Sociological Images

Cross-posted at Montclair SocioBlog.

In case you wondered about what we in the U.S. pay for health care compared with those unfree unfortunates who suffer under various forms of socialized medicine, here are some graphs from 2009 showing the advantages of what is sometimes called “the best health care system in the world.”

The graphs are from the International Federation of Health Plans. I’ve selected only four — to show the relative costs* of

• an office visit
• a day in the hospital
• a common procedure (childbirth without complications)
• a widely used drug (Lipitor)

You can download all the charts here, but be warned: it gets boring. We’re number one in every chart, at least in this one category of how much we shell out.

Since we have the best health care in the world, this must mean that you get what you pay for. Our Lipitor must be four to ten times as good as the Lipitor that Canadians take.

Hat tip: Ezra Klein.

———————–

*These amounts are what providers are paid by governments or other insurers, not what the patient pays, which in many Eurpean countries is essentially nothing. See the footnotes for the tables in the original document. Or look at the comments on this at Boing Boing, a discussion which is remarkably civil (do they monitor comments?).

Norton Sociology recently posted an image that illustrate differences in rates of imprisonment in a number of countries. Imprisonment rates are influenced by a number of factors — what is made illegal, how intense law enforcement efforts are, preference for prison time over other options, etc. The U.S. does not compare favorably, with 74.3 per 100,000 10,000 of our population behind bars (click here for a version you can zoom in on, and sorry for the earlier typo!):

Here’s a close-up of the breakdown of the U.S. prison population:

Via Urban Demographics.

The Paris School of Economics has posted a database, compiled by Facundo Alvaredo, Tony Atkinson, Thomas Piketty, and Emmanuel Saez, of the distribution of top incomes in a number of nations, with more on the way. Using income tax records, they provide a quick glance at concentration of income among the wealthy over decades (and in some cases, data extends back over a century). As the authors point out, there are limitations to using tax info to measure inequality, so it’s important to be aware of the limitations of this data series. Most obviously, individuals may take steps to hide their income to evade taxes, and the very wealthy may be particularly able to do so through the use of tax havens, etc. Also, tax policies change, so what counts as “income” at one point might not at another. The authors also had to contend with differences in the taxation unit (households vs. individuals) in different countries to provide some level of comparability.

The database allows you to select a country, a time period, and a variable (top 5% income share, etc.), and get a table showing the results for all years in which data were available. Here, for instance, is part of the table for the share of income earned by the top 1% in Singapore:

Of course, this includes only data on income. In many countries, including the U.S., wealth (value of all assets) is significantly more concentrated than income.

Looking at the dataset, you can see patterns over time. For instance, here’s part of the data from the U.S. (notice there are time gaps between the end of each column and the beginning of the next–I was just grabbing some illustrative screencaps), showing how the percent of income earned by the top 0.1% decreased significantly starting in the 1940s, but began creeping up again by the late 1980s and has grown since then:

The site also allows you to create graphs. They provide a comparison of the share of income earned by the top 1% in 2005 in the U.S., Japan, Australia, and France, but you can look at data for individual nations:

It’s worth playing around a bit, but keeping in mind the caveats about what these data do and don’t tell us. Thanks to Shamus Khan for the tip!

A recent post on Boing Boing discussed the newly discovered “rules for jazz performers during the Nazi occupation.”  Jewish and Black people — two groups targeted by the Nazis — were also the primary innovators of jazz music. But even as the German state denigrated jazz, jazz musicians, and swing dancers, Nazi soldiers loved jazz!  How to handle such a contradiction? Rules for playing jazz music: no “Jewishy gloomy lyrics,”  no “Negroid excesses in tempo,” and no “hysterical rhythmic reverses characteristic of the barbarian races.”  

It’s well worth a look, as is this post from 2010 explaining how many groups vilified by Nazis survived the Holocaust by playing jazz for Nazi soldiers…

————————–

I have a favorite historical musician: Django Reinhardt.

Reinhardt was a Roma jazz musician. During World War II both Roma and jazz musicians were targeted by the Nazi regime. Over a million Roma were exterminated for presumed racial inferiority and jazz was believed to combine the worst of Blacks and Jews (i.e., “musical race defilement”). Just listening to a jazz record could get you sent to a concentration camp.

Reinhardt, however, enjoyed the most lucrative period of his career during the war, while living and playing openly among Nazi soldiers.

How?

Reinhardt biographer Michael Dregni, recently interviewed by NPR, explained:

The Germans used Paris basically as their rest-and-relaxation center, and when the soldiers came, they wanted wine and women and song. And to many of them, jazz was the popular music, and Django was the most famous jazz musician in Paris… And it was really a golden age of swing in Paris, with these [Romas] living kind of this grand irony.

Reinhardt, then, survived because the Nazis loved jazz music, even as Hitler censored the music and, on his orders, people who dared to listen to, dance to, or play it were encamped and members of the groups who invented it were murdered.  Irony indeed.

For more on Reinhardt, jazz, and World War II, here is a clip from a documentary on Reinhardt’s remarkable talent, career, and luck:

—————————

UPDATE: A commenter, Bernardo Soares, offered an interesting critique/clarification in the thread.  Here’s part of what he had to say:

…I think it is grossly misleading to write that Reinhardt “enjoyed the most lucrative period of his career during the war”. He enjoyed the protection of some individuals in the German occupation force. This is not so unusual — the composer Richard Strauss who headed the Reichsmusikkammer used his influence to protect some Jewish composers. But as many other examples show, this was extremely precarious. As long as these individuals had the power to protect him, he was probably relatively safe, but he could still be shot by any soldier at a whim or be accidentally included in a deportation action. Also, these individuals could lose their power, or some higher-ranking officer could order him to be deported. Reinhardt tried several times to escape occupied France.

[Also] …the whole issue of music and art politics in the Third Reich is much more complex than stated in the video. The Reichsmusikkammer (Reich Music Chamber) was not the only institution regulating music politics. As with many other bureaucratic institutions in the Third Reich, several agencies struggled for influence and power. This means that music politics was often contradictory, and the absence of a clear regulation as stated in the video opened the door for arbitrary measures – again emphasizing the precarious situation of musicians. The competition and struggle for power between different agencies led to a radicalisation of racial and cultural politics, and this was even taken further in the occupied countries.

I do love this topic.  I also have a post on racial borrowing and lindy hop, the dance that made me love Django.  A paper I wrote about gender and lindy hop can be found in the journal Ethnography. And I have a talk based on the paper that I love to give in theory classes.

—————————

Lisa Wade is a professor of sociology at Occidental College. You can follow her on Twitter and Facebook.

UPDATE:  Since posting this, I’ve discovered that the numbers do not accurately reflect the ratio of CEO vs. worker pay.  Writes PolitiFact:

We don’t doubt the chart’s underlying point that the ratio of CEO pay to worker pay is high in the United States, and is likely higher in our free-wheeling economy than it is in the historically more egalitarian nations of Europe.

But in its claim that the U.S. ratio is 475 to 1, the chart conveys a sense of certitude and statistical precision that simply isn’t warranted — and which is contradicted by the facts. The latest number for the U.S. is 185 to 1 in one study and 325 to 1 in another [though in previous years, those ratios have reached as high as 525 to 1] — and those numbers were not generated by groups that might have an ideological interest in downplaying the gaps between rich and poor. We rate the claim on the U.S. ratio False.

I apologize for not vetting this more carefully.

H/T KeepYourHopesUpHigh via GlobalSociologyBlog.

Cross-posted at Family Inequality.

In 1994, Sara McLanahan and Gary Sandefur published, Growing Up With A Single Parent: What Hurts, What Helps. The growth of children living with only their mothers was — then as now — a matter of concern not only for children’s well-being, but for intergenerational mobility. One of their empirical conclusions was this:

For children living with a single parent and no stepparent, income is the single most important factor in accounting for their lower well-being as compared with children living with both parents. It accounts for as much as half of their disadvantage. Low parental involvement, supervision, and aspirations and greater residential mobility account for the rest.

The biggest problem, in other words, is economic. The other factors —  involvement, supervision, aspirations, mobility — are related to social class and the time poverty that economically-poor parents experience.

Examples

Here are some bivariate illustrations — that is, head-to-head comparisons of the difference between children of poor and non-poor versus single and married parents.

These are the “skill group” rankings by teachers of children by socioeconomic status (or SES, a composite of parents’ education, occupational prestige and income) versus race/ethnicity, gender and family structure. SES shows the widest spread in reading teachers’ group placement of first graders.

Source: Condron (2007)

Similarly, the poor/nonpoor difference is greater than the two-parent/single-parent difference in kindergarten entry scores:

Source: Early Childhood Longitudinal Study (2009)

Those are just two examples from early-childhood assessments. More importantly, here is the breakdown seen in a longitudinal study of children growing up. When women grow up to be mothers, their poverty level in childhood is more important than their family structure for predicting whether they will be in poverty themselves. The poverty difference is large, the family structure difference is not:

Source: Musik & Mare (2006)

This study included a more sophisticated set of multivariate analyses than this simple graph, but the author’s conclusion fits it:

Net of the correlation between poverty and family structure within a generation, the intergenerational transmission of poverty is significantly stronger than the intergenerational transmission of family structure, and neither childhood poverty nor family structure affects the other in adulthood.

That is, childhood poverty matters more.

Fewer single parents, or less poverty?

But if single parenthood and poverty are so closely related, some people say, we should spend hundreds of millions of dollars promoting marriage to help children avoid poverty (and other problems). That’s what the government has done, with money from the welfare budget. Even if it worked, which it apparently doesn’t, it’s only one approach. What about reducing poverty? And, more specifically, reducing the relative likelihood of poverty in single-parent families versus those with married parents. That is, address the poverty gap between the two groups, rather than the size of the two groups. This has the added advantage of not singling out one group — single mothers — for social stigmatization (of the kind I mentioned here). And, because it defines the problem as economic rather than moral, may make it easier to build public support for helping the poor.

Consider a recent paper by David Brady and Rebekah Burroway, which will be published in Demography. They analyzed the relative poverty of single mothers versus the total population — that is, what percentage had incomes below half the median (per person, after accounting for taxes and government transfers). Such a relative poverty measure is really a measure of inequality, but specifically inequality at the low end. (Regardless of how rich the rich are, it’s theoretically possible to have no one below half the median income). Here is my graph showing that result, with only the countries that have reliable sample sizes in the survey:

The Nordic countries have the lowest overall poverty rates. But in absolute terms their advantage is much bigger for single mothers. (The red line shows equal poverty rates for single mothers and the total population.) The US and UK have the largest difference in poverty rates between single mothers and overall poverty. That is, we have the largest poverty penalty for single motherhood. If the relative poverty rates for single mothers were lower in the US, we might spend more time and money addressing poverty and less trying to change family structures.

Cross-posted at Reports from the Economic Front.

There is big trouble brewing in Europe.  John Ross, in his blog Key Trends in the World Economy, highlights this brewing crisis in a series of charts, some of which I repost below.

This first chart shows the extent of the recovery from the recent economic crisis in the U.S., the EU, and Japan.  While the U.S. GDP has finally regained its past business cycle peak, the same cannot be said for Europe (or Japan).  As of the 3rd quarter 2011, EU GDP was still 1.7% below its previous business cycle peak.  The Eurozone was 1.9% below.

Recent GDP estimates for the 4th quarter show European GDP once again contracting, which strongly suggests that the region is headed back into recession without having regained its previous business cycle peak.  This development implies that Europe faces serious stagnationist pressures.

This chart looks at the growth record for the 5 largest European economies.  Germany has regained its previous GDP peak.  France is making progress toward that end.  These two countries account for 36.2% of European GDP.  However, things are quite different for the UK, Italy, and Spain.  These three countries account for 34.7% of European GDP and not only do they each remain far below their respective previous GDP peaks, their economies are once again heading downward.

The third chart highlights the economic performance of the three countries which have received the most media attention because of fears that their governments will be unable to repay their respective debts.  They are clearly in trouble, adding to the downward pressure on European GDP.  However, despite all the attention paid to them, their combined economies are only one-eighth the size of the combined economies of the UK, Italy and Spain.

The next two charts highlight the fact that economic trends are also dire throughout much of Eastern Europe.

The take-away is that European economic problems are not limited to a few smaller countries.  Some of the largest are also performing poorly and apparently headed back into recession without ever having regained their past business cycle peaks.  It is hard to see Europe escaping recession.  And it is hard to see the U.S., Asia, and Africa escaping the consequences.