Life expectancy at birth is not a predictor of health care efficiency…

This is going to be a short post to argue that pundits (and some economists) need to stop quoting life expectancy figures to argue for/against a particular health care system. This belief is best exemplified in a recent paper in the Journal of the American Medical Association where Papanicolas et al. (2018)  point out that the United States “spent nearly twice as much as 10 high-income countries (…) and performed less well on many population health outcomes”. While the authors make good points about administrative costs, they point out that the US has a low level of life expectancy.

Sure, that is actually true – but Americans tend to die in greater proportions from homicides, drug overdoses and car accidents (Americans drive more than Europeans) than in other rich countries. While these factors of mortality are tragic (except car accidents since Americans seem to prefer the benefits of mobility to the safety of not driving), they are in no way related to the efficiency of health care provision. How much of a deal are these in explaining differences with other industrialized countries? A pretty big deal.  For example, these three factors alone account for 64% of the male life expectancy gap between Austria and the United States (see table reproduced below). For women, 26% of the gap between Austria and the United States is explained by these three factors.

The study I cite here only includes three factors. If you add in other factors like drownings among youths (Americans tend to have more drownings than several industrialized countries) which is a result of the fact that Americans are richer and can afford pools (while Europeans tend not to), then you keep explaining away the difference.  This is not to say that American health care is great. However, this says that American health care is not as bad as life expectancy outcomes suggest.

Mortality

 

In health care, expenditures to GDP may be misleading!

In debates over health care reform in the US, it is frequent for Canada’s name to pop up in order to signal that Canada is spending much less of its GDP to health care and seems to generate relatively comparable outcomes. I disagree.

Its not that the system presently in place in the US is so great, its that the measure of resources expended on each system is really bad. In fact, its a matter of simple economics.  Imagine two areas (1 and 2), the first has single-payer health care, the other has fully-private health care.

In area 2, prices ration access to health care so that people eschew visits to the emergency room as a result of a scraped elbow. In area 1, free access means no rationing through price and more services are consumed. However, to avoid overspending, the government of area 1 has waiting lists or other rationing schemes. In area 2, which I have presented as an ideal free market for the sake of conversation,  whatever people expend can be divided over GDP and we get an accurate portrait of “costs”. However, in area 1, costs are borne differently – through taxes and through waiting times. As such, comparing what is spent in area 1 to what is spent in area 2 is a flawed comparison.

So when we say that Canada spends 10.7% of GDP on health care (2013 numbers) versus 17.1% of GDP in the US, is it a viable comparison? Not really.  In 2008, the Canadian Medical Association produced a study evaluating the cost of waiting times for four key procedures : total joint replacement surgery, cataract surgery, coronary artery bypass
graft (CABG) and MRI scans. These procedures are by no means exhaustive and they concern only “excessive” waiting times (rather than the whole waiting times or at least the difference with the United States). However, the CMA found that, for the 2007 (the year they studied), the cost of waiting was equal to 14.8$ billion (CAD).  Given the size of the economy back in 2007, this represented 1.3% of GDP. Again, I must emphasize that this is not an exhaustive measure of the cost of waiting times. However, it does bring Canada closer to the United States in terms of the “true cost” of health care.  Any estimate that would include other wait times would increase that proportion.

I know that policy experts are aware of that, but it is so frequent to see comparisons based on spending to GDP in order to argue for X and Y policy as being relatively cheap.  I just thought it was necessary to remind some people (those who decide to read me) that prudence is mandatory here.

On the paradox of poverty and good health in Cuba

One of the most interesting (in my opinion) paradox in modern policy debates relates to how Cuba, a very poor country, has been able to generate health outcomes close to the levels observed in rich countries. To be fair, academics have long known that there is only an imperfect relation between material living standards and biological living standards (full disclosure: I am inclined to agree, but with important caveats better discussed in a future post or article, but there is an example). The problem is that Cuba is really an outlier. I mean, according to the WHO statistics, its pretty close to the United States in spite of being far poorer.

In the wake of Castro’s death, I believed it necessary to assess why Cuba is an outlier and creates this apparent paradox. As such, I decided to move some other projects aside for the purposes of understanding Cuban economic history and I have recently finalized the working paper (which I am about to submit) on this paradox (paper here at SSRN).

The working paper, written with physician Gilbert Berdine (a pneumologist from Texas Tech University), makes four key arguments to explain why Cuba is an outlier (that we ought not try to replicate).

The level of health outcomes is overestimated, but the improvements are real

 Incentives matter, even in the construction of statistics and this is why we should be skeptical. Indeed, doctors are working under centrally designed targets of infant mortality that they must achieve and there are penalties if the targets are not reached. As such, physicians respond rationally and they use complex stratagems to reduce their reported levels. This includes the re-categorization of early neonatal deaths as late fetal deaths which deflates the infant mortality rate and the pressuring (sometimes coercing) of mothers with risky pregnancies to abort in order to avoid missing their targets. This overstates the level of health outcomes in Cuba since accounting for reclassification of deaths and a hypothetically low proportions of pressured/coerced abortions reduces Cuban life expectancy by close to two years (see figure below). Nonetheless, the improvements in Cuba since 1959 are real and impressive – this cannot be negated.

Cuba1.png

 

Health Outcomes Result from Coercive Policy 

Many experts believe that we ought to try to achieve the levels of health outcomes generated by Cuba and resist the violations of human rights that are associated with the ruling regime. The problem is that they cannot be separated. It this through the use of coercive policy that the regime is able to allocate more than 10% of its tiny GDP to health care and close to 1% of its population to the task of being a physician. It ought also be mentioned that physicians in Cuba are also mandated to violate patient privacy and report information to the regime. Consequently, Cuban physicians (who are also members of the military) are the first line of internal defense of the regime. The use of extreme coercive measures has the effect of improving health outcomes, but it comes at the price of economic growth. As documented by Werner Troesken, there are always institutional trade-offs in term of health care. Either you adopt policies that promote growth but may hinder the adoption of certain public health measures or you adopt these measures at the price of growth. The difference between the two choices is that economic growth bears fruit in the distant future (i.e. there are palliative health effects of economic growth that take more time to materialize).

Health Outcomes are Accidents of Non-Health Related Policies

As part of the institutional trade-off that make Cubans poorer, there might be some unintended positive health-effects. Indeed, the rationing of some items does limit the ability of the population to consume items deleterious to their health. The restrictions on car ownership and imports (which have Cuba one of the Latin American countries with the lowest rate of car ownership) also reduces mortality from road accidents which,  in countries like Brazil, knock off 0.8 years of life expectancy at birth for men and 0.2 years for women.  The policies that generate these outcomes are macroeconomic policies (which impose strict controls on the economy) unrelated to the Cuban health care system. As such, the poverty caused by Cuban institutions  may also be helping Cuban live longer.

Human Development is not a Basic Needs Measure

The last point in the paper is that human development requires agency.  Since life expectancy at birth is one of the components of the Human Development Indexes (HDI),  Cuba fares very well on that front. The problem is that the philosophy between HDIs is that individual must have the ability to exercise agency. It is not a measure of poverty nor a measure of basic needs, it is a measure meant to capture how well can individual can exercise free will: higher incomes buy you some abilities, health provides you the ability to achieve them and education empowers you.

You cannot judge a country with “unfree” institutions with such a measure. You need to compare it with other countries, especially countries where there are fewer legal barriers to human agency. The problem is that within Latin America, it is hard to find such countries, but what happens when we compare with the four leading countries in terms of economic freedom. What happens to them? Well, not only do they often beat Cuba, but they have actually come from further back and as such they have seen much larger improvements that Cuba did.

This is not to say that these countries are to be imitated, but they are marginal improvements relative to Cuba and because they have freer institutions than Cuba, they have been able to generate more “human development” than Cuba did.

Cuba2.png

Our Conclusion

Our interpretation of Cuban health care provision and health outcomes can be illustrated by an analogy with an orchard. The fruit of positive health outcomes from the “coercive institutional tree” that Cuba has planted can only be picked once, and the tree depletes the soil significantly in terms of human agency and personal freedom. The “human development tree” nurtured in other countries yields more fruit, and it promises to keep yielding fruit in the future. Any praise of Cuba’s health policy should be examined within this broader institutional perspective.

Aggregate measures of well-being, England 1781-1850

I went in the field of economic history after I discovered how much it was to properly measure living standards. The issue that always interested me was how to “capture” the multidimensional nature of living standards. After all, what weight should we give to an extra year of life relative to the quality of that extra year (see all my stuff on Cuba)?

However, I never tried to create “a composite” measure of living standards. I thought that it was necessary, first, to get the measurements right. However, I had been aware of the work of Leandro Prados de la Escosura who has been doing considerable work on this in order to create composite measures (Leandro also influenced me on my Cuba reasoning – see this article).

A year ago, I discovered the work of Daniel Gallardo Albarrán from the University of Groningen at the meeting of the Economic History Society (EHS). Daniel’s work is particularly interesting because he is trying to generate a composite measure of well-being at one of the most important moment in history: the start of the British industrial revolution.

Because of its importance and some pieces of contradicting evidence (inequality, stature, amplitude of real wage increases, amplitude of income increases, urban pollution leading to increased mortality risks etc), the period has been begging for some form of composite measure to come along (at least a serious attempt at generating it). Drawing on some pretty straightforward microeconomic theory (the Beckerian in me likes this), Daniel generates this rich graph (see the paper here).

Daniel

The idea is very neat and I hope it will inspire some economic historians to attempt an expansion upon Daniel’s work. I have already drawn outlines for my own stuff on Canada since I study an era when (from the early 1800s to the mid-1850s) real wages and incomes seem to be going up but stature and mortality are either deteriorating or remaining stable while inequality is clearly increasing.

The Heights of French-Canadian Convicts, 1780 to 1830

A few days ago, it was confirmed that my article with Vadim Kufenko and Alex Arsenault Morin on the heights of French-Canadians between 1780 and 1830 was accepted for publication in Economics and Human Biology. In that paper, we try to introduce French-Canadians before 1850 to the anthropometric history literature by using the records of the prison of Quebec City. Stature is an important measure of living standards. As it is heavily related to other aspects of health outcomes, it is a strong measure of biological living standards. More importantly, there are moments in history when material living standards and biological living standards move in opposite directions (in the long-run, this is not the case).

We find three key results. The first is that the French-Canadians grew shorter throughout the era when living standards did not increase importantly (and were very volatile). This puts them at odds from other places in North America where increases in stature were experienced up until the 1820s. Furthermore, stature stops falling around 1820 when economic growth picked up. This places the French-Canadians in a unique category in North America since it seems unlikely that they experienced a strong version of the antebellum puzzle (decline in stature with increases in material living standards which is what the US experienced). The second key result is that the French-Canadians are the shortest in North America, shorter even than Black Americans in slavery. However, they are considerably taller than most (save Argentinians) Latin Americans. More importantly, they are considerably taller than their counterparts in France. The third key result is related to the second key result. Today, French-Canadians are noticeably shorter than other Canadians. However, the gap was more important in the late 19th century and early 20th century. Pegged as a “striking exception” within Canada, we do not know when it actually started. Thanks to our work, we know that this was true as far back at the early 19th century.

The working paper (dramatically different than the accepted version) is here and I am posting key results in tables and figures below.  Moreover, I will be talking about anthropometric history and economic history with Garrett Petersen of Economics Detective Radio this Tuesday (I do not know when the podcast will be made available, but you should subscribe to that show anyways).

Heights.png

Table3.png

Is Trump So Old? Its all relative really!

Today is inauguration day. Donald Trump will officially be the 45th President of the United States of America. Many have pointed out that Trump is the oldest president (slightly above 70 years of age). I disagree.

Old is not a “purely” absolute concept. Advances in living standards mean advances in our ability to live longer lives. Not only do we live longer lives than in the past, but at any point in our life, our health is better. Someone who reached 65 years of age in 1900 probably did not have the same health prospects as someone who reaches that age today. Basically, the “quality” of old age has increased over time (see this great book on the economic history of aging). So, when people say “old”, I ask “old as compared to what”.

To meet that test, I took the CDC data on life expectancy as well as soon historical database  from 1900 to today. I combined it with David Hacker’s work on life tables in the US from 1790 to 1900 which can be found in this article of Historical Methods.  Hacker’s data concerns only the white population. I took only the age expectancy at birth of males. Then, I plotted the age of the president at the time of inauguration as a share of the life expectancy at birth (E0). This is the result:

inauguration

As one can see, the age of presidents as a share of life expectancy is falling steadily since the early 1900s. In this light, Donald Trump is not the oldest president. In fact, the oldest president is …. drumroll…James Buchanan (1.85 times the life expectancy of white males at birth). Moreover, in this light, the youngest president at inauguration is not Teddy Roosevelt (Kennedy was the youngest elected). Rather, the youngest is Barack Obama followed very closely by Bill Clinton and John F. Kennedy.

I find this post to be interesting as it shows something more important in my eyes: how the poorest in society have done. Presidents have generally stemmed from the top of the income distribution. Over time, the ages of presidents at inauguration (in absolute terms) has not followed any clear trend. The drop seen in the graph above is entirely driven by increases in the life expectancy of the “average” American. In a certain way, it shows that the distance between that “Joe the Plumber” and the “Greatest Man in America” (huh…Lord Acton anyone?) seems to be diminishing over time.

How Well Has Cuba Managed To Improve Health Outcomes? (part 2)

In a recent post, I pointed out that life expectancy in Cuba was high largely as a result of really low rates of car ownerships.  Fewer cars, fewer road accidents, higher life expectancy. As I pointed out using a paper published in Demography, road fatalities reduced life expectancy by somewhere between 0.2 and 0.8 years in Brazil (a country with a car ownership rate of roughly 400 per 1,000 persons). Obviously, road fatalities have very little to do with health care. Praising high life expectancy in Cuba as the outcome Castrist healthcare is incorrect, since the culprit seems to be the fact that Cubans just don’t own cars (only 55 per 1,000). But that was a level argument – i.e. the level is off.

It was not a trend argument. The rapid increase in life expectancy is undeniable, so my argument about level won’t affect the claim that Cubans saw their life expectancy increase under Castro.

I say “wait just a second”.

Cuba is quite unique with regards to car ownership. In 1958, it had the second highest rate of car ownership of all Latin America. However, while the rate went up in all of Latin America between 1958 and 1988, it went down in Cuba. During that period, life expectancy went up in all countries while there were substantial increases in car ownership (which would, all things being equal, slow down life expectancy growth). Take Chile and Brazil as example. In these countries, the rate went up by 6.9% and 8.1% every year – these are fantastic rates of growth. During the same period, life expectancy increased 25% in Chile and 19% in Brazil compared with Cuba where the increase stood at 17%. In Cuba, the moderate decline in car ownership (-0.1% per annum) would have (very) modestly contributed to the increase of life expectancy. In the other countries, car ownership hindered the increase. (The data is also from the WHO section on Road Safety while the life expectancy data is from the World Bank Database)

This does not alter the trend of life expectancy in Cuba dramatically, but it does alter it in a manner that forces us, once more, to substract from Castro’s accomplishments. This increase would not have been the offspring of the master plan of the dictator, but rather an accidental side-effect springing from policies that depressed living standards so much that Cubans drove less and were less subjected to the risk of dying while driving. However, I am unsure as to whether or not Cubans would regard this as an “improvement”.

Below are the comparisons between Cuba, Chile and Brazil.

cars

The other parts of How Well Has Cuba Managed To Improve Health Outcomes?

  1. Life Expectancy Changes, 1960 to 2014
  2. Car ownership trends playing in favor of Cuba, but not a praiseworthy outcome
  3. Of Refugeees and Life Expectancy
  4. Changes in infant mortality
  5. Life expectancy at age 60-64
  6. Effect of recomputations of life expectancy
  7. Changes in net nutrition
  8. The evolution of stature
  9. Qualitative evidence on water access, sanitation, electricity and underground healthcare
  10. Human development as positive liberty (or why HDI is not a basic needs measure)