al. add:

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. Moreover, equity in the capability to maintain good health is central to any larger concept of societal justice.

I think what they say about differences between countries would apply to differences between groups within a society as well.

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