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RichardKennaway comments on Smoking lesion as a counterexample to CDT - Less Wrong Discussion

6 Post author: Stuart_Armstrong 26 October 2012 12:08PM

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Comment author: RichardKennaway 29 October 2012 05:20:42PM 0 points [-]

How would you rule out that taxes cause lesions, or that taxes cause cancer? How would you show that taxes reduce smoking, given only that higher taxes are a leading indicator of reduced smoking?

At some point, you have to bring in domain knowledge of causation. How do you know that pushing on the accelerator will make the car go faster?

One can think up scenarios in which taxes do indirectly cause cancer (or lesions): higher tax on tobacco --> people continue to use tobacco but switch to some cheaper, less preferred foodstuffs --> among which is one that unknown to anyone yet causes cancer (or lesions). But the first of those links is observable. If they don't change their diet but do reduce their tobacco consumption, this chain is refuted.

For taxes causing reduced smoking, you could look at temporal relations, or ask people why they've cut down. If you find yourself inventing reasons why no-one can detect the dragon in your garage, at some point you have to accept that there is no dragon.

Comment author: Decius 30 October 2012 06:48:01PM 0 points [-]

Evenly divide all people into two groups, and apply higher taxes to one group.

Changing taxes for everyone fails to test for a common cause of tax changes and smoking.

I can track a solid determimistic relationship from the accelerator pedal to the drivetrain. Deterministic cause and effect is easy to test. Stochastic cause and effect, much less so, especially with unknown confounding factors.

Comment author: RichardKennaway 30 October 2012 07:27:04PM 0 points [-]

Evenly divide all people into two groups, and apply higher taxes to one group.

Best of luck getting that one to fly in practice.

Changing taxes for everyone fails to test for a common cause of tax changes and smoking.

That's the general problem with instrumental variables. But sometimes that's all you have to work with.

Deterministic cause and effect is easy to test. Stochastic cause and effect, much less so, especially with unknown confounding factors.

That is the fundamental problem of statistical experiments.

Comment author: Decius 31 October 2012 03:18:38PM 0 points [-]

Well, it's just as easy as varying smoking directly, which would also work to identify a smoking->cancer effect.

Without experimentation, there is no way to distinguish between the world of smoker's lesion and the world of carcinogenic cigarettes.