MarkPNeyer.com

I’ve been studying global climate change a lot lately.  I  just can’t make up my mind. It’s basically a fight between my rational/logical brain, and my intuition.

My rational, logical mind understands the basic physics behind the theory that all the Carbon Dioxide we’ve put into the air has altered (and will continue to alter) the climate. The theory has been around a long time and has been experimentally verified.  There are a lot of really smart people who think the earth is getting warmer due to human activity.  They couldn’t all be wrong, could they?

My intuitive mind, on the other hand, has a hard time believing that climatologists have gotten it all correct. I have a lot of questions about their methodologies and the results they have found. I figured the best way to answer these questions would be to talk to a climatologist, so that’s what I decided to do. I’ve emailed several climatologists with questions I had about global climate change. I’ll post the answers when I get them back.  Stay tuned!

Here are the questions I asked:

1. From what I’ve read, there are a bunch of weather stations around the world, and the temperature measurements from these weather stations are mathematically combined to form the global average temperature. How can climate scientists be sure that the mathematics they are using to combine the temperature measurements together are correct? A theory which proposes an experiment can easily be validated – you simply perform the experiment and see if the theory holds up. How do you validate something that is purely a measurement, and makes no direct predictions?
2. I have a similar question about paleo-climatology. I don’t see how ice core measurements, tree ring data, and other proxies for temperature that are used before the mid 1800’s could give any degree of accuracy. Wouldn’t you need to measure tree rings all around the world and then combine them together, again using some complicated math?  Are there statistical confidence intervals for the accuracies of historical climate reconstructions? Where can i find those?
   
   
3. The changes in the earth’s average temperature are measured to be on the order of 1 degree Celsius over 100 years. That doesn’t seem like much to me. The only explanation that I have come up with for the reason that such a small change puts us in danger is if the climate system is a chaotic system.  Is our climate a chaotic system? If so, my understanding of chaotic systems is limited but it seems unlikely to me that a computer simulation could ever have much hope of predicting much about a chaotic system, because you’d never have an accurate understanding of the initial conditions, and even slight errors in the initial conditions would cause the climate’s actual behavior to diverge wildly from what our models predict [see question 5]. If the climate system is not chaotic, then how does such a small change in temperature cause so much damage?
   
4. Mathematically, the temperature of the earth has to exist, but it seems to me that it would change so fast and fluctuate so much that talking about changes of fractions of a degree doesn’t make much sense. My understanding of atmospheric models is that they usually treat the atmosphere as having different layers, each with different thermodynamical properties. If the average surface temperature increases, but this increase is offset by a decrease in the average temperature of one layer of the atmosphere, I should think the climate would definitely change even though the ‘average global temperature’ would remain unchanged. Is it ever useful to talk about a “global average temperature”? Can we get a more complete picture by looking at the temperature distribution function over time? I’m curious to know what that function would look like, but I have been unable to find it.
   
   
5. The best thing about science (in my humble opinion) is that it’s usually pretty easy to tell who’s right; if a theory is repeatedly verified experimentally then there’s a good bet that the theory is accurate. It’s my understanding that the theory of Carbon Dioxide trapping some radiation into space and thereby increasing the temperature of the stratosphere has been repeatedly experimentally verified. I’m very curious, however, about the historical accuracy of climate models. So far, all I have been able to find is a comparison of James Hansen’s 1988 predictions of the change in temperature anomaly and the actual observations made up to 2006. It looks like the models accurately predicted the real change in temperature, but in his paper “Global Temperature Change,” Hansen says that “Close agreement of observed temperature change with simulations for the most realistic climate forcing is accidental, given the large unforced variability in both model and real world.” Maybe I’m misreading him, but it sounds like he’s saying ‘the models were right, but that was a fluke.’    How statistically accurate were climate models from the 90’s in predicting the climate variability we experienced over the past decade?

I have heard many different predictions about the effects of anthropogenic global warming, ranging from incredibly bad (the demise of many species, potentially including the human race) to mildly good (improved crop yields in the northern hemisphere, fewer deaths due to extreme cold.) How much danger do you believe global warming poses for the human race? Is it true that some countries might actually benefit from global warming?


6. I read that even if we stopped all CO2 emissions immediately, the earth’s temperature would still rise at the same rate (~1 Degree Celcius / Century) for some time, because it would take a long time to remove those gases from our atmosphere. Some people have proposed geoengineering as the solution to the problem of global warming, arguing that cutting emissions would be “too little, too late.”  Do you think any geoengineering approaches are a viable solution to the problem?

The BBC is reporting that thousands of Britons are now calling upon their government to posthumously pardon and knight Alan Turing. If you don’t know his story, you should.

Alan Turing is one of the founders of the field of Computer Science, which is the study of the mathematical laws underlying computation.   He proved, among other things, that there are some problems that cannot be solved by a computational device. Not only was Turing’s work theoretically impressive and groundbreaking, it was also of incredible importance to the allied effort during the second world war.  The British intelligence ran an outfit called Bletchley Park, whose sole purpose was to intercept German and Japaneses messages, break open the encryption schemes, and use the gleaned secrets to help the Allies.  The Germans had a complicated encryption computer called ‘Enigma,’ which they believed to be unbreakable.  There was a herculean effort on the part of the allies  to break open this encryption system, and it succeeded.  Alan Turing devised a machine called ‘the Bombe’ which could reverse engineer the settings on the enigma machine, to help decode its messages. It is entirely possible that without the efforts at Bletchley Park,  the war might have lasted a long longer or ended on an entirely different note.

Alan Turing was not only a genius who worked tirelessly to save the free world, he was a homosexual living in an age when homosexuality was illegal. In 1952 he was charged with having a homosexual relationship, and he accepted a sentence of chemical castration via estrogen injection.  His security clearance was stripped, he was forbidden form working at Bletchley Park, and a year later, he killed himself. Now, I suppose an apology on behalf of the British government would be nice, but it wouldn’t accomplish much.  After reading the story of Alan Turing, I realized that there is an entire class of people who live as second class citizens. If we would like to honor the memory of Alan Turing, the best response is to end the “Don’t Ask, Don’t Tell” policy and to stop treating a group of our fellow citizens as if there were something wrong with them. I am not homosexual and I do not really understand what causes some people to be so, but to me the reason is irrelevant -  there’s simply no excuse for discriminating against someone because of whom they happen to be attracted to.

I wrote this macro for work and thought other people might be able to use it.

Public Sub MakeAllRefsCopyLocal()
    For Each aproj As Project In DTE.Solution.Projects
        If (aproj.Kind = PrjKind.prjKindCSharpProject) Then
            Dim vsProj As VSProject = CType(aproj.Object, VSProject)
            For Each ref As Reference In vsProj.References
                Try
                    ref.CopyLocal = False
                Catch ex As Exception
                End Try
            Next
        End If
    Next
    MsgBox("All References Made To Copy Local")
End Sub

In my last post, I discussed a simple mathematical model of happiness. I made quite a few assumptions in building the model, and I thought I’d revisit one of them. In my model, people traveled through a world with one spatial dimension, and were either happy or sad depending upon their location and the time. It was quite a simple model, but it still yielded what I believe to be reasonable advice – listen to other people’s experiences and try to use that information to form a more complete picture of the world, in order to make yourself happier.

The strategy I proposed in the last post was to simply maximize the sum of the happiness you experience at each individual moment.  Let’s call this the SumOfHappinesses strategy. Is that a reasonable strategy? Despite my last post, I argue that it actually is not a good strategy to pursue.   My reasoning follows.

Suppose you live in a universe where you have 100 coins, and you have a device which flips them all at the same time. You’ll be very happy if they all come up ‘heads’. As happy as you possibly could be.  That happiness will last you for the rest of your life, too. In this universe, What do you do?  The SumOfHappinesses strategy says to keep on flipping as often as you can, in order to maximize your happiness.

Think about this for a second, though.  You spend your life doing nothing but flipping coins? I don’t care how happy it makes you, waiting your whole life for one extremely unlikely event to occur can’t be worth it.  Every time the event doesn’t occur, you’ll get upset, and most likely you’ll never reach the event.  The odds of all coins coming up heads are 1 in 2¹⁰⁰, which is about one in 1.26 x 10³⁰ . If you flipped the coins ten times a second, nonstop, for the age of the entire universe you’d still be very very unlikely to ever reach that ultimate happiness event.

You might argue that I’ve created an absurd universe – who would really be that happy if they flipped 100 heads in a row? It turns out that there are plenty of things that happen in the real world that are similar to my coin-flipping example.  The lottery is one thing that comes to mind – even if you could get one free lottery ticket each day, it wouldn’t be worth it to go out and pick the thing up, because your probability of winning is so small.

What are some other examples?  Becoming famous works perfectly here.  Let’s suppose your goal is to become the next rock superstar. You’d have to practice really hard, meet the right people, and be extraordinarily lucky.  If you put all your life’s effort and energy into becoming a rock star, the overwhelming probability is that you’ll end your life no more famous than you began.   The same is true in any other field that has ’super stars’  which is pretty much every field I can think of.

Does this mean you shouldn’t “shoot for the top?” Absolutely not – it just means you shouldn’t make “getting to the top”  your only source of happiness. If you like playing guitar, then by all means shoot for stardom, but make sure you don’t forget to derive happiness from your daily practicing.  If you focus only on the goal and not the process of getting there, you’re going to be unhappy. No matter how happy extremely unlikely events could make you, the fact that they’re extremely unlikely means that they’re really not worth pursuing unless you enjoy the act of pursuing them.

With the Obama administration pushing a massive reform of our Health Care system, I figured I would share my opinion on the subject, for all of those interested.  I firmly believe that if you want to solve a problem, the best approach is to come up with mathematical models for your problem, analyze them, and do what the models suggest.  In this post, I will gradually build a mathematical model that describes health care, asking questions about the model and proposing policies reflecting the outcomes of the model.  Let’s begin!

Model Version 1: There is a universe of N individuals with two states: healthy and sick.  Let the variable t represent time, with t =  0 being some arbitrary date, say January 1, 2009. In this model, t is discrete – that is, it takes on the values -3,-2,-1,0,1,2… &c.  In other words, there are no fractional times.  At each time t , there is a certain probability p_sick that an individual will become sick. It costs c_cure dollars for a sick become healthy.

How much does Health Care cost in version 1 of the model? If we have N people, then at teach time tick, p_sick * N become sick, then the total cost of keeping everyone health is

c_total  = N *p_sick *c_cure.

In this simple model, we have only one question to ask: who pays the cost of health care? Should the individual who becomes sick pay for his own cure, or should the government foot the bill?  I contend that this this question is entirely a value judgment.   Everyone has a different opinion on what’s fair or just. We could argue about constitutionality, but that wouldn’t get us anywhere either – everyone interprets the constitution differently and different people will just claim that the constitution backs their case.  Thus, the first conclusion:

Conclusion 1: The question of “who should pay for health care” is entirely a personal value judgement.

Model Version 2:  In version 2 of the model, we add in different diseases, and choices.  Let D = {d_0, d_1, d_2….} be different diseases that people could acquire.   Note that we could consider things like  broken legs and concussions to be ‘diseases’ because people do suffer from them, and they do cost money to cure. For each d_i, there is a cost c_i to cure that disease. Note that for some i, c_i is infinite. In other words, for some ailments, there are no known cures.  Additionally, let A = {a_o, a_1, …} be a set of actions that an individual could perform.   The actions a person takes affect the probability that they catch certain diseases. For example, if you choose to drive a car to work, you increase the probability of getting any number of bodily ailments. If you eat a bag of Cheetos for lunch, you increase your probability of getting a heart attack.  Let risk be a function that takes an action a_i and a disease d_j as input, and returns p_j. In other words, risk(a_i,d_j) is the probability that you will suffer from disease d_j if you perform action a_i.
How much does health care cost in this model? It’s almost impossible to answer. You’d have to know risk(a_i,d_j) for each possible combination of i and j.   As the models get more and more complex, we see that we can’t really predict from logical principles how much health care is going to cost unless we can predict what kind of actions people are likely to take.  What we can observe, though, is that the question of ‘who pays’ becomes more interesting. If the government pays for all health care, then people have no incentive to minimize the risks they take.   If individuals pay for their healthcare, however, they have every incentive to minmize the risks that they take, reducing the total cost of healthcare.  Model 2 suggests that the best solution is to have individuals pay for their own health care, so that they minimize the amount of risk that they take.

Suppose one of the actions is ‘going to the doctor for a routine checkup.’ Clearly, this action reduces the risk of many diseases.  If individuals are forced to pay for their own health care, and rational individuals wish to minimize the cost they spend on health care, then rational individuals would go to doctors for routine checkups.  In reality, this often doesn’t happen – so something is wrong with the model. Let’s expand it.

Model 3: Same as Model 2, except the concepts of “cost” and “cure” change. Now, instead of cost being associated only with disease, each action a_i has an associated cost given by cost(a_i) Sometimes the cost of an action is positive (going to the doctor, going to see a movie, buying gas) and sometimes the cost of an action is negative (i.e. selling a house, going to work.) For each disease d_i,  there is an action that cures the disease. Let this action be called cure_i. Additionally,  the function risk now takes a third argument as input: the state of the individual at time t. In other words, if you’ve currently got a cold, then your risk of sinus infection might go up.

How does Model 3 differ from Model 2? We have removed cures as some abstract thing that happens to people, and transformed them into actions that people take. As a result, the incentive structure of the system changes.  When some diseases increase the risk of other diseases, rational people are more willing to pay to treat the first disease, in order to prevent themselves from getting the second.   We can also explain why a lot of people people don’t go to the doctor under our current health care system -  the cost of going to the doctor is positive, but the benefits are small, becuase insurance is more likely to cover catastrophic illnesses than it is to cover minor ones.

I could go on and continue to expand the model, but I won’t (although I’d find it very interesting to do so.)  The conclusion I’ve drawn from the modelling process is that healthcare is really complex, invovling many value judgments. Answering questions such as ‘who should pay for what’ and ‘how much will it cost’ is not easy to do.  In light of that conclusion, the question you should ask yourself is: “What is the best way of answering complex questions involving the value judgements of many individuals?” Economists have been studying this question for centuries, and, empirically, the answer is pretty clear – governments are notoriously bad at answering these questions satisfactorily. Markets, while far from perfect, are the best solution anyone has ever devised.

The primary problem with a Market-oriented solution to health care is that it excludes those who are unable to afford health care. I believe that the best way to handle those who are unable to afford health care is to supply them with vouchers that they can use to purchase health insurance of their own choice.  This would create competition and reduce costs. The Obama administration seems to belive  not only that the government is entitled to answer all of these questions for us, but the government is actually capable of doing so, in a fair and just manner. Believing that requires a hurculanean leap of faith in government.  If you think the government is capable of solving the healthcare problem better than markets, you must certainly believe that the government can solve the question of ‘who should produce what, and who should consume what’ even better.   Communism died for a reason: governments are not as efficient or responsive as markets. Listen to the empircal evidence of history, and make up your mind accordingly. I welcome your comments.