We analyze a two-country economy with complete markets, featuring two national currencies as well as a global (crypto)currency. If the global currency is used in both countries, the national nominal interest rates must be equal and the exchange rate between the national currencies is a risk- adjusted martingale. We call this result Crypto-Enforced Monetary Policy Synchronization (CEMPS). Deviating from interest equality risks approaching the zero lower bound or the abandonment of the national currency. If the global currency is backed by interest-bearing assets, additional and tight restrictions on monetary policy arise. Thus, the classic Impossible Trinity becomes even less reconcilable.
That is a new paper from Pierpaolo Benigno, Linda Schilling, Harald Uhlig.
Russ was the interviewer, he and I both think it is the best discussion we have had of eleven (!) interactions. Here is the link. Recommended.
Some of the negative nominal premium comes from the fact that you need these govt. securities for collateral, REPOs, clearinghouse margin, etc.
That doesn’t explain *the change*, but this point is often overlooked and it makes the puzzle somewhat less mysterious.
In part, negative nominal (and real) rates reflect a scarcity of good opportunities *at the margin*, but of course inframarginal opportunities may be fine.
If you wish to try a further de-weirding of this, it may reflect a truth about agency problems rather than absolute pessimism.
If capital is relatively plentiful, and talent is super-scarce, and you don’t know how to find marginal talent, you may be stuck just storing your money. But when talent and liquidity are combined — say Mark Zuckerberg — it will earn phenomenal returns, the other side of the coin.
In other words, this may all be a kind of correlate to income inequality and massive returns for founders…
…you have extra money, you really would like to lend it out for a real productive investment, rather than storing it at slightly negative nominal interest. [savings glut, a’la Softbank]
But whom to trust? Who is your local Mark Zuckerberg? You just don’t know. The uncle you might give it to will just rip you off and he is a dope anyway. [tech talent harder to spot because you can’t rely on traditional credentials]
If the agency wedge is larger, because the talented are already occupied for the most part, you might just have to store it.
This implies mega-returns for good talent spotters, which in fact we observe as of late.
Pino Musolino, president of the Port Authority of Venice, told: “Venice port has long worked to seize the opportunities that China’s New Silk Roads strategy offers, with the aim of having positive spillovers on local business and job levels.”
On February 11, Venice signed a memo of understanding with Piraeus to improve overall capacities of the two seaports as important hubs in the Belt and Road scheme. The two port facilities had already set up a weekly ferry service last October. Venice port also has a new rail link to Duisburg, in western Germany, which is the European hub for the land-based Silk Road Economic Belt.
“In regard with the dualism between Venice and Trieste, the two ports actually service different markets,” Musolino emphasised.
“Our facility is the main gateway to industrial clusters in northern Italy, importing raw materials and exporting high-added-value products. For its part, Trieste is focused on Central and Eastern Europe.”
Musolino believes North Adriatic ports should combine their efforts to better manage increased Mediterranean trade resulting from the Belt and Road plan.
Here is the full article.
The graph at right made the twitter rounds a few days ago (1.3k RTs and 2.7k likes for Noah). The graph looked off to me immediately. Between approximately 1992 and 1994 the number of administrators went up by a factor of 4? (Or, if something goes from a 500% growth since 1970 to a 2000% growth rate since 1970, is that a factor of 3? Confusing! Anyway, a big jump.) Big jumps are often a sign that definitions, not reality, have changed. Indeed, what is an administrator?
There’s another problem with this type of graph which shows not absolute numbers but percent growth since 1970. Everything in this graph depends on getting one number, the number of administrators in 1970, exactly correct! But the first number is the one that is the farthest in the past, often the hardest to find and the most suspect. But if that first number is underestimated then every other number in the chart is overestimated.
People send me this kind of thing all the time. “See,” they say, “Why are the Prices So D*mn High is wrong! It isn’t Baumol!”–and I am always reluctant to follow-up because tracking down the underlying data, figuring out what it means, if there are mistakes etc. is a huge time sink. It was the excellent Conversable Economist who go the ball rolling on the latest iteration of this graph, however, and he cites the graph to noted health economist Uwe Reinhardt’s last book, Priced Out so I thought it could be worthwhile to go deeper.
Unfortunately, Reinhardt simply calls this a “famous graph” and it’s clear that he just found it on the internet like everyone else! Oh dear. Following up further, I did find the original Woolhandler-Himmelstein analysis written in 1991 and taking the data up to 1987. WH cite the Statistical Abstract of the United States (Table 64-2, 109th edition). You can find the SA 109th edition here but it doesn’t have the data. At least, I couldn’t find it. Ok, several hours wasted.
Finally, however, I did find a number for health administrators in an earlier edition of the SA. In the 1980 edition in Table 165, Employed Persons in Selected Health Occupations, there is a number for “Health administrators,” which says 118 thousand in 1972. Aha! Now things are beginning to make sense because from that same table there were at least 3.5 million workers (physicians, nurses, technicians and others) in health occupations and 118 thousand administrators is clearly far too low. Indeed, in a later paper Woolhandler, Campbell and Himmelstein estimate that in 1969, 18.2% of health care workers were in administration which would imply a figure of 639 thousand health administrators circa 1970, a much more plausible number.
The Woolhandler, Campbell and Himmelstein piece also finds that between 1989 and 1994 the share of health care administrators as a percent of the health care workforce increased from 25.5% to….wait for it….25.7%. In other words, no big jump and inconsistent with the huge jump seen in the graph.
It was at this point that I found Kevin Drum’s excellent analysis. Drum was also suspicious of the graph and after a lot of work he concludes that the graph exaggerates by at least a factor of 3 and probably more. Drum estimates an increase in administrators of 831%; using my initial number and Drum’s end number, I estimate an increase of 682%. All numbers to be taken with a grain of salt. Is that a big increase? Compared to what? Drum gives his best takeaway of the data as this graph, administration costs as a percent of health care costs :
I agree with Drum–this way of presenting the data looks plausible, sensible and much less sensationalist than the original graph. Note that there has been an increase in administrative costs. Why? Here’s Drum’s bottom line:
Bottom line: the health care system has grown tremendously over the past 50 years, but that’s mostly not because we have a lot more doctors. It’s because we have MRI techs and ultrasound specialists and more kinds of nurses and more kinds of pills and enormous proton beams to cure cancer. (Those proton beams are massively expensive and require large staffs, but that doesn’t mean you need any more oncologists per patient.) To manage all this new stuff, we need bigger admin and support staffs. As a result, admin and support have grown about 50-100 percent on a relative basis. That’s the real number.
I believe the original graph uses a number for administrators that is too low in 1970 and includes what I suspect was a change in definitions around 1992 (project the 1970 to 1990 line forward or the 1994 to 2009 line backward and you will get a more accurate graph.) More generally, the graph is misleading because it suggests that “administrators” are to blame for high health care costs and if only we could focus on the “real producers” of medicine, the physicians, costs would be much lower. Blaming administrators for high prices is a lot like blaming “the middlemen.” It’s easy to say and easy to tweet but blaming the middlemen reflects a naive perspective on how goods and services are actually produced in a modern economy.
Administrative costs in the United States are high compared to other countries like Canada. (Helland and I discuss this in Why are the Prices So D*mn High.) We might even be able to lower administrative costs by moving to a single-payer, universal system. But there is no free lunch and there is no returning to an administrative free Eden.
To understand why these reasonable-sounding proposals should be rejected, consider what has happened to elephant numbers since CITES most recently authorised some legal trade, when Botswana, Namibia and South Africa were allowed in 2007 to sell a fixed amount of ivory to Japan, as a one-off. Elephant numbers started falling again. A survey conducted in 2014-15 estimated that elephant numbers had fallen by 30% across 18 countries since 2007; another estimated a decline of over 100,000 elephants, a fifth of the total number, between 2006 and 2015. Increased poaching was at least partly to blame.
These numbers suggest that the existence of even a small legal market increases the incentive for poaching. It allows black-marketeers to pass off illegal ivory as the legal variety, and it sustains demand. The biggest market is in China. Last year the government banned domestic sales of ivory, but its customs officials seize a lot of smuggled products—notably from Japan, which licensed as a market in 2007. For the poachers, ivory is fungible. If it is hard to secure in Zambia or Botswana, another country’s elephants will be in the gun-sights. Congo, Mozambique and, especially, Tanzania, have seen sharp declines. Unfair though it is, countries with better-run conservation programmes are, in effect, paying for the failings of those with feeble institutions.
That is from The Economist. Yet there is another twist:
In the long run technology can help make trade compatible with conservation. In better-resourced national parks, drones are used to make it easier for rangers to spot poachers. DNA testing of ivory shipments can establish where they came from, and thus whether they are legal. As prices fall and countries get richer, both technologies are likely to spread.
Dave is an actuary, super-talented, and one of my very favorite interviewers and best prepared interviewers in the whole wide world (do say yes if he offers to interview you for his podcast).
Here is the audio, most of the questions go well beyond the usual. It starts with my book Big Business but even gets into the Straussian side of things, globalization, the price of fame, and much more.
That is the topic of my latest Bloomberg column, they chose an appropriate image, here is one excerpt:
Decay is another problem faced by Italy, including decay of its natural and cultural heritage. The city of Venice — a wonder of mankind and also a big money-maker as a tourist destination — is threatened by rising water levels. The Roman Coliseum is endangered by traffic fumes and exhaust. Solving those problems requires (again) extra money. As it stands, Italy has some of the worst-maintained cultural heritage in the Western world, and further decay could cut into Italy’s tourist income, producing another dangerous downward spiral.
There is much more at the link.
The subtitle of the paper is: “Evidence from Over 250,000 Projects and 2.5 Million Wage Bill Proposals” and here is the abstract:
We explore whether there is a gender wage gap in one of the largest EU online labor markets, PeoplePerHour. Our unique dataset consists of 257,111 digitally tradeable tasks of 55,824 hiring employers from 188 countries and 65,010 workers from 173 countries that made more than 2.5 million wage bill proposals in the competition for contracts. Our data allows us to track the complete hiring process from the employers’ design of proposed contracts to the competition among workers and the final agreement between employers and successful candidates. Using Heckman and OLS estimation methods we provide empirical evidence for a statistically significant 4% gender wage gap among workers, at the project level. We also find that female workers propose lower wage bills and are more likely to win the competition for contracts. Once we include workers’ wage bill proposals in the regressions, the gender wage gap virtually disappears, i.e., it is statistically insignificant and very small in magnitude (0.3%). Our results also suggest that female workers’ higher winning probabilities associated with lower wage bill proposals lead to higher expected revenues overall. We provide empirical evidence for heterogeneity of the gender wage gap in some of the job categories, all job difficulty levels and some of the worker countries. Finally, for some subsamples we find a statistically significant but very small “reverse” gender wage gap.
Here is the paper by Estrella Gomez Herra and Frank Mueller-Langer, via Luke Froeb.
According to a Vulture article, Comenos then put together a squad of researchers in India to do the same thing: comb the trashiest ends of the web for iffy tweets, racial slurs and ill-advised sexts sent by about 27,000 prominent figures. These are then fed to a team of data specialists in Boston who crunch the numbers, based on 224 factors, and generate a “risk score” out of 100 for each person to gauge how close they are to getting permanently cancelled (shamed, rejected or boycotted for offensive behaviour or language).
Comenos’s company is called SpottedRisk: a “disgrace insurer” backed by Lloyds of London and touting for business from studios and brands badly burned by a celebrity shooting themselves in the foot – and damaging whatever project they were involved in. These losses have been substantial. Tiger Woods’ 2009 car crash, plus revelations about his infidelities, cost him $22m in brand contracts – and the shareholders of those brands up to $12bn. Meanwhile,#MeToo has escalated Hollywood blacklisting. After sexual abuse allegations against Kevin Spacey in 2017, Ridley Scott reshot the thriller All the Money in the World with Christopher Plummer in Spacey’s role – at a cost of $10m. Another Spacey movie, The Billionaire’s Boys Club, ploughed on with its planned release regardless of increasing public disgust at its star. It made £98 on its opening night.
SpottedRisk says its payout for Spacey would be about $8m – a number generated by combining his risk score with its “outcry index” to gauge public reaction. Bill Cosby and Harvey Weinstein would merit $10m payouts, while Roseanne Barr is relatively small change at $6m.
Here is the full Catherine Shoard article, via Michael, note that Donald Trump and R. Kelly are considered “uninsurable.”
We are now well into another housing boom but as shown by Aasteveit, Albuquerque and Anundsen this boom is in some ways worse than the previous 1996-2006 boom because the supply response has been lower. The first figure, for example, shows that since the trough in 2012 house prices have risen a little bit faster in this boom than in the 1996-2006 boom and they have risen much faster relative to income (HPI is housing price index).
Over the same time, however, the number of new building permits and housing starts has been lower than in the previous boom (top two panels of figure 2 below). If prices have gone up as much as before but quantity has not, it follows that the elasticity of housing supply has fallen. Occasionally it’s suggested that there is an “overhang” of housing from the previous boom but that is not true. If anything, as shown in the bottom left panel, there is a decline in the housing stock relative to population.
The authors suggest that one reason why the elasticity of housing supply has fallen is that developers are fearful of being hit in another bust. I find that implausible. Developers don’t hold onto their stock for very long and often sell even before completion so they worry at most about a year or so forward. A better explanation is that housing supply remains especially constrained in the coastal cities by regulation and limited land capacity and those constraints are becoming more binding over time–in other words, the previous boom filled the infill. It may also be the case that fear of the bust is increasing regulation as people worry even more about downward fluctuations in the price of their primary asset.
Either way, housing continues to eat the world.
One of the more important things I’ve changed my mind about recently is the best cause to donate to. I now put the most credence on the possibility that the best option is donating to a fund that invests the money and disburses strategically in the future. I will refer to this as “giving later”, though I actually support giving now to a donor-advised fund set up to disburse in the future, for the value that donating now can have for encouraging others to donate (and because of the risk that even if one thinks one will donate later, one will at some point change one’s mind).
There are several reasons why I prefer a fund that disburses in the future. First, I believe people currently discount the future too much (see hyperbolic discounting, climate change). If people discount the future, that causes the rate of return on investments to always be higher than the growth rate (else people would not be willing to invest). In economics, the Ramsey equation is often used to determine how much a social planner should discount future consumption. It is specified by r=ηg+δ, where r is the real rate of return on investment, η is the extent to which marginal utility decreases with consumption, g is the growth rate, and δ represents pure time preferences. Unless one personally puts a particularly high value on δ, it makes sense to invest today and spend later to take advantage of the gap between the real rate of return on investment (~7%) and the growth rate (~3-4%).
…A second reason that I prefer a fund that disburses in the future is that I think we have very limited knowledge today and that our knowledge is increasing. I am concerned about the problem that research results do not generalize all that well, but with respect to economic development I am optimistic that the situation can improve. With respect to technological change which could bring huge benefits or risks, I think we know even less about the problems future generations will face and may be able to understand them better in the future. It seems unlikely to me that we are at the exact moment in time, out of all periods of time from here on out into the future, that we actually have the best opportunity to do good. We may not recognize the best moment when it comes, but that just pushes the argument back a step: I also think it unlikely that we are at the best moment, out of the whole foreseeable future, to have the best combination of knowledge and opportunity to do good.
Interesting throughout, here is the link, and in sum:
I think it appeals psychologically to many people – myself included – to think that we are living at a particularly important time. However, I recognize that people have thought this throughout history. As more time has passed, I have become increasingly confident that my gut antipathy to the idea that it’s better to “give later” is just a cognitive bias.
In an insightful paper with human interest but also public policy implications Jasmin Barman-Aksözen writes:
My parents and I searched throughout my entire childhood for an explanation of why I frequently had unbearable burning pain after spending even short periods of time outdoors on a sunny day. This pain was incapacitating and often left me in agony for days, during which I was unable to go to school, to sleep, to tolerate even weak light exposure, or the body heat of my parents as they tried to comfort me. Not a single pain killer provided any relief, and the only option for me was to wait alone in a darkened and cooled room until the pain sub-sided. Of course, we tried everything that physicians recommended; still, not even high sun protection factor sunscreens helped prevent the symptoms despite the fact that they were obviously caused by sunlight. It must have been hard for my parents to see me in such a painful state without being able to alleviate or prevent it. What’s more, the worst thing was that classmates, teachers, and even physicians did not believe me when I told them about the symptoms; I even brought photographs showing myself with swollen and burnt hands and face. Yet, this didn’t stop some from making fun of me when I wore long clothing, hats, or used an umbrella on sunny days to protect myself from the sun’s rays. Eventually, after I was sent to see a psychologist for my “made-up symptoms,” I could no longer tolerate the derision and being treated with such condescension, and decided to stop sharing my experiences with healthcare professionals altogether.
Finally, a full 26 years after the first symptoms, Dr Google provided the answer! In April 2006, I found myself yet again unable to sleep because, despite all precautionary measures taken, I had burnt myself in the strong sunlight of spring. I entered the combination of my symptoms in the Google search mask and, surprisingly, there was a new link in Wikipedia with an expression I had not encountered before “Erythropoietic Protoporphyria.”
The made-for-tv aspect continues as Barman-Aksözen earns a PhD, moves to Switzerland to join the world’s leading lab studying these issues and, yes, develops the first effective treatment!
Afamelanotide was approved for the treatment of adult EPP patients in the European Union (EU) at the end of 2014.
But now is where reality and public policy step back in.
In April 2019, most EPP patients in Europe, however, still do not have access to the only treatment for their condition and are still unnecessarily suffering from fre-quent excruciating pain, social isolation, and impaired life choices. What went wrong? Before a newly approved medicine reaches patients, most European countries per-form a Health Technology Assessment (HTA) to evaluate the benefits in relation to the costs of the new product in order to support decisions on whether it should be reimbursed by the respective national health systems.
Getting the drug approved is only the first step. Now they have to get the medical authorities to pay for it and that means they have to show the drug is not only effective but cost effective given the disability. Barman-Aksözen goes on to describe her efforts to get the drug approved for actual use. She doesn’t put it this way but essentially she has to solve the collective action problem and form a lobbying group to make the case that patients with her disease, EPP, face a serious disability. It’s easy to measure death, however, but hard to measure the “disability weight” on say blindness. The WHO says blindness has a disability weight of .195 today, but in 2004 they gave it a weight of 0.594. Hmmm. One study of Afamelanotide suggests it has a cost of £373,000 per DALY averted, which is high, even though the article recommends adoption. Many meetings ensue in which the case for and against Afamelanotide is made. The process is slow. Years go by. Much depends on seemingly minor choices in how to present the data.
I was reminded of Mancur Olson’s discussion in the Rise and Decline of Nations:
Distributional coalitions make decisions more slowly than the individuals and firms which they comprise [and] tend to have crowded agendas and bargaining tables…The accumulation of distributional coalitions increases the complexity of regulation, the role of government, and the complexity of understandings, and changes the direction of social evolution.
In other words, socializing health care means socializing decisions about how to allocate health care. A difficult tradeoff.
Addendum: The FDA has yet to approve Afamelanotide.
Hat tip: Joe P.
I am pleased to have made the longlist (FT link) with my Big Business: A Love Letter to an American Anti-Hero*.