In this post I shall argue two things which together may confuse people. First, that life expectancy is so valuable that the money the US spends on healthcare relative to Europe could be well spent. Second that the extra spending is not in fact due to higher quality and does not explain rising prices over time.
What explains rising prices in some sectors of the economy? A common argument, at least from economists, is that there may be unmeasured improvements in quality. I don’t think that there have been marked improvements in quality in education so that argument doesn’t get off the ground (see my earlier post and the book for evidence). But health care quality has increased. Moreover, the value of life is so high that the improvements in quality could justify the cost increases. Here from Why Are The Prices So D*mn High is a back of the envelope calculation:
The United States spends about 5 percent more of GDP on health-care than do other developed countries. US GDP is almost $20 trillion, so 5 percent is approximately $1 trillion. The US population is 325 million, so the United States spends an extra $3,000 per person each year on healthcare. Is the expense worthwhile?
A value of a statistical life-year of around $200,000 is a mid-range, widely used estimate in the United States. Thus, if the extra US spending generated an extra $3,000 per $200,000 of a life-year, it would pay for itself. In other words, for the extra US spending to be worthwhile it must generate 3,000/200,000 × 365 = 5.45 extra days of statistical life, and, of course, it must do so every year. In recent years, life expectancy in the United States has increased by about 52 days a year. Thus, a little more than 10 percent of the increase in actual life expectancy must be a result of the extra US spending for that spending to be worthwhile. That hardly appears impossible. It’s also not impossible that the increase in life expectancy was not caused by the extra spending.
The bottom line is that the value of life is so high that US levels of spending could be worthwhile, but the high value of life and the difficulty of measuring the effectiveness of healthcare makes the question impossible to answer with certainty.
Nevertheless,I don’t think the increases in quality explain the increases in cost:
…even if the spending on healthcare is well justified by the improvements in life expectancy, it does not follow that the cause of higher spending is the improvement in life expectancy. As with education, many of the increases in life expectancy come from better knowledge, which does not necessarily cost more to use. It does not cost much more to treat an infection with antibiotics than with bloodletting; perhaps it costs less. We do use more technology in healthcare than in previous years—this includes computerized tomography (CT) scanners, magnetic resonance imaging (MRI) systems, and positron emission tomography (PET). Technology, however, is falling in price. At some point one would expect that decreases in the cost of existing technologies would overwhelm increases in costs owing to the introduction of new technologies. As with education, it would be peculiar if the only place in which technology raised costs was in healthcare (but see Joseph P. Newhouse for a strong argument that healthcare costs are driven by technology.)
Let’s put this argument more generally. Most increases in quality *over time* are similar to increases in productivity, i.e. A in A*f(K,L), an unpriced factor. Computers today are much higher quality than in the past. Indeed, so much so that today’s computers couldn’t be bought at any price not that long ago but we don’t pay more because what makes them higher quality is general knowledge.
In my view, most quality increases over time are due to improvements in knowledge. In other words, quality increases over time are much more about better recipes than better cooks. As a result, at a given point in time, higher quality is associated with higher prices but over time higher quality is more often associated with *lower* prices. Thus, in general, higher quality is not a good explanation for higher prices over time.
Tomorrow: The Baumol Effect.
Addendum: Other posts in this series.
The feared street gangster El Negrito sleeps with a pistol under his pillow and says he’s lost track of his murder count. But despite his hardened demeanor, he’s quick to gripe about how Venezuela’s failing economy is cutting into his profits.
Firing a gun has become a luxury. Bullets are expensive at $1 each. And with less cash circulating on the street, he says robberies just don’t pay like they used to.
For the 24-year-old, that has all given way to a simple fact: Even for Venezuelan criminals it’s become harder to get by.
“If you empty your clip, you’re shooting off $15,” said El Negrito, who spoke to The Associated Press on the condition he be identified only by his street name and photographed wearing a hoodie and face mask to avoid attracting unwelcomed attention. “You lose your pistol or the police take it and you’re throwing away $800.”
In something of an unexpected silver lining to the country’s all-consuming economic crunch, experts say armed assaults and killings are plummeting in one of the world’s most violent nations. At the Venezuelan Observatory of Violence, a Caracas-based nonprofit group, researchers estimate homicides have plunged up to 20% over the last three years based on tallies from media clippings and sources at local morgues.
Officials of President Nicolás Maduro’s socialist administration have drawn criticism for not releasing robust crime statistics, but the government on Tuesday gave the AP figures showing a 39 percent drop in homicides over the same three-year period, with 10,598 killings in 2018. Officials also report a fall in kidnappings.
The decline has a direct link to the economic tailspin that has helped spark a political battle for control of the once-wealthy oil nation.
There has been a lot of ink spilled over the rising cost of health care and in Why Are the Prices So D*mn High? Helland and I do not cover every theory and cannot satisfy every objection. Our goal is more modest. We can say that one major factor in rising health care costs is the rising price of skilled labor.
We argue that there is a direct, obvious, and measurable cause of higher costs in healthcare—namely, the price of skilled labor. No profession other than physicians has seen such large increases in incomes over the past 50 years. Figure 19 shows the real income of physicians from 1960 to 2016, indexed to 100 in 1960. Since 1960 the real income of physicians has increased by a factor of three. By comparison, barbers and bus drivers have seen essentially no increase in real incomes. Median incomes are up only modestly whereas mean incomes, which are pulled up by outliers, are up by only 50 percent.
Moreover, nurse incomes have risen in lock-step with those of physicians.
At the same time, we have hired more physicians and more nurses per capita. As Figure 20 shows since 1960 the number of physicians and the number of nurses has more than doubled.
With more physicians and more nurses each making more, it’s not surprising that the cost of medical care would increase.
Addendum: Other posts in this series.
That is the new and very interesting forthcoming book by Janek Wasserman, focusing on the history of the Austrian school of economics and due out in September. A few comments:
1. It is the best overall history of the Austrian school.
2. It is in some early places too wordy, though perhaps that is necessary for the uninitiated.
3. I don’t think actual “Austrian school members” will learn much economics from it, though it has plenty of useful historical detail, far more than any other comparable book. And much of it is interesting, not just: “Adolph Wagner and Albert Schaeffler taught in the Austrian capital in the 1860s and early 1870s, but quarrels with fellow incumbent Lorenz von Stein led to their departure.”
4. Even a full decade after its release in 1871, Menger’s Principles was not achieving much attention outside of Vienna.
5. The early Austrians favored progressive taxation and fairly standard Continental approaches to government spending.
6. The Austrian school of those earlier times was in danger of disappearing, as Boehm-Bawerk was working in government and the number of “Austrian students” was drying up, circa 1905.
7. The very first articles of Mises were empirical, and covered factory legislation, labor law, and welfare programs.
8. Wieser and some of the others lost status with the fall of the Dual Monarchy after WWI; Wieser for instance no longer had a House of Lords membership. Schumpeter and Mises responded to these changes by writing more for a broader public, often through newspapers (not blogs). Mises’s market-oriented views seemed to stem from this time.
9. Hayek in fact struggled in high school, though his grandfather had gone on Alpine hikes with Boehm-Bawerk.
10. The Lieder of the original Mises circle were patterned after the poems of Karl Kraus, and one of them mentioned spaghetti and risotto.
11. Much of this book is strong evidence for the “small group” theory of social change.
12. The patron institution for Hayek’s business cycle research of 1927 to 1931 was partly sponsored by the Rockefeller Foundation.
13. By the mid-1930s, Mises, Tinbergen, Koopmans, and Nurkse were all living in Geneva. There was a Vienna drinking song saying farewell to Mises.
14. I wonder how these guys would have looked as Emergent Ventures applicants. [“We’re going to run away from the Nazis and recreate anew our whole school of thought in America, with thick Austrian accents…and with a night school class at NYU to boot.”]
15. The Austrian school eventually was reborn in the United States, which accounts for many more chapters in this book, some of them concerned with the ties between the Austrian school and libertarianism. There are some outright errors of fact in this section of the book, sometimes involving matters I was involved with personally (and which are non-controversial, not a question of “taking sides”). I think also the latter parts of the book do not quite grasp the extensive influence of the Austrian school on America, extending up through the current day, and covering such diverse areas as regulatory policy and tech and crypto.
Nonetheless, recommended as an important contribution to the history of economic thought.
There was some head-scratching this week, as data showed Japan’s economy growing by 2.1% in the first quarter at an annualised rate, defying expectations of a slight contraction. Most of the growth was explained by a huge drop in imports. Because they fell at a faster rate than exports, gdp rose.
Nope. Imports do not influence Gross Domestic Product, at least not in the mechanical way suggested by The Economist. Here’s how Tyler and I explain it in Modern Principles:
It’s important to remember the Domestic in Gross Domestic Product. When we add C+I+G we are adding up all national spending but some of that spending was on imports, goods that were not produced domestically. So we subtract imports from national spending to get national spending on domestically produced goods, C+I+G – Imports.
…Here is a mistake to avoid. The national spending approach to calculating GDP requires a step where we subtract imports but that doesn’t mean that imports are bad for GDP! Let’s consider a simple economy where I, G, and Exports are all zero and C=$100 billion. Our only imports come from a container ship that once a year delivers $10 billion worth of iPhones. Thus when we calculate GDP we add up national spending and subtract $10 billion for the imports, $100-$10=$90 billion. But suppose that this year the container ship sinks before it reaches New York. So this year when we calculate GDP there are no imports to subtract. But GDP doesn’t change! Why not? Remember that part of the $100 billion of national spending was $10 billion spent on iPhones. So this year when we calculate GDP we will calculate $90 billion-$0=$90 billion. GDP doesn’t change and that shouldn’t be surprising since GDP is about domestic production and the sinking of the container ship doesn’t change domestic production.
If we want to understand the role of imports (and exports) on GDP and national welfare. We have to go beyond accounting to think about economics. If we permanently stopped all the container ships from delivering iPhones, for example, then domestic producers would start producing more cellphones and that would add to GDP but producing more cellphones would require producing less of other goods. If we were buying cellphones from abroad because producing them abroad requires fewer resources then GDP would actually fall—this is the standard argument for trade that you learned in your microeconomics class. The standard answer could change, however, if there were lots of unemployed resources, an issue we will discuss in Chapter 32 and later chapters. The point we want to emphasize here is not whether trade is ultimately good or bad but rather that Y+C+I+G+NX is an accounting identity that can’t by itself answer this question.
Here is the announcement. Presumably they wish to claw back some of the quantity going to the ever-multiplying number of AEA journals and to thus avoid being an afterthought. Will the average quality of JPE article decline? I suppose by one definition it has to, but in such a rapidly specializing discipline, who will notice? Is it really so clear which pieces come close but don’t quite deserve to belong in the JPE? I for one could not pass this “blind taste test” in my role as a JPE reader, and I have been following the rag for decades.
As a polar experiment, what if they put out an issue every day, and in essence the top journals took all the published pieces? Then the notion of having a “top three” hit (or whatever) would dwindle and people actually would have to judge the work. A modest move in that direction should be just fine, said the daily blogger.
In the meantime, the leading lights of the profession — most of all in the earlier parts of their careers — should be prepared for that much more refereeing. Ay!
Chernobyl, HBO’s taut 5-part mini-series, is excellent and it sticks close to the facts (although one female character played by Emily Watson is clearly made up). By all accounts, the series accurately represents life in the former Soviet Union and through a variety of means from color palette to casting and dialogue it does a remarkable job at capturing the political economy. One thing I learned (so far, it hasn’t all appeared yet) is that it could have been much, much worse but the Russians avoided the worst scenario with a combination of bravery, smarts and luck.
The number of cancer deaths from Chernobyl appears to be quite low. The WHO estimated an additional 9,335 deaths with about half of those coming from workers and nearby residents and other half more distant impacts, other estimates are higher. More recent analysis, however, suggests that Chernobyl and its aftermath had relatively small but significant effects across a large number of people. Here are two recent papers:
Chernobyl’s Subclinical Legacy: Prenatal Exposure to Radioactive Fallout and School Outcomes in Sweden by Almond, Edlund and Palme.
Abstract: We use prenatal exposure to Chernobyl fallout in Sweden as a natural experiment inducing variation in cognitive ability. Students born in regions of Sweden with higher fallout performed worse in secondary school, in mathematics in particular. Damage is accentuated within families (i.e., siblings comparison) and among children born to parents with low education. In contrast, we detect no corresponding damage to health outcomes. To the extent that parents responded to the cognitive endowment, we infer that parental investments reinforced the initial Chernobyl damage. From a public health perspective, our findings suggest that cognitive ability is compromised at radiation doses currently considered harmless.
and The long-run consequences of Chernobyl: Evidence on subjective well-being, mental health and welfare by Danzer and Danzer.
Abstract: This paper assesses the long-run toll taken by a large-scale technological disaster on welfare, well-being and mental health. We estimate the causal effect of the 1986 Chernobyl catastrophe after 20 years by linking geographic variation in radioactive fallout to respondents of a nationally representative survey in Ukraine according to their place of residence in 1986. We exclude individuals who were exposed to high levels of radiation—about 4% of the population. Instead, we focus on the remaining majority of Ukrainians who received subclinical radiation doses; we find large and persistent psychological effects of this nuclear disaster. Affected individuals exhibit poorer subjective well-being, higher depression rates and lower subjective survival probabilities; they rely more on governmental transfers as source of subsistence. We estimate the aggregate annual welfare loss at 2–6% of Ukraine’s GDP highlighting previously ignored externalities of large-scale catastrophes.
Hat tip: Jennifer Doleac and Wojtek Kopczuk.
That is a new paper by Germán Gutiérrez and Sophie Pitony. I am on the road and have not had a chance to go through this, but the abstract is of interest:
We identify two undocumented measurement challenges affecting corporate sector labor shares outside the United States: the inclusion of dwellings and the inclusion of self-employed workers in the corresponding sectoral accounts. Both issues have become more important over time, biasing corporate labor shares downward. We propose two methods to correct for these challenges and obtain `true’ non-housing labor share series. Contrary to common wisdom, the corrected series exhibit stable labor shares across all major economies, except the US, where the corrected labor share declines by 6 percentage points since 1980.
For the pointer I thank Ilya Novak.
We also find that stronger peer effects are exerted by more price-sensitive individuals. This positive correlation suggests that the elasticity of aggregate demand is substantially larger than the elasticity of individual demand. Through this channel, peer effects reduce firms’ markups and, in many models, contribute to higher consumer surplus and more efficient resource allocation.
That is from a new NBER working paper by Michael Bailey, Drew M. Johnston, Theresa Kuchler, Johannes Stroebel, and Arlene Wong.
In Why Are The Prices So D*mn High? Helland and I examine lower education, higher education and health care in-depth and we do a broader statistical analysis of 139 industries. Today, I will make a few points about education. First, costs in both lower and higher education are rising faster than inflation and have been doing so for a very long time. In 1950 the U.S. spent $2,311 per elementary and secondary public school student compared with $12,673 in 2013, over five times more (both figures in $2015). The rate of increase was fastest in the 1950s and 1960s–a point to which I will return later in this series.
College costs have also increased dramatically over time. For this book, we are interested in costs more than tuition because we want to know what society is giving up to produce education rather than who, in the first instance, is paying for it. Costs are considerably higher than tuition even today, although in recent years tuition has been catching up. Essentially students and their parents have been paying an increasing share of the increasing cost of higher education. Moreover, as with lower education, costs have been rising for a very long period of time.
I will take it as given that the explanation for higher costs isn’t higher quality. The evidence on tests scores is discussed in the book:
It is sometimes argued that how we teach has not changed but that what we teach has improved in quality. It is questionable whether studies of Shakespeare have improved, but there have been advances in biology, computer science, and physics that are taught today but were not in the past. However, these kinds of improvements cannot explain increases in cost. It is no more expensive to teach new theories than old. In a few fields, one might argue that lab equipment has improved, which it certainly has, but we know from figure 1 that goods in general have decreased in price. It is much cheaper today, for example, to equip a classroom with a computer than it was in the past.
The most popular explanation why the cost of education has increased is bloat. Elizabeth Warren and Chris Christie, for example, have both blamed climbing walls and lazy rivers for higher tuition costs. Paul Campos argues that the real reason college costs are growing is “the constant expansion of university administration.” Redundant administrators are also commonly blamed for rising public school costs.
The bloat theory is superficially plausible. The lazy rivers do exist! But the bloat theory requires longer and lazier rivers every year, which is less plausible. It’s also peculiar that the cost of education is rising in both lower and higher education and in public and private colleges despite very different competitive structures. Indeed, it’s suspicious that in higher education bloat is often blamed on competition–the “amenities arms race“–while in lower education bloat is often blamed on lack of competition! An all-purpose theory doesn’t explain much.
More importantly, the data reject the bloat theory. Figure 8 shows spending shares in higher education. Contrary to the bloat theory, the administrative share of spending has not increased much in over thirty years. The research share, where you might expect to find higher lab costs, has fluctuated a little but also hasn’t risen much. The plant share which is where you might expect to find lazy rivers has even gone down a little, at least compared to the early 1980s.
Nor is it true that administrators are taking over the public schools, see Figure 10.
Compared with teachers and other staff, the number of principals and administrators is vanishingly small, only 0.4 per 100 students over the 1950–2015 period. It is true, if one looks closely, that the number of principals and administrators doubled between 1970 and 1980. It is unclear whether this is a real increase or a data artifact (we only have data for 1970 and 1980, not the years in between during this period). But because the base numbers are small, even a doubling cannot explain much. A bloated little toe cannot explain a 20-pound weight gain. Moreover, the increase in administrators was over by 1980, but expenditures kept growing.
If bloat doesn’t work, what is the explanation for higher costs in education? The explanation turns out to be simple: we are paying teachers (and faculty) more in real terms and we have hired more of them. It’s hard to get costs to fall when input prices and quantities are both rising and teachers are doing more or less the same job as in 1950.
We are not arguing, however, that teachers are overpaid!
Indeed, it is part of our theory that teachers are earning a normal wage for their level of skill and education. The evidence that teachers earn substantially above-market wages is slim. Teachers’ unions in public schools, for example, cannot explain decade-by-decade increases in teacher compensation. In fact, most estimates find that teachers’ unions raise the wage level by only approximately 5 percent. In other words, teachers’ unions can explain why teachers earn 5 percent more than similar workers in the private sector, but unions cannot explain why teachers’ wages increase over time.
If the case for unions as a cause of rising teacher compensation in public schools is weak, it is nonexistent for increased compensation for college faculty, for whom wage bargaining is done worker by worker with essentially no collective bargaining whatsoever.
A signal to where we are heading is this:
If increasing labor costs explain the increasing price of education but teachers are not overpaid relative to similar workers in other industries, then increasing labor costs must lead to higher prices in the education industry more than in other industries.
Read the whole thing. Next up, health care.
Addendum: Other posts in this series.
This paper investigates the local labor supply effects of changes to the minimum wage by examining the response of low-skilled immigrants’ location decisions. Canonical models emphasize the importance of labor mobility when evaluating the employment effects of the minimum wage; yet few studies address this outcome directly. Low-skilled immigrant populations shift toward labor markets with stagnant minimum wages, and this result is robust to a number of alternative interpretations. This mobility provides behavior-based evidence in favor of a non-trivial negative employment effect of the minimum wage. Further, it reduces the estimated demand elasticity using teens; employment losses among native teens are substantially larger in states that have historically attracted few immigrant residents.
I find that areas in which the minimum wage increases receive fewer low-wage commuters. A 10 percent increase in the minimum wage reduces the inflow of low-wage commuters by about 3 percent.
And here is one bit from a research paper by Terra McKinnish:
Low wage workers responded by commuting out of states that increased their minimum wage.
Via the excellent Jonathan Meer, you don’t hear about this evidence as much as you should.
The Persistence of Chaos is an Airgapped Samsung 10.2-Inch Blue Netbook (2008) that is running Windows XP SP3 and 6 pieces of malware that collectively caused some $95 billion in damages. One of the worms trapped on the computer, for example, is:
SoBig was a worm and trojan that circulated through emails as viral spam. This piece of malware could copy files, email itself to others, and could damage computer software/hardware. This piece of malware caused $37B in damages and affected hundreds of thousands of PCs.
The terms of sale include the following:
The sale of malware for operational purposes is illegal in the United States. As a buyer you recognize that this work represents a potential security hazard. By submitting a bid you agree and acknowledge that you’re purchasing this work as a piece of art or for academic reasons, and have no intention of disseminating any malware. Upon the conclusion of this auction and before the artwork is shipped, the computer’s internet capabilities and available ports will be functionally disabled.
The current high bid is over $1,200,750.
Hat tip: Paul Kedrosky.
During the last 50 years, the earnings of prime-age men in the United States have stagnated and dispersed across the education distribution. At the same time, the labor-force participation rates of men without a college education have steadily declined. While wage and participation trends are often linked for this population, we have argued that this connection cannot solely be the result of an inward labor demand shift across a stable and elastic labor supply curve. The uncompensated labor supply elasticities implied by the twin declines of wages and participation during the 1970s, 1980s, and 2000s appear too large to be plausible. Moreover, labor-force participation continued to decrease in the 1990s while wages were rising. While the increasing availability of disability benefits and the increase in the fraction of the population with prior incarceration exposure may help explain some of the participation decline, we doubt either factor can explain the bulk of the decline.
We have argued that more plausible explanations for the observed patterns involve feedbacks from male labor demand shocks, which often involve substantial job displacement, to worker adjustment frictions and to family structure. Marriage rates, and corresponding male labor supply incentives, have also fallen for reasons other than changing labor demand. Moreover, we have noted interactions between labor demand and disability benefit take-up, and between mass incarceration and family structure. These factors have all converged to reduce the feasibility and desirability of stable employment, leading affected men—who may not often be eligible for disability or other benefits—to participate sporadically in the labor market and depend primarily on family members for income support.
That is from the concluding remarks of Ariel J. Binder and John Bound, in the most recent Journal of Economic Perspectives. I’ll just highlight one bit again, bolded by me:
At the same time, the labor-force participation rates of men without a college education have steadily declined. While wage and participation trends are often linked for this population, we have argued that this connection cannot solely be the result of an inward labor demand shift across a stable and elastic labor supply curve.
In case you missed it.
Why have some prices increased since 1950 by a factor of four while other prices have decreased by a factor of four? Technology is making so many goods and services much cheaper than in the past–that seems to be the normal situation–so why do some industries seem not only to be not progressing but actually retrogessing? As Scott Alexander put it, why are some industries so weird?
Those are the questions that motivated my latest piece, a short book with Eric Helland just released by the Mercatus Center titled, Why are the Prices so D*mn High?
In approaching this question I had some ideas in mind. I assumed that regulation, bloat and bureaucracy, monopoly power and the Baumol effect would each explain some of what is going on. After looking at this in depth, however, my conclusion is that it’s almost all Baumol effect. That conclusion radically changes one’s evaluation of price increases and decreases over the long run and it changes what, if anything, one might try to do to address such price changes.
Next week I will examine some of the evidence that pushes me towards this verdict. I’ll also take a closer look at the Baumol effect, which is mistakenly called the cost disease.
Let’s note here, however, what we need to explain. For the most part, we don’t see quick, big changes in prices that then level off. That in itself is interesting since policy tends to be discontinuous. We might expect a big regulation, for example, to cause a big increase in prices as industries adjust but then growth should return to normal. Instead, what we see and need to explain is slow, steady rising relative prices that happens over decades. Indeed, in some cases, such as education, prices have been increasing faster than average for more than a century! Puzzle over that over the long weekend. More next week!
Addendum: Other posts in this series.
The Agriculture Department is moving nearly all its researchers into the economic effects of climate change, trade policy and food stamps – subjects of controversial Trump administration initiatives – outside of Washington, part of what employees claim is a political crackdown on economists whose assessments have raised questions about the president’s policies.
Since last year, employees in the department’s Economic Research Service have awaited news of which members of their agency would be forced to relocate, after Agriculture Secretary Sonny Perdue stunned them by declaring he was moving most of the agency to a location outside the capital. The announcement sparked claims that Perdue was trying to pressure economists into leaving the agency rather than move their families.
On March 5, the department began notifying people who were allowed to stay in Washington, but didn’t provide a comprehensive list, only telling employees in person if they made the cut.
But current and former employees compiled one anyway, covering all 279 people on staff, 76 of whom are being allowed to stay in Washington…
A USDA spokesman declined to directly address the employees’ allegation of political bias, but provided a written statement from Perdue saying that the moves were not prompted by the work being done by ERS.
In general I am reluctant to post this kind of report, because I find it difficult to know what is truly going on here, so do read this with an open mind. Still, it seemed newsworthy.
I thank John Chamberlin for the pointer.