Lots of fire! Here is the podcast link.
That is the topic of my latest Bloomberg column, here is one excerpt:
From about 1973 to 1985, Israel had very high rates of inflation at one point reaching over 400%. That was the result of excessively loose monetary policy. Over time, printing money at such a clip took in successively less government revenue, as Israelis adjusted to the inflation and worked around it by holding less cash and denominating their contracts in foreign currencies. The inflation stopped giving macroeconomic benefits, even for government revenue, and Israel moved toward a regime of lower inflation and fiscal strength, to the benefit of the country’s longer-term growth.
This is a classic episode of MMT — “Modern Monetary Theory” — getting it wrong, as argued by Assaf Razin in his recent study of Israeli macroeconomic history. Under MMT, monetary policy can cover government spending, and fiscal policy can regulate price levels. Israel wisely followed more mainstream approaches.
Even many of the microeconomic developments in Israel fit standard models. As you might expect, given the aridity of the region, Israel has had longstanding issues with water supply. Yet today water is not a huge practical problem in Israel, though it requires constant attention. Under the Israeli water regime, which has strong governmental support, high prices and well-defined property rights encourage conservation and careful use. Remarkably, the Israeli population basically quadrupled from 1964 to 2013, but water consumption barely went up. Israel has become a world leader in dealing with water problems, and in turn the country has become an exporter of sophisticated systems for water management.
There is much more at the link, and note Israel is neo-liberal only in some ways, see this earlier link I put up (which I link to in the piece).
Recent research suggests that rates of extreme poverty, commonly defined as living on less than $2/person/day, are high and rising in the United States. We re-examine the rate of extreme poverty by linking 2011 data from the Survey of Income and Program Participation and Current Population Survey, the sources of recent extreme poverty estimates, to administrative tax and program data. Of the 3.6 million non-homeless households with survey-reported cash income below $2/person/day, we find that more than 90% are not in extreme poverty once we include in-kind transfers, replace survey reports of earnings and transfer receipt with administrative records, and account for the ownership of substantial assets. More than half of all misclassified households have incomes from the administrative data above the poverty line, and several of the largest misclassified groups appear to be at least middle class based on measures of material well-being. In contrast, the households kept from extreme poverty by in-kind transfers appear to be among the most materially deprived Americans. Nearly 80% of all misclassified households are initially categorized as extreme poor due to errors or omissions in reports of cash income. Of the households remaining in extreme poverty, 90% consist of a single individual. An implication of the low recent extreme poverty rate is that it cannot be substantially higher now due to welfare reform, as many commentators have claimed.
That is from a new NBER working paper by Bruce D. Meyer, Derek Wu, Victoria R. Mooers, and Carla Medalia.
Perhaps the biggest complaint about tech companies today is that they do not respect our privacy. They gather and store data on us, and in some cases, such as Facebook, they charge companies for the ability to send targeted ads to us. They induce us to self-reveal on the internet, often in ways that are more public than we might at first expect. Furthermore, tech data practices are not entirely appropriate, as for instance Facebook recently stored user passwords in an insecure, plain text format.
This entire debate is overblown, and the major tech companies are much less of a threat to our actual privacy than is typically assumed.
For most people, gossip from friends, relatives, colleagues, and acquaintances is a bigger privacy risk than is information garnered on-line. Gossip is an age-old problem, and still today many of the biggest privacy harms come through very traditional channels. And unlike false charges planted on social media, often there is no way to strike back against secretive whisperings behind one’s back. In the workplace, one employee may tell the boss that another employee does not work hard enough, or high school gossip may destroy reputations and torment loners and non-conformists, to give two common examples of many.
If anything, the niche worlds made possible by the internet, and yes by Facebook and Google, are giving many people refuges from those worlds of public scrutiny and mockery – you can more easily find the people who and like respect you for what you really are.
Life in small towns and rural areas is another major threat to privacy – too often everybody knows everybody else’s business. In contrast, if you live in a major city or suburban area, you have a much greater ability to choose whom you interact with, and you are more protected from the prying of your neighbors and relatives. And it seems that so far, contrary to some initial “death of distance” predictions, the internet has encouraged people to move to major urban centers such as New York and San Francisco. To that extent, internet life has boosted privacy rather than destroying it.
There’s also evidence that young Americans are having less sex these days and they are less likely to be in a serious relationship. The internet is likely one cause of that isolation, and in my view those changes are probably social negatives on the whole, and they represent a valid criticism of on-line life. But is the internet in this regard boosting privacy? Absolutely. The internet makes it much easier to be in less contact with other people, whether or not that is always wise or the best life course overall. It strikes me as odd when the same people blame the internet for both loneliness and privacy destruction.
A lot of actual privacy problems in the public arena don’t seem to attract much attention, unless they are tied into a critique of big tech. For instance, autocratic governments are using Interpol and its police powers and databases (NYT) to track down and apprehend ostensible criminals who are in fact sometimes merely domestic political dissidents. It is likely that many innocent individuals have ended up in jail (can the same be said from social media violations of privacy?) That’s an example of using databases for truly evil ends and, while it was covered by The New York Times (p.A10), it is hardly a major story.
It is striking to me how much the advocates focus on regulating the big tech companies, because a true pro-privacy movement might not have that as a priority at all.
By the way, how do you feel about obituaries? The newspaper collects information on you for years, and then suddenly one day they publish it all and then keep it on the web, whether you like this or not. They’ll even throw in snide remarks, sarcastic tone, or moral judgments about you, depending on the outlet of course.
If the privacy landscape is so complex, why then is there so much anger at Facebook and other social media companies? First, most users of services such as Facebook and Google are actually pretty happy with those services and with the companies. Some of the opposition is coming from intellectuals with core anti-business grudges, politicians looking to get headlines, or often from media itself, who face Google and Facebook as major and far more profitable competitors.
Second, social media themselves create contagion effects, whereby attention is piled on a relatively small number of select victims. For instance, the #MeToo campaign has focused condemnation on a small set of offenders, such as Harvey Weinstein, then magnified by Twitter and other social media. Many other offenders get off scot-free, simply because attention has not been directed their way. Ironically, one of the better arguments against social media is to look at how social media treat and discuss social media itself. On the privacy issue, Facebook rather than say Google has ended up as the main whipping boy, even though it might have gone the other way (who again controls your gmail?). Ironically, perhaps the actual best argument about social media is how social media reflexively covers social media itself.
Third, many of the supposed concerns about privacy are perhaps questions of control. It is correct that the major tech companies do “funny things” with our data which we neither see nor understand nor control.This unsettles many people, even if it never means that some faux pas of yours is revealed in front of a party of your mocking friends. Still, I am not sure the underlying notion of “control” here has been satisfactorily defined. Many marketers, and not just on the internet, do things you do not control or even know about. Furthermore, see Jim Harper on privacy, who covers security, seclusion, autonomy, and absence of objectification as some of the different features of privacy concerns.
Of course, just as privacy violations do not stem mainly from the big tech companies, we have never been in control of what is done with information and opinion about us, again think back on social gossip. This fundamental lack of control is just now being pushed in our faces in new and unexpected ways. In part it is actually unsettling, but in part we also are overreacting.
Privacy is a real issue, but to the extent it can be fixed, most of that needs to happen outside of the major tech companies. Most of what is written about tech and privacy is simply steering us down the wrong track.
The podcast master himself, here is the audio and transcript, here is the opening summary:
What are the virtues of forgiveness? Are we subject to being manipulated by data? Why do people struggle with prayer? What really motivates us? How has the volunteer army system changed the incentives for war? These are just some of the questions that keep Russ Roberts going as he constantly analyzes the world and revisits his own biases through thirteen years of conversations on EconTalk.
Russ made his way to the Mercatus studio to talk with Tyler about these ideas and more. The pair examines where classical liberalism has gone wrong, if dropping out of college is overrated, and what people are missing from the Bible. Tyler questions Russ on Hayek, behavioral economics, and his favorite EconTalk conversation. Ever the host, Russ also throws in a couple questions to Tyler.
Here is one excerpt:
COWEN: Here’s a reader question. “In which areas are you more pro-regulation than the average American?” They mean government regulation.
ROBERTS: Than the average American?
ROBERTS: I can’t think of any. Can you help me out there, Tyler?
COWEN: Well, I’m not sure I know all of your views.
ROBERTS: What would you guess? Give me some things to think about there. In general, I think government should be smaller and regulations should be smaller.
COWEN: I’ll give you–
ROBERTS: Let me give you a trick answer. Then I’ll let you feed me some.
ROBERTS: Many people believe that the financial crisis was caused by deregulation. I think that’s a misreading of the evidence. It’s true that some pieces of the financial sector were deregulated, but government intervention in the financial sector was quite significant in advance of the crisis. In particular, the bailouts that we did of past failed financial institutions, I think, encouraged lenders to be more careless with how they lent their money, mainly to other institutions, not so much to people out in the world like you and me.
Deregulation’s a little bit tricky, so I wanted to get that in. I’m not sure how that pertains to the question. It does, probably, in some way. So give me something I should be more regulatory about.
COWEN: Well, one answer —
ROBERTS: Baseball? Baseball, of course. [laughs]
COWEN: I would say animal welfare — government should have a larger role. But also what counts as a tax-exempt institution, I would prefer our government be stricter.
ROBERTS: Well, I’m with you there. Yeah, okay, kind of.
COWEN: Well, that’s more regulation, okay?
ROBERTS: I guess.
COWEN: Kind of.
ROBERTS: Yeah, kind of. It’s different standards.
COWEN: Higher capital requirements for banks.
ROBERTS: I’m okay with that. Yeah, that’s a good one. I’d prefer a laissez-faire world for banks, more or less. If we can’t credibly promise not to bail out banks — if that’s the case, we live in a world where banks get to keep their profits and put their losses on taxpayers — bad world. A more regulated world would be better than the world we live in; not as good as my ideal world, though. But there’s a case where I would be in favor — like you just said — more capital requirements.
You’re on a roll. See what else you can come up with for me.
COWEN: Spending more money for tax enforcement, especially on the wealthy.
ROBERTS: Not the worst thing in the world.
COWEN: You can spend a dollar and bring in several times that, it seems.
ROBERTS: I don’t think rich people cheat on their taxes. Do you? [laughs]
COWEN: “Cheat” is a tricky word, but I think we could spend more money.
ROBERTS: We could probably collect more effectively.
COWEN: And it would more than pay for itself.
ROBERTS: Yeah. That’s probably true.
COWEN: We’re actually big fans of government regulation today.
ROBERTS: Yeah, we’ve really expanded the tent here. [laughs]
Do read or listen to the whole thing.
Taiwan may be small, but the island has emerged as a financial superpower thanks to the thriftiness of local savers and an eye-watering current account surplus of about 15 per cent of gross domestic product. The country now has the second-largest financial system in the world, relative to gross domestic product. And its life insurance industry is the biggest, with assets-to-GDP of 145 per cent, according to JPMorgan.
The local economy is not big enough to accommodate these enormous sums, so Taiwanese financial institutions have funnelled a whopping $1.2tn abroad.
…Taiwanese insurers hold about 4 per cent of the entire US investment-grade corporate bond market, and 14 per cent of longer-term corporate bonds, according to JPMorgan. Insurers’ holdings of US mortgage-backed securities have nearly doubled over the past five years, to $260bn. That makes Taiwan the second-biggest foreign owner of such securities.
Here is the FT piece by Robin Wigglesworth.
I explained the Baumol effect in an earlier post based on Why Are the Prices So D*mn High?. In this post, I want to point out some special features of the Baumol effect that help to explain the data. Namely:
- The Baumol effect predicts that more spending will be accompanied by no increase in quality.
- The Baumol effect predicts that the increase in the relative price of the low productivity sector will be fastest when the economy is booming. i.e. the cost “disease” will be at its worst when the economy is most healthy!
- The Baumol effect cleanly resolves the mystery of higher prices accompanied by higher quantity demanded.
First, in the literature on rising prices it’s common to contrast massive increases in spending with little to no increases in quality, as for example, in contrasting education expenditures with mostly flat test scores (see at right). We have spent so much and gotten so little! Cui Bono? It must be teacher unions, administrators or the government!
All of that could be true but the Baumol effect predicts that more spending will be accompanied by no increase in quality. Go back to the classic example of the string quartet which becomes more expensive because labor in other industries increases in productivity over time. The price of the string quartet rises but does anyone expect that the the quality rises? Of course not. In the classic example the inputs to string quartet playing don’t change. The wages of the players rise because of productivity increases in other industries but we don’t invest any more real resources in string quartet playing and so we should not expect any increases in quality.
In just the same way, to the extent that greater spending on education, health care, or car repair is due to the rising opportunity costs of inputs we should not expect any increase in quality. (Note that increases in real resource use such as more teachers per student should result in increases in quality (and perhaps they do) but by eliminating the price increase portion of the higher spending we have eliminated a large portion of the mystery of higher spending with no increase in quality.)
Second, explanations of rising prices that focus on bad things such as monopoly power or rent seeking tend to imply that price increases should be largest when the economy is doing poorly. In contrast, the Baumol effect predicts that increases in relative prices will be largest when the economy is booming. Consider health care. From news reports you might think that health care costs have gotten more “out of control” over time. In fact, the fastest increases in health care costs were in the 1960s. The graph at left is on a ratio scale so slopes indicate rates of growth and what one sees is that the growth rate of health expenditures per person is slowing. That might seem good but remember, from the Baumol point of view, the decline in relative price growth reflects slowing growth elsewhere in the economy.
Third, holding all else equal, the only rational response to an ordinary cost increase is to substitute away from the good. But in many rising price sectors we see not only greater expenditures (driven by increased prices and inelastic demand) but also greater quantity demanded. As I showed earlier, for example, we have increased the number of doctors, nurses and teachers per capita even as prices have risen. John Cochrane correctly noted that this is puzzling but it’s a bigger puzzle for non-Baumol theories than for Baumol. For non-Baumol theories to explain increases in the quantity purchased, we need two theories. One theory to explain the increase in price (bloat/regulation etc.) and another theory to explain why, despite the increase in price, people are still purchasing more (e.g. income effect). The world is a messy place and maybe that is what is happening. But the Baumol effect offers a cleaner answer.
A Baumol increase in relative price is always accompanied by higher income so it’s much easier to explain how price increases can accompany increases in quantity as well as increases in expenditure. The Baumol story for increased purchase of medical care even as prices increase, for example, is no more mysterious than why people can take more leisure when wages increase–namely the higher wage means a higher income for any given hours and people choose to take some of this higher income in leisure. Similarly, higher productivity in say goods production increases income at any given production level and people choose to take some of this higher income in services.
Summing up, if we examine each sector–education, health care, the arts, etc.–on its own then there are always many possible explanations for why prices might be increasing. Many of these explanations have true premises–there are a lot of administrators in higher education, health care is highly regulated, lower education is government run. But, on closer inspection the arguments often don’t fit the data very well. Prices were increasing before administrators were important, health care is highly regulated but so is manufacturing, private education is also increasing in price, the arts are not highly regulated. It’s impossible to knock down each of these arguments in every industry, so there is always room for doubt. Indeed, the great difficult is that these factors often do result in higher costs and greater inefficiency but I believe those are predominantly level effects not effects that accumulate over time. Moreover, when one considers the rising price industries as a whole these explanations begin to look ad hoc. In contrast, the Baumol effect appears capable of explaining the pricing behavior of a wide variety of industries over a long period of time using a simple but powerful and unified theory.
Addendum: Other posts in this series.
Here are various links, Kevin we shall miss ye…it’s not your grandpa’s Trump administration anymore…
We briefly cover higher education in Why Are the Prices So D*mn High? If you are interested in a longer treatment that covers many more issues I highly recommend Archibald and Feldman’s The Road Ahead for America’s Colleges & Universities. Archibald and Feldman reach the same conclusion we do with regard to dysfunction versus the cost disease:
We have offered two contending viewpoints about the drivers of college cost, and we have made a judgement between them. The dysfunction stories form the dominant narrative in public discussion, but we think it’s a story with weak foundations. Yet we agree that the status quo likely costs more than it could or perhaps should. You might notice that we mounted no defense of lazy rivers. Still, the cost consequences of true excesses probably are small. The major drivers of college costs are as follows (1) higher education is a service, and productivity growth in services lags productivity growth in goods; (2) higher education relies on highly educated service providers, and the income gap in favor of highly-educated workers has grown; and (3) higher education institutions adopt technology to meet a standard of care, even if meeting that standard pushes up cost.
In addition to discussing costs, Archibald and Feldman look at the demand for college, the role of the federal and state governments, online education, policy proposals such as free college and much more. Throughout their book they are data driven, analytic, and judicious.
As incentives to take higher actions increase—due to higher stakes or more manipulable signaling technology—more information is revealed about gaming ability, and less about natural actions. We explore a new externality: showing agents’ actions to additional observers can worsen information for existing observers. Applications to credit scoring, school testing, and web searching are discussed.
That is from a forthcoming JPE paper “Muddled Information,” by Alex Frankel and Navin Kartik.
Using twenty years of earnings data on Finnish twins, we find that about 40% of the variance of women’s and little more than half of men’s lifetime labour earnings are linked to genetic factors. The contribution of the shared environment is negligible. We show that the result is robust to using alternative definitions of earnings, to adjusting for the role of education, and to measurement errors in the measure of genetic relatedness.
That is from a newly published paper by Ari Hyytinen, Pekka Ilmakunnas, Edvard Johansson, and Otto Toivanen.
The social and the private returns to education differ when education can increase productivity and also be used to signal productivity. We show how instrumental variables can be used to separately identify and estimate the social and private returns to education within the employer learning framework of Farber and Gibbons (1996) and Altonji and Pierret (2001). What an instrumental variable identifies depends crucially on whether the instrument is hidden from or observed by the employers. If the instrument is hidden, it identifies the private returns to education, but if the instrument is observed by employers, it identifies the social returns to education. Interestingly, however, among experienced workers the instrument identifies the social returns to education, regardless of whether or not it is hidden. We operationalize this approach using local variation in compulsory schooling laws across multiple cohorts in Norway. Our preferred estimates indicate that the social return to an additional year of education is 5%, and the private internal rate of return, aggregating the returns over the life-cycle, is 7.2%. Thus, 70% of the private returns to education can be attributed to education raising productivity and 30% to education signaling workers’ ability.
That is from a new NBER Working Paper by Gaurab Aryal, Manudeep Bhuller, and Fabian Lange. You can enter “education signaling” into the MR search function for much more on this ongoing debate.
After looking at education and health care and doing a statistical analysis covering 139 industries, Helland and I conclude that a big factor in price increases over time in the rising price of skilled labor. Many industries use skilled labor, however, and even so prices decline so that cannot be a full explanation. Moreover, why is the price of skilled labor increasing? The Baumol effect answers both of these questions. In this post, I’ll explain the effect drawing from Why Are the Prices so D*mn High.
The Baumol effect is easy to explain but difficult to grasp. In 1826, when Beethoven’s String Quartet No. 14 was first played, it took four people 40 minutes to produce a performance. In 2010, it still took four people 40 minutes to produce a performance. Stated differently, in the nearly 200 years between 1826 and 2010, there was no growth in string quartet labor productivity. In 1826 it took 2.66 labor hours to produce one unit of output, and it took 2.66 labor hours to produce one unit of output in 2010.
Fortunately, most other sectors of the economy have experienced substantial growth in labor productivity since 1826. We can measure growth in labor productivity in the economy as a whole by looking at the growth in real wages. In 1826 the average hourly wage for a production worker was $1.14. In 2010 the average hourly wage for a production worker was $26.44, approximately 23 times higher in real (inflation-adjusted) terms. Growth in average labor productivity has a surprising implication: it makes the output of slow productivity-growth sectors (relatively) more expensive. In 1826, the average wage of $1.14 meant that the 2.66 hours needed to produce a performance of Beethoven’s String Quartet No. 14 had an opportunity cost of just $3.02. At a wage of $26.44, the 2.66 hours of labor in music production had an opportunity cost of $70.33. Thus, in 2010 it was 23 times (70.33/3.02) more expensive to produce a performance of Beethoven’s String Quartet No. 14 than in 1826. In other words, one had to give up more other goods and services to produce a music performance in 2010 than one did in 1826. Why? Simply because in 2010, society was better at producing other goods and services than in 1826.
The 23 times increase in the relative price of the string quartet is the driving force of Baumol’s cost disease. The focus on relative prices tells us that the cost disease is misnamed. The cost disease is not a disease but a blessing. To be sure, it would be better if productivity increased in all industries, but that is just to say that more is better. There is nothing negative about productivity growth, even if it is unbalanced.
In this post, I will discuss some implications of the fact that productivity is unbalanced. See the book for more discussion and speculation about why productivity growth is systematically unbalanced.
The Baumol effect reminds us that all prices are relative prices. An implication is that over time prices have very little connection to affordability. If the price of the same can of soup is higher at Wegmans than at Walmart we understand that soup is more affordable at Walmart. But if the price of the same can of soup is higher today than in the past it doesn’t imply that soup was more affordable in the past, even if we have done all the right corrections for inflation.
We can see this in the diagram at right. We have a two-good economy, Cars and Education. The production possibilities frontier shows all the combinations of Cars and Education that we can afford given our technology and resources at time 1 (PPF 1). Now suppose society chooses to consume the bundle of goods denoted by point (a). The relative price of Cars and Education is given by the slope of the PPF at that point. That price/slope tells us if we give up some education how many more cars can we get? In a market economy the price has to be given by the slope of the PPF because that is the only price at which people will willing consume the bundle of goods at point (a), i.e. it’s the equilibrium price.
Now at time 2, productivity has increased which means that with the same resources we can now have more of both goods. Productivity of Car production has increased more than that of Education production, however, so the curve shifts out more towards Cars than towards Education. Suppose society continues to consume Cars and Education in the same proportions, i.e. at point (b). The price of education must increase–and all that means is that if we give up a unit of education at point b we will get more cars than before which is the same as saying that if we want more education at point b we must give up more cars than before, i.e. the price has increased.
Notice, however, that although the price of education has increased, education is not less affordable. Indeed, at point (b) we are consuming more of both goods–broadly speaking this is exactly what has happened–namely, the price of education has increased and we now consume more of it than ever before.
When we recognize that all prices are relative prices the following simple yet deep facts follow:
- If productivity increases in some industries more than others then, ceteris paribus, some prices must increase.
- Over time, all real prices cannot fall.
In Figure 22 the economy moves from point (a) to point (b). If we graph the same transition over time it will look something like Figure 23.
Looking at such graphs, our attention naturally is drawn to the rising cost of education. Why are costs rising so quickly? Entranced by such graphs, we may enter into a detailed analysis of the special factors of education—regulation, unionization, government purchases, insurance, international trade, and so forth—to try to explain the dramatic increase in costs. Yet the rising costs in the education sector are simply a reflection of increased productivity in the car sector. Thus, another deep lesson of the Baumol effect is that to understand why costs in the stagnant sector are rising, we must look away from the stagnating sector and toward the progressive sector.
Finally, there is one other addition to the Baumol effect which is not often recognized but worth drawing attention to. In Figure 22, I assumed that preferences were such that people wanted to consume the same ratio of goods over time so we moved from point (a) to point (b). But suppose that as we get wealthier we get tired of more cars and would like relatively more education so we move towards point (d). As we move from point (b) to point (d) we are taking resources away from car production, resources which were probably well-suited to making cars, and instead moving them towards education where they are probably less well suited. As a result as we move from point (b) to point (d) we are driving up the price of education as we try to turn auto workers into teachers. In this case, the Baumol effect gets magnified. We could alternatively move from point (b) to point (c) which would turn teachers into less productive auto workers thus driving down the price of education (i.e. increasing the price of cars). Thus, depending on preferences, the Baumol effect can be magnified or ameliorated.
As a society it appears that with greater wealth we have wanted to consume more of the goods like education and health care that have relatively slow productivity growth. Thus, preferences have magnified the Baumol effect.
Next week, I will wrap up the discussion by explaining some features of the data that the Baumol effect fits much better than do other theories.
Addendum: Other posts in this series.
In this paper, I estimate the causal effect of increased exposure to online social networks during college on future labor market outcomes.
Using quasi-random variation from Facebook’s entry to college campuses during its infancy, I exploit a natural experiment to determine the relationship between online social network access and future earnings.
I find a positive effect on wages from Facebook access during college. This positive effect is largest in magnitude for female students, and students from lower-middle class families.
I provide evidence that this positive effect from Facebook access comes through the channel of increased social ties to former classmates, which in turn leads to strengthened employment networks between college alumni.
My estimates imply that access to Facebook for 4 years of college causes a 2.7 percentile increase in a cohort’s average earnings, relative to the earnings of other individuals born in the same year. This translates to an average nominal wage increase of $3,000-$5,000 in 2014.
To be clear, some of that could be a wage distribution effect. Still, this paper points to the possibility of some very real networking and matching gains from the use of Facebook, and perhaps those gains do not favor traditional elites.
For the pointer I thank the excellent Kevin Lewis.
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.