U.S. Child Poverty in International Context

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UNICEF Innocenti Research Centre has issued its report: "Measuring child poverty: New league tables of child poverty in the world’s rich countries.  The United States doesn't stack up very well, although it's important to be clear on just what the comparisons are showing.

For comparability across countries with different income levels, the report uses a working definition of "poverty" as half of the median income in that country. This graph shows the share of children in each country who are growing up in families where the income is less than half the median income for that country. The U.S., with 23.1% of its children in such families, ranks 34th out of 35 countries.


It's important to be clear on what this graph doesn't show. It doesn't show that U.S. children are more deprived in absolute terms than children in other countries. The U.S. has a higher level if incomes than these other countries--much higher than some of them. Indeed, the UNICEF report notes that half of the median income for the 10 richest countries in this table is more than the actual median income for the 10 poorest countries in the table.

In addition, income is more unequally distributed in the U.S. than in many of these other countries. As a result, the U.S. will have a larger share of its population living in households that earn less than 50% of the median income compared with countries that have a much more equal distribution of income like Iceland or Finland.  The UNICEF report offers an extended discussion of poverty lines set in absolute terms and those set in relative terms, and the report offers data and examples for both approaches. The argument that it can be useful to look at a relative poverty line, like 50% of median income in a country, goes like this:

"In sum, a relative poverty line drawn at 50% of median income is an attempt to define a concept of poverty on which there is widespread agreement in principle – a concept which says that the poor are those who do not have access to the possessions, amenities, activities and opportunities that are considered normal by most people in the society in which they live ... 50% of the median is a plausible measure of what it is intended to measure – the sense of falling so far behind the norms of one’s society as to be at risk of social exclusion. ...

Thus, this argument holds that  the reason why the proportion of children in households below 50% of median income matters is that it represents the share of children missing the "possessions, amenities, activities and opportunities that are considered normal by most people in the society in which they live." As an example of how these forces play out, I posted on May 23 about "Dimensions of College Attendance," One figure in that post shows that for Americans born between 1979 and 1982, of those born into families in the bottom quarter of the income distribution, 9% completed a four-year college degree by age 25, and of those born into families in the top quarter of the income distribution, 54% completed a four-year college degree by age 25. I strongly suspect that this enormous gap has little to do with the cost of college or the availability of loans, but instead is closely linked to how those born into lower-income families get on average less support from family, local community, and the K-12 education system to prepare them for a college degree.


The UNICEF report also looks at the share of children living in households with less than 50% of median income before and after government taxes and transfers are taken into account. The darker blue bars show the child poverty rates from the preceding figure--that is, after government taxes and transfers are taken into account. The lighter blue bars show what the poverty rate among children would have been, if those taxes and transfers had not occurred. For countries at the top of the list, like Ireland, Hungary, the United Kingdom, Finland, and Australia, the overall effect of government taxes and transfers is a dramatic reduction in the proportion of children that would have been living in households below half of the median income. In the U.S., in contrast, the overall pattern of government taxes and transfers lead to a relatively small reduction in the number of children in such households. In Greece, remarkably enough, the overall pattern of government transfers actually increases the share of children living in households below 50% of the median income--which can happen if taxes are tilted toward families with kids and spending is focused on retirees.



The politics of designing government policies that affect children is complex, because only adults can vote. In many countries, including the United States, children are a decreasing share of the population. For example, U.S. Census data from 2010 showed that those under 18 years of age were 24% of the U.S. population--an all-time low. The U.S. Census Bureau (Table AVG1) estimates that America had 118 million households in 2011, which it divides into 78 million "family" households with an average of 3.25 people each and 40 million "nonfamily" households with 1.25 people each. Of the subset of "family" households, only about 46% have children--also an all-time low. No politician attuned to re-election ever says anything negative about "the children," but as the proportion of children in the population and the share of households with children drops, it becomes politically harder to focus spending and tax policy on the concerns of families with children. 
 
Of course, it is always delicate to design government policy in support of children, because a sensible policymaker needs to be concerned about the incentives created when resources typically flow through their parents. But along with thinking about how U.S. tax and spending policy might support families with children in direct ways, it's also useful to think about how schools, libraries, community organizations, and public areas like parks and sidewalks can be supportive to the children.


I ran across the UNICEF report at Miles Corak's blog here.  In a post called "The sad, sad story of the UNICEF Child Poverty Report and its critics,"  Corak offers some pointed commentary on how such reports have been received in the past.

Long-Term Budget Outlook from CBO

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The Congressional Budget Office has published "The 2012 Long-Term Budget Outlook." It's a go-to source for balanced and unheated analysis on this subject. The main focus is not on the annual budget deficits of the last few years or the next few years, but rather on the overall accumulation of federal debt. Here are some points that caught my eye.

Current Federal Debt in Long-Run Perspective
Here's a figure showing the ratio of federal debt/GDP from 1790 to the present. Notice that before World War II, the highest points of federal borrowing--the Revolutionary War, the Civil War,  World War I, and the Great Depression--were all below a debt/GDP ratio of 50%. World War II pushed the debt/GDP ratio above 110%, but then it dropped back down after a few decades. Even after the big budget deficits of the 1980s and early 1990s, the debt/GDP ratio didn't get above 50%. But the current debt/GDP ratio is now above 70%, higher than any previous episode in U.S. history other than World War II. The federal debt isn't in completely uncharted territory, but it hasn't visited this neighborhood often before.


Alternative Scenarios for Long-Run Debt
The CBO does two main projections for long-run federal debt. One projection assumes that current law will be followed exactly. Under this scenario, which the CBO calls the "Extended Baseline Scenario," the debt/GDP ratio soon flattens out and fades. But frankly, this current law scenario can't be trusted. After all, nothing stops Congress from passing and the President from signing a law that says all federal budgets will be balanced after, say, 2020. On paper, this solves the debt problem! But in practice, if the law is virtually certain to be changed before 2020, it solves nothing.

Thus, the CBO also offers the "Extended Alternative Fiscal Scenario," which "incorporates the assumptions that certain policies that have been in place for a number of years will be continued
and that some provisions of law that might be difficult to sustain for a long period will be modified, thus maintaining what some analysts might consider “current policies,” as opposed to current laws."

For example, tax cuts enacted by a Republican Congress and signed into law by President Bush in 2001 were scheduled to expire in 2010. But in 2010, a Democratic Congress and President Obama extended those tax cuts through 2012. The CBO "alternative" scenario assumes that this lower level of taxes will continue after 2012. It also assumes that Congress will continue to pass "temporary" relief from the Alternative Minimum Tax. It assumes that Congress will prevent the large cuts in Medicare now written into current law: a 31% cut in physician payments scheduled for next year, and automatic reductions of 1% per year in other reimbursements over the long term.  The alternative fiscal scenario also assumes that federal spending for activities other than health care and Social Security will remain more or less at their average levels for the last two decades (as a share of GDP), rather than dramatically falling in size over the next decade or two as current law somewhat mysteriously requires. The alternative scenario concludes that when push comes to shove, Congress and the President won't let the automatic spending cuts mandated by the Budget Control Act a few years ago take effect.

Under the alternative "current policies" scenario, the federal debt takes off.  It hits a debt to GDP ratio around 100% in about 2023, 150% by the early 2030s, and 200% by 2040. Of course, matters are unlikely to go that far. One way or another, the wheels would come off the wagon by then.

Health Care Spending Drives the Long-Run Debt Forecast
Social Security spending is slated to rise as the post WWII baby boomers hit retirement age, rising from 5% now to about 6% of GDP in 2037. However, spending on federal health care programs under current law (that is, assuming the unrealistic cuts in Medicare) would still rise from 5^% of GDP today to 10% of GDP by 2037. The sustained rise in federal spending in the alternative scenario is first due to health care spending and to not assuming that all other federal spending is slashed as current law projects--and then later due to monumental interest costs that build up from the earlier borrowing.

The upper left bar graph compares the average level of Social Security and federal health spending for the average of 1972-2011, and then looks at what it would be 25 years from now in 2037 under the baseline and the alternative scenario. Notice that under the baseline scenario the increase is large, and under the alternative scenario it's even larger. Under both scenarios, all other federal spending (except interest payments) decreases. Total revenues are higher in the baseline scenario, which assumes that the Bush/Obama tax cuts will be eliminated and the reach of the Alternative Minimum tax will greatly expand.



Why acting sooner is better than later.
The CBO is careful to take no stand on exactly how soon federal deficits should start coming down.  The report does make the point that sooner is better than later for long-term economic growth. But it also points out that postponing a solution tends to be better for anyone born more than 21 years ago---that is, for most voters!--because it pushes more of the costs of addressing the federal debt on to those who are under 21 or not yet born.

"CBO’s analysis suggested that, depending on the policy used to stabilize the debt, delaying action for 10 years—which would allow the debt-to-GDP ratio to rise by an additional 40 percentage points under the assumptions used for that analysis—would cause real output to be lower by between 2½ percent and 7 percent in the long run than it would have been if the ratio had been stabilized earlier at a lower level. ... Most of the decline in output caused by delaying action would stem from two factors: the crowding out of investment in productive capital, which would reduce the size of the capital stock by between 7 percent and 18 percent; and the effects of higher marginal tax rates (which would ultimately be required under the policy that stabilizes debt by raising taxes) on people’s incentives to work and save.

Another conclusion of CBO’s analysis was that generations born after about 2015 would be worse off if action to stabilize the debt-to-GDP ratio was postponed from 2015 to 2025. People born before 1990, however, would be better off if action was delayed, largely because they would partly or wholly avoid the policy changes needed to stabilize the debt ..."

There is legitimate room for disagreement over how quickly and how severely to try to reduce federal budget deficits, given the continued sluggishness of the economy. But a growing body of research (for example, see here and here) suggests that the ratio of public debt/GDP can reach about 90% of GDP without much negative effect, and then the chances of reduced growth or even a financial crisis become much more severe. Over the next 10 years, or maybe sooner, current federal budget policies are putting the debt/GDP ratio on a collision course with a very hard reality.

Teen Pregnancy: What Causes What?

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Here is a classic problem of cause and effect. Teenagers who give birth are more likely to be from households with lower income levels. Also, teenagers who give tend to end up later in life in households with lower income levels. But does the lower income level cause teens to be more likely to give birth? Or does giving birth cause as a teen cause that woman to be more likely to end up in a lower-income household? How can one untangle cause and effect? Melissa S. Kearney and Phillip B. Levine tackle these questions in "Why is the Teen Birth Rate in the United States So High and Why Does It Matter?" which appears in the Spring 2012 issue of my own Journal of Economic Perspectives. They have lots of interesting comments to make about variation in teen birthrates across states and countries. Here, I'll focus on their analysis of the cause and effect question, which surprised me and offers a nice example of  how economist try to disentangle these sorts of issues.

"Our reading of the totality of evidence leads us to conclude that being on a low economic trajectory in life leads many teenage girls to have children while they are young and unmarried and that poor outcomes seen later in life (relative to teens who do not have children) are simply the continuation of the original low economic trajectory. That is, teen childbearing is explained by the low economic trajectory but is not an additional cause of later difficulties in life. Surprisingly, teen birth itself
does not appear to have much direct economic consequence."


Conceptually, how would one tell whether giving birth as a teenager is a cause of lower future economic prospects? Just comparing life outcomes for teenage girls who give birth and those who don't will give you a correlation, but not causation.  "A comparison of the outcomes of women who did and who did not give birth as teens is inherently biased by selection effects: teenage girls who “select” into becoming pregnant and subsequently giving birth (as opposed to choosing abortion) are different in terms of their background characteristics and potential future outcomes than teenage girls who delay childbearing." The problem is made more difficult because some of the background characteristics may be measurable in the data (like family income level, or ethnicity, or if it's a single-parent family) but many other characteristics are not available in the data (like the personality traits of the teenage girl or the values lived by the family).

 In an ideal experiment, one might want a research design in which a random sample of teenagers becomes pregnant and gives birth, and then you could track the outcomes. Of course, randomized pregnancy is an impractical research design! But here are four approaches used by clever economists to disentangle this question of cause and effect. 


A within-family approach. Look at life outcomes for sisters who give birth at different ages. The result of this kind of study is "once background characteristics are controlled for, the differences are quite modest. Furthermore, even these modest differences likely overstate the costs of teen childbearing, since the sister who gives birth as a teen is likely to be “negatively” selected compared
to her sister who does not."

Miscarriages.  Of those teens who become pregnant, some will suffer miscarriages. Compare women who are similar in measured characteristics of family background, but some of whom gave birth as teenagers while others had a miscarriage. It turns out that their life outcomes look quite similar: that is, giving birth as a teenager doesn't appear to cause any additional decline in later life outcomes.

Age at first menstruation. Girls who menstruate earlier are at greater risk of becoming pregnant as teenagers. One can use a statistical approach to look at two groups of women who are similar in measured characteristics of family background, but where one group has a higher pregnancy rate because they began their menstrual cycle earlier. However, the life outcomes for these groups look quite similar; is not correlated with lower life outcomes: that is, a random chance of being more likely to give birth as a teenager (because of an earlier age of first menstruation) doesn't appear to cause any additional decline in later life outcomes.


 Propensity scores. Look at girls within a certain school, so that they live in more-or-less the same neighborhood. Using the available data, develop a "propensity score" that measures how likely a girl is to give birth as a teenager. Then compare the life outcomes for girls with similar propensity scores, some of whom gave birth and some of whom did not. There doesn't seem to be a difference in life outcomes, again suggesting that giving birth as a teenager doesn't much alter other life outcomes. 

Kearney and Levine sum up the evidence on cause and effect this way: "Taken as a whole, previous research has had considerable difficulty finding much evidence in support of the claim that teen childbearing has a causal impact on mothers and their children. Instead, at least a substantial majority of the observed correlation between teen childbearing and inferior outcomes is the result of underlying differences between those who give birth as a teen and those who do not."

Kearney and Levine also offer an unexpected (to me) perspective on policies to reduce teen pregnancy:

"Moreover, no silver bullet such as expanding access to contraception or abstinence education will solve this particular social problem. Our view is that teen childbearing is so high in the United States because of underlying social and economic problems. It reflects a decision among a set of girls to “drop-out” of the economic mainstream; they choose nonmarital motherhood at a young age instead of investing in their own economic progress because they feel they have little chance of advancement. This thesis suggests that to address teen childbearing in America will require addressing some difficult social problems: in particular, the perceived and actual lack of economic opportunity among those at the bottom of the economic ladder."

The statement about teenage girls "choosing" nonmarital motherhood should be understood not as a claim that all pregnant 15 year-olds carefully considered their life options and decided on pregnancy!  Instead, the economists' view of choice is that we all make groups of choices every day--say, choices about exercise and calories consumed--that make certain outcomes more likely. Decisions that are not well-considered, or that raise the risk of undesired side effects, still have a large ingredient of choice. For example, we typically view those who drive drunk as having made a "choice."

The cause-and-effect evidence here suggests that for many women who give birth as teenagers, their life outcomes like level of education achieved, income, employment, and chance of marriage are already so constrained that they are not made worse off by having a child as a teenager. Encouragement about contraception or abstinence can help reduce teen pregnancy on the margin. But what many teen girls from low socioeconomic status backgrounds need is a reduced prospect of marginalization, and a greater chance for personal and economic advancement.

Occupational Licensing and Low-Income Jobs

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Pretty much everything I know about the economics of occupational licensing I learned from Morris Kleiner, a colleague from the days when I was based at the Humphrey School at the University of Minnesota. Morrie lays out many of the issues here in a Fall 2000 article in my own Journal of Economic Perspectives, as well as in his  2006 book, Licensing Occupations: Ensuring Quality or Restricting Competition?

He points out that nearly one-third of the U.S. labor force works in jobs where some form of government license is a requirement. Some of the largest occupations that require licenses include teachers, nurses, engineers, accountants, and lawyers.  Occupational licensing poses a potential tradeoff: on one side, requiring licenses offers a promise of a reliably high quality of service; on the other side, requiring licenses is a barrier to entry that tends to reduce the quantity of jobs in that occupation but increase the wage. Kleiner and others investigate this subject by looking at differences in licensing requirements for a certain occupation across states, and searching for evidence of wage and quality differences. A typical finding is that the wage differences are readily perceptible, but the quality differences are not. Licensing is distinguishable from certification: with certification, you are free to hire someone who doesn't possess the certification if you like, but with licensing, hiring someone without the license is illegal. As an example, travel agents and mechanics are often certified, but they are typically not licensed.

Dick M. Carpenter II, Ph.D., Lisa Knepper, Angela C. Erickson and John K. Ross focus on documenting differences between states in 102 of the job categories counted by the Bureau of Labor Statistics that requires a license in at least one state and that pay below-average wages. They report the results in License to Work: A National Study of Burdens from Occupational Licensing, a report from the Institute for Justice. They make the case that many of these occupational rule are more about limiting competition than about quality of service in an indirect way: they point out that licensing rules about fees, training, exams, minimum age, and minimum schooling vary enormously across states, with no particular evidence that reliability or safety are worse in states with lesser or no licensing requirements. The report goes into state-by-state and occupation-by-occupation detail, but here are some summary comments: 



"The need to license any number of the occupations in this sample defies common sense. A short list would include interior designers, shampooers, florists, upholsterers, home entertainment installers, funeral attendants, auctioneers and interpreters for the deaf. Most of these occupations are licensed in just a handful of states; interpreters are licensed in only 16 states, while auctioneers are licensed in 33. If, as licensure proponents often claim, a license is required to protect the public health and safety, one would expect more consistency. For example, only five states require licenses for shampooers, but it is highly unlikely that conditions in those five states are any different ..."


"Quite literally, EMTs [emergency medical technicians] hold lives in their hands, yet 66 other occupations have greater average licensure burdens than EMTs. This includes interior designers, barbers and cosmetologists, manicurists and a host of contractor designations. By way of perspective, the average cosmetologist spends 372 days in training; the average EMT a mere 33."



"Licensure irrationalities are doubly evident in the inconsistencies by burden across states. Looking again at manicurists, while 10 states require four months or more of training, Alaska demands only about three days and Iowa about nine days. It seems unlikely that aspiring manicurists in Alabama (163 days) and Oregon (140 days) truly need so much more time in training. But manicurists are not alone. The education and experience requirements for animal trainers range from zero to almost 1,100 days, or three years. And for vegetation pesticide handlers, training obligations range from zero to 1,460 days, or four years, with fees up to $350. This high degree of variation is prevalent throughout
the occupations. Thirty-nine of them have differences of more than 1,000 days between the minimum and maximum number of days required for education and experience. And another 23 occupations have differences of more than 700 days."


"Finally, irrationalities are particularly notable when few states license an occupation but do so onerously. One clear example is interior design, the most difficult of the 102 occupations to enter, yet licensed in only three states and D.C. Another is social service assistants, the fourth most difficult occupation to enter. It requires nearly three-and-a-half years of training but is only licensed in six states and D.C. Dietetic technicians must spend 800 days in education and training, making for the eighth most burdensome requirements, but they are licensed in only three states. Home entertainment installers must have about eight months of training on average, but only in three states. The seven states that license tree trimmers require, on average, more than a year of training."



"The 102 occupational licenses studied require of aspiring workers, on average, $209 in fees, one exam and about nine months of education and training. ·· Thirty-five occupations require more
than a year of education and training, on average, and another 32 require three to nine months. At least one exam is required for 79 of the occupations. ... Particularly noteworthy is the percentage of low- and middle-income workers with less than a high school diploma—15.7 percent. As documented below, a number of the 102 occupations studied require the completion of at least 12th grade, a requirement that effectively bans a substantial number of people from those occupations."

"[S]even of the 102 occupations studied are licensed in all 50 states and the District of Columbia:
pest control applicator, vegetation pesticide handler, cosmetologist, EMT, truck driver, school bus driver and city bus driver. Another eight occupations are licensed in 40 to 50 states. Thus, the vast majority of these occupations are licensed in fewer than 40 states, and five are licensed in only
one state each: florist, forest worker, fire sprinkler system tester, conveyor operator and non-contractor pipelayer. On average, the occupations on this list are licensed in about 22 states."

My own guess is that the politics of passing state-level occupational licensing laws is driven by three factors: 1) lobbying by those who already work in the occupation to limit competition; 2) passing laws in response to wildly unrepresentative anecdotes of terrible or dangerous service; and 3) the tendency when setting standards to feel like more is better. But in a U.S. economy which is hurting for job creation, especially jobs for low-income workers, states should be seriously rethinking many of their occupational licensing rules. Many would be better-replaced with lower standards, certification rather than licenses, or even no licenses at all. 

Why Does the U.S. Spend More on Health Care than Other Countries?

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Everyone knows that the U.S. spends far more on health care than other countries, but do you know how much more? In 2009, the U.S. spent 17.4% of GDP on health care (using OECD data). The closest contenders are Netherlands (12% of GDP), France (11.8%), Germany (11.6%), Denmark (11.5%), and Canada (11.4%). The U.S. has higher per capita GDP than these countries, so the gap in absolute spending is even higher. In 2009, the U.S. spent $7,960 per person on health care, and the closest contenders were Switzerland ($5,144 per person) and Netherlands ($4,914).

When I hear people argue that the U.S. should follow the path of the UK health care system, I sometimes find myself thinking: "You mean that U.S. health care spending per person should be slashed by 56%, from $7,960 per person to $3,487 per person? Really?"

What accounts for these differences in health care spending across countries? David Squires assembles some of the evidence in "Explaining High Health Care Spending in the United States: An International Comparison of Supply, Utilization, Prices and Quality," a May 2012 "issue brief" written for the Commonwealth Fund. I ran across it here at Larry Willmore's Thought du Jour blog.   I'll also contrast and compare it with a paper by David M. Cutler and Dan P. Ly, "The (Paper)Work of Medicine: Understanding International Medical Costs," which appeared in the Spring 2011 issue of my own Journal of Economic Perspectives. For readability, footnotes and references to exhibits are omitted from the quotations below.

 Higher U.S. health care spending is not because Americans on average are notably less healthy.
As Squires sums up: "U.S. has smaller elderly population and fewer smokers, but higher obesity rates. ...  Higher rates of obesity undoubtedly inflate health spending; one study estimates the medical costs attributable to obesity in the U.S. reached almost 10 percent of all medical spending in 2008. However, the younger population and lower rates of smoking likely have an opposite effect, reducing U.S. health care spending relative to most other countries."

Higher U.S. health care spending is not because the U.S. has more doctors or hospital beds.
"There were 2.4 physicians per 1,000 population in the U.S. in 2009, fewer than in all other study countries except Japan. Likewise, patients had fewer doctor consultations in the U.S. (3.9 per capita)
than in any other country except Sweden. Hospital supply and use showed similar trends, with the U.S. having fewer hospital beds (2.7 per 1,000 population), shorter lengths of stay for acute care (5.4
days), and fewer discharges (131 per 1,000 population) than the OECD median ..."



Prices for brand-name drugs are much higher in the U.S., but generics are cheaper.
Squires writes: "[P]rices for the 30 most-commonly prescribed drugs are one-third higher than in Canada and Germany, and more than double the prices in Australia, France, Netherlands, New Zealand, and the U.K. Notably, prices for generic drugs are lower in the U.S. than in these other countries, whereas prices for brand-name drugs are much higher."

Cutler and Ly confirm this general pattern, but also put the potential cost savings in perspective: "However, because pharmaceuticals are only about 10 percent of U.S. healthcare spending, the overall amount that could be saved by moving to U.S. government monopsony purchasing of drugs
is relatively small—perhaps 20 to 30 percent of pharmaceutical spending, or 2 to 3 percent of total medical costs. These cost savings also would have to be weighed against the possibility of reduced incentives for investment and innovation in the pharmaceutical industry. The dollar amount of excess pharmaceutical payments in the United States is approximately the total amount of pharmaceutical company research and development (R&D)."


U.S. doctors are paid more, but they also live in an economy with a more unequal distribution of wages.
Squires writes: "U.S. primary care physicians generally receive higher fees for office visits and orthopedic physicians receive higher fees for hip replacements than in Australia, Canada, France, Germany, and the U.K. ... U.S. primary care doctors ($186,582) and particularly orthopedic doctors ($442,450) earned greater income than in the other five countries ..."

Cutler and Ly confirm: "The average U.S. specialist physician earns $230,000 annually—
78 percent above the average in other countries ... . Primary care physicians earn less (they earn $161,000 on average), but the same percentage more than their peers in other countries. ... If we reduced all physician incomes in the United States to match the international ratio of physicians’ incomes to per capita GDP, U.S. healthcare spending would be lower by roughly 2 percent.However, these seemingly high salaries for U.S. physicians appear less high in the context of the broader income distribution." Cutler and Ly go on to point out that high-compensation workers in the U.S. economy earn more than their international counterparts in just about every profession--after all, that's part of what it means to say that the U.S. has a less equal distribution of income.

Some medical device technologies like scanning are more widely used in the U.S; some like hip replacements are not.
"In 2009, the U.S., along with Germany, performed the most knee replacements (213 per 100,000
population) among the study countries, and 75 percent more knee replacements than the OECD median (122 per 100,000 population). However, the U.S. performed barely more hip replacements than the OECD median, and significantly less than several of the other study countries ..."

"Relative to the other study countries where data were available, there were an above-average
number of magnetic resonance imaging (MRI) machines (25.9 per million population), computed
tomography (CT) scanners (34.3 per million), positron emission tomography (PET) scanners (3.1 per million), and mammographs (40.2 per million) in the U.S. in 2009. Utilization of imaging was also highest in the U.S., with 91.2 MRI exams and 227.9 CT exams per 1,000 population. MRI and CT devices were most prevalent in Japan, though no utilization data were available for that country. ... [T]he U.S. commercial average diagnostic imaging fees ($1,080 for an MRI and $510 for a CT exam) are far higher than what is charged in almost all of the other countries ..."

The U.S. does a relatively poor job of managing chronic disease.
Squires writes: "[Consider] rates of potentially preventable mortality due to asthma (for those between ages 5 and 39) and lower-extremity amputations due to diabetes per 100,000 population. On both measures, the U.S. had among the highest rates, suggesting a failure to effectively manage these chronic conditions that make up an increasing share of the disease burden."

Many chronic diseases share the general property that if they are well-managed every single day, with a combination of drugs, lifestyle, and certain kinds of monitoring of physical conditions, it is possible to reduce the need for enormously costly episodes of hospitalization. As the Centers for Disease Control puts it: "Chronic diseases—such as heart disease, cancer, and diabetes—are the leading causes of death and disability in the United States. Chronic diseases account for 70% of all deaths in the U.S., which is 1.7 million each year. These diseases also cause major limitations in daily living for almost 1 out of 10 Americans ...."

Prices for hospital stays are substantially higher in the U.S.
Squires points out: "[H]ospital stays in the U.S. were far more expensive than in the other study countries, exceeding $18,000 per discharge compared with less than $10,000 in Sweden, Australia, New Zealand, France, and Germany." And remember, these higher costs per hospital stay happen even though the stays themselves are on average shorter in the U.S.

The tougher question is to what extent these higher costs per hospital stay reflect a larger quantity of concentrated and effective high-tech care being provided, and to what extent its just a matter of higher prices. The evidence here is mixed. It does appear that for some conditions, Americans receive more hospital care. Cutler and Ly write:  Americans also receive more-intensive care than do Canadians. While the population-adjusted hospital admission rates are about the same in the two countries, additional procedures are provided to those with the same diagnosis in the United States. For example, people with a heart attack in the United States are twice as likely to receive bypass surgery or angioplasty than are similar people in Canada." When it comes to cancer survival rates, Squires points out: "The U.S. had the highest survival rates among the study countries for breast cancer (89%) and, along with Norway, for colorectal cancer (65%)."

On the other side, the more aggressive use of heart surgery in the U.S. as compared to Canada doesn't seem to mean better health outcomes; instead, it reflects the existence of more heart-surgery facilities. Cutler and Ly: "  On one side, the greater use of intensive therapies after a heart attack in the United States compared to Canada is not associated with improved mortality, though morbidity is more diffifult to determine. Similarly, a recent study concluded that there was no systematic difference in outcomes in favor of the United States over Canada; if anything, Canadians had better outcomes in most circumstances ... [T]he province of Ontario has 11 open-heart surgery facilities, while the state of Pennsylvania, with roughly the same population as Ontario, has more than five times the number of heart surgery facilities. California is three times larger in population but has 10 times the number of heart surgery facilities. Given this difference in the number of facilities, it is simply impossible for physicians in Ontario to perform as many open heart surgery operations as those in Pennsylvania or California."

Also, not all cancer survival rates are better in the U.S. Squires writes: "However, at 64 percent, the survival rate for cervical cancer in the U.S. was worse than the OECD median (66%), and well below the 78 percent survival rate in Norway—indicating significant room for improvement."

Administrative costs of health care are much higher in the U.S.
Squires doesn't mention this point, but it is a main emphasis for Cutler and Ly. They write:

"[T]the U.S. healthcare system is in great need of administrative simplification. There are few other areas of the U.S. economy where waste is so apparent and the possibility of savings is so tangible. ... Perhaps the most troubling difference between the U.S. and Canadian healthcare systems is the differential amount spent on administration. For every office-based physician in the United States, there are 2.2 administrative workers. That exceeds the number of nurses, clinical assistants, and technical staff put together. One large physician group in the United States estimates that it spends 12 percent of revenue collected just collecting revenue. Canada, by contrast, has only half as many administrative workers per office-based physician.  The situation is no better in hospitals. In the United States, there are 1.5 administrative personnel per hospital bed, compared to 1.1 in Canada. Duke University Hospital, for example, has 900 hospital beds and 1,300 billing clerks. On top of this are the administrative workers in health insurance. Health insurance administration is 12 percent of premiums in the United States and less than half that in Canada.

"International comparisons of medical care occupations are difficult, but they suggest that the United States has more administrative personnel than other countries do. ... [T]he United States has 25 percent more healthcare administrators than the United Kingdom, 165 percent more than the Netherlands, and 215 percent more than Germany. The number of clerks of all forms (including data entry clerks) is much higher in the United States as well."

"What are all these administrative personnel doing? ... One part is credentialing—receiving permission to practice medicine in a particular hospital or for a particular health plan. The average physician submits 18 credentialing applications annually—each insurer, hospital, ambulatory surgery facility, and the like, requires a different one—consuming 70 minutes of staff time and 11 minutes of physician time per application. Verifying eligibility for services is also costly. Insurance information must be verified for 20 to 30 patients daily, including three or four patients for whom verification must be sought orally. Because people change insurance plans frequently and the cost-sharing they are charged varies with plan and with past utilization (for example, how much of the deductible have they spent?), the determination of what to charge a patient is especially difficult. ... Finally, significant time is spent on billing and payment collection. On average, about three claims are denied per physician per week and need to be rebilled. ...  Three-quarters of denied bills are ultimately paid, but the administrative cost of securing the payment is very high. Provider groups in the United States employ 770 full-time equivalent workers per $1 billion collected, compared to an average in other U.S. industries of about 100. By all indications, the administrative burden is rising over time as insurance policies have become more complex, while the technology of administration has not kept pace."

Conclusion

The question of why the U.S. spends more than 50% more per person on health care than the next highest countries (Switzerland and Netherlands), and more than double per person what many other countries spend, may never have a simple answer. Still, the main ingredients of an answer are becoming more clear. The U.S. spends vastly more on hospitalization and acute care, with a substantial share of that going to high-tech procedures like surgery and imaging. The U.S. does a poor job of managing chronic conditions, which then lead to episodes of costly hospitalization. The U.S. also seems to spend vastly more on administration and paperwork, with much of that related to credentialing, documenting, and billing--which is again a particular important issue in hospitals. Any honest effort to come to grips with high and rising U.S. health care costs will have to tackle these factors head-on. 

The Shifting U.S.-China Trade Picture

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The standard story of U.S.-China trade over the last decade or so goes like this: Huge U.S. trade deficits, matched by huge Chinese trade surpluses. One underlying reason for the imbalance is that China has been acting to hold its exchange rate unrealistically low, which means that within-China production costs are lower compared to the rest of the world, thus encouraging exports from China, and outside-China production costs are relatively high, thus discouraging imports into China.

This story is simplified, of course, but it holds a lot of truth. But it's worth pointing out that these developments are fairly recent--really just over a portion of the last decade--and not a pattern that China has been following since its period of rapid growth started back around 1980. In addition, these development seem to be turning: the U.S. trade deficit is falling, China's trade surplus is declining, and China's exchange rate is appreciating. Here's the evolution in graphs that I put together using the ever-helpful FRED website from the St. Louis Fed.

First, here's a look at China's balance of trade over time. The top graph shows China's  current account balance since 1980, roughly when China's process of economic growth got underway. Notice that China a trade balance fairly close to zero until the early 2000s, when the surpluses took off. Because the first graph stops in 2010, the second graph shows China's trade balance from 2010 through the third quarter of 2011. Clearly, China's trade surplus has dropped in the last few years, and in all likelihood will be lower in 2011 than in 2010.



China's pattern of trade surpluses maps loosely follows its exchange rate. Here is China's exchange rate vs. the U.S. dollar since 1980. When an economy is experiencing extremely rapid productivity growth, the expected economic pattern is that its currency will appreciate over time--that is, become more valuable. However, as China's growth took off in the 1980s and into the 1990s, its currency depreciated--on the graph, it took more Chinese yuan to equal $1 U.S. than before. In about 1994, there is an especially sharp depreciation of the yuan, as it went very quickly from about 5.8 yuan/$1 to about 8.6 yuan/$1. During the booming U.S. economy of the late 1990s, this change had relatively little effect on the balance of trade, but by the early 2000s, it began to pump up China's trade surplus.  However, notice also that the value of China's exchange rate has dropped quite substantially over the last few years, withe much of the change coming before the Great Recession hit (U.S. recessions are shown with shaded gray vertical bands in the figure.)



The U.S. balance of trade in the last decade or so looks like China's pattern, in reverse. As China's trade surplus takes off around 2000 or so, the U.S. trade deficit plummets at about that time. As China's trade surplus diminishes in the last few years, the U.S. trade deficit also diminishes.


So what about the story with which I started: an overvalued Chinese currency, leading to huge Chinese trade surpluses and correspondingly huge U.S. trade deficits? At a minimum, the story is much less true that it was a few years back. Indeed, William R. Cline and John Williamson at the Peterson Institute for International Economics argue that the U.S.-China exchange rate has largely returned to the fundamental value justified by productivity and price differences between the two economies. Their argument appears in a May 2012 Policy Brief called  "Estimates of Fundamental Equilibrium Exchange Rates, May 2012."

They point out that China's trade surpluses are likely to be much smaller than the IMF, for example, was predicting a few years ago. And while they believe China's currency is still slightly undervalued, and needs to continue appreciating over time, they estimate that it's current value is not far from their "fundamental equilibrium exchange rate" or FEER.  They write:

"China is still judged undervalued by about 3 percent ... Thus, whereas a year ago we estimated that the renminbi needed to rise 16 percent in real effective terms and 28.5 percent bilaterally against the dollar (in a general realignment to FEERs), the corresponding estimates now are 2.8 and 7.7 percent, respectively. It is entirely possible that future appreciation will bring the surplus [China's trade surplus] down to less than 3 percent of GDP. But China still has fast productivity growth in the tradable goods industries, which implies that a process of continuing appreciation is essential to maintain its current account balance at a reasonable level."

In short, the episode of an overvalued Chinese currency driving huge trade imbalances may be largely behind us. The current U.S. trade deficits are thus more rooted in an economy which continues to save relatively little and to consume more than domestic production--thus drawing in imports.  

Household Production: Levels and Trends

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Since the early days of GDP accounting, and in every intro econ class since then, a  standard talking-point is that measures of economic output leave out home production. Further, if two neighbors stopped doing home production and instead hired each other to do housework and yardwork, total GDP would rise because those activities were now part of paid market exchange, even though the quantity of housework and yardwork actually done didn't rise.  But how much is household production actually worth in the U.S. economy and how has it changed over time? Benjamin Bridgman, Andrew Dugan, Mikhael Lal, Matthew Osborne, and Shaunda Villones tackle this question in Accounting for Household Production in the National Accounts, 1965–2010, which appears in the May 2012 issue of the Survey of Current Business. (I found this study at Gene Hayward's HaywardEconBlog.) Here are a few points that jumped out at me (footnotes omitted).

How can one estimate the value of home production?  
Get an estimate of hours devoted to home production, and then multiply by the wage that would be paid to domestic labor. "To measure the value of nonmarket services, we make use of two unique surveys that track household labor activities and apply a wage to the total number of hours spent in home production. One of these surveys is the Multinational Time Use Survey (MTUS), which combined a number of time use surveys conducted by academic institutions into a single data set. These surveys were taken sporadically between 1965 and 1999. The other is the American Time Use Survey (ATUS) produced by the Bureau of Labor Statistics (BLS). This survey was taken annually between 2003 and 2010.  ...

How does the value of home production relate to GDP?
"We find that incorporating home production in GDP raises the level of GDP 39 percent in 1965 and
25.7 percent in 2010."

 Why has the value of home production fallen over time? 
Fewer hours spent in home production over time, and the wage of household workers relative to other workers in the economy has fallen. "The impact of home production has dropped over time because women have been entering the workforce. This trend is driven by an increasing trend in the wage disparity between household workers and employees (that is, the opportunity cost of household labor)."

How would including home production in national output alter the growth rate of this expanded definition of GDP over time?
"Because standard GDP does not account for home production, some of the increase over time in GDP will be due to women switching from home production to market-based production. Our adjusted GDP measure includes the unmeasured home production, so the increase in GDP that occurs due to substitution from home production to market-based production will be smaller. During 1965 to 2010, the annual growth rate of nominal GDP was 6.9 percent. When household production is included, this growth rate drops to 6.7 percent."

How does time spent in home production vary with income level? How would including home production in output affect the inequality of income?
"We find that home production hours do not vary with family income: for women, who contribute to the bulk of home production hours, the correlation between family income and home production is about 0.01. Therefore, adding home production income to family income is essentially the same as adding a constant number to family income, which will raise the income of low income families proportionately more than high income families, leading to a decrease in inequality. This finding is consistent with earlier work in this literature ..."

What are the gender patterns for time spent in home production?
"In 1965, men and women spent an average of 27 hours in home production, and by 2010, they spent 22 hours. This overall decline reflects a drop in women’s home production from 40 hours to 26 hours, which more than offset an increase in men’s hours from 14 hours to 17 hours."

What is the connection between income and hours of household production?
 Those with more income spend tend to spend slightly more time on home production. "Averaged over the years 2003 to 2010, the home production for women (men) in the lowest income category was 32.2  (23.3) hours per week, while in the highest income category it was 26.3 (19.0) hours per week."