Josh Barro, writing for businessinsider.com, recently made the claim that private health insurance is "a government benefit provided through public channels". At the risk of opening myself to political argument, I'd like to address his major point, which is that health insurance is not a typical insurance product,  "designed to turn an individual's risk of loss into a predictable cost". I claim that it he is correct, but by changing the word "individual" to "group", changing the dimensionality of the insurance's target, he would be incorrect. 

Barro argues that sick people's benefits from health insurance exceed their monetized risk, and healthy people pay more than they actually expect to gain. This is a patently wrong conclusion: "broken" homes have "benefits" that exceed their homeowners monetized risk (homeowner's insurance policy), and "well-maintained" homes are on the opposite side of the spectrum. There just isn't a false equivalency here, as Barro explains it. 

So it is a bit striking that Barro is actually able to make his point well, because while, as he first explains it, health insurance is equivalent to homeowner's insurance, he accurately later points out that regulated health insurance:

Buzzwords aside, simple insurance (Barro's homeowner's insurance) is fundamentally a functional agreement which takes present risk and monetizes it over a long period of time: in other words it spreads risk across one dimension. Since my home's risk of, say, termite damage is (largely) has a relatively small spatial covariance with other homes, my contract with an insurer is one-dimensional. I give the insurer money, and they spread my risk over time for a small fee.

In the health sphere, however, my personal risk of illness is considerably tied in to that around me. If you are not convinced, consider the rapid outbreak of swine flue, or peruse the wikipedia entry on epidemic, the common code, the flu, etc, etc... Not only do I encounter risk in terms of random fluctuations in my health over time, but also in the random interactions between myself and others. Health insurance requires a spreading of risk over two-dimensions, across time and between people. 

It is for this reason why, for health insurance to mean anything, it must be imposed on a supra-individual level, such as at the national level.  Because any one person's engagement in a health insurance scheme is an implicit contracted two-dimensional spreading of risk, they are effectively losing their insurance when other individuals fail to enroll. 

Capital-h Health, not health insurance, is what is not a toaster, and so to insure it is to contract in a two-dimensional relationship between individuals and with an insurer. Barro is (almost) right. 

Ever wonder what the most-heard phrase in the world is? A good bet would be:

Which repeats every 15 seconds at at least two locations at (approximately) all of the 50,000 airports in the world (assuming there's a few more moving walks at, for example, LHR than in a small regional Tibetan airport). That gives us a quarter of a billion broadcasts per day, meaning it could probably compete with the Muslim call to prayer, "Mind the gap", or that stupid R.Fancourt roofing song for the most heard or repeated non-spoken phrase. 

Here's a similar one:

Which got me thinking about what exactly this statement meant. One hears it over and over again, to the point where I'd bet most people can form some approximation of it when asked.

Here's the thing, though: there's a difference between the prohibition of "unattended baggage" and "baggage left unattended". Prohibition necessarily requires an actor to be prohibited from performing an action, in this case leaving your bags alone in an airport. The TSA's statement, however, is banning the unattended baggage itself, without reference to who is to be punished!

This is just a good example of the implicit way language can be used to signify meaning. On its grammatical and lexical construction, the TSA's statement is a bit funky because of the misuse of "prohibition".  And this may be by construction, because unattended baggage, by its very nature, has no person to blame for its existence. All interesting things to think about. Just how intelligent is the TSA?

Still, this is the danger of speaking about explicit things (scientific results, for example) using a language which places a considerable weight on implicit meaning. Words mean things that are not immediately self-evident, but data and information is independent of context, which is one of a myriad ways of viewing the reflexive disdain scientists and journalists have for one another. 

I recently attended a talk by Gernot Wagner (with some commentary by Richard Zeckhauser) on the implications of the IPCC's widening of their "likely" 2100 global temperature rise from 2.0 to 4.5 degrees to 1.5 to 4.5 degrees. It is entitled:  "Expecting a Black Swan but Getting a Dragon: Deep Uncertainty and Climate Change" 

The major point of their argument was that a shift in the kurtosis of the distribution (made by taking out the "most likely" estimate of climate sensitivity) increased the net cost (in a metric known as willingness to pay (WTP)) by increasing the uncertainty of future predictions. There is nothing wrong with this as an exercise: two different pdfs passed through a certain set of filters and evaluated will produce different things. In this cases, pdfs of varying kurtosis produce more of a net WTP as the kurtosis increases. Nothing to see here. 

The problem is that this is taken incredibly seriously by the public, as the results from this and similar studies have been used to price carbon. This increase in IPCC related uncertainty has the potential effect of doubling the cost of carbon from $40 to $80 per ton, though this depends on your pricing metric.  These exercises are interpreted (and the author's are entirely complicit, spending a majority of the presentation talking about climate science) as being real authoritative pricing schemes, which they can not be. 

Suppose I have a pdf of future warming which peaks at 3 degrees with a kurtosis of 2, and variance of 1 degree, a gaussian. The IPCC's release would indicate that the mean of the distribution would shift by half a degree, the kurtosis would increase, and so would the variance. So why is this not considered? How can we price carbon using the kurtosis shift but not include the mean shift too? It's a damning question, but not one that is considered. The authors, when confronted, go at great lengths to discuss the limitations of the model. Yet when left to speak freely, and in publications, the results are discussed as saying something real about the world. The rather bald-faced contradiction is difficult to swallow. 


A link to the discussed paper is here

Here is a link to a recent paper discussing the negative correlation between African literacy rates in the colonial and post-colonial times and the "slave export intensity" during the pre-colonial era. 

Cherokee Gothic rightly points out that this is an example of economic path-dependency, a concept familiar to mathematicians: for certain quantities, it isn't where you end up, but how you got there. 

Example: if one pegs their net worth at the value of the stock AAPL, and through some sorcery predicts every upturn and downturn in the stock price, liquidating at peaks and converting all cash to stock at local minima, in a year that person would have a considerable amount more money than the person who held the stock fixed, and much more than the person who made the opposite choices. The path taken to the end is what caused the discrepancy in wealth after a year. 

Path dependancy is a familiar trope in political theater and is, depending on the political and philosophical bent of the person, the reason for gender and race gaps in education, poverty, and incarceration.  It can be summarized (thanks to Scott E. Page) in the "old Bostonian jump roping rhyme"

And so this recent paper attempts to gauge the level to which slave export has biased literacy rates in African countries over the proceeding centuries. The answer? According to the abstract: "a negative and signicant relationship between slave
export intensity before the colonial era and literacy rates during the colonial era."

Here's the data used to support that claim, buried in a plot in the supplementary material. This image plots literacy rate against some normalized quantity representing pre-colonial slave exports as a percentage of the extant population. Where's the trend? 

To me (and this is just me), this appears to be a classic case of oversimplification. If the author wrote this paper with the exact opposite conclusion, I would be equally swayed. What causes the four outlier groups in slave export to be there? Why is there seemingly no trend? Why did the author connect two clusters with a line and call it a trend?

Bad science, even in Path Dependancy