Tag Archives: income

Global inequality, within and between countries

Most of the talk about income inequality is about inequality within countries – between rich and poor Americans, versus between rich and poor Swedes, for example. The new special issue of Science magazine about inequality focuses that way as well, for example with this nice figure showing inequality within countries around the world.

But what if there were no income inequality within countries? If everyone within each country had the same income, but we still had rich and poor countries, how unequal would our world be? It turns out that’s an easy question to answer.

Using data from the World Bank on income for 131 countries, comprising 91% of the world population, here is the Lorenz curve showing the distribution of gross national income (GNI) by population, with each person in each country assumed to have the same income (using the purchasing power parity currency conversion). I’ve marked the place of the three largest countries: China, India, and the USA:

lorenza1

The Gini index value for this distribution is .48, which means the area between the Lorenz curve and the blue line – representing equality, is 48% of the lower-right triangle. (Going all the way to 1.0 would mean one person had all the money.)

But there is inequality within countries. In that Science figure the within-country Ginis range from .24 in Belarus to .67 in South Africa. (And that’s using after-tax household income, which assumes each person within each household has the same income. So there’s that, too.)

The World Bank data I’m using includes within-country income distributions broken into 7 quantiles: 5 quintiles (20% of the population each), with the top and bottom further broken in half. If I assume that the income is shared equally within each of these quantiles, I can take those 131 countries and turn them into 917 quantiles (just assigning each group its share of the country’s GNI). These groups range in average income from $0 (due to rounding) in the bottom 10th of Bolivia and Guyana, or $43 per person in the bottom 10th of the Democratic Rep. of Congo, up to $305,800 per person in the top 10th of Macao.

To illustrate this, here are India, China, and the USA, showing average incomes for the quantiles and the countries as a whole:

lorenza2

This shows that the average income of China’s top 10th is between the second and third quntiles of the US income distribution, and the top 10th of India has an average income comparable to the US 10-19th percentile range. Obviously, this breakdown shows a lot more inequality.

So here I add the new Lorenz curve to the first figure, counting each of those 917 quantiles as a separate group with its own income:

lorenza3

Now the Gini index has risen a neat 25%, to an even .60. Is that a big difference? Clearly, between country inequality — the red line — is vast. If every country were a household, the world would be almost as unequal as Nigeria. In this comparison, you could say you get 80% of the income inequality to show up just looking at whole countries. But of course even that obscures much more, especially at the high end, where there is no limit.

Years ago I followed the academic debate over how to measure inequality within and between countries. If I were to catch up with it again, I would start with this article, by my friends Tim Moran and Patricio Korzeniewicz. That provoked a debate over methods and theory, and they eventually published this book, which argues: “within-country analyses alone have not adequately illuminated our understanding of global stratification.” There is a lot more to read, but their work, and the critiques they’re received, is a good place to start.

Note: I have put my Excel worksheet for this post here. It has the original data and my calculations, but not the figures.

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The War on Poverty at 50: Swimming against the tide

I have written a brief report for the Council on Contemporary Families, released today, for the 50th anniversary of the War on Poverty declaration by Lyndon Johnson: Was the War on Poverty a Failure? Or Are Anti-Poverty Efforts Swimming Simply Against a Stronger Tide?

The figures include this one, showing changes in earnings by gender and education over the past two decades:

fig5-earnings

In between figures and statistics, key points:

  • The suite of social welfare programs introduced or expanded in that era moved millions of people out of poverty and improved the lives of millions more who remained income-poor.
  • In recent years, however, poverty has been rising once again.
  • Focusing on children, our most vulnerable citizens, highlights both the strengths and the limits of our current anti-poverty programs.
  • The high rates of child poverty in America highlight a basic feature about the U.S. system, and its principal vulnerability: ours remains predominantly a market-based system of care.
  • And the multiplication of low-wage jobs that has come with widening inequality is a formidable obstacle to reducing poverty today.
  • Despite frequent claims to the contrary, that government can play a key role in reducing poverty.

The report is paired with an excellent piece by Kristi Williams: Promoting Marriage among Single Mothers: An Ineffective Weapon in the War on Poverty? Her bullet points are:

  • The rapid rise in nonmarital fertility is arguably the most significant demographic trend of the past two decades.
  • How can we improve the lives of the growing numbers of unmarried mothers and their children? So far, a dominant approach has been to encourage their mothers to marry.
  • The flaw in this argument is the assumption that all marriages are equally beneficial.
  • Our recent research adds to the growing body of evidence that promoting marriage is not the answer to the problems facing single mothers and their children.
  • A more promising approach is to focus on reducing unintended or mistimed births.
  • If the goal of marriage promotion efforts was truly to lower poverty rates and improve the well-being of unmarried parents and their children, then it is time to take a different approach toward this goal.

Kudos and thanks to the Council on Contemporary Families (of which I’m a board member) for putting this together, especially Stephanie Coontz and Virginia Rutter, who did the work of coordinating, editing, and distributing the reports.

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Race, class, and gender in one chart (just kidding)

You can’t do it (or much of anything) in one chart.

A colleague reports that a college student wrote to her:

The wage gap itself shows white women earn more than more than black men; that is to say my race is a greater determinant of wage than is my gender.

Her link was to this pretty confused post by Derek Thompson, which I’m not going to get into except to show this figure he made:

thompson-earnsThis shows earnings, not taking into account education. Later he shows earnings by education, not taking into account gender. Not wrong, but you can see the confusion it caused for the student quoted above. If she finishes college, she will be in a group whose earnings hierarchy is more by gender than by race, as I show in this figure I made from 2011 American Community Survey data from IPUMS:

earns-race-gen

This shows that Black men and White women — full-time, year-round, 25-54 — have the same median earnings if you don’t take into account education. Within each education group, however, Black men earn more. Who gets to be in the full-time, year-round population (instead of dead, incarcerated, unemployed or underemployed), of course, is a big issue. I can’t show that in one chart.

 

 

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Gender Gap Statistic Gets it from All Sides

I was very happy to write this post for the Gender & Society blog, where it first appeared.

The “gender gap” has gotten a lot of attention this fall. This hard-working statistic is as often abused and attacked by antifeminists as it is misused and misunderstood by those sympathetic to feminism. But it is good for one thing: information.

The statistic is released each year with the U.S. Census Bureau’s income and poverty report. This year they reported 2012 annual earnings as recorded in the March 2013 Current Population Survey (CPS): the median earnings of full-time, year-round working women ($37,791) was 76.5% of men’s ($49,398). That is the source of (accurate) statements such as, “Women still earned only 77 cents for every dollar that men earned in 2012.”

In the category of reading too much into a single number, I put this data brieffrom the Institute for Women’s Policy Research, which helpfully informed us that, “Most Women Working Today Will Not See Equal Pay during their Working Lives.” Here is the chart:

Cohen_image1

Of course, real life projections are not usually made by simply extending a trend with a straight line. The future is not that easy to foresee. If you did want to fit a line to that trend, however, the bad news is that it’s not a straight line that fits, but a third-order polynomial (which improves the measure of fit from .90 to .98). And projected this way, the trend will never reach equality:

Cohen_image2

Fortunately, curvy lines are often no better at predicting the future than straight ones.

Flog that stat

Some defenders of equal pay for women misstate the statistic, as President Bill Clinton did when he said:

“How would you like to show up for work every day, but only get to take home three out of every four paychecks? … if you get paid 75 percent for the same kind of work, it’s as if you were only picking up three paychecks, instead of four, in four pay periods. The average woman has to work, therefore, an extra 17 weeks a year to earn what a similarly-qualified man in the same kind of job makes.”

The mistake here is that he said “same kind of work” and “similarly-qualified man.” That led to the screaming headline on the American Enterprise Institute website, “Still Hyping the Phony Pay Gap.”

But he also went on to say:

“Yes, some of this can be explained — by differences in education, experience and occupation. But even after you make all those adjustments, there is still a very significant gap.”

So he belatedly acknowledged the complexities, and that second statement is true.

Oh, and that exchange occurred in 2000. How far we’ve come.

When Clinton, ever a repository for handy statistics, essentially repeated his statement on September 29 of this year, he played right into the screaming headlines of today’s anti-feminists, including Hanna Rosin, who declared, “I feel the need to set the record straight” in a piece she titled, “The Gender Gap Lie.” Kay Hymowitz also has written extensively to debunk the gender gap, arguing that it mostly results from women’s choices – the educations and occupations they choose, the hours they choose, the “mommy track” they prefer. (Naturally, sociologists are very interested in that construction of “choice.”)

There is no single number that can tell us the true state of gender inequality. But if you had to pick one, this one is pretty good. That’s because it combines factors that affect employment levels, work experience, occupational distributions, and pay discrimination – to give a sense of the place of the typical worker. As long as that number is not zero, there is a gender inequality problem to discuss, whether it results from socialization, family demands, educational sorting and tracking, hiring and promotion discrimination, or pay discrimination – and the details depend on further scrutiny.

Take your pick

We could use a different gender gap. The next figure shows some gender gaps for earnings among full-time, full-year workers in the 2011 American Community Survey (ACS). I’ve cut the sample to compare men and women by education, long-hours status (50+ hours), parenthood (no co-residential children) and marital status (never married). As you can see, the gaps range from a low of 65% for women with an MA degree and no children all the way up to 93% for never-married professional degree or PhD holders with no kids. Generally, the 50-hour limit doesn’t help, but marriage and children make a big difference.Cohen_image3

Another way of restricting the data to consider real-world gaps is shown in the next figure. Here, from the same data, I’ve taken full-time, full-year workers who have a bachelor’s degree and no further education, and sorted them by college major. So these gaps account for educational specialization, and reflect – in addition to any hiring and pay discrimination – occupational sorting within those categories, as well as other educational processes such as university prestige and school performance. The gaps range from 69% for transportation science majors all the way up to 94% for architecture majors.

Cohen_image4

Finally, we might look more closely at occupations. In this figure, again from the 2011 ACS, I have sorted 484 detailed occupational categories according to the median earnings wage gap within them, for full-time, year-round workers. The y-axis shows the cumulative percentage of women who work at or below each level as you move from less equal occupations on the left to more equal ones on the right. I’ve labeled the 25th, 50th and 75th percentile, showing, for example, that half of women work in occupations with a wage gap of 83% or worse.Cohen_image5

Although this figure shows inequality within occupations, it is occupational segregation itself, which extends the gender division of labor into the labor market, that lies behind much of the gender gap – representing the culmination of historical and contemporary processes of allocating people to tasks.

In summary, the wage gap clearly is smaller in some situations than others – smaller for workers without children, especially if they’re never married, smaller for some college majors and in some occupations. Each of these comparisons tells us something different. (More complete statistical analysesthat control for several factors at once create counterfactuals that don’t actually exist, but that do help us isolate important dynamics behind the gender gap.)

We mustn’t read into these numbers more than they can tell us. None of the numbers I’ve shown can discern occupational choice from employer discrimination, for example; or the cumulative effects of time out of the labor force versus discrimination in previous jobs. But the gender gap numbers are measures of inequality. And as long as we are accurate and responsible in our use of these numbers, they are useful sources of information.

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More married mothers earn more than their husbands

For this Washington Post article by Brigid Schulte, I did some calculations that allowed her to add, “In a trend accelerated by the recent recession” to the first sentence. When you line up the numbers this way — percentage of married mothers with children present who have higher incomes their husbands — there was a steep acceleration:

pew-post-trendSource: My calculation from Census and American Community Survey data from IPUMS.

My explanation for this was:

“The decade of the 2000s witnessed the most rapid change in the percentage of married mothers earning more than their husbands of any decade since 1960,” said Philip Cohen, a University of Maryland sociologist who studies gender and family trends. “This reflects the larger job losses experienced by men at the beginning of the Great Recession. Also, some women decided to work more hours or seek better jobs in response to their husbands’ job loss, potential loss or declining wages.”

The trend was reported by Pew Research in this report, titled “Breadwinner Moms,” which wrote:

A record 40% of all households with children under the age of 18 include mothers who are either the sole or primary source of income for the family, according to a new Pew Research Center analysis of data from the U.S. Census Bureau. The share was just 11% in 1960.

I just did the married mothers earning more, and added the data from the years between 2000 and 2011, to show the recession-period acceleration of the higher-earning mothers. Pew added polling numbers about attitudes toward women’s income, and Schulte added exemplary interviews.

Breadwinning

A wife who earns $1 more than her husband for one year is not the “breadwinner” of the family. That’s not what made “traditional” men the breadwinners of their families — that image is of a long-term pattern in which the husband/father earns all or almost all of the money, which implies a more entrenched economic domination.

However, she can be the “primary breadwinner,” a post-1970s concept acknowledging the rise of secondary breadwinners (usually women) in families. Here is the Google ngrams trend showing appearances of “primary breadwinner” as a fraction of all uses of “breadwinner” since 1920 (click to enlarge):

breadwinner-ngrams

I have previously complained about lumping single mothers together with higher-earning wives to construct an image of “female breadwinners.” That’s partly because the $1-more-for-one-year problem, and partly that I object to using the single-mother trend to inflate descriptions of women’s advancement.

Anyway, it’s hard to capture the trends without overdoing it, but Brigid Schulte and the Pew authors (Wendy Wang, Kim Parker and Paul Taylor) did a nice job.

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Gender wage gap, 2012 edition

Gender inequality stagnation continues apace.

The Bureau of Labor Statistics has released the wage report for 2012, which shows women’s earnings relative to men’s falling back to the 2005 level. The gender breakdown is available here (the content at that link changes when new data come out), and the historical series from 1979 to 2011 is available here.

The usually-reported number is the median weekly earnings of full-time wage and salary workers. These are the gender ratios (women’s earnings divided by men’s):

gender earnings gap 2012

 

Follow the gender inequality tag for updates and previous posts.

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More Women Are Doctors and Lawyers Than Ever—but Progress Is Stalling

Originally posted on The Atlantic.

In the Wall Street Journal last week, Josh Mitchell reported that “Women account for a third of the nation’s lawyers and doctors, a major shift from a generation ago.” The report was triggered by anew analysis of occupations from the Census Bureau, which showed women increased their share of doctor and lawyer by four percent and six percent, respectively, from a decade earlier.

These professional advances mark “very significant progress,” according to feminist economist Heidi Hartmann, and I don’t disagree. Still, when I spoke to Mitchell I suggested he consider a glass-half-empty perspective, which somehow ended up on the cutting-room floor.

My question is, will progress continue? It doesn’t look good. I happen to be a demographer, but you don’t need to be one to see that progress for women in these fields is stalling.

First, look at the degrees earned. This figure uses statistics from the Department of Education and breaks the gender trend in law and medical degrees up by decades. Both trends show slowing progress—a smaller increase in women’s representation each decade—and both peaked (for now) at just under 50 percent female.

cohen_doctorlawyer.png

If half of new doctors and lawyers are women, eventually it should be possible to have professions that are gender-balanced. But don’t hold your breath.

I looked at today’s doctors and lawyers using the 2008-2010 American Community Survey (you can get the data here). Here is the representation of women among full-time and year-round working doctors and lawyers by age. Half of the youngest doctors and lawyers are women, while only one in eight of the oldest are. So as they all age, equal representation should be on the way.

cohen_doctorlawyer2.png

But women are much more likely to drop out of these professions (and others). Among early-career professionals—people ages 25 to 44—who list their most recent jobs as doctor or lawyer, you can see that women are much more likely to be out of the labor force:

cohen_doctorlawyer3.png

With the kind of dropout rates that produce these disparities, we would need much more than 50 percent female in the graduating classes to reach equal representation in these professions.

In Mitchell’s report, the economist Claudia Goldin, who has recently investigated women’s success as pharmacists, argues that the corporatization of medicine has helped women by introducing the concept of work-family balance, and reducing the gender earnings gap—all changes that helped women in pharmacies as well. But I don’t see the evidence that such practices have yet changed the medical industry enough to reduce the gender differences in drop-out rates. And the research evidence shows that explicit diversity policies—with teeth—often are necessary to break the logjam.

And Mitchell’s story did not mention any efforts to reduce the segregation of men and women—especially in medicine—into different specialties. That segregation is a big part of what drives the earnings gap among doctors and lawyers. Here are the median earnings by age for doctors and lawyers, from the same source:

cohen_doctorlawyer4.png

At the peak of that curve—ages 45 to 50—female doctors are earning just 62 percent of men’s median earnings. As they make their decisions about whether to enter the field, and how to specialize, and how to handle their family demands and opportunities, these disparities in representation and rewards come into play. The decisions men and women in these professions make should never be seen as free choices unconstrained or unaffected by the institutional environment.

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